Matineh Rahmatbakhsh
| Snapshot Date: 2022-04-12 01:55:07 -0400 (Tue, 12 Apr 2022) |
| git_url: https://git.bioconductor.org/packages/HPiP |
| git_branch: RELEASE_3_14 |
| git_last_commit: e3d7cf4 |
| git_last_commit_date: 2021-10-26 13:12:29 -0400 (Tue, 26 Oct 2021) |
| Back to Multiple platform build/check report for BioC 3.14 |
|
This page was generated on 2022-04-13 12:06:42 -0400 (Wed, 13 Apr 2022).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 20.04.4 LTS) | x86_64 | 4.1.3 (2022-03-10) -- "One Push-Up" | 4324 |
| tokay2 | Windows Server 2012 R2 Standard | x64 | 4.1.3 (2022-03-10) -- "One Push-Up" | 4077 |
| machv2 | macOS 10.14.6 Mojave | x86_64 | 4.1.3 (2022-03-10) -- "One Push-Up" | 4137 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
|
To the developers/maintainers of the HPiP package: - Please allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/HPiP.git to reflect on this report. See How and When does the builder pull? When will my changes propagate? for more information. - Make sure to use the following settings in order to reproduce any error or warning you see on this page. |
| Package 886/2083 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| HPiP 1.0.0 (landing page) Matineh Rahmatbakhsh
| nebbiolo2 | Linux (Ubuntu 20.04.4 LTS) / x86_64 | OK | OK | OK | | ||||||||
| tokay2 | Windows Server 2012 R2 Standard / x64 | OK | OK | OK | OK | | ||||||||
| machv2 | macOS 10.14.6 Mojave / x86_64 | OK | OK | OK | OK | | ||||||||
| Package: HPiP |
| Version: 1.0.0 |
| Command: C:\Users\biocbuild\bbs-3.14-bioc\R\bin\R.exe CMD check --force-multiarch --install=check:HPiP.install-out.txt --library=C:\Users\biocbuild\bbs-3.14-bioc\R\library --no-vignettes --timings HPiP_1.0.0.tar.gz |
| StartedAt: 2022-04-12 21:12:52 -0400 (Tue, 12 Apr 2022) |
| EndedAt: 2022-04-12 21:21:48 -0400 (Tue, 12 Apr 2022) |
| EllapsedTime: 536.2 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: HPiP.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### C:\Users\biocbuild\bbs-3.14-bioc\R\bin\R.exe CMD check --force-multiarch --install=check:HPiP.install-out.txt --library=C:\Users\biocbuild\bbs-3.14-bioc\R\library --no-vignettes --timings HPiP_1.0.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory 'C:/Users/biocbuild/bbs-3.14-bioc/meat/HPiP.Rcheck'
* using R version 4.1.3 (2022-03-10)
* using platform: x86_64-w64-mingw32 (64-bit)
* using session charset: ISO8859-1
* using option '--no-vignettes'
* checking for file 'HPiP/DESCRIPTION' ... OK
* checking extension type ... Package
* this is package 'HPiP' version '1.0.0'
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking whether package 'HPiP' can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking 'build' directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking R files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* loading checks for arch 'i386'
** checking whether the package can be loaded ... OK
** checking whether the package can be loaded with stated dependencies ... OK
** checking whether the package can be unloaded cleanly ... OK
** checking whether the namespace can be loaded with stated dependencies ... OK
** checking whether the namespace can be unloaded cleanly ... OK
* loading checks for arch 'x64'
** checking whether the package can be loaded ... OK
** checking whether the package can be loaded with stated dependencies ... OK
** checking whether the package can be unloaded cleanly ... OK
** checking whether the namespace can be loaded with stated dependencies ... OK
** checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
Package unavailable to check Rd xrefs: 'ftrCOOL'
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of 'data' directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in 'vignettes' ... OK
* checking examples ...
** running examples for arch 'i386' ... OK
Examples with CPU (user + system) or elapsed time > 5s
user system elapsed
corr_plot 37.29 1.08 39.25
var_imp 35.70 2.05 37.75
FSmethod 34.44 2.42 36.86
pred_ensembel 21.00 0.43 13.47
enrichfindP 0.50 0.03 8.40
** running examples for arch 'x64' ... OK
Examples with CPU (user + system) or elapsed time > 5s
user system elapsed
var_imp 33.42 2.34 35.81
corr_plot 34.53 1.17 35.73
FSmethod 31.45 2.27 33.76
pred_ensembel 18.45 0.27 13.83
enrichfindP 0.47 0.03 8.31
* checking for unstated dependencies in 'tests' ... OK
* checking tests ...
** running tests for arch 'i386' ...
Running 'runTests.R'
OK
** running tests for arch 'x64' ...
Running 'runTests.R'
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes in 'inst/doc' ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 1 NOTE
See
'C:/Users/biocbuild/bbs-3.14-bioc/meat/HPiP.Rcheck/00check.log'
for details.
HPiP.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### C:\cygwin\bin\curl.exe -O http://155.52.207.166/BBS/3.14/bioc/src/contrib/HPiP_1.0.0.tar.gz && rm -rf HPiP.buildbin-libdir && mkdir HPiP.buildbin-libdir && C:\Users\biocbuild\bbs-3.14-bioc\R\bin\R.exe CMD INSTALL --merge-multiarch --build --library=HPiP.buildbin-libdir HPiP_1.0.0.tar.gz && C:\Users\biocbuild\bbs-3.14-bioc\R\bin\R.exe CMD INSTALL HPiP_1.0.0.zip && rm HPiP_1.0.0.tar.gz HPiP_1.0.0.zip
###
##############################################################################
##############################################################################
% Total % Received % Xferd Average Speed Time Time Time Current
Dload Upload Total Spent Left Speed
0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0
22 2994k 22 684k 0 0 1074k 0 0:00:02 --:--:-- 0:00:02 1073k
88 2994k 88 2658k 0 0 1623k 0 0:00:01 0:00:01 --:--:-- 1623k
100 2994k 100 2994k 0 0 1708k 0 0:00:01 0:00:01 --:--:-- 1708k
install for i386
* installing *source* package 'HPiP' ...
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
converting help for package 'HPiP'
finding HTML links ... done
FSmethod html
FreqInteractors html
Gold_ReferenceSet html
UP000464024_df html
calculateAAC html
calculateAutocor html
calculateBE html
calculateCTDC html
calculateCTDD html
calculateCTDT html
calculateCTriad html
calculateDC html
calculateF html
calculateKSAAP html
calculateQD_Sm html
calculateTC html
calculateTC_Sm html
corr_plot html
enrich.df html
enrichfindP html
enrichplot html
example_data html
filter_missing_values html
getFASTA html
getHPI html
get_negativePPI html
get_positivePPI html
host_se html
impute_missing_data html
plotPPI html
pred_ensembel html
predicted_PPIs html
unlabel_data html
var_imp html
viral_se html
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
install for x64
* installing *source* package 'HPiP' ...
** testing if installed package can be loaded
* MD5 sums
packaged installation of 'HPiP' as HPiP_1.0.0.zip
* DONE (HPiP)
* installing to library 'C:/Users/biocbuild/bbs-3.14-bioc/R/library'
package 'HPiP' successfully unpacked and MD5 sums checked
|
HPiP.Rcheck/tests_i386/runTests.Rout
R version 4.1.3 (2022-03-10) -- "One Push-Up"
Copyright (C) 2022 The R Foundation for Statistical Computing
Platform: i386-w64-mingw32/i386 (32-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> BiocGenerics:::testPackage('HPiP')
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
avNNet
Loading required package: ggplot2
Loading required package: lattice
Fitting Repeat 1
# weights: 103
initial value 95.973158
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 101.041972
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 96.815728
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 97.367979
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 109.101767
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 98.112847
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 95.176102
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 109.086890
iter 10 value 94.276316
final value 94.132982
converged
Fitting Repeat 4
# weights: 305
initial value 104.541369
final value 94.477594
converged
Fitting Repeat 5
# weights: 305
initial value 98.800468
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 114.793083
final value 94.046704
converged
Fitting Repeat 2
# weights: 507
initial value 107.493035
iter 10 value 94.275362
iter 10 value 94.275362
iter 10 value 94.275362
final value 94.275362
converged
Fitting Repeat 3
# weights: 507
initial value 97.620601
iter 10 value 93.843967
final value 93.843960
converged
Fitting Repeat 4
# weights: 507
initial value 101.086037
final value 94.275362
converged
Fitting Repeat 5
# weights: 507
initial value 115.269503
final value 94.275362
converged
Fitting Repeat 1
# weights: 103
initial value 102.026223
iter 10 value 94.399523
iter 20 value 88.558443
iter 30 value 88.417183
iter 40 value 87.457927
iter 50 value 87.315386
iter 60 value 87.122308
iter 70 value 84.741663
iter 80 value 84.453877
iter 90 value 84.020589
iter 100 value 83.990042
final value 83.990042
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 97.894756
iter 10 value 94.105469
iter 20 value 85.532707
iter 30 value 85.012826
iter 40 value 84.544459
iter 50 value 84.298913
iter 60 value 84.068454
iter 70 value 83.988630
final value 83.987960
converged
Fitting Repeat 3
# weights: 103
initial value 96.276633
iter 10 value 94.486235
iter 20 value 87.584474
iter 30 value 84.873955
iter 40 value 84.396049
iter 50 value 84.289654
iter 60 value 84.084284
iter 70 value 84.081532
iter 80 value 84.008862
iter 90 value 83.987971
final value 83.987960
converged
Fitting Repeat 4
# weights: 103
initial value 103.698037
iter 10 value 94.479525
iter 20 value 94.119437
iter 30 value 94.101321
iter 40 value 94.100769
iter 50 value 89.355855
iter 60 value 87.477616
iter 70 value 87.278386
iter 80 value 86.710906
iter 90 value 84.817131
iter 100 value 84.615581
final value 84.615581
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 98.188841
iter 10 value 94.484273
iter 20 value 94.359707
iter 30 value 88.431923
iter 40 value 86.226178
iter 50 value 85.416470
iter 60 value 84.576198
iter 70 value 83.848842
iter 80 value 83.622019
iter 90 value 83.535449
iter 100 value 83.470471
final value 83.470471
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 114.239716
iter 10 value 94.430649
iter 20 value 91.569683
iter 30 value 86.137953
iter 40 value 85.122132
iter 50 value 83.138965
iter 60 value 82.348222
iter 70 value 82.144676
iter 80 value 81.893021
iter 90 value 81.564854
iter 100 value 81.378277
final value 81.378277
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 113.733152
iter 10 value 94.502631
iter 20 value 92.800275
iter 30 value 92.103694
iter 40 value 91.948409
iter 50 value 91.710087
iter 60 value 88.088442
iter 70 value 85.323163
iter 80 value 84.366849
iter 90 value 83.746289
iter 100 value 83.357081
final value 83.357081
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 109.252723
iter 10 value 94.488168
iter 20 value 93.693062
iter 30 value 91.360821
iter 40 value 86.446222
iter 50 value 85.936819
iter 60 value 83.745754
iter 70 value 82.758278
iter 80 value 82.333247
iter 90 value 81.568360
iter 100 value 81.498417
final value 81.498417
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 107.388562
iter 10 value 94.483518
iter 20 value 87.026190
iter 30 value 84.589606
iter 40 value 81.102861
iter 50 value 81.055105
iter 60 value 80.733846
iter 70 value 80.433755
iter 80 value 80.067518
iter 90 value 79.967575
iter 100 value 79.856456
final value 79.856456
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 99.860245
iter 10 value 94.536915
iter 20 value 89.134451
iter 30 value 85.386017
iter 40 value 84.231332
iter 50 value 81.831026
iter 60 value 81.283897
iter 70 value 80.905085
iter 80 value 80.659140
iter 90 value 80.522483
iter 100 value 80.514529
final value 80.514529
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 112.343790
iter 10 value 94.595159
iter 20 value 93.408952
iter 30 value 85.341969
iter 40 value 84.809293
iter 50 value 82.812204
iter 60 value 81.833052
iter 70 value 81.287081
iter 80 value 80.563014
iter 90 value 80.462170
iter 100 value 80.264959
final value 80.264959
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 109.747888
iter 10 value 94.513110
iter 20 value 93.407995
iter 30 value 86.290833
iter 40 value 85.999016
iter 50 value 85.401810
iter 60 value 84.631814
iter 70 value 84.083744
iter 80 value 83.793810
iter 90 value 83.699397
iter 100 value 83.670151
final value 83.670151
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 114.823889
iter 10 value 94.576749
iter 20 value 94.345343
iter 30 value 87.585442
iter 40 value 86.599932
iter 50 value 84.661758
iter 60 value 83.889376
iter 70 value 82.299547
iter 80 value 81.736143
iter 90 value 81.272033
iter 100 value 80.854713
final value 80.854713
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 108.285811
iter 10 value 94.808041
iter 20 value 94.507477
iter 30 value 85.554783
iter 40 value 85.087973
iter 50 value 84.512625
iter 60 value 83.827592
iter 70 value 82.894309
iter 80 value 81.969106
iter 90 value 81.854800
iter 100 value 81.851255
final value 81.851255
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 122.591084
iter 10 value 94.617947
iter 20 value 93.474612
iter 30 value 84.278028
iter 40 value 83.181120
iter 50 value 82.500039
iter 60 value 81.854570
iter 70 value 80.848300
iter 80 value 80.507751
iter 90 value 80.155081
iter 100 value 79.937859
final value 79.937859
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 102.180205
iter 10 value 94.277126
iter 20 value 94.273678
final value 94.265967
converged
Fitting Repeat 2
# weights: 103
initial value 95.408976
iter 10 value 94.277236
iter 20 value 94.275916
iter 30 value 93.884162
iter 40 value 84.052562
