##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.20-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.20-bioc/R/site-library --timings HPiP_1.12.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck’
* using R version 4.4.2 (2024-10-31)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 13.2.0-23ubuntu4) 13.2.0
    GNU Fortran (Ubuntu 13.2.0-23ubuntu4) 13.2.0
* running under: Ubuntu 24.04.1 LTS
* using session charset: UTF-8
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.12.0’
* 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 for sufficient/correct file permissions ... 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 ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* 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 loading without being on the library search path ... 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 ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* 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 ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
var_imp       35.983  0.337  36.369
corr_plot     34.822  0.332  35.228
FSmethod      34.381  0.509  34.892
pred_ensembel 12.841  0.100  11.751
enrichfindP    0.543  0.035   8.969
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE

Status: 3 NOTEs
See
  ‘/home/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.20-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.20-bioc/R/site-library’
* installing *source* package ‘HPiP’ ...
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** 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
* DONE (HPiP)

R version 4.4.2 (2024-10-31) -- "Pile of Leaves"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

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
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
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
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 107.239691 
iter  10 value 94.484477
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.230059 
final  value 94.088889 
converged
Fitting Repeat 3 

# weights:  103
initial  value 111.949781 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.735535 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.462903 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.480949 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.810426 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.834452 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 126.555806 
iter  10 value 94.363647
final  value 94.363636 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.969829 
iter  10 value 94.070883
iter  20 value 94.057008
final  value 94.056928 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.854911 
iter  10 value 87.050663
final  value 86.935656 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.630376 
final  value 94.354396 
converged
Fitting Repeat 3 

