##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings HPiP_1.17.2.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2026-03-05 r89546)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
    GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
* running under: Ubuntu 24.04.4 LTS
* using session charset: UTF-8
* current time: 2026-03-14 04:26:01 UTC
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.17.2’
* 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 ... INFO
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       35.660  0.645  36.332
corr_plot     34.976  0.462  35.484
FSmethod      33.452  0.640  34.126
pred_ensembel 13.158  0.312  12.147
enrichfindP    0.529  0.050  11.546
* 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: 2 NOTEs
See
  ‘/home/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.23-bioc/R/site-library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.17.2’
** 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 Under development (unstable) (2026-03-05 r89546) -- "Unsuffered Consequences"
Copyright (C) 2026 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 113.629573 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 109.407832 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.766616 
final  value 94.050051 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.282245 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.562715 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.436560 
final  value 93.915746 
converged
Fitting Repeat 2 

# weights:  305
initial  value 113.471556 
iter  10 value 93.697116
iter  20 value 93.688290
final  value 93.687996 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.132697 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.188722 
final  value 93.371808 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.409090 
iter  10 value 93.371782
iter  20 value 92.740832
iter  30 value 92.735651
final  value 92.735634 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.984728 
iter  10 value 93.697415
iter  20 value 93.697146
final  value 93.697144 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.365007 
final  value 94.050051 
converged
Fitting Repeat 3 

# weights:  507
initial  value 137.666010 
final  value 94.050051 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.202736 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.826835 
iter  10 value 93.915746
iter  10 value 93.915746
iter  10 value 93.915746
final  value 93.915746 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.458138 
iter  10 value 94.051957
iter  20 value 93.981796
iter  30 value 93.946442
iter  40 value 93.750875
iter  50 value 87.370721
iter  60 value 83.304845
iter  70 value 82.318565
iter  80 value 81.715815
iter  90 value 81.590310
iter 100 value 81.467854
final  value 81.467854 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 105.653089 
iter  10 value 93.458377
iter  20 value 90.523562
iter  30 value 87.105711
iter  40 value 86.216155
iter  50 value 85.638835
iter  60 value 85.008617
iter  70 value 83.813267
iter  80 value 83.787301
iter  90 value 83.780241
final  value 83.780213 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.042852 
iter  10 value 94.048174
iter  20 value 93.779438
iter  30 value 93.415023
iter  40 value 93.376443
iter  50 value 88.207676
iter  60 value 83.822489
iter  70 value 83.170194
iter  80 value 82.915281
iter  90 value 82.740026
iter 100 value 82.719599
final  value 82.719599 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.699706 
iter  10 value 94.037432
iter  20 value 89.437554
iter  30 value 85.434424
iter  40 value 83.533356
iter  50 value 82.707635
iter  60 value 82.393980
iter  70 value 81.978885
iter  80 value 81.514827
iter  90 value 81.359778
iter 100 value 81.270465
final  value 81.270465 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 96.743510 
iter  10 value 94.033815
iter  20 value 87.874553
iter  30 value 86.328122
iter  40 value 85.443099
iter  50 value 81.847420
iter  60 value 81.605196
iter  70 value 81.563134
iter  80 value 81.428077
iter  90 value 81.261757
iter 100 value 81.232991
final  value 81.232991 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 103.628447 
iter  10 value 95.023455
iter  20 value 94.138118
iter  30 value 94.019947
iter  40 value 91.951463
iter  50 value 88.289720
iter  60 value 85.146963
iter  70 value 84.345092
iter  80 value 83.629979
iter  90 value 81.550645
iter 100 value 80.818742
final  value 80.818742 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 98.997300 
iter  10 value 94.454417
iter  20 value 88.474147
iter  30 value 86.298775
iter  40 value 85.276501
iter  50 value 84.466383
iter  60 value 84.325090
iter  70 value 83.880588
iter  80 value 83.780432
iter  90 value 83.778603
iter 100 value 83.674237
final  value 83.674237 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.381603 
iter  10 value 94.050296
iter  20 value 87.891026
iter  30 value 83.827931
iter  40 value 83.773932
iter  50 value 82.418158
iter  60 value 81.873515
iter  70 value 81.641489
iter  80 value 81.141943
iter  90 value 80.569866
iter 100 value 80.439915
final  value 80.439915 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.380440 
iter  10 value 94.093977
iter  20 value 92.526475
iter  30 value 88.226639
iter  40 value 82.814568
iter  50 value 80.907679
iter  60 value 80.593427
iter  70 value 80.517231
iter  80 value 80.488652
iter  90 value 80.467582
iter 100 value 80.461493
final  value 80.461493 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.947032 
iter  10 value 94.017641
iter  20 value 93.368888
iter  30 value 86.820386
iter  40 value 85.065880
iter  50 value 84.165123
iter  60 value 83.388219
iter  70 value 82.248959
iter  80 value 81.198139
iter  90 value 80.484691
iter 100 value 80.311018
final  value 80.311018 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.148543 
iter  10 value 92.517040
iter  20 value 88.766006
iter  30 value 83.809013
iter  40 value 83.616381
iter  50 value 83.486734
iter  60 value 83.441284
iter  70 value 82.955085
iter  80 value 81.875580
iter  90 value 81.330000
iter 100 value 81.136716
final  value 81.136716 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 124.963561 
iter  10 value 93.668341
iter  20 value 86.314455
iter  30 value 82.783372
iter  40 value 81.354743
iter  50 value 80.664964
iter  60 value 80.520581
iter  70 value 80.290809
iter  80 value 80.120718
iter  90 value 80.050741
iter 100 value 80.033538
final  value 80.033538 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.379610 
iter  10 value 94.427627
iter  20 value 93.335024
iter  30 value 91.748722
iter  40 value 84.876183
iter  50 value 84.122462
iter  60 value 83.486226
iter  70 value 83.215999
iter  80 value 82.745733
iter  90 value 80.724703
iter 100 value 79.813818
final  value 79.813818 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 117.996609 
iter  10 value 94.263047
iter  20 value 93.881105
iter  30 value 92.854846
iter  40 value 86.162398
iter  50 value 83.032993
iter  60 value 82.613982
iter  70 value 82.171208
iter  80 value 81.274985
iter  90 value 80.978911
iter 100 value 80.095789
final  value 80.095789 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 102.866291 
iter  10 value 95.431396
iter  20 value 92.159375
iter  30 value 87.780507
iter  40 value 85.524823
iter  50 value 83.201225
iter  60 value 81.982835
iter  70 value 81.096669
iter  80 value 80.821266
iter  90 value 80.613402
iter 100 value 80.348414
final  value 80.348414 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.050530 
final  value 93.917511 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.900223 
final  value 94.054635 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.058791 
final  value 94.054534 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.830427 
final  value 94.054610 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.107022 
final  value 94.054563 
converged
Fitting Repeat 1 