iter 50 value 84.036995
iter 60 value 84.036596
iter 70 value 83.721944
final value 83.721836
converged
Fitting Repeat 3
# weights: 103
initial value 100.183191
iter 10 value 94.485969
final value 94.484215
converged
Fitting Repeat 4
# weights: 103
initial value 98.776340
final value 94.486033
converged
Fitting Repeat 5
# weights: 103
initial value 99.966403
iter 10 value 94.277138
iter 20 value 94.276491
iter 30 value 94.038841
final value 94.038329
converged
Fitting Repeat 1
# weights: 305
initial value 104.606116
iter 10 value 89.848018
iter 20 value 88.160475
iter 30 value 87.928704
iter 40 value 87.921633
iter 50 value 85.686037
iter 60 value 85.546261
final value 85.546259
converged
Fitting Repeat 2
# weights: 305
initial value 98.986516
iter 10 value 94.492095
iter 20 value 94.486501
final value 94.486479
converged
Fitting Repeat 3
# weights: 305
initial value 94.478930
iter 10 value 94.280559
iter 20 value 94.050878
iter 30 value 94.038328
final value 94.038275
converged
Fitting Repeat 4
# weights: 305
initial value 109.212602
iter 10 value 94.489104
iter 20 value 94.483753
iter 30 value 85.712624
iter 40 value 85.041134
iter 50 value 83.565204
iter 60 value 83.555400
iter 70 value 83.554650
iter 80 value 83.546371
iter 90 value 83.032029
iter 100 value 82.887540
final value 82.887540
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 98.153405
iter 10 value 94.488302
iter 20 value 94.342388
iter 30 value 89.005744
iter 40 value 86.833151
iter 50 value 85.569840
iter 60 value 82.597522
iter 70 value 82.578686
iter 80 value 82.578309
iter 80 value 82.578308
iter 80 value 82.578308
final value 82.578308
converged
Fitting Repeat 1
# weights: 507
initial value 119.688935
iter 10 value 94.492886
iter 20 value 94.377285
iter 30 value 91.954178
iter 40 value 87.946979
iter 50 value 82.662678
iter 60 value 82.524545
final value 82.524263
converged
Fitting Repeat 2
# weights: 507
initial value 98.634256
iter 10 value 94.492508
iter 20 value 94.458399
iter 30 value 91.412784
iter 40 value 90.286072
iter 50 value 90.280042
iter 60 value 90.274897
iter 70 value 88.865189
iter 80 value 82.626159
iter 90 value 79.951983
iter 100 value 79.951030
final value 79.951030
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 97.870794
iter 10 value 89.871686
iter 20 value 89.714231
iter 30 value 89.674470
iter 40 value 89.660951
iter 50 value 89.551252
iter 60 value 89.547763
iter 70 value 89.546064
iter 80 value 87.001066
iter 90 value 83.700046
iter 100 value 83.521722
final value 83.521722
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 102.871124
iter 10 value 94.283676
iter 20 value 93.907703
iter 30 value 87.601365
iter 40 value 86.885530
iter 50 value 86.885149
iter 60 value 85.915207
iter 70 value 85.845920
iter 80 value 85.845687
iter 90 value 85.776459
iter 100 value 83.100220
final value 83.100220
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 97.355334
iter 10 value 94.273752
iter 20 value 92.107896
iter 30 value 86.564986
final value 86.564984
converged
Fitting Repeat 1
# weights: 103
initial value 103.670461
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 110.237799
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 99.757383
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 95.796855
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 95.774905
final value 94.466823
converged
Fitting Repeat 1
# weights: 305
initial value 94.587641
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 101.841456
final value 93.783647
converged
Fitting Repeat 3
# weights: 305
initial value 107.237209
final value 94.466823
converged
Fitting Repeat 4
# weights: 305
initial value 115.737916
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 106.700461
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 97.691506
iter 10 value 87.472619
iter 20 value 82.808819
iter 30 value 82.296137
iter 40 value 82.283572
iter 50 value 82.283358
iter 50 value 82.283357
iter 50 value 82.283357
final value 82.283357
converged
Fitting Repeat 2
# weights: 507
initial value 111.604078
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 101.996039
final value 94.484138
converged
Fitting Repeat 4
# weights: 507
initial value 112.226766
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 105.294747
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 97.744742
iter 10 value 94.478302
iter 20 value 94.316069
iter 30 value 94.257422
iter 40 value 88.911257
iter 50 value 85.221249
iter 60 value 84.488457
iter 70 value 84.148638
iter 80 value 84.121115
final value 84.120913
converged
Fitting Repeat 2
# weights: 103
initial value 102.227216
iter 10 value 94.488425
iter 20 value 91.182130
iter 30 value 85.061667
iter 40 value 83.882146
final value 83.727542
converged
Fitting Repeat 3
# weights: 103
initial value 104.260287
iter 10 value 94.451200
iter 20 value 86.351411
iter 30 value 84.617539
iter 40 value 84.183663
iter 50 value 83.467367
iter 60 value 82.528698
iter 70 value 82.514662
final value 82.514655
converged
Fitting Repeat 4
# weights: 103
initial value 97.176591
iter 10 value 93.928426
iter 20 value 91.393071
iter 30 value 87.654162
iter 40 value 86.112871
iter 50 value 84.751616
iter 60 value 84.312719
iter 70 value 84.134079
iter 80 value 84.121236
final value 84.120913
converged
Fitting Repeat 5
# weights: 103
initial value 102.385968
iter 10 value 94.475649
iter 20 value 93.046598
iter 30 value 92.003840
iter 40 value 91.894174
iter 50 value 91.618790
iter 60 value 87.636132
iter 70 value 86.351702
iter 80 value 85.774914
iter 90 value 85.062874
iter 100 value 83.795141
final value 83.795141
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 105.857223
iter 10 value 94.493221
iter 20 value 90.210645
iter 30 value 88.655479
iter 40 value 88.346361
iter 50 value 88.196618
iter 60 value 86.116246
iter 70 value 84.296551
iter 80 value 83.166322
iter 90 value 82.468428
iter 100 value 82.144334
final value 82.144334
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 102.518429
iter 10 value 94.407583
iter 20 value 87.168961
iter 30 value 83.300859
iter 40 value 81.555862
iter 50 value 81.112584
iter 60 value 81.021134
iter 70 value 80.580585
iter 80 value 80.520564
iter 90 value 80.333062
iter 100 value 80.276720
final value 80.276720
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 105.306703
iter 10 value 94.456336
iter 20 value 93.879783
iter 30 value 93.754035
iter 40 value 89.652787
iter 50 value 87.662201
iter 60 value 85.060912
iter 70 value 84.446625
iter 80 value 83.977937
iter 90 value 81.750723
iter 100 value 81.120581
final value 81.120581
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 98.263117
iter 10 value 84.759185
iter 20 value 83.632575
iter 30 value 82.813634
iter 40 value 82.399355
iter 50 value 82.347610
iter 60 value 82.296951
iter 70 value 82.085402
iter 80 value 81.831413
iter 90 value 81.619822
iter 100 value 81.355367
final value 81.355367
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 101.196305
iter 10 value 94.519837
iter 20 value 89.675552
iter 30 value 85.949481
iter 40 value 84.793537
iter 50 value 84.390382
iter 60 value 83.620488
iter 70 value 81.989234
iter 80 value 81.476101
iter 90 value 81.209181
iter 100 value 81.065317
final value 81.065317
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 108.563220
iter 10 value 92.682946
iter 20 value 87.773353
iter 30 value 86.902767
iter 40 value 84.699102
iter 50 value 84.196064
iter 60 value 83.578744
iter 70 value 83.055543
iter 80 value 82.604974
iter 90 value 82.240617
iter 100 value 82.143257
final value 82.143257
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 104.120483
iter 10 value 94.636138
iter 20 value 88.030540
iter 30 value 84.353486
iter 40 value 83.643665
iter 50 value 82.863914
iter 60 value 82.372324
iter 70 value 81.678086
iter 80 value 80.668819
iter 90 value 80.170471
iter 100 value 79.984030
final value 79.984030
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 119.832858
iter 10 value 87.279131
iter 20 value 85.893470
iter 30 value 84.516541
iter 40 value 82.924900
iter 50 value 82.352765
iter 60 value 81.877463
iter 70 value 81.739632
iter 80 value 81.626668
iter 90 value 81.458921
iter 100 value 81.261008
final value 81.261008
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 109.314296
iter 10 value 94.776375
iter 20 value 94.462971
iter 30 value 89.547385
iter 40 value 85.834026
iter 50 value 84.150987
iter 60 value 83.579116
iter 70 value 82.001992
iter 80 value 81.659064
iter 90 value 81.486227
iter 100 value 80.959685
final value 80.959685
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 138.425035
iter 10 value 103.579923
iter 20 value 93.477849
iter 30 value 85.703142
iter 40 value 84.305869
iter 50 value 84.027600
iter 60 value 83.588688
iter 70 value 81.650254
iter 80 value 80.849688
iter 90 value 80.597278
iter 100 value 80.410365
final value 80.410365
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 102.184533
final value 94.485823
converged
Fitting Repeat 2
# weights: 103
initial value 99.142165
final value 94.485804
converged
Fitting Repeat 3
# weights: 103
initial value 100.705956
final value 94.468413
converged
Fitting Repeat 4
# weights: 103
initial value 115.903725
iter 10 value 94.485956
iter 20 value 94.484216
iter 20 value 94.484216
iter 20 value 94.484216
final value 94.484216
converged
Fitting Repeat 5
# weights: 103
initial value 98.098801
final value 94.485700
converged
Fitting Repeat 1
# weights: 305
initial value 134.572859
iter 10 value 94.391872
iter 20 value 94.389382
iter 30 value 94.312801
iter 40 value 94.310657
final value 94.310652
converged
Fitting Repeat 2
# weights: 305
initial value 96.111607
iter 10 value 94.451668
iter 20 value 94.272985
iter 30 value 94.253275
final value 94.252665
converged
Fitting Repeat 3
# weights: 305
initial value 97.088890
iter 10 value 93.607357
iter 20 value 87.077341
iter 30 value 86.781830
iter 40 value 86.777095
final value 86.776609
converged
Fitting Repeat 4
# weights: 305
initial value 115.086785
iter 10 value 94.488621
iter 20 value 85.409885
iter 30 value 85.061922
iter 40 value 85.038243
final value 85.038239
converged
Fitting Repeat 5
# weights: 305
initial value 95.886535
iter 10 value 94.488308
iter 20 value 94.320376
iter 30 value 88.353765
iter 40 value 88.310284
iter 50 value 87.564489
iter 60 value 86.487816
iter 70 value 85.603189
iter 80 value 84.668563
iter 90 value 83.047921
iter 100 value 81.169030
final value 81.169030
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 110.644859
iter 10 value 94.384523
iter 20 value 94.169043
iter 30 value 94.140183
iter 40 value 92.852965
iter 50 value 92.290216
iter 60 value 92.289779
iter 70 value 90.317698
iter 80 value 87.702343
iter 90 value 87.579544
iter 100 value 87.092116
final value 87.092116
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 106.203060
iter 10 value 94.492783
iter 20 value 94.391985
iter 30 value 86.902453
iter 40 value 86.878711
iter 50 value 86.876252
iter 60 value 85.666032
iter 70 value 84.878970
iter 80 value 84.877902
iter 90 value 84.732285
iter 100 value 83.912785
final value 83.912785
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 116.274401
iter 10 value 94.492601
iter 20 value 94.443786
iter 30 value 86.508260
iter 40 value 84.875876
final value 84.875138
converged
Fitting Repeat 4
# weights: 507
initial value 98.498298
iter 10 value 94.318093
iter 20 value 94.296018
iter 30 value 92.837433
iter 40 value 86.979508
iter 50 value 83.462985
iter 60 value 83.457606
iter 70 value 83.456895
final value 83.456832
converged
Fitting Repeat 5
# weights: 507
initial value 113.588452
iter 10 value 94.321322
iter 20 value 94.150036
iter 30 value 92.214662
iter 40 value 84.293677
final value 84.293104
converged
Fitting Repeat 1
# weights: 103
initial value 97.917530
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 112.480556
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 95.189288
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 97.251037
final value 92.892738
converged
Fitting Repeat 5
# weights: 103
initial value 99.499798
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 97.673972
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 102.011108
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 100.933269
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 94.176089
iter 10 value 91.192764
final value 90.811799
converged
Fitting Repeat 5
# weights: 305
initial value 97.412113
final value 92.892737
converged
Fitting Repeat 1
# weights: 507
initial value 112.600017
final value 94.052910
converged
Fitting Repeat 2
# weights: 507
initial value 98.365475
iter 10 value 89.905822
iter 20 value 81.685350
iter 30 value 81.550164
iter 40 value 81.548537
final value 81.548373
converged
Fitting Repeat 3
# weights: 507
initial value 120.450231
final value 94.052910
converged
Fitting Repeat 4
# weights: 507
initial value 102.357817
final value 94.052910
converged
Fitting Repeat 5
# weights: 507
initial value 114.239050
iter 10 value 93.836066
iter 10 value 93.836066
iter 10 value 93.836066
final value 93.836066
converged
Fitting Repeat 1
# weights: 103
initial value 104.209604
iter 10 value 94.056772
iter 20 value 93.942770
iter 30 value 86.177455
iter 40 value 84.068530
iter 50 value 83.725794
iter 60 value 83.591529
iter 70 value 83.195111
final value 83.164809
converged
Fitting Repeat 2
# weights: 103
initial value 114.356014
iter 10 value 93.394439
iter 20 value 91.677089
iter 30 value 85.677656
iter 40 value 84.221165
iter 50 value 83.823717
iter 60 value 83.425088
iter 70 value 82.890696
iter 80 value 82.742123