# weights:  507
initial  value 123.889248 
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.680466 
final  value 94.353550 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.784294 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.117218 
iter  10 value 94.488614
iter  20 value 90.481555
iter  30 value 85.459230
iter  40 value 84.464103
iter  50 value 84.200345
final  value 84.194723 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.475649 
final  value 94.488534 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.774349 
iter  10 value 94.487084
iter  20 value 94.434693
iter  30 value 94.156268
iter  40 value 94.138098
iter  50 value 94.133216
iter  60 value 86.360307
iter  70 value 84.517898
iter  80 value 84.334117
iter  90 value 84.197180
final  value 84.194723 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.813032 
iter  10 value 91.487842
iter  20 value 87.511376
iter  30 value 85.430928
iter  40 value 85.210906
iter  50 value 85.123136
iter  60 value 84.361129
iter  70 value 84.195036
final  value 84.194723 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.666704 
iter  10 value 94.111946
iter  20 value 86.790022
iter  30 value 85.614463
iter  40 value 84.450477
iter  50 value 83.899265
iter  60 value 83.751917
iter  70 value 83.721938
final  value 83.721920 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.711965 
iter  10 value 96.457687
iter  20 value 91.185185
iter  30 value 86.962366
iter  40 value 86.147551
iter  50 value 85.693829
iter  60 value 85.321443
iter  70 value 85.264663
iter  80 value 84.865956
iter  90 value 84.310186
iter 100 value 82.205263
final  value 82.205263 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 112.265891 
iter  10 value 94.501317
iter  20 value 91.496350
iter  30 value 88.578718
iter  40 value 87.179366
iter  50 value 85.529897
iter  60 value 85.064761
iter  70 value 84.335892
iter  80 value 84.091290
iter  90 value 83.233309
iter 100 value 83.043362
final  value 83.043362 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 116.390164 
iter  10 value 94.490589
iter  20 value 85.552770
iter  30 value 85.319067
iter  40 value 83.589775
iter  50 value 82.265659
iter  60 value 82.044224
iter  70 value 81.871700
iter  80 value 81.636752
iter  90 value 81.110358
iter 100 value 80.954390
final  value 80.954390 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.566071 
iter  10 value 95.192221
iter  20 value 92.839067
iter  30 value 88.054736
iter  40 value 87.252252
iter  50 value 84.712622
iter  60 value 84.137634
iter  70 value 83.139207
iter  80 value 82.569791
iter  90 value 82.288292
iter 100 value 81.749515
final  value 81.749515 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.241728 
iter  10 value 90.693366
iter  20 value 89.564169
iter  30 value 86.733989
iter  40 value 85.258270
iter  50 value 84.156832
iter  60 value 83.650335
iter  70 value 83.310867
iter  80 value 83.095356
iter  90 value 83.076515
iter 100 value 82.957862
final  value 82.957862 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.667270 
iter  10 value 94.607403
iter  20 value 93.868138
iter  30 value 89.327861
iter  40 value 87.503688
iter  50 value 85.171329
iter  60 value 83.256318
iter  70 value 82.710627
iter  80 value 82.377422
iter  90 value 81.811296
iter 100 value 81.340877
final  value 81.340877 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.089642 
iter  10 value 95.863618
iter  20 value 89.116390
iter  30 value 86.227249
iter  40 value 84.354772
iter  50 value 84.245616
iter  60 value 84.058052
iter  70 value 82.940044
iter  80 value 82.089133
iter  90 value 81.719534
iter 100 value 81.558362
final  value 81.558362 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 112.836369 
iter  10 value 94.808820
iter  20 value 88.043891
iter  30 value 85.550579
iter  40 value 85.266862
iter  50 value 83.519194
iter  60 value 82.713206
iter  70 value 82.331613
iter  80 value 81.827166
iter  90 value 81.424414
iter 100 value 81.383729
final  value 81.383729 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.262223 
iter  10 value 93.808923
iter  20 value 87.994698
iter  30 value 86.575009
iter  40 value 85.497112
iter  50 value 83.629489
iter  60 value 82.884463
iter  70 value 82.322971
iter  80 value 81.597925
iter  90 value 81.445832
iter 100 value 81.268783
final  value 81.268783 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.785041 
iter  10 value 93.301139
iter  20 value 85.744378
iter  30 value 84.354220
iter  40 value 83.495255
iter  50 value 82.388567
iter  60 value 81.655085
iter  70 value 81.417668
iter  80 value 81.305658
iter  90 value 81.214422
iter 100 value 80.992538
final  value 80.992538 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.329723 
final  value 94.486160 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.959703 
iter  10 value 94.485967
iter  20 value 94.484273
iter  30 value 94.067516
iter  40 value 93.211857
iter  50 value 93.099026
iter  60 value 93.095911
iter  70 value 93.063298
final  value 93.063282 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.911198 
final  value 94.485661 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.183710 
iter  10 value 94.485893
iter  20 value 94.484276
final  value 94.484218 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.134097 
final  value 94.485832 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.147260 
iter  10 value 94.489272
iter  20 value 94.484474
iter  30 value 94.170940
final  value 94.145097 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.593635 
iter  10 value 94.489080
iter  20 value 94.408009
iter  30 value 93.524613
iter  40 value 84.553764
iter  50 value 84.494671
iter  60 value 82.672324
iter  70 value 81.498852
iter  80 value 81.487812
iter  90 value 81.486834
final  value 81.486640 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.697596 
iter  10 value 94.217976
iter  20 value 94.215173
iter  30 value 94.212899
final  value 94.212782 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.461133 
iter  10 value 94.488540
iter  20 value 94.355410
iter  30 value 94.143822
iter  40 value 94.141965
final  value 94.141955 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.676499 
iter  10 value 94.359571
iter  20 value 94.355045
iter  30 value 94.354451
iter  40 value 93.452831
iter  50 value 83.262445
iter  60 value 83.247764
iter  70 value 83.103615
iter  80 value 83.087569
iter  90 value 83.082051
iter 100 value 81.005461
final  value 81.005461 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.958590 
iter  10 value 94.490083
iter  20 value 90.407161
iter  30 value 86.778333
iter  40 value 86.440873
iter  50 value 86.233420
final  value 86.232848 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.457888 
iter  10 value 94.492540
iter  20 value 94.462811
iter  30 value 89.167982
iter  40 value 88.541232
iter  50 value 88.111110
iter  60 value 87.936523
iter  70 value 87.936223
iter  80 value 85.514766
iter  90 value 83.891614
iter 100 value 83.871830
final  value 83.871830 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.183397 
iter  10 value 92.579591
iter  20 value 83.199754
iter  30 value 82.899083
iter  40 value 82.727492
iter  50 value 82.308313
iter  60 value 82.258681
iter  70 value 81.735025
iter  80 value 81.684962
iter  90 value 81.682715
iter 100 value 81.677440
final  value 81.677440 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 122.694006 
iter  10 value 94.492001
iter  20 value 94.484468
iter  30 value 93.745116
iter  40 value 90.258079
iter  50 value 90.244454
iter  60 value 90.243981
iter  70 value 90.242408
iter  70 value 90.242408
final  value 90.242408 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.311284 
iter  10 value 94.168647
iter  20 value 94.140507
iter  30 value 94.133497
final  value 94.133482 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.014375 
final  value 93.447848 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.625315 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.780767 
iter  10 value 91.017521
iter  20 value 90.201642
iter  30 value 90.157486
final  value 90.157444 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.480426 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.622686 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.521308 
final  value 94.409356 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.090815 
iter  10 value 94.483835
iter  20 value 94.474697
final  value 94.473126 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.975108 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 112.701488 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.055159 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 117.568955 
iter  10 value 94.473121
final  value 94.473118 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.479148 
iter  10 value 94.725387
iter  20 value 85.424952
iter  30 value 84.903076
iter  40 value 84.814545
iter  50 value 84.717684
final  value 84.717425 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.172135 
final  value 94.473118 
converged
Fitting Repeat 4 