# weights:  305
initial  value 121.857734 
iter  10 value 94.058158
iter  20 value 94.030081
iter  30 value 92.015365
iter  40 value 91.503406
iter  50 value 91.503085
iter  60 value 91.502925
iter  70 value 87.530052
iter  80 value 85.069632
iter  90 value 84.414199
iter 100 value 84.400427
final  value 84.400427 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 94.847816 
iter  10 value 86.558546
iter  20 value 84.280111
iter  30 value 84.196858
iter  40 value 83.953454
iter  50 value 83.162618
iter  60 value 82.837821
iter  70 value 82.834380
iter  80 value 82.833798
iter  90 value 82.370197
iter 100 value 81.694907
final  value 81.694907 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 96.238188 
iter  10 value 94.055229
iter  20 value 94.045077
iter  30 value 90.947046
iter  40 value 90.734864
iter  50 value 90.733813
final  value 90.733805 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.920482 
iter  10 value 94.057382
iter  20 value 94.034652
iter  30 value 92.088438
iter  40 value 85.788185
iter  50 value 85.695663
iter  60 value 85.676664
iter  70 value 85.675038
iter  80 value 83.618798
iter  90 value 83.444657
iter 100 value 81.529233
final  value 81.529233 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 122.681135 
iter  10 value 94.057472
iter  20 value 93.981585
iter  30 value 85.315048
iter  40 value 82.879397
iter  50 value 81.950784
iter  60 value 80.417404
iter  70 value 80.061498
iter  80 value 79.737007
iter  90 value 79.735857
final  value 79.735825 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.922072 
iter  10 value 93.923470
iter  20 value 93.580483
iter  30 value 93.570648
final  value 93.570540 
converged
Fitting Repeat 2 