final value 82.742064
converged
Fitting Repeat 3
# weights: 103
initial value 98.700098
iter 10 value 94.056247
iter 20 value 94.047970
iter 30 value 83.134085
iter 40 value 82.581237
iter 50 value 81.529627
iter 60 value 81.097359
iter 70 value 80.112072
iter 80 value 79.922493
final value 79.908483
converged
Fitting Repeat 4
# weights: 103
initial value 96.107964
iter 10 value 93.706026
iter 20 value 89.317745
iter 30 value 83.092564
iter 40 value 81.660645
iter 50 value 81.429848
final value 81.405313
converged
Fitting Repeat 5
# weights: 103
initial value 96.121908
iter 10 value 94.057027
iter 20 value 89.252391
iter 30 value 84.999483
iter 40 value 84.403293
iter 50 value 84.163401
iter 60 value 83.631902
iter 70 value 83.211173
iter 80 value 83.164958
final value 83.164809
converged
Fitting Repeat 1
# weights: 305
initial value 104.182339
iter 10 value 94.100810
iter 20 value 93.821039
iter 30 value 93.507316
iter 40 value 93.255009
iter 50 value 91.787211
iter 60 value 81.104359
iter 70 value 79.374445
iter 80 value 77.851533
iter 90 value 77.414992
iter 100 value 77.211548
final value 77.211548
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 105.797905
iter 10 value 93.883538
iter 20 value 85.672143
iter 30 value 85.142325
iter 40 value 84.309289
iter 50 value 80.591593
iter 60 value 78.718807
iter 70 value 78.345468
iter 80 value 77.424044
iter 90 value 77.052811
final value 77.004072
converged
Fitting Repeat 3
# weights: 305
initial value 108.303133
iter 10 value 93.904270
iter 20 value 86.069602
iter 30 value 85.293523
iter 40 value 84.799713
iter 50 value 82.171671
iter 60 value 79.736720
iter 70 value 78.001722
iter 80 value 77.414539
iter 90 value 77.206898
iter 100 value 76.987986
final value 76.987986
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 112.845410
iter 10 value 93.888119
iter 20 value 82.106119
iter 30 value 81.299904
iter 40 value 80.299459
iter 50 value 78.840011
iter 60 value 78.547901
iter 70 value 78.175478
iter 80 value 78.054504
iter 90 value 77.681625
iter 100 value 77.394890
final value 77.394890
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 114.826069
iter 10 value 93.809697
iter 20 value 86.182913
iter 30 value 82.652648
iter 40 value 79.251527
iter 50 value 77.545259
iter 60 value 76.917779
iter 70 value 76.702337
iter 80 value 76.594560
iter 90 value 76.486580
iter 100 value 76.429622
final value 76.429622
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 108.861885
iter 10 value 94.198417
iter 20 value 88.100979
iter 30 value 83.099591
iter 40 value 81.974363
iter 50 value 81.519679
iter 60 value 80.966997
iter 70 value 79.406116
iter 80 value 78.628241
iter 90 value 78.066973
iter 100 value 77.920645
final value 77.920645
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 126.781090
iter 10 value 93.948335
iter 20 value 87.097036
iter 30 value 80.712961
iter 40 value 78.708020
iter 50 value 77.257782
iter 60 value 77.015401
iter 70 value 76.767047
iter 80 value 76.728279
iter 90 value 76.672311
iter 100 value 76.632871
final value 76.632871
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 123.704559
iter 10 value 94.120218
iter 20 value 84.828884
iter 30 value 82.076702
iter 40 value 80.074469
iter 50 value 78.303843
iter 60 value 77.236488
iter 70 value 76.735702
iter 80 value 76.582786
iter 90 value 76.431798
iter 100 value 76.234934
final value 76.234934
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 118.922102
iter 10 value 95.592365
iter 20 value 92.515889
iter 30 value 89.555619
iter 40 value 83.229041
iter 50 value 80.788410
iter 60 value 80.264410
iter 70 value 79.448905
iter 80 value 78.221081
iter 90 value 77.927294
iter 100 value 77.220051
final value 77.220051
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 119.483319
iter 10 value 93.745080
iter 20 value 87.488023
iter 30 value 81.307679
iter 40 value 80.243789
iter 50 value 77.931278
iter 60 value 77.789093
iter 70 value 77.674672
iter 80 value 77.629988
iter 90 value 77.454675
iter 100 value 77.410129
final value 77.410129
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.441344
final value 94.054569
converged
Fitting Repeat 2
# weights: 103
initial value 96.183035
final value 94.054622
converged
Fitting Repeat 3
# weights: 103
initial value 95.767253
final value 94.054511
converged
Fitting Repeat 4
# weights: 103
initial value 98.803409
iter 10 value 94.054497
iter 20 value 94.052940
final value 94.052912
converged
Fitting Repeat 5
# weights: 103
initial value 98.595770
iter 10 value 92.935198
iter 20 value 92.933878
iter 30 value 92.933665
iter 40 value 91.924274
iter 50 value 79.169274
iter 60 value 77.758484
iter 70 value 77.484625
iter 80 value 77.164498
iter 90 value 77.163159
iter 100 value 77.162642
final value 77.162642
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 95.055126
iter 10 value 93.710098
iter 20 value 93.677407
iter 30 value 92.937279
iter 40 value 92.934643
final value 92.934445
converged
Fitting Repeat 2
# weights: 305
initial value 113.346913
iter 10 value 94.058068
iter 20 value 94.053387
iter 30 value 92.937299
final value 92.933709
converged
Fitting Repeat 3
# weights: 305
initial value 97.149676
iter 10 value 93.841251
iter 20 value 93.836794
final value 93.836288
converged
Fitting Repeat 4
# weights: 305
initial value 94.132402
iter 10 value 83.940394
iter 20 value 81.594443
iter 30 value 80.663059
iter 40 value 79.939583
iter 50 value 79.504483
iter 60 value 79.500518
iter 70 value 79.496677
iter 80 value 79.460376
iter 90 value 79.038756
iter 100 value 79.009856
final value 79.009856
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 100.799278
iter 10 value 93.769617
iter 20 value 93.768224
iter 30 value 93.765275
iter 40 value 93.765137
final value 93.765111
converged
Fitting Repeat 1
# weights: 507
initial value 101.909753
iter 10 value 93.844129
iter 20 value 93.836654
iter 30 value 93.836173
iter 40 value 90.011305
iter 50 value 89.958259
final value 89.958103
converged
Fitting Repeat 2
# weights: 507
initial value 100.319602
iter 10 value 93.845891
iter 20 value 93.833385
iter 30 value 92.918324
iter 40 value 92.764775
iter 50 value 86.315663
iter 60 value 83.195622
iter 70 value 83.186018
final value 83.186015
converged
Fitting Repeat 3
# weights: 507
initial value 100.453446
iter 10 value 89.596284
iter 20 value 86.460913
iter 30 value 81.249476
iter 40 value 79.842034
iter 50 value 79.638093
iter 60 value 79.052408
iter 70 value 78.667699
iter 80 value 78.457544
iter 90 value 77.412223
iter 100 value 77.034730
final value 77.034730
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 109.261094
iter 10 value 92.725339
iter 20 value 92.722470
iter 30 value 92.716386
iter 40 value 91.538326
iter 50 value 85.771494
iter 60 value 79.380836
iter 70 value 78.599823
iter 80 value 77.424947
iter 90 value 76.174759
iter 100 value 75.803774
final value 75.803774
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 98.941184
iter 10 value 94.061524
iter 20 value 94.003499
iter 30 value 93.766362
iter 40 value 93.764074
iter 40 value 93.764073
iter 40 value 93.764073
final value 93.764073
converged
Fitting Repeat 1
# weights: 103
initial value 95.001266
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 95.876303
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 102.757999
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 96.359311
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 99.550603
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 108.048578
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 104.762103
final value 94.338744
converged
Fitting Repeat 3
# weights: 305
initial value 121.323184
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 104.174506
final value 94.264858
converged
Fitting Repeat 5
# weights: 305
initial value 118.012879
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 97.873213
final value 94.312036
converged
Fitting Repeat 2
# weights: 507
initial value 119.099506
iter 10 value 94.433817
iter 10 value 94.433816
iter 10 value 94.433816
final value 94.433816
converged
Fitting Repeat 3
# weights: 507
initial value 110.931250
final value 94.443243
converged
Fitting Repeat 4
# weights: 507
initial value 98.686712
final value 94.443243
converged
Fitting Repeat 5
# weights: 507
initial value 98.118038
iter 10 value 94.324994
iter 20 value 94.323863
final value 94.323810
converged
Fitting Repeat 1
# weights: 103
initial value 100.343802
iter 10 value 94.492299
iter 20 value 88.773544
iter 30 value 85.389552
iter 40 value 85.320028
iter 50 value 82.961037
iter 60 value 82.762309
iter 70 value 82.752079
iter 80 value 82.709841
iter 90 value 82.598164
final value 82.594913
converged
Fitting Repeat 2
# weights: 103
initial value 100.724696
iter 10 value 94.486847
iter 20 value 93.745791
iter 30 value 92.944923
iter 40 value 85.620523
iter 50 value 82.998928
iter 60 value 82.792364
iter 70 value 82.758259
iter 80 value 82.726191
iter 90 value 82.620193
iter 100 value 82.595618
final value 82.595618
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 102.956962
iter 10 value 94.417742
iter 20 value 89.661485
iter 30 value 85.867941
iter 40 value 83.053528
iter 50 value 82.420394
iter 60 value 82.353929
iter 70 value 82.347971
iter 80 value 82.334414
iter 90 value 82.237605
iter 100 value 82.196658
final value 82.196658
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 98.502779
iter 10 value 94.452764
iter 20 value 93.852244
iter 30 value 91.605758
iter 40 value 88.596907
iter 50 value 86.554618
iter 60 value 83.536639
iter 70 value 82.679915
iter 80 value 81.292365
iter 90 value 81.224353
iter 100 value 81.214088
final value 81.214088
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 109.768685
iter 10 value 94.353525
iter 20 value 90.314333
iter 30 value 86.931519
iter 40 value 84.663307
iter 50 value 82.959748
iter 60 value 82.772454
iter 70 value 82.742824
iter 80 value 82.595460
final value 82.594914
converged
Fitting Repeat 1
# weights: 305
initial value 133.232299
iter 10 value 93.193536
iter 20 value 86.768013
iter 30 value 86.149252
iter 40 value 83.512464
iter 50 value 83.000665
iter 60 value 82.956777
iter 70 value 82.847765
iter 80 value 81.975398
iter 90 value 81.146345
iter 100 value 80.582653
final value 80.582653
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 111.695489
iter 10 value 93.945323
iter 20 value 87.282671
iter 30 value 86.970814
iter 40 value 86.754894
iter 50 value 85.837579
iter 60 value 85.635520
iter 70 value 85.480627
iter 80 value 85.179888
iter 90 value 83.562271
iter 100 value 81.330442
final value 81.330442
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 107.111461
iter 10 value 94.477947
iter 20 value 93.723382
iter 30 value 89.809833
iter 40 value 88.083366
iter 50 value 84.235597
iter 60 value 82.045073
iter 70 value 81.356400
iter 80 value 81.057759
iter 90 value 80.917545
iter 100 value 80.435004
final value 80.435004
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 100.553325
iter 10 value 94.409021
iter 20 value 86.542648
iter 30 value 84.998129
iter 40 value 82.854376
iter 50 value 81.185967
iter 60 value 80.696293
iter 70 value 80.491024
iter 80 value 80.233952
iter 90 value 80.177441
iter 100 value 80.148084
final value 80.148084
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 105.704897
iter 10 value 94.918867
iter 20 value 89.458467
iter 30 value 87.737620
iter 40 value 86.575941
iter 50 value 84.677646
iter 60 value 84.266479
iter 70 value 82.184129
iter 80 value 81.390273
iter 90 value 80.763415
iter 100 value 80.504033
final value 80.504033
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 126.665860
iter 10 value 94.313345
iter 20 value 87.610766
iter 30 value 86.579609
iter 40 value 85.050005
iter 50 value 83.675268
iter 60 value 82.372425
iter 70 value 82.158286
iter 80 value 81.909787
iter 90 value 81.010164
iter 100 value 80.538717
final value 80.538717
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 107.213648
iter 10 value 93.004367
iter 20 value 92.267161
iter 30 value 91.221564
iter 40 value 90.802041
iter 50 value 90.394879
iter 60 value 88.284978
iter 70 value 84.336093
iter 80 value 81.648787
iter 90 value 81.028858
iter 100 value 80.547062
final value 80.547062
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 108.301701
iter 10 value 94.072501
iter 20 value 84.323089
iter 30 value 83.466848
iter 40 value 82.579200
iter 50 value 81.949125
iter 60 value 81.351585
iter 70 value 80.965180
iter 80 value 80.374813
iter 90 value 80.157663
iter 100 value 80.145821
final value 80.145821
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 109.151476
iter 10 value 94.512339
iter 20 value 94.204070
iter 30 value 93.246799
iter 40 value 89.752850
iter 50 value 84.359279
iter 60 value 81.700953
iter 70 value 80.856965
iter 80 value 80.770853
iter 90 value 80.645951
iter 100 value 80.589812
final value 80.589812
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 107.316446
iter 10 value 95.946378
iter 20 value 94.475183
iter 30 value 88.583865
iter 40 value 86.637530
iter 50 value 86.081030
iter 60 value 83.946091
iter 70 value 83.164507
iter 80 value 82.338563
iter 90 value 81.081002
iter 100 value 80.885319
final value 80.885319
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 100.294144
final value 94.495512
converged
Fitting Repeat 2
# weights: 103
initial value 101.064182
final value 94.485654
converged
Fitting Repeat 3
# weights: 103
initial value 95.253594
final value 94.485860
converged
Fitting Repeat 4
# weights: 103
initial value 95.862166
final value 94.485999
converged
Fitting Repeat 5