# weights:  507
initial  value 115.696007 
iter  10 value 93.179554
iter  20 value 90.592583
iter  30 value 90.489212
final  value 90.489136 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.054916 
iter  10 value 92.604672
iter  20 value 92.522771
final  value 92.522763 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.306931 
iter  10 value 94.492656
iter  20 value 94.452544
iter  30 value 90.662737
iter  40 value 89.097517
iter  50 value 83.984900
iter  60 value 80.703479
iter  70 value 79.865948
iter  80 value 79.687803
iter  90 value 78.601889
iter 100 value 77.902604
final  value 77.902604 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 100.322934 
iter  10 value 94.228854
iter  20 value 88.918165
iter  30 value 83.445614
iter  40 value 82.637460
iter  50 value 82.113520
iter  60 value 81.243523
iter  70 value 81.079832
final  value 81.079478 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.262386 
iter  10 value 94.488707
iter  20 value 94.023699
iter  30 value 83.626797
iter  40 value 80.737526
iter  50 value 80.199071
iter  60 value 79.563127
iter  70 value 79.065561
iter  80 value 78.534877
iter  90 value 78.138388
iter 100 value 77.630736
final  value 77.630736 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.940423 
iter  10 value 94.563796
iter  20 value 94.488281
iter  30 value 85.676434
iter  40 value 83.432876
iter  50 value 82.756223
iter  60 value 82.315113
iter  70 value 81.957795
iter  80 value 81.759998
final  value 81.736814 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.036322 
iter  10 value 94.488517
iter  20 value 93.466441
iter  30 value 91.231194
iter  40 value 89.689830
iter  50 value 87.078739
iter  60 value 86.485860
iter  70 value 85.964257
iter  80 value 83.403844
iter  90 value 83.050690
iter 100 value 82.020054
final  value 82.020054 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 99.525289 
iter  10 value 94.136773
iter  20 value 81.720040
iter  30 value 80.213821
iter  40 value 80.066717
iter  50 value 78.810098
iter  60 value 78.313171
iter  70 value 77.943307
iter  80 value 77.887590
iter  90 value 77.861800
iter 100 value 77.821661
final  value 77.821661 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.077703 
iter  10 value 94.476467
iter  20 value 88.080000
iter  30 value 85.994022
iter  40 value 82.889344
iter  50 value 81.867069
iter  60 value 79.535101
iter  70 value 79.373800
iter  80 value 79.356545
iter  90 value 79.047281
iter 100 value 78.308118
final  value 78.308118 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.692121 
iter  10 value 94.605838
iter  20 value 90.063577
iter  30 value 82.823461
iter  40 value 82.246822
iter  50 value 81.691980
iter  60 value 81.395351
iter  70 value 79.104158
iter  80 value 77.876593
iter  90 value 77.787545
iter 100 value 77.459979
final  value 77.459979 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 119.517199 
iter  10 value 94.460927
iter  20 value 88.897670
iter  30 value 83.091083
iter  40 value 79.558145
iter  50 value 77.889351
iter  60 value 76.954154
iter  70 value 76.892252
iter  80 value 76.721449
iter  90 value 76.602700
iter 100 value 76.578514
final  value 76.578514 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.002486 
iter  10 value 94.860895
iter  20 value 93.381013
iter  30 value 86.167099
iter  40 value 84.673023
iter  50 value 81.407475
iter  60 value 78.609433
iter  70 value 77.831792
iter  80 value 77.512961
iter  90 value 76.577828
iter 100 value 75.950896
final  value 75.950896 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.388643 
iter  10 value 94.469747
iter  20 value 92.869915
iter  30 value 89.170272
iter  40 value 87.763863
iter  50 value 82.988491
iter  60 value 80.080790
iter  70 value 79.392913
iter  80 value 77.721434
iter  90 value 77.379546
iter 100 value 77.249316
final  value 77.249316 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.406061 
iter  10 value 95.539818
iter  20 value 94.446563
iter  30 value 84.155166
iter  40 value 81.510599
iter  50 value 80.082782
iter  60 value 79.013929
iter  70 value 77.794779
iter  80 value 77.423229
iter  90 value 77.306327
iter 100 value 77.218269
final  value 77.218269 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.610635 
iter  10 value 94.741564
iter  20 value 94.319771
iter  30 value 87.516832
iter  40 value 86.334782
iter  50 value 84.204686
iter  60 value 82.850900
iter  70 value 82.119413
iter  80 value 78.942557
iter  90 value 77.486666
iter 100 value 76.363779
final  value 76.363779 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.911251 
iter  10 value 95.386733
iter  20 value 84.220664
iter  30 value 83.396667
iter  40 value 82.154132
iter  50 value 79.358808
iter  60 value 78.366704
iter  70 value 77.674336
iter  80 value 77.002699
iter  90 value 76.638525
iter 100 value 76.514667
final  value 76.514667 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.591677 
iter  10 value 94.261043
iter  20 value 92.921860
iter  30 value 88.550735
iter  40 value 84.262274
iter  50 value 79.892907
iter  60 value 79.219104
iter  70 value 78.809654
iter  80 value 78.498507
iter  90 value 76.442980
iter 100 value 76.013287
final  value 76.013287 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.785130 
final  value 94.485737 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.270291 
iter  10 value 94.485837
final  value 94.484232 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.931896 
iter  10 value 92.095192
iter  20 value 91.957493
iter  30 value 91.954949
iter  40 value 91.888479
iter  50 value 91.855644
iter  60 value 91.807733
iter  70 value 88.128216
iter  80 value 84.323673
iter  90 value 84.262991
iter 100 value 81.869330
final  value 81.869330 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 101.176886 
final  value 94.485660 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.235700 
final  value 94.485912 
converged
Fitting Repeat 1 

# weights:  305
initial  value 127.505947 
iter  10 value 94.489441
iter  20 value 94.484745
iter  30 value 93.799730
iter  40 value 90.877517
iter  50 value 83.502064
iter  60 value 83.439247
final  value 83.438388 
converged
Fitting Repeat 2 