# weights:  507
initial  value 117.491028 
iter  10 value 87.421365
iter  20 value 85.529157
iter  30 value 85.524251
iter  40 value 85.518795
iter  50 value 85.126506
iter  60 value 82.438127
iter  70 value 82.375167
iter  80 value 82.094554
iter  90 value 80.558278
iter 100 value 79.295748
final  value 79.295748 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.389787 
iter  10 value 91.001737
iter  20 value 89.990582
iter  30 value 89.974215
iter  40 value 89.973337
iter  50 value 86.992825
iter  60 value 86.048071
iter  70 value 85.884956
iter  80 value 85.734875
iter  90 value 85.508135
final  value 85.507581 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.469372 
iter  10 value 94.060959
iter  20 value 90.429005
iter  30 value 87.059194
iter  40 value 84.614482
iter  50 value 84.554257
iter  60 value 84.314708
iter  70 value 84.312554
iter  80 value 84.259848
iter  90 value 83.915034
iter 100 value 83.811773
final  value 83.811773 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 123.210839 
iter  10 value 93.924332
iter  20 value 93.919037
iter  30 value 93.917475
iter  40 value 93.912049
iter  50 value 92.606702
iter  60 value 87.534375
iter  70 value 87.532017
iter  80 value 87.530431
iter  90 value 87.505601
iter 100 value 85.827012
final  value 85.827012 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.482475 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.331486 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.247366 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.552307 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.292519 
final  value 94.033149 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.438147 
final  value 94.052904 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.468806 
final  value 94.008696 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.352477 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.345821 
iter  10 value 92.034212
final  value 92.034056 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.900085 
final  value 94.052911 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.019592 
iter  10 value 93.994012
iter  10 value 93.994012
iter  10 value 93.994012
final  value 93.994012 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.545889 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 130.339878 
iter  10 value 94.052910
iter  10 value 94.052910
iter  10 value 94.052910
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.429051 
iter  10 value 92.929795
iter  20 value 88.107700
iter  30 value 88.094418
final  value 88.024699 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.986286 
final  value 94.017143 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.711964 
iter  10 value 92.320154
iter  20 value 92.079155
iter  30 value 91.660682
iter  40 value 91.528105
iter  50 value 90.975114
iter  60 value 90.922819
iter  70 value 90.922313
final  value 90.922310 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.844253 
iter  10 value 94.056715
iter  20 value 92.181511
iter  30 value 86.237626
iter  40 value 84.996915
iter  50 value 84.596883
iter  60 value 84.073893
final  value 84.067342 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.990907 
iter  10 value 94.058331
iter  20 value 94.056654
iter  30 value 86.118435
iter  40 value 85.047702
iter  50 value 84.968524
iter  60 value 83.963554
iter  70 value 83.552779
iter  80 value 83.414371
iter  90 value 83.389407
final  value 83.385077 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.521802 
iter  10 value 93.528764
iter  20 value 91.639168
iter  30 value 91.230675
iter  40 value 91.059127
iter  50 value 91.045043
final  value 91.045013 
converged
Fitting Repeat 5 

# weights:  103
initial  value 109.998440 
iter  10 value 93.735075
iter  20 value 90.050161
iter  30 value 87.012862
iter  40 value 86.654344
iter  50 value 86.029216
iter  60 value 84.177439
iter  70 value 83.393416
iter  80 value 82.571946
iter  90 value 81.877853
iter 100 value 81.653278
final  value 81.653278 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 106.518053 
iter  10 value 94.878210
iter  20 value 93.599353
iter  30 value 89.012909
iter  40 value 85.867004
iter  50 value 84.711777
iter  60 value 84.546904
iter  70 value 84.357713
iter  80 value 82.540931
iter  90 value 81.952292
iter 100 value 81.739616
final  value 81.739616 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.989526 
iter  10 value 93.044746
iter  20 value 88.726056
iter  30 value 85.875603
iter  40 value 84.016048
iter  50 value 83.934535
iter  60 value 83.841951
iter  70 value 83.816801
iter  80 value 83.776500
iter  90 value 83.698448
iter 100 value 83.632808
final  value 83.632808 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.361288 
iter  10 value 94.058543
iter  20 value 90.948843
iter  30 value 85.865152
iter  40 value 83.006699
iter  50 value 82.500080
iter  60 value 81.976931
iter  70 value 81.308247
iter  80 value 80.605064
iter  90 value 80.269113
iter 100 value 80.166727
final  value 80.166727 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.299285 
iter  10 value 93.843332
iter  20 value 85.562421
iter  30 value 85.058076
iter  40 value 84.934599
iter  50 value 84.849163
iter  60 value 83.528914
iter  70 value 81.743148
iter  80 value 81.451859
iter  90 value 81.327772
iter 100 value 81.283155
final  value 81.283155 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.823508 
iter  10 value 94.093494
iter  20 value 92.520181
iter  30 value 88.552102
iter  40 value 84.343118
iter  50 value 83.819710
iter  60 value 83.340046
iter  70 value 82.487685
iter  80 value 81.646927
iter  90 value 81.337858
iter 100 value 80.898794
final  value 80.898794 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 126.216733 
iter  10 value 94.205781
iter  20 value 94.104688
iter  30 value 91.518031
iter  40 value 90.472912
iter  50 value 89.943345
iter  60 value 87.789118
iter  70 value 83.439002
iter  80 value 82.647459
iter  90 value 82.287802
iter 100 value 81.938189
final  value 81.938189 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.133426 
iter  10 value 94.065752
iter  20 value 90.000312
iter  30 value 87.056510
iter  40 value 83.443931
iter  50 value 82.924532
iter  60 value 82.334076
iter  70 value 81.392246
iter  80 value 81.132089
iter  90 value 80.941127
iter 100 value 80.722229
final  value 80.722229 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 125.066053 
iter  10 value 94.483876
iter  20 value 90.998835
iter  30 value 89.774216
iter  40 value 89.471456
iter  50 value 86.251302
iter  60 value 82.547299
iter  70 value 82.262323
iter  80 value 81.401534
iter  90 value 81.199783
iter 100 value 81.044074
final  value 81.044074 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.954634 
iter  10 value 93.391805
iter  20 value 86.100932
iter  30 value 85.490277
iter  40 value 84.813677
iter  50 value 84.495644
iter  60 value 83.809522
iter  70 value 83.485445
iter  80 value 83.282832
iter  90 value 83.069079
iter 100 value 81.862777
final  value 81.862777 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.162565 
iter  10 value 93.001530
iter  20 value 89.240735
iter  30 value 87.596197
iter  40 value 84.681710
iter  50 value 83.544829
iter  60 value 81.919006
iter  70 value 81.335226
iter  80 value 80.987661
iter  90 value 80.852694
iter 100 value 80.759126
final  value 80.759126 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 107.319367 
final  value 94.054578 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.371459 
final  value 94.054439 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.609881 
final  value 94.054573 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.598724 
final  value 94.054778 
converged
Fitting Repeat 5 