# weights: 103
initial value 95.067812
final value 94.485744
converged
Fitting Repeat 1
# weights: 305
initial value 131.674123
iter 10 value 94.489499
iter 20 value 94.484302
iter 30 value 90.290258
iter 40 value 87.801608
iter 50 value 85.299975
iter 60 value 83.793256
iter 70 value 83.792401
iter 80 value 83.618828
iter 90 value 83.559129
iter 100 value 83.550138
final value 83.550138
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 95.317582
iter 10 value 94.485420
iter 20 value 94.166892
iter 30 value 85.660118
iter 40 value 84.693130
iter 50 value 83.581159
iter 60 value 83.576706
iter 70 value 82.874178
iter 80 value 82.865126
iter 90 value 82.289483
iter 100 value 80.809734
final value 80.809734
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 100.919194
iter 10 value 94.488754
final value 94.484223
converged
Fitting Repeat 4
# weights: 305
initial value 95.949802
iter 10 value 86.454047
iter 20 value 86.335216
iter 30 value 86.003086
iter 40 value 85.869443
iter 50 value 85.866548
iter 60 value 85.862650
iter 70 value 82.051691
iter 80 value 81.650818
iter 90 value 79.874799
iter 100 value 79.123610
final value 79.123610
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 99.107007
iter 10 value 91.430551
iter 20 value 90.684023
iter 30 value 87.303425
iter 40 value 86.231912
iter 50 value 86.231287
iter 60 value 85.855388
iter 70 value 84.458210
iter 80 value 79.377300
iter 90 value 78.676577
iter 100 value 78.418960
final value 78.418960
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 102.310332
iter 10 value 82.872710
iter 20 value 82.294104
iter 30 value 82.274394
iter 40 value 82.273079
iter 50 value 82.061833
iter 60 value 81.596116
iter 70 value 81.574776
iter 80 value 81.573239
iter 90 value 81.546185
iter 100 value 80.311009
final value 80.311009
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 115.833525
iter 10 value 94.488843
iter 20 value 94.219459
iter 30 value 94.143022
final value 94.142989
converged
Fitting Repeat 3
# weights: 507
initial value 101.198886
iter 10 value 94.483002
iter 20 value 94.419380
iter 30 value 88.634130
iter 40 value 88.381459
iter 50 value 88.380213
iter 60 value 88.093463
iter 70 value 85.380300
iter 80 value 84.956239
iter 90 value 84.955464
final value 84.955104
converged
Fitting Repeat 4
# weights: 507
initial value 107.161015
iter 10 value 92.284824
iter 20 value 91.962046
iter 30 value 86.195131
iter 40 value 84.718268
iter 50 value 83.818653
iter 60 value 83.797439
iter 70 value 83.755974
iter 80 value 83.745882
iter 90 value 83.735109
iter 100 value 83.707040
final value 83.707040
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 109.078568
iter 10 value 94.492449
iter 20 value 94.484597
iter 30 value 94.273487
final value 94.263488
converged
Fitting Repeat 1
# weights: 103
initial value 100.932021
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 97.040801
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 97.132874
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 100.593930
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 97.537988
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 111.265455
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 95.798280
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 99.431856
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 98.665493
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 104.915658
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 98.025365
final value 93.915746
converged
Fitting Repeat 2
# weights: 507
initial value 98.243613
final value 94.052910
converged
Fitting Repeat 3
# weights: 507
initial value 100.566033
final value 93.915746
converged
Fitting Repeat 4
# weights: 507
initial value 94.337343
final value 94.052910
converged
Fitting Repeat 5
# weights: 507
initial value 98.447772
iter 10 value 93.954865
final value 93.954846
converged
Fitting Repeat 1
# weights: 103
initial value 100.320452
iter 10 value 94.025020
iter 20 value 93.736471
iter 30 value 92.487468
iter 40 value 90.045142
iter 50 value 89.269186
iter 60 value 88.898083
iter 70 value 86.297738
iter 80 value 86.110970
iter 90 value 86.073341
iter 100 value 86.034828
final value 86.034828
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 102.944187
iter 10 value 93.993243
iter 20 value 87.085388
iter 30 value 86.552043
iter 40 value 86.017934
iter 50 value 85.839289
iter 60 value 84.933848
iter 70 value 84.534984
iter 80 value 84.320159
final value 84.320030
converged
Fitting Repeat 3
# weights: 103
initial value 98.960805
iter 10 value 93.925385
iter 20 value 93.803450
iter 30 value 93.791183
iter 40 value 93.761773
iter 50 value 93.730506
iter 60 value 89.988934
iter 70 value 87.140203
iter 80 value 86.231344
iter 90 value 86.115943
iter 100 value 86.043539
final value 86.043539
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 101.230342
iter 10 value 93.360772
iter 20 value 86.259143
iter 30 value 84.985000
iter 40 value 84.654316
iter 50 value 84.538165
final value 84.536517
converged
Fitting Repeat 5
# weights: 103
initial value 101.660332
iter 10 value 93.863184
iter 20 value 93.161308
iter 30 value 89.734542
iter 40 value 88.280625
iter 50 value 87.852297
iter 60 value 86.654605
iter 70 value 84.739506
iter 80 value 84.537432
final value 84.536517
converged
Fitting Repeat 1
# weights: 305
initial value 108.380955
iter 10 value 95.677846
iter 20 value 93.665975
iter 30 value 88.675357
iter 40 value 86.856239
iter 50 value 86.465373
iter 60 value 85.368540
iter 70 value 84.553869
iter 80 value 84.402944
iter 90 value 83.986157
iter 100 value 83.522164
final value 83.522164
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 108.560816
iter 10 value 94.121443
iter 20 value 89.813878
iter 30 value 87.762886
iter 40 value 86.619583
iter 50 value 84.945351
iter 60 value 84.036593
iter 70 value 83.856476
iter 80 value 83.695574
iter 90 value 83.512590
iter 100 value 83.344826
final value 83.344826
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 99.975903
iter 10 value 94.117337
iter 20 value 87.379660
iter 30 value 86.718844
iter 40 value 86.654048
iter 50 value 86.570647
iter 60 value 85.846397
iter 70 value 84.598325
iter 80 value 84.006859
iter 90 value 83.425753
iter 100 value 82.867231
final value 82.867231
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 106.323970
iter 10 value 94.010653
iter 20 value 91.941352
iter 30 value 90.588074
iter 40 value 87.512563
iter 50 value 85.540736
iter 60 value 83.897831
iter 70 value 83.331297
iter 80 value 83.140395
iter 90 value 82.998566
iter 100 value 82.797236
final value 82.797236
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 105.988465
iter 10 value 93.964069
iter 20 value 88.334901
iter 30 value 87.426720
iter 40 value 86.989630
iter 50 value 84.497548
iter 60 value 83.718065
iter 70 value 83.369661
iter 80 value 83.075968
iter 90 value 83.066788
iter 100 value 82.760860
final value 82.760860
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 104.940723
iter 10 value 94.220660
iter 20 value 90.182734
iter 30 value 86.635863
iter 40 value 85.989732
iter 50 value 84.397721
iter 60 value 84.153456
iter 70 value 83.393349
iter 80 value 83.226666
iter 90 value 82.801332
iter 100 value 82.693331
final value 82.693331
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 122.027626
iter 10 value 93.990608
iter 20 value 86.000065
iter 30 value 84.274202
iter 40 value 83.586916
iter 50 value 83.050952
iter 60 value 82.643613
iter 70 value 82.605351
iter 80 value 82.589360
iter 90 value 82.578189
iter 100 value 82.529539
final value 82.529539
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 131.133262
iter 10 value 94.374933
iter 20 value 88.789666
iter 30 value 86.948834
iter 40 value 86.057188
iter 50 value 84.053321
iter 60 value 83.620422
iter 70 value 83.396084
iter 80 value 82.844545
iter 90 value 82.539970
iter 100 value 82.504424
final value 82.504424
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 108.059692
iter 10 value 94.008560
iter 20 value 93.060266
iter 30 value 90.689855
iter 40 value 84.602092
iter 50 value 84.054024
iter 60 value 83.792582
iter 70 value 83.429974
iter 80 value 82.943025
iter 90 value 82.617378
iter 100 value 82.534583
final value 82.534583
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 114.277144
iter 10 value 96.084491
iter 20 value 87.173882
iter 30 value 86.374307
iter 40 value 85.956187
iter 50 value 85.854297
iter 60 value 85.207777
iter 70 value 84.523013
iter 80 value 83.982557
iter 90 value 83.339653
iter 100 value 83.320946
final value 83.320946
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 102.416125
final value 93.914436
converged
Fitting Repeat 2
# weights: 103
initial value 100.530109
final value 94.054619
converged
Fitting Repeat 3
# weights: 103
initial value 101.157253
final value 94.054542
converged
Fitting Repeat 4
# weights: 103
initial value 99.051776
final value 93.765407
converged
Fitting Repeat 5
# weights: 103
initial value 96.084821
final value 93.917520
converged
Fitting Repeat 1
# weights: 305
initial value 96.833722
iter 10 value 94.057519
iter 20 value 94.052944
iter 30 value 93.715339
iter 40 value 88.700030
iter 50 value 85.647793
iter 60 value 84.779572
iter 70 value 84.577577
iter 80 value 84.545327
iter 80 value 84.545326
iter 90 value 84.543605
iter 100 value 84.543400
final value 84.543400
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 110.731636
iter 10 value 91.803883
iter 20 value 91.739900
iter 30 value 91.739352
iter 40 value 91.738493
iter 50 value 91.737185
iter 60 value 91.735917
iter 70 value 91.735410
iter 80 value 91.735218
final value 91.735143
converged
Fitting Repeat 3
# weights: 305
initial value 134.800501
iter 10 value 94.057994
final value 94.053406
converged
Fitting Repeat 4
# weights: 305
initial value 120.390464
iter 10 value 93.768629
iter 20 value 93.766282
iter 30 value 93.760347
iter 40 value 93.757355
iter 50 value 90.256911
iter 60 value 86.195123
iter 70 value 86.182347
final value 86.181716
converged
Fitting Repeat 5
# weights: 305
initial value 99.791238
iter 10 value 94.057904
iter 20 value 93.735047
iter 30 value 86.935174
iter 40 value 86.934837
iter 40 value 86.934837
iter 50 value 86.543640
iter 60 value 86.543435
iter 60 value 86.543434
iter 60 value 86.543434
final value 86.543434
converged
Fitting Repeat 1
# weights: 507
initial value 105.455567
iter 10 value 94.064563
iter 20 value 94.053112
iter 30 value 93.752457
final value 93.705080
converged
Fitting Repeat 2
# weights: 507
initial value 95.045856
iter 10 value 94.060386
iter 20 value 93.148940
iter 30 value 86.952204
iter 40 value 86.936908
iter 50 value 86.936058
iter 60 value 86.935544
iter 70 value 86.935089
iter 80 value 86.283227
iter 90 value 83.864511
iter 100 value 82.194101
final value 82.194101
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 111.581768
iter 10 value 93.615057
iter 20 value 93.575530
iter 30 value 89.192834
iter 40 value 86.991309
iter 50 value 86.921645
final value 86.920395
converged
Fitting Repeat 4
# weights: 507
initial value 105.463398
iter 10 value 93.772604
iter 20 value 93.765517
iter 30 value 91.638889
iter 40 value 91.247262
iter 50 value 91.175946
iter 60 value 91.171992
final value 91.171935
converged
Fitting Repeat 5
# weights: 507
initial value 116.777141
iter 10 value 93.924009
iter 20 value 93.798048
iter 30 value 89.076233
iter 40 value 88.706331
final value 88.706167
converged
Fitting Repeat 1
# weights: 507
initial value 135.012263
iter 10 value 118.756487
iter 20 value 107.316003
iter 30 value 105.930962
iter 40 value 105.421463
iter 50 value 105.162071
iter 60 value 104.809406
iter 70 value 104.748291
iter 80 value 104.696245
iter 90 value 103.935796
iter 100 value 103.346886
final value 103.346886
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 135.037525
iter 10 value 117.846235
iter 20 value 117.606335
iter 30 value 116.323995
iter 40 value 109.266489
iter 50 value 106.714496
iter 60 value 105.242196
iter 70 value 104.380415
iter 80 value 104.245683
iter 90 value 103.195108
iter 100 value 102.918942
final value 102.918942
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 150.060395
iter 10 value 117.311345
iter 20 value 107.772899
iter 30 value 106.682926
iter 40 value 106.537130
iter 50 value 102.830456
iter 60 value 101.210719
iter 70 value 100.988949
iter 80 value 100.947281
iter 90 value 100.717034
iter 100 value 100.551067
final value 100.551067
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 130.951953
iter 10 value 117.810905
iter 20 value 108.352514
iter 30 value 106.243194
iter 40 value 103.646806
iter 50 value 103.076980
iter 60 value 102.346206
iter 70 value 101.946898
iter 80 value 101.871858
iter 90 value 101.851859
iter 100 value 101.808664
final value 101.808664
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 149.693655
iter 10 value 115.285543
iter 20 value 111.575863
iter 30 value 111.012650
iter 40 value 108.133764
iter 50 value 105.688059
iter 60 value 104.873774
iter 70 value 103.662146
iter 80 value 103.253480
iter 90 value 102.809083
iter 100 value 102.309617
final value 102.309617
stopped after 100 iterations
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
RUNIT TEST PROTOCOL -- Tue Apr 12 21:20:50 2022
***********************************************
Number of test functions: 8
Number of errors: 0
Number of failures: 0
1 Test Suite :
HPiP RUnit Tests - 8 test functions, 0 errors, 0 failures
Number of test functions: 8
Number of errors: 0
Number of failures: 0
Warning messages:
1: The `.data` argument of `add_column()` must have unique names as of tibble 3.0.0.