# weights:  305
initial  value 111.492549 
iter  10 value 94.477882
iter  20 value 94.468588
iter  30 value 89.620058
iter  40 value 82.585922
final  value 82.584191 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.980943 
iter  10 value 94.486877
iter  20 value 87.975643
iter  30 value 82.754162
iter  40 value 82.728553
iter  50 value 81.523258
iter  60 value 78.291809
iter  70 value 76.693918
iter  80 value 76.600070
iter  90 value 76.599507
iter 100 value 76.597393
final  value 76.597393 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.048468 
iter  10 value 93.240758
iter  20 value 90.350509
iter  30 value 90.285630
iter  40 value 90.283944
iter  50 value 90.282739
iter  60 value 90.201861
iter  70 value 90.201460
final  value 90.201370 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.424311 
iter  10 value 94.488561
iter  20 value 94.484245
final  value 94.484214 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.744719 
iter  10 value 94.492277
iter  20 value 94.482879
iter  30 value 93.858752
iter  40 value 85.443855
iter  50 value 84.882805
iter  60 value 82.747368
iter  70 value 81.145337
iter  80 value 81.142714
iter  90 value 81.027865
final  value 80.969297 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.339333 
iter  10 value 94.478186
iter  20 value 94.473672
iter  20 value 94.473671
iter  20 value 94.473671
final  value 94.473671 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.583996 
iter  10 value 94.493381
iter  20 value 94.485250
iter  30 value 94.358601
iter  40 value 89.306248
iter  50 value 83.142365
iter  60 value 81.270200
final  value 81.000905 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.591317 
iter  10 value 94.336446
iter  20 value 94.261108
iter  30 value 93.857554
iter  40 value 91.014441
iter  50 value 90.662795
iter  60 value 89.523808
iter  70 value 88.794311
final  value 88.749493 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.462176 
iter  10 value 94.253561
iter  20 value 94.247499
iter  30 value 94.247190
iter  40 value 94.245506
iter  50 value 93.159772
iter  60 value 90.067478
iter  70 value 80.649008
iter  80 value 76.799987
iter  90 value 75.583515
iter 100 value 74.445330
final  value 74.445330 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.490412 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.211962 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.336895 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.937777 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.264893 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.166301 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 120.626544 
iter  10 value 93.104041
iter  20 value 92.831045
final  value 92.828413 
converged
Fitting Repeat 3 

# weights:  305
initial  value 124.123609 
iter  10 value 93.329582
final  value 93.328261 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.311490 
iter  10 value 92.043188
final  value 92.043182 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.010483 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.214140 
iter  10 value 91.588451
iter  20 value 86.789460
final  value 86.256677 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.987624 
final  value 93.697143 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.705658 
iter  10 value 93.328262
final  value 93.328261 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.435834 
iter  10 value 92.043238
final  value 92.043182 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.846507 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 107.552526 
iter  10 value 92.519536
iter  20 value 86.666013
iter  30 value 85.937711
iter  40 value 85.262587
iter  50 value 81.102856
iter  60 value 80.486561
iter  70 value 80.398571
final  value 80.397924 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.857330 
iter  10 value 94.057213
iter  20 value 93.023733
iter  30 value 85.532746
iter  40 value 83.364693
iter  50 value 82.828036
iter  60 value 82.701458
final  value 82.700725 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.243412 
iter  10 value 93.544907
iter  20 value 93.013858
iter  30 value 89.357990
iter  40 value 88.092447
iter  50 value 87.412689
iter  60 value 82.876481
iter  70 value 82.083242
iter  80 value 81.968455
iter  90 value 80.992056
iter 100 value 80.822275
final  value 80.822275 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 100.054633 
iter  10 value 94.057032
iter  20 value 94.050451
iter  30 value 89.982345
iter  40 value 88.713712
iter  50 value 88.678262
iter  60 value 88.674950
iter  70 value 84.730133
iter  80 value 83.199851
iter  90 value 83.031367
final  value 83.026513 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.141390 
iter  10 value 94.051398
iter  20 value 93.232616
iter  30 value 93.026357
iter  40 value 93.017446
iter  50 value 92.721302
iter  60 value 90.898073
iter  70 value 87.200804
iter  80 value 87.108713
iter  90 value 87.057196
iter 100 value 82.031324
final  value 82.031324 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 100.427339 
iter  10 value 94.028322
iter  20 value 93.148934
iter  30 value 92.993874
iter  40 value 92.884939
iter  50 value 89.792976
iter  60 value 83.011821
iter  70 value 80.480503
iter  80 value 80.009904
iter  90 value 79.525066
iter 100 value 79.344510
final  value 79.344510 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.685176 
iter  10 value 93.162837
iter  20 value 87.745288
iter  30 value 83.159413
iter  40 value 82.578401
iter  50 value 81.773422
iter  60 value 80.893930
iter  70 value 80.727081
iter  80 value 80.412743
iter  90 value 80.357433
iter 100 value 80.322722
final  value 80.322722 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 116.170507 
iter  10 value 94.067441
iter  20 value 93.385992
iter  30 value 86.020864
iter  40 value 85.569894
iter  50 value 84.081459
iter  60 value 81.470248
iter  70 value 81.189509
iter  80 value 81.115666
iter  90 value 80.789279
iter 100 value 80.419030
final  value 80.419030 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.503072 
iter  10 value 93.766971
iter  20 value 93.302620
iter  30 value 93.000694
iter  40 value 84.703428
iter  50 value 83.040284
iter  60 value 82.109683
iter  70 value 81.664633
iter  80 value 80.198809
iter  90 value 79.845980
iter 100 value 79.508643
final  value 79.508643 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.630312 
iter  10 value 93.645311
iter  20 value 92.926572
iter  30 value 84.481870
iter  40 value 83.012696
iter  50 value 82.654070
iter  60 value 81.387345
iter  70 value 80.259143
iter  80 value 79.948160
iter  90 value 79.854534
iter 100 value 79.796408
final  value 79.796408 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 119.859327 
iter  10 value 94.170904
iter  20 value 92.226393
iter  30 value 88.371175
iter  40 value 83.469188
iter  50 value 82.130694
iter  60 value 81.586026
iter  70 value 80.420648
iter  80 value 80.287316
iter  90 value 80.120107
iter 100 value 79.767935
final  value 79.767935 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 124.865022 
iter  10 value 94.041867
iter  20 value 92.139768
iter  30 value 85.882295
iter  40 value 84.595442
iter  50 value 83.304459
iter  60 value 81.909749
iter  70 value 81.322882
iter  80 value 80.144612
iter  90 value 79.475296
iter 100 value 79.097648
final  value 79.097648 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.325709 
iter  10 value 93.687503
iter  20 value 84.661373
iter  30 value 83.302721
iter  40 value 82.880495
iter  50 value 82.284644
iter  60 value 81.518654
iter  70 value 80.445327
iter  80 value 80.294479
iter  90 value 80.277028
iter 100 value 80.034000
final  value 80.034000 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.868617 
iter  10 value 95.420534
iter  20 value 90.057645
iter  30 value 84.731005
iter  40 value 82.629912
iter  50 value 80.789222
iter  60 value 79.868655
iter  70 value 79.338273
iter  80 value 79.046702
iter  90 value 78.886891
iter 100 value 78.869978
final  value 78.869978 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 128.652146 
iter  10 value 98.900860
iter  20 value 95.959398
iter  30 value 85.960297
iter  40 value 83.373942
iter  50 value 83.164063
iter  60 value 83.014808
iter  70 value 82.784921
iter  80 value 82.496844
iter  90 value 80.861795
iter 100 value 80.249253
final  value 80.249253 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.628382 
iter  10 value 93.107794
iter  20 value 93.089160
iter  30 value 93.087977
final  value 93.087681 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.429328 
final  value 94.054434 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.896439 
final  value 94.054806 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.829632 
final  value 94.054251 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.942165 
final  value 94.054530 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.226229 
iter  10 value 94.057519
iter  20 value 92.147055
iter  30 value 91.361277
iter  40 value 91.281610
final  value 91.259795 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.838887 
iter  10 value 94.058598
iter  20 value 93.837637
iter  30 value 82.569627
iter  40 value 81.942629
iter  50 value 81.643053
iter  60 value 81.629287
iter  70 value 81.610132
iter  80 value 81.610060
iter  90 value 81.364371
iter 100 value 81.331200
final  value 81.331200 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 98.114533 
final  value 94.057910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.804058 
iter  10 value 93.332932
iter  20 value 93.330321
iter  30 value 92.673154
iter  40 value 83.610641
iter  50 value 80.308293
iter  60 value 79.396345
iter  70 value 78.685003
iter  80 value 78.629009
final  value 78.628933 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.353382 
iter  10 value 94.057565
iter  20 value 94.052676
iter  30 value 90.377249
iter  40 value 86.091509
iter  50 value 85.198690
iter  60 value 84.166937
iter  70 value 84.125588
final  value 84.125574 
converged
Fitting Repeat 1 