# weights:  103
initial  value 118.513123 
final  value 94.054625 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.868361 
iter  10 value 94.058269
iter  20 value 93.914509
iter  30 value 85.634077
iter  40 value 84.088571
iter  50 value 83.838884
iter  60 value 83.552426
iter  70 value 82.412715
iter  80 value 82.377784
iter  90 value 82.372012
iter 100 value 82.304902
final  value 82.304902 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.157927 
iter  10 value 94.056534
iter  20 value 92.921065
iter  30 value 86.826489
iter  40 value 86.775854
iter  50 value 86.775615
iter  60 value 86.432573
iter  70 value 86.388689
final  value 86.387938 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.695090 
iter  10 value 94.057081
iter  20 value 91.386258
iter  30 value 91.252036
final  value 91.251876 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.634219 
iter  10 value 94.057808
iter  20 value 93.908243
iter  30 value 86.933603
final  value 86.796406 
converged
Fitting Repeat 5 

# weights:  305
initial  value 117.427690 
iter  10 value 94.013529
iter  20 value 93.914565
iter  30 value 93.735284
iter  40 value 92.235506
iter  50 value 92.174467
iter  60 value 92.174221
final  value 92.173865 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.956221 
iter  10 value 94.026094
iter  20 value 87.926431
iter  30 value 85.681037
iter  40 value 84.462093
iter  50 value 84.367570
iter  60 value 84.332367
iter  70 value 84.249716
iter  80 value 84.123722
iter  90 value 84.119710
iter 100 value 83.438741
final  value 83.438741 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.512869 
iter  10 value 94.061602
iter  20 value 93.275385
iter  30 value 84.899872
iter  40 value 84.039401
final  value 84.038929 
converged
Fitting Repeat 3 

# weights:  507
initial  value 112.151244 
iter  10 value 94.060888
iter  20 value 91.955794
iter  30 value 91.616146
iter  40 value 91.615907
iter  50 value 91.147623
iter  60 value 91.143462
final  value 91.143433 
converged
Fitting Repeat 4 