Use `.name_repair = "minimal"`.
This warning is displayed once every 8 hours.
Call `lifecycle::last_lifecycle_warnings()` to see where this warning was generated.
2: `repeats` has no meaning for this resampling method.
3: executing %dopar% sequentially: no parallel backend registered
>
>
>
>
> proc.time()
user system elapsed
73.78 1.67 48.59
|
HPiP.Rcheck/tests_x64/runTests.Rout
R version 4.1.3 (2022-03-10) -- "One Push-Up"
Copyright (C) 2022 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64 (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> BiocGenerics:::testPackage('HPiP')
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
avNNet
Loading required package: ggplot2
Loading required package: lattice
Fitting Repeat 1
# weights: 103
initial value 95.981120
iter 10 value 88.631249
iter 20 value 85.356059
iter 30 value 85.146555
iter 40 value 85.145639
iter 40 value 85.145638
iter 40 value 85.145638
final value 85.145638
converged
Fitting Repeat 2
# weights: 103
initial value 114.581580
iter 10 value 93.493988
iter 20 value 93.262930
final value 92.945355
converged
Fitting Repeat 3
# weights: 103
initial value 97.839945
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 98.121816
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 101.108027
iter 10 value 92.893450
final value 92.878839
converged
Fitting Repeat 1
# weights: 305
initial value 109.017330
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 98.026434
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 104.540318
iter 10 value 94.052915
iter 10 value 94.052914
iter 10 value 94.052914
final value 94.052914
converged
Fitting Repeat 4
# weights: 305
initial value 98.831762
final value 94.052911
converged
Fitting Repeat 5
# weights: 305
initial value 103.129835
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 95.151299
iter 10 value 92.945355
iter 10 value 92.945355
iter 10 value 92.945355
final value 92.945355
converged
Fitting Repeat 2
# weights: 507
initial value 99.570657
iter 10 value 93.347629
iter 20 value 92.855550
final value 92.814053
converged
Fitting Repeat 3
# weights: 507
initial value 103.289108
iter 10 value 92.944705
iter 20 value 92.878841
iter 20 value 92.878841
iter 20 value 92.878841
final value 92.878841
converged
Fitting Repeat 4
# weights: 507
initial value 106.116381
iter 10 value 94.052911
final value 94.052910
converged
Fitting Repeat 5
# weights: 507
initial value 107.692610
final value 94.052910
converged
Fitting Repeat 1
# weights: 103
initial value 111.753088
iter 10 value 94.054839
iter 20 value 93.613412
iter 30 value 93.456488
iter 40 value 93.186798
iter 50 value 92.623828
iter 60 value 87.100771
iter 70 value 86.397094
iter 80 value 86.067026
iter 90 value 85.321336
iter 100 value 84.322413
final value 84.322413
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 96.175055
iter 10 value 91.794247
iter 20 value 85.209203
iter 30 value 84.730246
iter 40 value 84.319044
iter 50 value 83.402117
iter 60 value 83.054881
iter 70 value 82.358094
iter 80 value 81.931799
iter 90 value 81.809691
final value 81.809433
converged
Fitting Repeat 3
# weights: 103
initial value 96.862880
iter 10 value 94.056241
iter 20 value 93.304763
iter 30 value 93.268627
iter 40 value 93.246570
iter 50 value 89.533919
iter 60 value 83.846129
iter 70 value 83.227149
iter 80 value 82.686719
iter 90 value 82.512767
iter 100 value 82.198267
final value 82.198267
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 109.621015
iter 10 value 93.323479
iter 20 value 85.792530
iter 30 value 85.122905
iter 40 value 84.794652
iter 50 value 84.127498
iter 60 value 83.926653
iter 70 value 83.917206
final value 83.917205
converged
Fitting Repeat 5
# weights: 103
initial value 97.832890
iter 10 value 94.056489
iter 20 value 86.852276
iter 30 value 83.056306
iter 40 value 82.342820
iter 50 value 82.254773
iter 60 value 82.199720
iter 70 value 82.128215
iter 80 value 82.119815
iter 90 value 82.107950
iter 100 value 82.102944
final value 82.102944
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 120.032434
iter 10 value 94.884228
iter 20 value 93.715500
iter 30 value 93.019567
iter 40 value 90.856053
iter 50 value 87.555257
iter 60 value 87.270041
iter 70 value 87.187554
iter 80 value 84.388490
iter 90 value 82.543476
iter 100 value 81.249412
final value 81.249412
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 103.165486
iter 10 value 94.130757
iter 20 value 92.809409
iter 30 value 89.863747
iter 40 value 86.634467
iter 50 value 83.537972
iter 60 value 82.942916
iter 70 value 82.660400
iter 80 value 81.719626
iter 90 value 81.391080
iter 100 value 81.224907
final value 81.224907
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 116.762088
iter 10 value 93.990843
iter 20 value 84.378799
iter 30 value 83.559726
iter 40 value 83.314497
iter 50 value 83.165597
iter 60 value 82.704977
iter 70 value 82.428180
iter 80 value 82.131727
iter 90 value 82.029531
iter 100 value 81.931886
final value 81.931886
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 103.184629
iter 10 value 94.169540
iter 20 value 93.489693
iter 30 value 93.198094
iter 40 value 84.014682
iter 50 value 83.425311
iter 60 value 83.043987
iter 70 value 82.635083
iter 80 value 82.512481
iter 90 value 82.319513
iter 100 value 82.017642
final value 82.017642
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 104.740215
iter 10 value 93.241495
iter 20 value 89.416982
iter 30 value 88.572630
iter 40 value 88.057735
iter 50 value 83.815033
iter 60 value 82.935381
iter 70 value 82.743634
iter 80 value 81.212271
iter 90 value 81.053992
iter 100 value 80.914589
final value 80.914589
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 105.857384
iter 10 value 94.951493
iter 20 value 93.624417
iter 30 value 92.868423
iter 40 value 87.908973
iter 50 value 86.212103
iter 60 value 83.600750
iter 70 value 82.195853
iter 80 value 81.918786
iter 90 value 81.420898
iter 100 value 81.233274
final value 81.233274
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 137.558764
iter 10 value 98.099519
iter 20 value 94.366685
iter 30 value 93.083363
iter 40 value 93.020614
iter 50 value 90.646431
iter 60 value 83.951625
iter 70 value 83.585661
iter 80 value 83.018132
iter 90 value 82.258271
iter 100 value 81.716560
final value 81.716560
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 111.745553
iter 10 value 98.357329
iter 20 value 92.845101
iter 30 value 86.797640
iter 40 value 86.339941
iter 50 value 85.861620
iter 60 value 82.688205
iter 70 value 81.851136
iter 80 value 80.987741
iter 90 value 80.905818
iter 100 value 80.750977
final value 80.750977
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 107.339456
iter 10 value 95.463155
iter 20 value 92.475503
iter 30 value 88.857001
iter 40 value 86.766705
iter 50 value 83.261576
iter 60 value 81.516167
iter 70 value 80.658561
iter 80 value 80.462553
iter 90 value 80.453412
iter 100 value 80.428519
final value 80.428519
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 124.338282
iter 10 value 94.010411
iter 20 value 91.979695
iter 30 value 89.685730
iter 40 value 87.365840
iter 50 value 85.120159
iter 60 value 83.455325
iter 70 value 82.419027
iter 80 value 81.922646
iter 90 value 81.625969
iter 100 value 81.157221
final value 81.157221
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 97.329325
final value 94.054481
converged
Fitting Repeat 2
# weights: 103
initial value 102.482421
final value 94.054697
converged
Fitting Repeat 3
# weights: 103
initial value 94.237441
final value 94.054717
converged
Fitting Repeat 4
# weights: 103
initial value 103.200775
final value 94.054488
converged
Fitting Repeat 5
# weights: 103
initial value 97.580705
iter 10 value 92.947382
iter 20 value 92.946105
iter 30 value 92.816314
iter 40 value 92.812532
iter 50 value 92.534340
iter 60 value 91.186058
iter 70 value 86.431604
iter 80 value 83.093309
iter 90 value 83.019114
iter 100 value 83.018237
final value 83.018237
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 97.641948
iter 10 value 92.887973
iter 20 value 92.884486
iter 30 value 92.817528
iter 40 value 92.816849
iter 50 value 92.814988
iter 60 value 92.442164
iter 70 value 86.209203
iter 80 value 86.203556
iter 90 value 86.144505
iter 100 value 86.142958
final value 86.142958
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 100.815872
iter 10 value 92.258697
iter 20 value 91.692938
iter 30 value 89.158589
iter 40 value 87.790377
iter 50 value 82.329245
iter 60 value 81.586836
iter 70 value 80.796320
iter 80 value 80.467908
iter 90 value 80.343819
iter 100 value 80.108908
final value 80.108908
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 98.029024
iter 10 value 93.742524
iter 20 value 93.736282
iter 30 value 91.103017
iter 40 value 91.074087
iter 50 value 91.073687
iter 60 value 91.070007
iter 70 value 90.997371
iter 80 value 90.824500
iter 80 value 90.824500
iter 80 value 90.824500
final value 90.824500
converged
Fitting Repeat 4
# weights: 305
initial value 96.688753
iter 10 value 94.057692
iter 20 value 94.052932
iter 30 value 92.946049
final value 92.946048
converged
Fitting Repeat 5
# weights: 305
initial value 109.702347
iter 10 value 94.057830
iter 20 value 94.052920
iter 30 value 93.965232
final value 92.891527
converged
Fitting Repeat 1
# weights: 507
initial value 94.256579
iter 10 value 90.963935
iter 20 value 90.929620
iter 30 value 90.926379
iter 40 value 90.923359
iter 50 value 85.564789
iter 60 value 83.458578
iter 70 value 83.422960
final value 83.422529
converged
Fitting Repeat 2
# weights: 507
initial value 111.828969
iter 10 value 93.196731
iter 20 value 87.005096
iter 30 value 86.396823
iter 40 value 86.390137
iter 50 value 85.751332
iter 60 value 85.545842
iter 70 value 85.544228
iter 80 value 85.539392
final value 85.537334
converged
Fitting Repeat 3
# weights: 507
initial value 98.815937
iter 10 value 94.099763
iter 20 value 94.088333
iter 30 value 88.820927
iter 40 value 88.171095
iter 50 value 82.531638
iter 60 value 82.349690
iter 70 value 82.331368
iter 80 value 82.228602
iter 90 value 82.225175
iter 100 value 82.167165
final value 82.167165
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 96.504708
iter 10 value 92.955936
iter 20 value 92.952737
iter 30 value 92.881762
iter 40 value 92.880923
iter 50 value 91.680490
iter 60 value 87.284807
iter 70 value 80.516771
iter 80 value 80.397525
iter 90 value 80.382749
final value 80.382569
converged
Fitting Repeat 5
# weights: 507
initial value 97.136308
iter 10 value 92.954168
iter 20 value 92.930855
iter 30 value 92.888660
iter 40 value 92.862519
iter 50 value 87.714562
iter 60 value 84.531226
iter 70 value 84.367453
iter 80 value 84.004943
iter 90 value 82.457173
iter 100 value 81.412555
final value 81.412555
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 97.642972
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 94.549244
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 100.865050
final value 94.409357
converged
Fitting Repeat 4
# weights: 103
initial value 98.827064
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 96.168967
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 95.456742
iter 10 value 85.793547
final value 85.647280
converged
Fitting Repeat 2
# weights: 305
initial value 96.549478
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 94.879583
iter 10 value 94.052440
final value 94.052435
converged
Fitting Repeat 4
# weights: 305
initial value 101.387093
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 100.633899
iter 10 value 94.026544
final value 94.026542
converged
Fitting Repeat 1
# weights: 507
initial value 98.182573
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 99.395409
final value 94.026542
converged
Fitting Repeat 3
# weights: 507
initial value 98.457152
final value 94.409356
converged
Fitting Repeat 4
# weights: 507
initial value 97.871258
iter 10 value 90.427640
iter 20 value 88.464016
iter 30 value 88.339496
iter 40 value 88.338172
final value 88.338164
converged
Fitting Repeat 5
# weights: 507
initial value 114.328937
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 100.804812
iter 10 value 93.953372
iter 20 value 90.112879
iter 30 value 87.615581
iter 40 value 87.189628
iter 50 value 84.109264