# weights:  507
initial  value 112.943507 
iter  10 value 94.061176
iter  20 value 93.610326
iter  30 value 92.829301
final  value 92.828966 
converged
Fitting Repeat 2 

# weights:  507
initial  value 120.908371 
iter  10 value 92.930561
iter  20 value 92.789171
iter  30 value 92.652255
iter  40 value 92.135897
iter  50 value 82.340606
iter  60 value 82.315904
iter  70 value 81.846802
iter  80 value 80.357647
iter  90 value 80.351748
iter 100 value 80.351154
final  value 80.351154 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 98.482000 
iter  10 value 94.061096
iter  20 value 94.052961
iter  30 value 92.726539
iter  40 value 87.175489
iter  50 value 85.912347
iter  60 value 85.779354
final  value 85.779353 
converged
Fitting Repeat 4 

# weights:  507
initial  value 107.660155 
iter  10 value 93.721045
iter  20 value 92.946011
iter  30 value 92.932204
iter  40 value 92.665408
iter  50 value 92.648815
iter  60 value 92.648076
iter  70 value 92.376352
iter  80 value 88.477107
iter  90 value 87.481589
iter 100 value 86.473894
final  value 86.473894 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 94.408678 
iter  10 value 93.341667
iter  20 value 93.336213
iter  30 value 93.326298
final  value 92.923455 
converged
Fitting Repeat 1 