# weights:  507
initial  value 114.497455 
iter  10 value 94.024969
iter  20 value 92.890287
iter  30 value 91.838936
iter  40 value 91.441643
iter  50 value 91.437484
iter  60 value 91.428955
iter  70 value 91.428736
iter  80 value 91.426890
iter  90 value 91.425820
iter 100 value 91.425071
final  value 91.425071 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.998332 
iter  10 value 94.017093
iter  20 value 94.009485
final  value 94.008951 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.959635 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.054612 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.242636 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.130480 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.386237 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.067177 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.644098 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.249182 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.658766 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.575845 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.999891 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 110.483987 
final  value 93.320225 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.208173 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 115.233320 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.783833 
final  value 94.026542 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.805698 
iter  10 value 94.488615
iter  10 value 94.488615
iter  20 value 94.386411
iter  30 value 89.168025
iter  40 value 88.437404
iter  50 value 88.167862
iter  60 value 87.499882
iter  70 value 86.198610
iter  80 value 84.775368
iter  90 value 84.253693
iter 100 value 83.983756
final  value 83.983756 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 103.540814 
iter  10 value 94.488831
iter  20 value 94.127294
iter  30 value 93.021778
iter  40 value 88.240103
iter  50 value 87.746576
iter  60 value 87.388882
iter  70 value 84.873352
iter  80 value 84.782265
iter  90 value 84.615720
iter 100 value 83.981472
final  value 83.981472 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 114.364575 
iter  10 value 94.486554
iter  20 value 94.275792
iter  30 value 93.653002
iter  40 value 93.451933
iter  50 value 93.170970
iter  60 value 88.904967
iter  70 value 87.680315
iter  80 value 87.266840
final  value 87.252415 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.101207 
iter  10 value 93.453526
iter  20 value 92.134416
iter  30 value 90.209798
iter  40 value 89.517463
iter  50 value 85.311762
iter  60 value 84.291745
iter  70 value 83.977392
iter  80 value 83.902943
final  value 83.902941 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.394807 
iter  10 value 93.694342
iter  20 value 93.163510
iter  30 value 88.897577
iter  40 value 88.433141
iter  50 value 88.201215
iter  60 value 88.181764
iter  70 value 87.211143
iter  80 value 86.830818
final  value 86.830123 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.228425 
iter  10 value 94.663343
iter  20 value 91.021276
iter  30 value 87.937796
iter  40 value 87.105297
iter  50 value 85.034964
iter  60 value 84.532536
iter  70 value 84.289897
iter  80 value 84.226998
iter  90 value 84.092177
iter 100 value 83.769940
final  value 83.769940 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 114.921215 
iter  10 value 94.028885
iter  20 value 89.111438
iter  30 value 88.364334
iter  40 value 88.032722
iter  50 value 87.430512
iter  60 value 86.590728
iter  70 value 86.078990
iter  80 value 84.828509
iter  90 value 84.337383
iter 100 value 84.215004
final  value 84.215004 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.823595 
iter  10 value 95.014525
iter  20 value 94.567400
iter  30 value 93.546255
iter  40 value 88.244389
iter  50 value 87.856460
iter  60 value 87.060099
iter  70 value 86.231780
iter  80 value 86.191364
iter  90 value 86.085941
iter 100 value 85.755138
final  value 85.755138 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 126.160124 
iter  10 value 94.506558
iter  20 value 93.938260
iter  30 value 91.426398
iter  40 value 86.273368
iter  50 value 85.780272
iter  60 value 84.256711
iter  70 value 83.677097
iter  80 value 83.269806
iter  90 value 83.085980
iter 100 value 82.991010
final  value 82.991010 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.574415 
iter  10 value 94.555197
iter  20 value 94.379281
iter  30 value 93.581981
iter  40 value 89.772367
iter  50 value 85.736854
iter  60 value 83.692857
iter  70 value 83.179084
iter  80 value 82.943021
iter  90 value 82.850611
iter 100 value 82.719670
final  value 82.719670 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.581143 
iter  10 value 94.408144
iter  20 value 88.811041
iter  30 value 87.247195
iter  40 value 85.505252
iter  50 value 84.123371
iter  60 value 83.701226
iter  70 value 83.180906
iter  80 value 83.087711
iter  90 value 82.831090
iter 100 value 82.802870
final  value 82.802870 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.145154 
iter  10 value 94.064385
iter  20 value 88.282372
iter  30 value 85.740613
iter  40 value 84.271567
iter  50 value 83.963517
iter  60 value 83.677634
iter  70 value 82.917505
iter  80 value 82.682346
iter  90 value 82.552604
iter 100 value 82.507234
final  value 82.507234 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 126.602057 
iter  10 value 94.784012
iter  20 value 93.276223
iter  30 value 88.371389
iter  40 value 88.052210
iter  50 value 87.023342
iter  60 value 86.801106
iter  70 value 86.531208
iter  80 value 86.052229
iter  90 value 84.658624
iter 100 value 83.593777
final  value 83.593777 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.268321 
iter  10 value 93.921144
iter  20 value 89.342319
iter  30 value 85.963384
iter  40 value 85.065675
iter  50 value 84.812890
iter  60 value 84.559227
iter  70 value 84.364958
iter  80 value 83.852409
iter  90 value 83.173161
iter 100 value 82.858445
final  value 82.858445 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 148.791193 
iter  10 value 100.645933
iter  20 value 99.109500
iter  30 value 94.533953
iter  40 value 94.251097
iter  50 value 94.125710
iter  60 value 92.408845
iter  70 value 88.693430
iter  80 value 87.791120
iter  90 value 85.807094
iter 100 value 85.360373
final  value 85.360373 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.954076 
final  value 94.485779 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.090565 
iter  10 value 94.485759
iter  20 value 93.914804
iter  30 value 87.486990
iter  40 value 86.030471
iter  50 value 85.989482
iter  60 value 85.988925
iter  70 value 85.958552
iter  80 value 85.953522
final  value 85.953407 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.629563 
final  value 94.485901 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.649448 
final  value 94.485952 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.667132 
final  value 94.485981 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.953091 
iter  10 value 93.958729
iter  20 value 93.863570
iter  30 value 91.859885
iter  40 value 87.111897
iter  50 value 86.482238
iter  60 value 86.412929
iter  70 value 85.148191
iter  80 value 82.625746
iter  90 value 81.959319
iter 100 value 81.769062
final  value 81.769062 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.004608 
iter  10 value 94.488627
iter  20 value 94.123642
iter  30 value 93.527481
iter  40 value 93.496328
final  value 93.489411 
converged
Fitting Repeat 3 

# weights:  305
initial  value 113.218216 
iter  10 value 93.400173
iter  20 value 93.325759
iter  30 value 93.320938
iter  40 value 93.239885
iter  50 value 93.189700
iter  60 value 91.157007
iter  70 value 87.592769
iter  80 value 85.037077
iter  90 value 84.577103
iter 100 value 84.490127
final  value 84.490127 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 94.890817 
iter  10 value 94.488920
iter  20 value 94.474549
iter  30 value 93.387005
iter  40 value 91.912176
iter  50 value 85.978503
iter  60 value 84.480086
iter  70 value 82.761404
iter  80 value 82.250915
iter  90 value 81.709606
iter 100 value 81.636905
final  value 81.636905 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.937434 
iter  10 value 94.489414
iter  20 value 94.412091
iter  30 value 91.122112
iter  40 value 85.667404
iter  50 value 85.652160
iter  60 value 85.585544
iter  70 value 85.578334
final  value 85.578302 
converged
Fitting Repeat 1 