iter 60 value 81.612777
iter 70 value 80.561498
iter 80 value 80.146791
iter 90 value 80.135556
iter 100 value 80.121120
final value 80.121120
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 98.467618
iter 10 value 91.561218
iter 20 value 83.595044
iter 30 value 82.864135
iter 40 value 82.591575
iter 50 value 81.855281
iter 60 value 81.517829
iter 70 value 81.493171
iter 80 value 81.486354
final value 81.486146
converged
Fitting Repeat 3
# weights: 103
initial value 99.711685
iter 10 value 94.429765
iter 20 value 92.874381
iter 30 value 83.616222
iter 40 value 82.919347
iter 50 value 82.215947
iter 60 value 81.849841
iter 70 value 81.825868
iter 80 value 81.702020
iter 90 value 81.605563
final value 81.604873
converged
Fitting Repeat 4
# weights: 103
initial value 105.198970
iter 10 value 93.240134
iter 20 value 89.769126
iter 30 value 89.362173
iter 40 value 85.283568
iter 50 value 84.915833
iter 60 value 84.297771
iter 70 value 83.876655
iter 80 value 83.817456
final value 83.817454
converged
Fitting Repeat 5
# weights: 103
initial value 97.563357
iter 10 value 94.485908
iter 20 value 88.923275
iter 30 value 84.151480
iter 40 value 81.743815
iter 50 value 80.313455
iter 60 value 80.261556
iter 70 value 80.138562
iter 80 value 80.121277
final value 80.121112
converged
Fitting Repeat 1
# weights: 305
initial value 110.915959
iter 10 value 94.557020
iter 20 value 93.979501
iter 30 value 87.310413
iter 40 value 84.268696
iter 50 value 81.510748
iter 60 value 80.216412
iter 70 value 79.718306
iter 80 value 79.224370
iter 90 value 78.774622
iter 100 value 78.663738
final value 78.663738
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 101.725478
iter 10 value 95.312630
iter 20 value 93.800865
iter 30 value 87.364904
iter 40 value 86.877679
iter 50 value 84.792379
iter 60 value 82.766751
iter 70 value 81.435925
iter 80 value 80.485085
iter 90 value 80.297402
iter 100 value 80.140702
final value 80.140702
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 100.399523
iter 10 value 92.094955
iter 20 value 85.818004
iter 30 value 82.665141
iter 40 value 82.541741
iter 50 value 82.090197
iter 60 value 79.870040
iter 70 value 79.104855
iter 80 value 78.970074
iter 90 value 78.559496
iter 100 value 78.369865
final value 78.369865
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 111.261977
iter 10 value 94.510948
iter 20 value 93.630187
iter 30 value 83.896774
iter 40 value 83.000670
iter 50 value 82.455193
iter 60 value 81.880955
iter 70 value 81.738695
iter 80 value 81.272491
iter 90 value 80.884425
iter 100 value 80.518385
final value 80.518385
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 104.408234
iter 10 value 93.611385
iter 20 value 92.259526
iter 30 value 91.658307
iter 40 value 88.829235
iter 50 value 86.723564
iter 60 value 85.221789
iter 70 value 82.636172
iter 80 value 80.545009
iter 90 value 79.970679
iter 100 value 79.745593
final value 79.745593
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 103.667559
iter 10 value 95.129167
iter 20 value 91.132134
iter 30 value 86.296416
iter 40 value 80.573193
iter 50 value 79.653783
iter 60 value 79.082149
iter 70 value 78.939057
iter 80 value 78.629873
iter 90 value 78.550894
iter 100 value 78.464899
final value 78.464899
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 112.485382
iter 10 value 98.672106
iter 20 value 89.469273
iter 30 value 82.094527
iter 40 value 80.465403
iter 50 value 79.242732
iter 60 value 78.986897
iter 70 value 78.908420
iter 80 value 78.798076
iter 90 value 78.781067
iter 100 value 78.749563
final value 78.749563
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 109.847933
iter 10 value 94.499827
iter 20 value 89.228908
iter 30 value 85.703810
iter 40 value 83.607119
iter 50 value 81.905658
iter 60 value 79.513321
iter 70 value 79.213103
iter 80 value 79.088422
iter 90 value 79.052760
iter 100 value 78.813278
final value 78.813278
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 110.799503
iter 10 value 95.883843
iter 20 value 92.849921
iter 30 value 88.392457
iter 40 value 85.566442
iter 50 value 83.671067
iter 60 value 82.195345
iter 70 value 81.370721
iter 80 value 80.240503
iter 90 value 79.252035
iter 100 value 78.614425
final value 78.614425
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 113.730804
iter 10 value 95.339122
iter 20 value 92.916164
iter 30 value 92.449951
iter 40 value 89.788765
iter 50 value 83.787635
iter 60 value 82.006028
iter 70 value 81.102701
iter 80 value 80.580748
iter 90 value 80.424294
iter 100 value 80.171445
final value 80.171445
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 95.497944
final value 94.485868
converged
Fitting Repeat 2
# weights: 103
initial value 96.285894
final value 94.485710
converged
Fitting Repeat 3
# weights: 103
initial value 100.539073
final value 94.485676
converged
Fitting Repeat 4
# weights: 103
initial value 98.358600
iter 10 value 94.028348
iter 20 value 94.027371
iter 30 value 89.699939
iter 40 value 86.568193
iter 50 value 86.261246
iter 50 value 86.261245
iter 50 value 86.261245
final value 86.261245
converged
Fitting Repeat 5
# weights: 103
initial value 96.808574
final value 94.485855
converged
Fitting Repeat 1
# weights: 305
initial value 95.442044
iter 10 value 94.490426
iter 20 value 94.485343
iter 30 value 94.027856
iter 40 value 94.026917
iter 50 value 94.026735
iter 50 value 94.026735
final value 94.026735
converged
Fitting Repeat 2
# weights: 305
initial value 105.379098
iter 10 value 94.488860
iter 20 value 94.484580
iter 20 value 94.484580
iter 20 value 94.484580
final value 94.484580
converged
Fitting Repeat 3
# weights: 305
initial value 102.233020
iter 10 value 94.031819
iter 20 value 93.982442
final value 93.976840
converged
Fitting Repeat 4
# weights: 305
initial value 99.607195
iter 10 value 94.489110
iter 20 value 94.314644
iter 30 value 82.576797
iter 40 value 82.278488
iter 50 value 82.278030
iter 60 value 82.277072
iter 60 value 82.277072
final value 82.277072
converged
Fitting Repeat 5
# weights: 305
initial value 95.246976
iter 10 value 94.486676
iter 20 value 89.455195
iter 30 value 82.796630
iter 40 value 82.179004
iter 50 value 82.168568
final value 82.166198
converged
Fitting Repeat 1
# weights: 507
initial value 101.984822
iter 10 value 94.492269
iter 20 value 94.298162
iter 30 value 91.070381
iter 40 value 87.291131
iter 50 value 87.204560
iter 60 value 86.096549
iter 70 value 86.092742
iter 80 value 85.112585
iter 90 value 84.692354
iter 100 value 84.641639
final value 84.641639
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 99.963433
iter 10 value 94.034423
iter 20 value 94.029413
final value 94.027936
converged
Fitting Repeat 3
# weights: 507
initial value 108.701197
iter 10 value 94.035477
iter 20 value 94.027320
iter 30 value 92.987728
iter 40 value 87.246768
iter 50 value 81.980777
iter 60 value 81.937082
final value 81.935615
converged
Fitting Repeat 4
# weights: 507
initial value 102.507805
iter 10 value 94.418366
iter 20 value 94.034410
iter 30 value 94.030434
iter 40 value 94.007549
iter 50 value 94.005122
iter 60 value 84.757062
iter 70 value 82.907824
iter 80 value 80.316578
iter 90 value 79.177804
iter 100 value 78.749104
final value 78.749104
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 95.836860
iter 10 value 94.491348
iter 20 value 89.225453
iter 30 value 84.627528
iter 40 value 84.511996
iter 50 value 84.218136
iter 60 value 84.140674
final value 84.128638
converged
Fitting Repeat 1
# weights: 103
initial value 101.985449
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 100.274998
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 97.994164
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 98.015751
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 100.179504
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 96.336216
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 95.163348
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 103.272731
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 114.573247
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 105.205258
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 100.639412
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 95.666689
final value 93.811828
converged
Fitting Repeat 3
# weights: 507
initial value 118.276308
final value 93.811828
converged
Fitting Repeat 4
# weights: 507
initial value 102.636534
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 95.700319
iter 10 value 93.706293
final value 93.705856
converged
Fitting Repeat 1
# weights: 103
initial value 96.637271
iter 10 value 93.987115
iter 20 value 89.562028
iter 30 value 88.593546
iter 40 value 87.672360
iter 50 value 85.434745
iter 60 value 84.535973
iter 70 value 84.398180
final value 84.397772
converged
Fitting Repeat 2
# weights: 103
initial value 96.996173
iter 10 value 94.451726
iter 20 value 91.230342
iter 30 value 90.715141
iter 40 value 86.973581
iter 50 value 85.931573
iter 60 value 85.737219
iter 70 value 85.720505
final value 85.715548
converged
Fitting Repeat 3
# weights: 103
initial value 101.585282
iter 10 value 94.477022
iter 20 value 92.729376
iter 30 value 92.098707
iter 40 value 89.657759
iter 50 value 88.285504
iter 60 value 87.202629
iter 70 value 86.562220
iter 80 value 85.874692
iter 90 value 84.770759
iter 100 value 84.764153
final value 84.764153
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 96.661132
iter 10 value 94.567072
iter 20 value 87.418665
iter 30 value 86.984180
iter 40 value 86.572383
iter 50 value 85.412731
iter 60 value 85.355152
iter 70 value 85.325878
iter 80 value 85.310922
final value 85.310910
converged
Fitting Repeat 5
# weights: 103
initial value 104.730162
iter 10 value 94.376519
iter 20 value 91.393306
iter 30 value 90.458544
iter 40 value 88.390498
iter 50 value 86.217548
iter 60 value 85.701927
iter 70 value 85.455658
iter 80 value 85.350442
iter 90 value 85.193770
iter 100 value 85.088054
final value 85.088054
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 101.968108
iter 10 value 94.724622
iter 20 value 92.715081
iter 30 value 89.016921
iter 40 value 87.560069
iter 50 value 87.089105
iter 60 value 85.342252
iter 70 value 83.748810
iter 80 value 82.768874
iter 90 value 82.124409
iter 100 value 81.993669
final value 81.993669
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 114.302512
iter 10 value 94.023852
iter 20 value 93.839617
iter 30 value 91.951187
iter 40 value 87.707506
iter 50 value 86.834130
iter 60 value 86.038990
iter 70 value 84.243223
iter 80 value 82.965522
iter 90 value 82.606815
iter 100 value 82.214041
final value 82.214041
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 101.615653
iter 10 value 94.490254
iter 20 value 87.371544
iter 30 value 83.912497
iter 40 value 83.399146
iter 50 value 83.067594
iter 60 value 82.537980
iter 70 value 82.438481
iter 80 value 81.933246
iter 90 value 80.992216
iter 100 value 80.861343
final value 80.861343
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 117.997592
iter 10 value 94.693713
iter 20 value 94.113615
iter 30 value 94.044231
iter 40 value 90.919993
iter 50 value 88.531031
iter 60 value 87.909956
iter 70 value 87.408568
iter 80 value 86.317964
iter 90 value 82.755182
iter 100 value 82.321372
final value 82.321372
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 101.975273
iter 10 value 94.523901
iter 20 value 94.482193
iter 30 value 94.272004
iter 40 value 93.491005
iter 50 value 92.099596
iter 60 value 86.270722
iter 70 value 84.273122
iter 80 value 83.124367
iter 90 value 82.480731
iter 100 value 82.276351
final value 82.276351
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 112.796052
iter 10 value 95.751754
iter 20 value 92.322429
iter 30 value 90.432853
iter 40 value 85.274132
iter 50 value 84.738600
iter 60 value 82.797777
iter 70 value 81.730164
iter 80 value 81.265987
iter 90 value 80.955376
iter 100 value 80.878861
final value 80.878861
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 115.312242
iter 10 value 93.951871
iter 20 value 87.770466
iter 30 value 85.907364
iter 40 value 84.824288
iter 50 value 84.668691
iter 60 value 84.480205
iter 70 value 84.192599
iter 80 value 83.293931
iter 90 value 82.263679