# weights:  103
initial  value 94.325812 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.365056 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 109.474714 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.454646 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.552700 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.848294 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 114.488433 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.034765 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.069273 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 120.163111 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.044502 
iter  10 value 93.672973
iter  10 value 93.672973
iter  10 value 93.672973
final  value 93.672973 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.975798 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.759646 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.337745 
final  value 93.915746 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.698250 
final  value 92.514379 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.173046 
iter  10 value 94.056789
iter  20 value 93.902211
iter  30 value 93.760497
iter  40 value 93.284031
iter  50 value 84.748106
iter  60 value 83.799984
iter  70 value 83.216910
iter  80 value 82.990125
iter  90 value 82.540278
iter 100 value 82.464352
final  value 82.464352 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.182540 
iter  10 value 89.854806
iter  20 value 86.160706
iter  30 value 83.926736
iter  40 value 82.685305
iter  50 value 82.483835
iter  60 value 82.464315
final  value 82.464300 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.371045 
iter  10 value 90.008309
iter  20 value 88.862656
iter  30 value 88.345316
iter  40 value 88.027397
iter  50 value 88.000463
final  value 88.000451 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.547020 
iter  10 value 93.718199
iter  20 value 93.658120
iter  30 value 87.277650
iter  40 value 85.085480
iter  50 value 83.953960
iter  60 value 83.860725
iter  70 value 83.343715
iter  80 value 83.015518
iter  90 value 82.983786
final  value 82.983502 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.572006 
iter  10 value 91.064314
iter  20 value 83.062983
iter  30 value 80.917075
iter  40 value 80.806358
iter  50 value 80.347559
iter  60 value 80.022595
iter  70 value 79.647539
iter  80 value 79.450071
final  value 79.447728 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.059569 
iter  10 value 93.980103
iter  20 value 93.196199
iter  30 value 88.500287
iter  40 value 83.726503
iter  50 value 83.367338
iter  60 value 81.054177
iter  70 value 80.212855
iter  80 value 79.564471
iter  90 value 79.303068
iter 100 value 79.017226
final  value 79.017226 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 112.444480 
iter  10 value 94.139498
iter  20 value 91.743142
iter  30 value 88.781556
iter  40 value 87.988246
iter  50 value 87.874743
iter  60 value 87.834638
iter  70 value 87.754313
iter  80 value 85.615234
iter  90 value 82.416909
iter 100 value 81.029927
final  value 81.029927 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 109.165361 
iter  10 value 94.027098
iter  20 value 90.982202
iter  30 value 88.164550
iter  40 value 85.119742
iter  50 value 81.309517
iter  60 value 80.641194
iter  70 value 80.468822
iter  80 value 79.842964
iter  90 value 79.410931
iter 100 value 79.088526
final  value 79.088526 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.405124 
iter  10 value 92.688104
iter  20 value 86.594529
iter  30 value 81.580255
iter  40 value 80.133948
iter  50 value 79.920690
iter  60 value 79.732460
iter  70 value 79.624769
iter  80 value 79.576973
iter  90 value 79.229444
iter 100 value 78.962240
final  value 78.962240 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.903731 
iter  10 value 92.186605
iter  20 value 88.468401
iter  30 value 87.196670
iter  40 value 83.110950
iter  50 value 80.914206
iter  60 value 80.371994
iter  70 value 79.755956
iter  80 value 79.634405
iter  90 value 79.596983
iter 100 value 79.535903
final  value 79.535903 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 111.460302 
iter  10 value 93.975465
iter  20 value 92.056957
iter  30 value 87.185456
iter  40 value 83.871483
iter  50 value 81.310356
iter  60 value 80.135016
iter  70 value 79.603553
iter  80 value 79.374154
iter  90 value 79.094259
iter 100 value 78.742889
final  value 78.742889 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.446278 
iter  10 value 93.720215
iter  20 value 84.467484
iter  30 value 82.307743
iter  40 value 81.975071
iter  50 value 81.371223
iter  60 value 79.848853
iter  70 value 79.169498
iter  80 value 78.985071
iter  90 value 78.863694
iter 100 value 78.637892
final  value 78.637892 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.884238 
iter  10 value 93.295324
iter  20 value 89.760376
iter  30 value 85.482793
iter  40 value 84.129964
iter  50 value 83.381859
iter  60 value 83.135693
iter  70 value 81.428638
iter  80 value 79.527915
iter  90 value 78.686579
iter 100 value 78.255218
final  value 78.255218 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 120.661133 
iter  10 value 97.318155
iter  20 value 93.594632
iter  30 value 90.653709
iter  40 value 87.855109
iter  50 value 86.126633
iter  60 value 84.725743
iter  70 value 80.141448
iter  80 value 79.408829
iter  90 value 79.089612
iter 100 value 79.003863
final  value 79.003863 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.298375 
iter  10 value 94.033326
iter  20 value 93.572734
iter  30 value 86.060386
iter  40 value 83.004922
iter  50 value 80.996798
iter  60 value 79.460312
iter  70 value 78.729775
iter  80 value 78.596931
iter  90 value 78.407682
iter 100 value 78.240365
final  value 78.240365 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.031208 
final  value 93.917316 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.597985 
final  value 94.054720 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.023853 
final  value 94.054730 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.901067 
final  value 94.054419 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.777466 
iter  10 value 94.070697
iter  20 value 94.067216
iter  30 value 94.038140
iter  40 value 93.605209
iter  50 value 93.548774
iter  60 value 93.547897
final  value 93.547789 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.380613 
iter  10 value 93.920649
iter  20 value 93.916355
final  value 93.916150 
converged
Fitting Repeat 2 

# weights:  305
initial  value 106.026894 
iter  10 value 94.057519
iter  20 value 93.978562
iter  30 value 93.142418
iter  40 value 87.132471
iter  50 value 84.861120
iter  60 value 80.369066
iter  70 value 79.621195
iter  80 value 78.741193
iter  90 value 77.773097
iter 100 value 77.771707
final  value 77.771707 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.249438 
iter  10 value 94.057564
iter  20 value 90.909431
iter  30 value 85.789978
iter  40 value 85.290521
iter  50 value 84.741521
iter  60 value 82.280305
iter  70 value 82.176621
iter  80 value 82.044677
iter  90 value 82.039941
iter 100 value 81.478909
final  value 81.478909 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.105746 
iter  10 value 88.965827
iter  20 value 88.856291
iter  30 value 88.849855
final  value 88.703206 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.354754 
iter  10 value 94.057393
iter  20 value 93.965646
iter  30 value 89.131753
iter  40 value 89.128689
iter  50 value 89.124497
iter  60 value 89.122139
iter  70 value 89.109230
iter  80 value 87.193788
iter  90 value 81.123937
iter 100 value 81.117080
final  value 81.117080 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.562568 
iter  10 value 90.914020
iter  20 value 89.469345
iter  30 value 89.434988
iter  40 value 88.738061
iter  50 value 81.003743
iter  60 value 80.759278
iter  70 value 80.757025
iter  80 value 80.733065
iter  90 value 80.730199
iter 100 value 80.668171
final  value 80.668171 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 95.737820 
iter  10 value 93.923926
iter  20 value 93.525587
iter  30 value 89.570081
iter  40 value 89.256224
iter  50 value 89.254546
iter  60 value 89.226488
iter  70 value 86.876044
iter  80 value 86.805319
iter  90 value 85.923744
iter 100 value 85.749817
final  value 85.749817 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.692511 
iter  10 value 92.952471
iter  20 value 87.051154
iter  30 value 86.995334
iter  40 value 86.890522
iter  50 value 86.864026
final  value 86.863159 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.688881 
iter  10 value 94.050386
iter  20 value 93.681082
iter  30 value 93.638779
final  value 93.522440 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.945137 
iter  10 value 93.923708
iter  20 value 93.917509
final  value 93.916485 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.064149 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.559417 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.268435 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.127249 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.104461 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.684445 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.160094 
iter  10 value 92.837252
iter  20 value 92.394207
final  value 92.392765 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.224416 
final  value 94.436782 
converged
Fitting Repeat 4 