# weights:  507
initial  value 111.696216 
iter  10 value 94.035825
iter  20 value 94.028891
iter  30 value 93.019709
iter  40 value 88.897236
iter  50 value 87.944307
iter  60 value 87.941583
iter  70 value 87.927178
iter  80 value 87.919615
iter  90 value 87.716330
iter 100 value 86.735882
final  value 86.735882 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.864678 
iter  10 value 94.403002
iter  20 value 92.746322
iter  30 value 91.840840
iter  40 value 91.795313
final  value 91.792296 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.108048 
iter  10 value 93.374026
iter  20 value 93.300965
iter  30 value 93.300415
iter  40 value 92.367458
iter  50 value 91.005434
iter  60 value 85.007271
iter  70 value 84.004780
iter  80 value 83.765049
iter  90 value 83.581618
iter 100 value 83.444169
final  value 83.444169 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.203826 
iter  10 value 93.328315
iter  20 value 93.266365
iter  30 value 93.181953
iter  40 value 87.892950
iter  50 value 87.459922
iter  60 value 87.457618
final  value 87.456857 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.475151 
iter  10 value 94.491453
iter  20 value 94.473103
iter  30 value 91.581870
iter  40 value 88.715993
iter  50 value 88.305220
iter  60 value 88.301925
iter  70 value 88.293236
final  value 88.293156 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.981032 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.992643 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 111.658711 
iter  10 value 92.676052
iter  20 value 92.468386
iter  30 value 90.150378
iter  40 value 90.130660
final  value 90.130615 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.500431 
final  value 94.484210 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.507171 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.075499 
final  value 94.484210 
converged
Fitting Repeat 2 

# weights:  305
initial  value 117.103888 
final  value 94.105263 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.402804 
iter  10 value 84.629369
iter  20 value 83.851904
iter  30 value 81.773239
iter  40 value 81.265735
iter  50 value 81.262695
final  value 81.262629 
converged
Fitting Repeat 4 

# weights:  305
initial  value 109.366845 
iter  10 value 94.332829
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.926770 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 125.316545 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.812083 
final  value 93.874609 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.724134 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 110.696498 
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.839570 
final  value 94.275362 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.479255 
iter  10 value 86.301980
iter  20 value 84.924711
iter  30 value 82.711313
iter  40 value 82.625275
iter  50 value 82.575727
iter  60 value 82.254549
iter  70 value 82.150897
iter  80 value 81.821502
iter  90 value 81.581199
final  value 81.580130 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.708738 
iter  10 value 94.354424
iter  20 value 90.032195
iter  30 value 89.442679
iter  40 value 85.565576
iter  50 value 83.653286
iter  60 value 83.290145
iter  70 value 83.179400
iter  80 value 83.153248
iter  90 value 83.128661
iter 100 value 80.482646
final  value 80.482646 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 130.074530 
iter  10 value 94.284859
iter  20 value 83.774724
iter  30 value 82.429068
iter  40 value 82.408244
iter  50 value 82.077796
iter  60 value 81.957814
iter  70 value 81.610217
iter  80 value 81.592147
final  value 81.591657 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.167386 
iter  10 value 94.491528
iter  20 value 91.077527
iter  30 value 87.272091
iter  40 value 85.473984
iter  50 value 81.687257
iter  60 value 81.584206
iter  70 value 81.580201
final  value 81.580130 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.916118 
iter  10 value 92.818882
iter  20 value 90.058630
iter  30 value 83.514597
iter  40 value 81.535500
iter  50 value 80.131253
iter  60 value 79.830968
iter  70 value 79.674057
iter  80 value 79.632825
iter  90 value 79.468108
iter 100 value 79.418666
final  value 79.418666 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 109.471812 
iter  10 value 94.643847
iter  20 value 94.337443
iter  30 value 92.753168
iter  40 value 82.480958
iter  50 value 80.858398
iter  60 value 80.059203
iter  70 value 79.916822
iter  80 value 79.374097
iter  90 value 78.645112
iter 100 value 78.208882
final  value 78.208882 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 114.325237 
iter  10 value 94.682729
iter  20 value 93.068696
iter  30 value 90.651045
iter  40 value 90.494110
iter  50 value 90.453988
iter  60 value 90.373840
iter  70 value 88.845457
iter  80 value 82.472772
iter  90 value 80.697448
iter 100 value 80.305944
final  value 80.305944 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 109.033500 
iter  10 value 94.488562
iter  20 value 83.409202
iter  30 value 82.392235
iter  40 value 82.068916
iter  50 value 80.352916
iter  60 value 79.115261
iter  70 value 78.692709
iter  80 value 78.553541
iter  90 value 78.369422
iter 100 value 78.147066
final  value 78.147066 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.158781 
iter  10 value 94.392000
iter  20 value 93.888409
iter  30 value 83.590576
iter  40 value 82.786778
iter  50 value 80.233688
iter  60 value 79.551946
iter  70 value 79.094758
iter  80 value 78.367852
iter  90 value 77.879634
iter 100 value 77.515997
final  value 77.515997 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.247010 
iter  10 value 94.481817
iter  20 value 83.674241
iter  30 value 82.336432
iter  40 value 82.023661
iter  50 value 80.896798
iter  60 value 79.770441
iter  70 value 79.651220
iter  80 value 79.435632
iter  90 value 79.130886
iter 100 value 79.083619
final  value 79.083619 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 119.782800 
iter  10 value 94.653470
iter  20 value 86.188028
iter  30 value 80.551307
iter  40 value 80.099570
iter  50 value 80.065511
iter  60 value 79.660871
iter  70 value 79.228665
iter  80 value 79.067916
iter  90 value 78.863010
iter 100 value 78.236406
final  value 78.236406 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.713211 
iter  10 value 100.014889
iter  20 value 94.389820
iter  30 value 87.340742
iter  40 value 82.818626
iter  50 value 80.023519
iter  60 value 78.799818
iter  70 value 77.929738
iter  80 value 77.662898
iter  90 value 77.405826
iter 100 value 77.329286
final  value 77.329286 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 122.764166 
iter  10 value 95.216884
iter  20 value 92.714011
iter  30 value 88.351020
iter  40 value 82.613477
iter  50 value 80.467946
iter  60 value 78.799616
iter  70 value 78.410723
iter  80 value 78.169241
iter  90 value 77.979637
iter 100 value 77.837624
final  value 77.837624 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 121.548662 
iter  10 value 94.456561
iter  20 value 81.595799
iter  30 value 80.570954
iter  40 value 80.458912
iter  50 value 79.912257
iter  60 value 78.673317
iter  70 value 78.097281
iter  80 value 77.974827
iter  90 value 77.840501
iter 100 value 77.598392
final  value 77.598392 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 122.218364 
iter  10 value 94.551216
iter  20 value 92.496902
iter  30 value 84.376250
iter  40 value 81.120625
iter  50 value 80.141899
iter  60 value 79.901435
iter  70 value 79.175817
iter  80 value 78.536635
iter  90 value 78.135483
iter 100 value 77.751685
final  value 77.751685 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.580140 
final  value 94.485789 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.047569 
final  value 94.485788 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.902247 
final  value 94.486124 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.040611 
final  value 94.485881 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.574956 
final  value 94.486040 
converged
Fitting Repeat 1 