iter 100 value 81.411751
final value 81.411751
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 123.712419
iter 10 value 94.585116
iter 20 value 92.349295
iter 30 value 89.650940
iter 40 value 87.033104
iter 50 value 83.454346
iter 60 value 81.491019
iter 70 value 80.921663
iter 80 value 80.704584
iter 90 value 80.529690
iter 100 value 80.325697
final value 80.325697
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 105.467795
iter 10 value 94.281489
iter 20 value 90.379002
iter 30 value 88.365297
iter 40 value 87.926968
iter 50 value 86.478115
iter 60 value 83.157785
iter 70 value 82.353927
iter 80 value 81.868816
iter 90 value 81.587425
iter 100 value 81.036804
final value 81.036804
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 120.579520
iter 10 value 94.992288
iter 20 value 89.562570
iter 30 value 88.151622
iter 40 value 85.038193
iter 50 value 84.136326
iter 60 value 82.591006
iter 70 value 81.369474
iter 80 value 81.155470
iter 90 value 80.726944
iter 100 value 80.628878
final value 80.628878
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 94.486104
final value 94.485703
converged
Fitting Repeat 2
# weights: 103
initial value 96.047594
final value 94.486029
converged
Fitting Repeat 3
# weights: 103
initial value 97.630659
iter 10 value 90.559963
iter 20 value 85.845778
iter 30 value 85.605217
iter 40 value 85.582576
final value 85.582109
converged
Fitting Repeat 4
# weights: 103
initial value 101.357622
iter 10 value 94.485902
iter 20 value 94.484057
iter 30 value 89.092001
iter 40 value 87.859754
iter 50 value 86.788519
iter 60 value 86.172077
iter 70 value 86.166276
iter 80 value 86.090494
final value 86.090466
converged
Fitting Repeat 5
# weights: 103
initial value 97.778994
iter 10 value 93.848114
iter 20 value 93.814348
iter 30 value 93.813845
iter 40 value 93.812219
final value 93.812183
converged
Fitting Repeat 1
# weights: 305
initial value 103.347342
iter 10 value 94.488972
iter 20 value 94.444946
iter 30 value 94.032737
iter 40 value 93.540289
final value 93.540184
converged
Fitting Repeat 2
# weights: 305
initial value 95.745375
iter 10 value 94.485734
iter 20 value 94.319391
iter 30 value 88.762696
iter 40 value 85.357036
iter 50 value 84.665804
iter 60 value 84.660054
final value 84.659896
converged
Fitting Repeat 3
# weights: 305
initial value 95.693652
iter 10 value 92.292068
iter 20 value 92.254791
iter 30 value 92.238765
iter 40 value 92.236255
iter 50 value 92.236090
iter 60 value 92.234424
final value 92.234194
converged
Fitting Repeat 4
# weights: 305
initial value 111.022461
iter 10 value 94.489106
iter 20 value 94.483915
iter 30 value 90.933152
iter 40 value 87.942801
iter 50 value 87.732241
iter 60 value 87.731377
iter 60 value 87.731377
final value 87.731377
converged
Fitting Repeat 5
# weights: 305
initial value 97.939578
iter 10 value 94.489030
iter 20 value 93.821560
final value 93.812314
converged
Fitting Repeat 1
# weights: 507
initial value 107.384016
iter 10 value 94.475833
iter 20 value 94.471380
iter 30 value 93.812939
final value 93.812897
converged
Fitting Repeat 2
# weights: 507
initial value 101.193315
iter 10 value 94.493052
iter 20 value 94.409868
iter 30 value 91.917681
final value 91.474114
converged
Fitting Repeat 3
# weights: 507
initial value 103.757271
iter 10 value 93.372741
iter 20 value 93.234498
iter 30 value 93.184300
iter 40 value 93.166751
iter 50 value 91.044518
iter 60 value 90.648868
iter 70 value 90.527369
iter 80 value 90.503587
final value 90.485960
converged
Fitting Repeat 4
# weights: 507
initial value 108.762154
iter 10 value 93.820580
iter 20 value 93.815312
iter 30 value 93.801265
iter 40 value 93.797310
final value 93.797282
converged
Fitting Repeat 5
# weights: 507
initial value 107.726348
iter 10 value 94.491497
iter 20 value 94.484335
iter 30 value 94.010284
iter 40 value 89.651853
iter 50 value 84.502929
iter 60 value 82.992498
iter 70 value 80.793262
iter 80 value 80.738211
iter 90 value 80.736932
iter 100 value 80.378953
final value 80.378953
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 99.810158
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 105.141446
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 98.440562
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 99.267191
final value 94.354396
converged
Fitting Repeat 5
# weights: 103
initial value 98.998292
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 129.754735
iter 10 value 94.354402
final value 94.354396
converged
Fitting Repeat 2
# weights: 305
initial value 102.001280
final value 94.354396
converged
Fitting Repeat 3
# weights: 305
initial value 139.977802
final value 94.057229
converged
Fitting Repeat 4
# weights: 305
initial value 103.734642
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 98.686822
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 96.441018
iter 10 value 93.147768
iter 20 value 91.568977
final value 91.568966
converged
Fitting Repeat 2
# weights: 507
initial value 96.033458
final value 94.354396
converged
Fitting Repeat 3
# weights: 507
initial value 94.724066
iter 10 value 94.484212
iter 10 value 94.484211
iter 10 value 94.484211
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 96.558423
iter 10 value 94.387501
iter 10 value 94.387501
iter 10 value 94.387501
final value 94.387501
converged
Fitting Repeat 5
# weights: 507
initial value 118.865811
iter 10 value 94.484211
iter 10 value 94.484211
iter 10 value 94.484211
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 105.628128
iter 10 value 94.576947
iter 20 value 94.488523
iter 30 value 93.705568
iter 40 value 93.488370
iter 50 value 84.859079
iter 60 value 82.526299
iter 70 value 81.874380
iter 80 value 81.804434
iter 90 value 81.793358
final value 81.792648
converged
Fitting Repeat 2
# weights: 103
initial value 97.984762
iter 10 value 93.994256
iter 20 value 85.347005
iter 30 value 83.288389
iter 40 value 82.536828
iter 50 value 82.100695
iter 60 value 82.034961
final value 82.032250
converged
Fitting Repeat 3
# weights: 103
initial value 98.523311
iter 10 value 94.246913
iter 20 value 93.526413
iter 30 value 93.240801
iter 40 value 88.241911
iter 50 value 81.997630
iter 60 value 81.358749
iter 70 value 80.405185
iter 80 value 80.256410
iter 90 value 79.962315
iter 100 value 79.487443
final value 79.487443
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 97.973264
iter 10 value 94.498924
iter 20 value 92.157282
iter 30 value 88.152063
iter 40 value 82.402531
iter 50 value 81.925727
iter 60 value 81.310690
iter 70 value 80.683380
iter 80 value 80.135833
iter 90 value 79.513052
iter 100 value 79.412494
final value 79.412494
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 108.202442
iter 10 value 94.412989
iter 20 value 92.379111
iter 30 value 91.647107
iter 40 value 91.612061
iter 50 value 91.611362
iter 60 value 91.610233
final value 91.609364
converged
Fitting Repeat 1
# weights: 305
initial value 103.462129
iter 10 value 94.475727
iter 20 value 93.008989
iter 30 value 82.921694
iter 40 value 82.739758
iter 50 value 82.613092
iter 60 value 82.522976
iter 70 value 82.009592
iter 80 value 80.523801
iter 90 value 79.212914
iter 100 value 78.213174
final value 78.213174
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 101.385247
iter 10 value 94.410969
iter 20 value 94.172290
iter 30 value 92.695080
iter 40 value 85.470458
iter 50 value 79.667375
iter 60 value 78.782270
iter 70 value 78.638057
iter 80 value 78.255915
iter 90 value 77.800894
iter 100 value 77.540752
final value 77.540752
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 102.732030
iter 10 value 94.683063
iter 20 value 86.224504
iter 30 value 85.496363
iter 40 value 83.109335
iter 50 value 82.632545
iter 60 value 81.646226
iter 70 value 79.926207
iter 80 value 78.583267
iter 90 value 77.997020
iter 100 value 77.877786
final value 77.877786
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 99.573000
iter 10 value 94.564251
iter 20 value 94.437722
iter 30 value 89.143840
iter 40 value 82.616224
iter 50 value 82.163082
iter 60 value 81.434992
iter 70 value 79.777468
iter 80 value 78.274540
iter 90 value 77.866264
iter 100 value 77.839767
final value 77.839767
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 107.897784
iter 10 value 94.555520
iter 20 value 94.475704
iter 30 value 93.810854
iter 40 value 86.546683
iter 50 value 85.937665
iter 60 value 83.822093
iter 70 value 82.449687
iter 80 value 81.953075
iter 90 value 81.704585
iter 100 value 80.937344
final value 80.937344
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 105.980969
iter 10 value 91.138035
iter 20 value 81.972393
iter 30 value 81.436139
iter 40 value 81.061380
iter 50 value 80.603893
iter 60 value 79.488245
iter 70 value 78.355653
iter 80 value 77.955283
iter 90 value 77.750842
iter 100 value 77.493434
final value 77.493434
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 115.824204
iter 10 value 93.598682
iter 20 value 87.514843
iter 30 value 84.028801
iter 40 value 82.518627
iter 50 value 80.568294
iter 60 value 80.408580
iter 70 value 79.823710
iter 80 value 79.521471
iter 90 value 79.158775
iter 100 value 78.900566
final value 78.900566
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 111.625379
iter 10 value 94.209838
iter 20 value 93.252515
iter 30 value 92.768186
iter 40 value 90.900320
iter 50 value 87.950807
iter 60 value 86.319408
iter 70 value 84.328911
iter 80 value 81.161342
iter 90 value 79.237355
iter 100 value 77.998113
final value 77.998113
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 117.938013
iter 10 value 95.346822
iter 20 value 92.765757
iter 30 value 86.444356
iter 40 value 82.803534
iter 50 value 81.334879
iter 60 value 80.333125
iter 70 value 78.261701
iter 80 value 77.996068
iter 90 value 77.820473
iter 100 value 77.784611
final value 77.784611
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 137.157110
iter 10 value 92.849691
iter 20 value 86.964691
iter 30 value 86.032205
iter 40 value 81.725611
iter 50 value 80.158984
iter 60 value 78.186599
iter 70 value 77.910151
iter 80 value 77.793634
iter 90 value 77.682369
iter 100 value 77.491641
final value 77.491641
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 100.207864
iter 10 value 94.317488
iter 20 value 92.574619
iter 30 value 92.550236
iter 40 value 92.434690
iter 50 value 92.431080
final value 92.431030
converged
Fitting Repeat 2
# weights: 103
initial value 99.314920
final value 93.321999
converged
Fitting Repeat 3
# weights: 103
initial value 98.638662
final value 94.485836
converged
Fitting Repeat 4
# weights: 103
initial value 97.797894
final value 94.486078
converged
Fitting Repeat 5
# weights: 103
initial value 101.432861
final value 94.485864
converged
Fitting Repeat 1
# weights: 305
initial value 96.425133
iter 10 value 94.358974
final value 94.356226
converged
Fitting Repeat 2
# weights: 305
initial value 104.632893
iter 10 value 94.488677
iter 20 value 94.478833
final value 94.354552
converged
Fitting Repeat 3
# weights: 305
initial value 96.126810
iter 10 value 94.489321
iter 20 value 94.484235
iter 30 value 94.419738
iter 40 value 93.868596
iter 50 value 93.660915
iter 60 value 93.185088
final value 91.810055
converged
Fitting Repeat 4
# weights: 305
initial value 107.413917
iter 10 value 94.489434
iter 20 value 94.402505
final value 94.354599
converged
Fitting Repeat 5
# weights: 305
initial value 103.508731
iter 10 value 94.488860
iter 20 value 94.456025
iter 30 value 83.938511
iter 40 value 82.413196
iter 50 value 82.411822
final value 82.411820
converged
Fitting Repeat 1
# weights: 507
initial value 99.045758
iter 10 value 94.362628
iter 20 value 93.784719
iter 30 value 93.321404
final value 93.321367
converged
Fitting Repeat 2
# weights: 507
initial value 99.797989
iter 10 value 94.492676
iter 20 value 94.484428
iter 30 value 94.479076
iter 40 value 87.882860
iter 50 value 87.776267
final value 87.775270
converged
Fitting Repeat 3
# weights: 507
initial value 106.343283
iter 10 value 94.362660
iter 20 value 94.280352
iter 30 value 85.706608
iter 40 value 80.039486
iter 50 value 80.038135
iter 60 value 79.943221
iter 70 value 79.938416
iter 80 value 79.589712
iter 90 value 79.479899
iter 100 value 79.476898
final value 79.476898