# weights:  305
initial  value 117.803686 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.886347 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.236692 
final  value 94.332857 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.601860 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.865613 
iter  10 value 94.194892
final  value 94.144481 
converged
Fitting Repeat 4 

# weights:  507
initial  value 117.658995 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.753082 
final  value 94.466822 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.733973 
iter  10 value 93.469847
iter  20 value 88.822285
iter  30 value 87.101948
iter  40 value 86.034062
iter  50 value 85.777207
iter  60 value 85.746267
iter  60 value 85.746266
iter  60 value 85.746266
final  value 85.746266 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.915530 
iter  10 value 94.490295
iter  20 value 94.478588
iter  30 value 86.473990
iter  40 value 86.357214
iter  50 value 86.168550
iter  60 value 86.030328
iter  70 value 85.935636
final  value 85.935104 
converged
Fitting Repeat 3 

# weights:  103
initial  value 108.015741 
iter  10 value 94.373832
iter  20 value 89.198900
iter  30 value 87.578224
iter  40 value 86.031231
iter  50 value 85.928114
final  value 85.917007 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.771565 
iter  10 value 94.581931
iter  20 value 94.487380
iter  30 value 94.397886
iter  40 value 93.266949
iter  50 value 86.112839
iter  60 value 85.842921
iter  70 value 85.289782
iter  80 value 85.277942
iter  90 value 85.274677
final  value 85.273965 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.014417 
iter  10 value 94.229194
iter  20 value 86.298886
iter  30 value 86.049903
iter  40 value 85.917184
iter  40 value 85.917183
iter  40 value 85.917183
final  value 85.917183 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.858782 
iter  10 value 95.258725
iter  20 value 94.605582
iter  30 value 92.036748
iter  40 value 86.270134
iter  50 value 85.874121
iter  60 value 84.265377
iter  70 value 82.803271
iter  80 value 82.266259
iter  90 value 82.144713
iter 100 value 82.136335
final  value 82.136335 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.476175 
iter  10 value 94.525325
iter  20 value 90.186838
iter  30 value 84.868457
iter  40 value 84.555691
iter  50 value 84.276987
iter  60 value 84.113617
iter  70 value 84.096014
iter  80 value 82.987692
iter  90 value 82.744104
iter 100 value 82.361521
final  value 82.361521 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.966343 
iter  10 value 94.367734
iter  20 value 88.580515
iter  30 value 85.802129
iter  40 value 84.033386
iter  50 value 83.008720
iter  60 value 82.854283
iter  70 value 82.736878
iter  80 value 82.563464
iter  90 value 82.533876
iter 100 value 82.508637
final  value 82.508637 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.216899 
iter  10 value 94.439523
iter  20 value 93.155640
iter  30 value 91.134982
iter  40 value 87.872584
iter  50 value 85.020824
iter  60 value 83.891590
iter  70 value 83.309949
iter  80 value 82.990438
iter  90 value 82.276396
iter 100 value 81.956442
final  value 81.956442 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 116.961942 
iter  10 value 94.436015
iter  20 value 87.216175
iter  30 value 85.538144
iter  40 value 84.841958
iter  50 value 84.067912
iter  60 value 83.064890
iter  70 value 82.208106
iter  80 value 82.058406
iter  90 value 81.845288
iter 100 value 81.833149
final  value 81.833149 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.761808 
iter  10 value 94.515492
iter  20 value 90.101678
iter  30 value 85.585323
iter  40 value 84.480298
iter  50 value 83.404301
iter  60 value 83.309076
iter  70 value 82.851210
iter  80 value 82.664550
iter  90 value 82.463339
iter 100 value 82.268149
final  value 82.268149 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.561124 
iter  10 value 94.676497
iter  20 value 90.279677
iter  30 value 86.482356
iter  40 value 84.539763
iter  50 value 83.855723
iter  60 value 83.251193
iter  70 value 83.086485
iter  80 value 82.809079
iter  90 value 82.524568
iter 100 value 82.137679
final  value 82.137679 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 118.191961 
iter  10 value 94.575380
iter  20 value 88.868012
iter  30 value 87.598013
iter  40 value 84.949585
iter  50 value 83.451750
iter  60 value 82.871613
iter  70 value 82.114763
iter  80 value 81.977546
iter  90 value 81.588124
iter 100 value 81.412577
final  value 81.412577 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.376593 
iter  10 value 94.112890
iter  20 value 91.659795
iter  30 value 89.502588
iter  40 value 87.765793
iter  50 value 86.517972
iter  60 value 85.523021
iter  70 value 84.878221
iter  80 value 83.977654
iter  90 value 83.353129
iter 100 value 83.292209
final  value 83.292209 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.212736 
iter  10 value 95.056051
iter  20 value 88.906596
iter  30 value 86.316012
iter  40 value 85.572627
iter  50 value 82.780979
iter  60 value 82.350929
iter  70 value 82.287814
iter  80 value 82.187196
iter  90 value 82.110899
iter 100 value 81.896029
final  value 81.896029 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.937220 
final  value 94.486075 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.300028 
final  value 94.485840 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.631697 
iter  10 value 94.466409
iter  20 value 87.955347
iter  30 value 87.277981
iter  40 value 86.641270
iter  50 value 86.628192
final  value 86.626033 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.295122 
iter  10 value 94.486308
final  value 94.484390 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.571376 
iter  10 value 94.468314
iter  20 value 94.458122
final  value 94.254619 
converged
Fitting Repeat 1 