# weights:  305
initial  value 119.571214 
iter  10 value 94.489244
iter  20 value 94.434607
final  value 93.871665 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.116742 
iter  10 value 94.061716
iter  20 value 94.056988
iter  30 value 94.051692
iter  40 value 93.856195
final  value 93.838804 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.112669 
iter  10 value 91.936097
iter  20 value 91.934274
iter  30 value 91.931784
iter  40 value 91.931429
iter  50 value 91.931115
iter  60 value 91.930974
iter  60 value 91.930973
iter  60 value 91.930973
final  value 91.930973 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.242143 
iter  10 value 94.279949
iter  20 value 94.146442
iter  30 value 89.768429
iter  40 value 79.883085
iter  50 value 79.804607
iter  60 value 79.803898
iter  70 value 79.803273
iter  80 value 79.319535
iter  90 value 77.958788
iter 100 value 77.886034
final  value 77.886034 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 98.166834 
iter  10 value 94.280345
iter  20 value 94.275359
iter  30 value 93.019203
iter  40 value 81.562894
iter  50 value 80.079701
iter  60 value 80.063781
iter  70 value 80.063419
final  value 80.063415 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.350272 
iter  10 value 85.837542
iter  20 value 78.905482
iter  30 value 77.506662
iter  40 value 77.312371
iter  50 value 77.308530
iter  60 value 77.300864
iter  70 value 77.282524
iter  80 value 77.260944
iter  90 value 77.230224
iter 100 value 77.152317
final  value 77.152317 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 96.052534 
iter  10 value 89.977365
iter  20 value 88.329216
iter  30 value 87.845093
iter  40 value 84.499981
iter  50 value 83.512722
iter  60 value 83.466557
iter  70 value 83.321913
iter  80 value 83.305002
iter  90 value 83.053672
iter 100 value 83.053528
final  value 83.053528 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.445964 
iter  10 value 93.597652
iter  20 value 93.505152
iter  30 value 93.430805
iter  40 value 93.170435
iter  50 value 93.168855
iter  60 value 93.167490
final  value 93.167288 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.155408 
iter  10 value 93.816226
iter  20 value 93.815604
iter  30 value 93.783123
iter  40 value 93.775938
final  value 93.774825 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.061135 
iter  10 value 87.326047
iter  20 value 87.198030
iter  30 value 87.033815
final  value 87.031547 
converged
Fitting Repeat 1 

# weights:  103
initial  value 115.294807 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.721623 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.555103 
iter  10 value 94.360495
final  value 94.355938 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.258612 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.055045 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 111.740220 
iter  10 value 94.022728
iter  10 value 94.022727
iter  10 value 94.022727
final  value 94.022727 
converged
Fitting Repeat 2 