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 113.733580
iter 10 value 94.492849
iter 20 value 94.483550
iter 30 value 85.301872
iter 40 value 84.552050
iter 50 value 84.488162
iter 50 value 84.488161
iter 50 value 84.488161
final value 84.488161
converged
Fitting Repeat 5
# weights: 507
initial value 110.396067
iter 10 value 94.466504
iter 20 value 87.278077
iter 30 value 83.554665
iter 40 value 83.550815
iter 50 value 83.491357
iter 60 value 83.269335
iter 70 value 80.751267
iter 80 value 80.255051
iter 90 value 80.249277
iter 100 value 80.180250
final value 80.180250
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 97.480021
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 95.428529
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 110.939362
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 112.824373
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 94.837967
final value 94.032967
converged
Fitting Repeat 1
# weights: 305
initial value 107.685803
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 102.931658
final value 94.032967
converged
Fitting Repeat 3
# weights: 305
initial value 106.604379
iter 10 value 93.994675
final value 93.869755
converged
Fitting Repeat 4
# weights: 305
initial value 97.550043
final value 94.032967
converged
Fitting Repeat 5
# weights: 305
initial value 98.258812
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 101.667010
final value 94.052910
converged
Fitting Repeat 2
# weights: 507
initial value 96.983602
iter 10 value 84.001631
iter 20 value 82.988338
iter 30 value 82.942895
final value 82.942859
converged
Fitting Repeat 3
# weights: 507
initial value 103.130956
final value 94.052910
converged
Fitting Repeat 4
# weights: 507
initial value 104.834473
final value 94.032967
converged
Fitting Repeat 5
# weights: 507
initial value 113.843079
final value 94.032967
converged
Fitting Repeat 1
# weights: 103
initial value 95.776968
iter 10 value 92.553220
iter 20 value 86.831130
iter 30 value 84.930745
iter 40 value 83.592635
iter 50 value 82.882322
iter 60 value 81.675505
iter 70 value 81.322887
iter 80 value 81.319729
final value 81.319472
converged
Fitting Repeat 2
# weights: 103
initial value 110.272342
iter 10 value 94.117369
iter 20 value 94.048010
iter 30 value 90.473480
iter 40 value 83.358748
iter 50 value 82.746959
iter 60 value 82.255672
iter 70 value 82.082245
iter 80 value 82.017320
iter 90 value 81.986201
final value 81.985724
converged
Fitting Repeat 3
# weights: 103
initial value 101.366589
iter 10 value 87.881014
iter 20 value 83.060860
iter 30 value 82.301186
iter 40 value 82.163785
iter 50 value 82.046535
final value 82.045333
converged
Fitting Repeat 4
# weights: 103
initial value 96.455758
iter 10 value 94.046264
iter 20 value 91.324518
iter 30 value 91.051271
iter 40 value 90.174019
iter 50 value 84.364358
iter 60 value 83.041411
iter 70 value 82.161086
iter 80 value 82.061059
iter 90 value 82.045351
final value 82.045332
converged
Fitting Repeat 5
# weights: 103
initial value 106.863713
iter 10 value 93.867262
iter 20 value 83.983152
iter 30 value 83.055499
iter 40 value 82.828646
iter 50 value 82.592777
iter 60 value 82.554228
iter 70 value 82.535644
final value 82.535614
converged
Fitting Repeat 1
# weights: 305
initial value 110.108495
iter 10 value 94.190154
iter 20 value 90.223835
iter 30 value 84.535066
iter 40 value 84.080329
iter 50 value 83.054955
iter 60 value 81.912827
iter 70 value 81.271473
iter 80 value 81.004568
iter 90 value 80.657986
iter 100 value 80.579202
final value 80.579202
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 111.101746
iter 10 value 94.352913
iter 20 value 93.749360
iter 30 value 85.943985
iter 40 value 84.664499
iter 50 value 83.253619
iter 60 value 82.448113
iter 70 value 82.375647
iter 80 value 82.317081
iter 90 value 82.196973
iter 100 value 82.092766
final value 82.092766
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 126.275515
iter 10 value 94.095934
iter 20 value 90.923812
iter 30 value 83.757815
iter 40 value 82.240539
iter 50 value 82.059268
iter 60 value 81.981611
iter 70 value 81.954518
iter 80 value 81.778607
iter 90 value 81.379947
iter 100 value 80.905294
final value 80.905294
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 111.879754
iter 10 value 94.056871
iter 20 value 93.504074
iter 30 value 93.205696
iter 40 value 91.816042
iter 50 value 85.224834
iter 60 value 82.629701
iter 70 value 82.382050
iter 80 value 81.886620
iter 90 value 81.391871
iter 100 value 81.147057
final value 81.147057
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 102.440714
iter 10 value 94.715155
iter 20 value 90.196510
iter 30 value 88.595266
iter 40 value 87.930332
iter 50 value 86.284499
iter 60 value 85.331636
iter 70 value 83.064348
iter 80 value 82.645111
iter 90 value 81.343082
iter 100 value 81.207068
final value 81.207068
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 122.487348
iter 10 value 94.019385
iter 20 value 85.962846
iter 30 value 83.586535
iter 40 value 83.069024
iter 50 value 81.893135
iter 60 value 80.630409
iter 70 value 80.017700
iter 80 value 79.748724
iter 90 value 79.629510
iter 100 value 79.505531
final value 79.505531
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 136.701407
iter 10 value 93.809740
iter 20 value 86.688653
iter 30 value 84.210867
iter 40 value 82.936457
iter 50 value 81.881774
iter 60 value 80.345377
iter 70 value 80.118436
iter 80 value 80.085729
iter 90 value 80.010664
iter 100 value 79.720056
final value 79.720056
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 110.526121
iter 10 value 93.998646
iter 20 value 86.664172
iter 30 value 85.172586
iter 40 value 84.185464
iter 50 value 82.435111
iter 60 value 82.081371
iter 70 value 81.566290
iter 80 value 81.309666
iter 90 value 80.466554
iter 100 value 80.129870
final value 80.129870
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 112.333405
iter 10 value 94.966760
iter 20 value 94.005005
iter 30 value 87.417280
iter 40 value 84.832451
iter 50 value 83.988784
iter 60 value 83.409342
iter 70 value 82.990276
iter 80 value 82.889904
iter 90 value 82.379679
iter 100 value 82.198441
final value 82.198441
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 115.713538
iter 10 value 94.044504
iter 20 value 85.835547
iter 30 value 83.331796
iter 40 value 83.222704
iter 50 value 82.317075
iter 60 value 80.652432
iter 70 value 80.495523
iter 80 value 80.220132
iter 90 value 80.032478
iter 100 value 79.726757
final value 79.726757
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 94.334727
final value 94.054446
converged
Fitting Repeat 2
# weights: 103
initial value 96.371298
final value 94.054705
converged
Fitting Repeat 3
# weights: 103
initial value 95.059470
final value 93.698712
converged
Fitting Repeat 4
# weights: 103
initial value 103.222871
final value 94.054430
converged
Fitting Repeat 5
# weights: 103
initial value 96.828976
final value 94.054585
converged
Fitting Repeat 1
# weights: 305
initial value 111.797417
iter 10 value 93.884266
iter 20 value 93.873252
iter 30 value 93.142189
iter 40 value 89.120160
iter 50 value 89.092767
iter 60 value 89.091051
iter 70 value 89.090502
iter 80 value 84.089729
iter 90 value 81.516735
iter 100 value 81.516073
final value 81.516073
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 110.030670
iter 10 value 94.056496
iter 20 value 93.922409
iter 30 value 93.455887
iter 40 value 93.416139
iter 50 value 93.412815
iter 50 value 93.412815
final value 93.412815
converged
Fitting Repeat 3
# weights: 305
initial value 99.330821
iter 10 value 94.057675
final value 94.053235
converged
Fitting Repeat 4
# weights: 305
initial value 105.690844
iter 10 value 94.057804
iter 20 value 94.025368
iter 30 value 91.081683
iter 40 value 91.074296
iter 50 value 91.072447
iter 60 value 91.072103
iter 70 value 90.679637
final value 90.502493
converged
Fitting Repeat 5
# weights: 305
initial value 115.222426
iter 10 value 94.057746
iter 20 value 94.004465
iter 30 value 93.402703
final value 93.377451
converged
Fitting Repeat 1
# weights: 507
initial value 104.793570
iter 10 value 94.062209
iter 20 value 93.804710
iter 30 value 90.056954
iter 40 value 89.552431
iter 50 value 89.543256
iter 60 value 85.969815
iter 70 value 82.393370
iter 80 value 82.117604
iter 90 value 80.791886
iter 100 value 80.780077
final value 80.780077
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 105.957183
iter 10 value 94.041725
iter 20 value 94.035654
iter 30 value 85.841436
iter 40 value 85.515394
iter 50 value 84.432871
iter 60 value 84.299578
iter 70 value 84.299292
iter 80 value 84.296443
iter 90 value 84.291988
iter 100 value 80.648390
final value 80.648390
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 94.915973
iter 10 value 94.042603
iter 20 value 94.001047
iter 30 value 90.817503
iter 40 value 90.671976
final value 90.671974
converged
Fitting Repeat 4
# weights: 507
initial value 95.541760
iter 10 value 94.060516
iter 20 value 88.579377
iter 30 value 86.822168
iter 40 value 83.873719
iter 50 value 82.913243
iter 60 value 82.749769
iter 70 value 82.748496
final value 82.748440
converged
Fitting Repeat 5
# weights: 507
initial value 111.214758
iter 10 value 93.659190
iter 20 value 93.376204
iter 30 value 93.374874
iter 40 value 87.527447
iter 50 value 82.889743
iter 60 value 82.013107
iter 70 value 81.774574
iter 80 value 81.744692
iter 90 value 81.547911
iter 100 value 81.051816
final value 81.051816
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 127.119755
iter 10 value 111.285631
iter 20 value 108.019526
iter 30 value 104.448156
iter 40 value 101.863498
iter 50 value 101.391508
iter 60 value 100.690436
iter 70 value 100.527352
iter 80 value 100.408242
iter 90 value 100.174702
iter 100 value 100.024760
final value 100.024760
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 139.966614
iter 10 value 118.282450
iter 20 value 111.238495
iter 30 value 108.165943
iter 40 value 106.139088
iter 50 value 105.139206
iter 60 value 104.908833
iter 70 value 104.863698
iter 80 value 104.780708
iter 90 value 103.954194
iter 100 value 103.229163
final value 103.229163
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 145.701976
iter 10 value 117.902540
iter 20 value 115.359987
iter 30 value 114.611336
iter 40 value 112.200656
iter 50 value 109.585556
iter 60 value 104.822243
iter 70 value 102.694258
iter 80 value 102.431252
iter 90 value 101.717349
iter 100 value 101.298668
final value 101.298668
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 143.770937
iter 10 value 118.013026
iter 20 value 117.925020
iter 30 value 117.648280
iter 40 value 117.506490
iter 50 value 109.922682
iter 60 value 104.481558
iter 70 value 104.020888
iter 80 value 102.832335
iter 90 value 101.501926
iter 100 value 101.036077
final value 101.036077
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 135.073723
iter 10 value 117.926747
iter 20 value 116.340125
iter 30 value 114.045700
iter 40 value 108.684599
iter 50 value 104.084102
iter 60 value 103.081978
iter 70 value 101.933933
iter 80 value 101.571185
iter 90 value 100.808389
iter 100 value 100.429793
final value 100.429793
stopped after 100 iterations
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
RUNIT TEST PROTOCOL -- Tue Apr 12 21:21:39 2022
***********************************************
Number of test functions: 8
Number of errors: 0
Number of failures: 0
1 Test Suite :
HPiP RUnit Tests - 8 test functions, 0 errors, 0 failures
Number of test functions: 8
Number of errors: 0
Number of failures: 0
Warning messages:
1: The `.data` argument of `add_column()` must have unique names as of tibble 3.0.0.
Use `.name_repair = "minimal"`.
This warning is displayed once every 8 hours.
Call `lifecycle::last_lifecycle_warnings()` to see where this warning was generated.
2: `repeats` has no meaning for this resampling method.
3: executing %dopar% sequentially: no parallel backend registered
>
>
>
>
> proc.time()
user system elapsed
60.39 1.34 48.09
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HPiP.Rcheck/examples_i386/HPiP-Ex.timings
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HPiP.Rcheck/examples_x64/HPiP-Ex.timings
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