# weights:  305
initial  value 115.876479 
iter  10 value 94.471509
iter  20 value 94.467620
iter  30 value 87.714659
iter  40 value 86.766732
iter  50 value 86.708715
iter  60 value 86.667609
iter  70 value 86.629568
iter  80 value 85.917255
iter  90 value 83.966807
iter 100 value 83.910672
final  value 83.910672 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 117.711236 
iter  10 value 94.489292
iter  20 value 94.479556
iter  30 value 88.135741
iter  40 value 87.836624
iter  50 value 87.085612
iter  60 value 85.057311
iter  70 value 84.653397
iter  80 value 82.774153
iter  90 value 82.474254
iter 100 value 82.472527
final  value 82.472527 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 98.893337 
iter  10 value 94.489044
iter  20 value 94.003290
iter  30 value 91.216818
iter  40 value 91.203194
iter  50 value 91.182759
iter  60 value 90.552937
iter  70 value 90.544802
final  value 90.544717 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.058565 
iter  10 value 94.471414
iter  20 value 94.429217
iter  30 value 92.613666
iter  40 value 92.393409
final  value 92.393385 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.121338 
iter  10 value 94.485810
iter  20 value 92.914211
final  value 92.889906 
converged
Fitting Repeat 1 

# weights:  507
initial  value 116.157719 
iter  10 value 94.156807
iter  20 value 93.885486
iter  30 value 93.878478
iter  40 value 93.872613
iter  50 value 92.449448
iter  60 value 85.478230
iter  70 value 85.199947
iter  80 value 85.151051
iter  90 value 84.385774
iter 100 value 84.335890
final  value 84.335890 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.174715 
iter  10 value 94.474879
iter  20 value 94.467384
iter  30 value 86.980651
iter  40 value 86.680508
iter  50 value 86.164995
iter  60 value 83.581377
iter  70 value 83.417296
iter  80 value 83.416338
iter  90 value 83.398712
iter 100 value 83.286978
final  value 83.286978 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 119.316790 
iter  10 value 94.474788
iter  20 value 94.467166
iter  30 value 94.323042
iter  30 value 94.323042
iter  30 value 94.323042
final  value 94.323042 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.955353 
iter  10 value 94.436211
iter  20 value 94.428632
iter  30 value 94.428291
final  value 94.428251 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.021584 
iter  10 value 94.489191
iter  20 value 93.984536
iter  30 value 86.366623
iter  40 value 83.749643
iter  50 value 83.745123
iter  60 value 83.737013
iter  70 value 83.729505
iter  80 value 83.728710
iter  90 value 83.700903
iter 100 value 83.476451
final  value 83.476451 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 135.095359 
iter  10 value 118.232221
iter  20 value 117.782249
iter  30 value 108.791980
iter  40 value 106.171993
iter  50 value 103.607007
iter  60 value 102.142179
iter  70 value 101.492908
iter  80 value 101.201908
iter  90 value 101.079810
iter 100 value 100.795200
final  value 100.795200 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 145.127346 
iter  10 value 117.905082
iter  20 value 115.331365
iter  30 value 108.789060
iter  40 value 107.643739
iter  50 value 106.870467
iter  60 value 106.142841
iter  70 value 102.762110
iter  80 value 102.347149
iter  90 value 101.629783
iter 100 value 101.435461
final  value 101.435461 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 125.641295 
iter  10 value 117.915615
iter  20 value 109.492402
iter  30 value 108.458327
iter  40 value 108.113136
iter  50 value 105.013237
iter  60 value 104.786502
iter  70 value 104.567805
iter  80 value 103.459983
iter  90 value 102.578512
iter 100 value 102.183443
final  value 102.183443 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 135.769523 
iter  10 value 116.782522
iter  20 value 108.162352
iter  30 value 107.565647
iter  40 value 105.844826
iter  50 value 102.972816
iter  60 value 102.426291
iter  70 value 101.926289
iter  80 value 101.377549
iter  90 value 101.100048
iter 100 value 100.919387
final  value 100.919387 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 139.829785 
iter  10 value 117.981790
iter  20 value 117.584089
iter  30 value 111.247074
iter  40 value 106.724038
iter  50 value 104.744526
iter  60 value 102.991703
iter  70 value 101.486446
iter  80 value 100.982962
iter  90 value 100.774076
iter 100 value 100.609937
final  value 100.609937 
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 -- Mon Feb  3 23:20:27 2025 
*********************************************** 
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 
Warning messages:
1: `repeats` has no meaning for this resampling method. 
2: executing %dopar% sequentially: no parallel backend registered 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
 38.951   0.826 116.466