# weights:  305
initial  value 108.301331 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.905769 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.643557 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.359951 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.869120 
iter  10 value 87.692844
iter  20 value 87.172846
iter  30 value 86.865049
final  value 86.864991 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.899590 
iter  10 value 88.314940
iter  20 value 86.683879
iter  30 value 86.653157
final  value 86.653104 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.632227 
iter  10 value 92.811996
iter  20 value 82.274755
iter  30 value 78.679021
iter  40 value 78.191438
iter  50 value 78.089311
iter  60 value 78.055706
final  value 78.055665 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.183181 
final  value 94.467391 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.393529 
final  value 94.467391 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.456710 
iter  10 value 94.572062
iter  20 value 92.612200
iter  30 value 90.658421
iter  40 value 90.113110
iter  50 value 89.835203
iter  60 value 82.903925
iter  70 value 81.783568
iter  80 value 81.164231
iter  90 value 80.083672
iter 100 value 79.062201
final  value 79.062201 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.801441 
iter  10 value 94.460425
iter  20 value 82.492092
iter  30 value 81.449413
iter  40 value 81.084773
iter  50 value 80.347357
iter  60 value 79.776856
iter  70 value 79.742897
final  value 79.742892 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.702522 
iter  10 value 94.424996
iter  20 value 89.271979
iter  30 value 84.099038
iter  40 value 82.962331
iter  50 value 82.745857
iter  60 value 81.781593
iter  70 value 81.334635
iter  80 value 81.167343
final  value 81.166345 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.914511 
iter  10 value 94.487833
iter  20 value 93.192958
iter  30 value 85.022661
iter  40 value 81.690409
iter  50 value 80.808573
iter  60 value 80.466039
iter  70 value 80.336161
iter  80 value 80.321253
final  value 80.321247 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.036623 
iter  10 value 94.492520
iter  20 value 94.444594
iter  30 value 83.284035
iter  40 value 82.151490
iter  50 value 81.823064
iter  60 value 81.101500
iter  70 value 80.871066
iter  80 value 80.870336
iter  80 value 80.870335
iter  80 value 80.870335
final  value 80.870335 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.305263 
iter  10 value 94.591288
iter  20 value 94.272454
iter  30 value 82.824626
iter  40 value 82.165427
iter  50 value 80.883746
iter  60 value 80.135364
iter  70 value 78.372206
iter  80 value 77.789074
iter  90 value 77.485201
iter 100 value 77.256413
final  value 77.256413 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 121.695029 
iter  10 value 94.504090
iter  20 value 92.381447
iter  30 value 83.909928
iter  40 value 83.030562
iter  50 value 82.103381
iter  60 value 81.818850
iter  70 value 81.224195
iter  80 value 81.081907
iter  90 value 80.009799
iter 100 value 79.337641
final  value 79.337641 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.092976 
iter  10 value 93.494604
iter  20 value 90.331914
iter  30 value 84.411788
iter  40 value 81.975778
iter  50 value 81.752032
iter  60 value 81.042471
iter  70 value 79.747251
iter  80 value 78.026162
iter  90 value 77.695822
iter 100 value 77.413027
final  value 77.413027 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 123.331791 
iter  10 value 94.274355
iter  20 value 86.471307
iter  30 value 83.555650
iter  40 value 82.245208
iter  50 value 81.645847
iter  60 value 80.917356
iter  70 value 80.295753
iter  80 value 79.753104
iter  90 value 79.720095
iter 100 value 79.649577
final  value 79.649577 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.783548 
iter  10 value 94.423268
iter  20 value 88.151615
iter  30 value 81.736227
iter  40 value 81.218309
iter  50 value 80.518832
iter  60 value 79.317198
iter  70 value 78.236358
iter  80 value 77.719379
iter  90 value 77.626005
iter 100 value 77.588298
final  value 77.588298 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 102.904910 
iter  10 value 95.916060
iter  20 value 88.597774
iter  30 value 87.514022
iter  40 value 87.103549
iter  50 value 86.567969
iter  60 value 83.859932
iter  70 value 81.984973
iter  80 value 81.478422
iter  90 value 80.860755
iter 100 value 80.167123
final  value 80.167123 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.508120 
iter  10 value 95.010753
iter  20 value 90.788998
iter  30 value 80.498380
iter  40 value 79.017971
iter  50 value 78.178798
iter  60 value 78.091498
iter  70 value 78.024812
iter  80 value 77.903601
iter  90 value 77.853758
iter 100 value 77.777935
final  value 77.777935 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 124.388587 
iter  10 value 94.265270
iter  20 value 89.279024
iter  30 value 85.346616
iter  40 value 82.512043
iter  50 value 81.113212
iter  60 value 79.002500
iter  70 value 78.000030
iter  80 value 77.823368
iter  90 value 77.713284
iter 100 value 77.602342
final  value 77.602342 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.942164 
iter  10 value 94.404548
iter  20 value 89.878346
iter  30 value 84.696099
iter  40 value 80.719383
iter  50 value 79.720033
iter  60 value 78.741838
iter  70 value 77.753699
iter  80 value 77.197734
iter  90 value 77.146571
iter 100 value 77.104047
final  value 77.104047 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 116.580021 
iter  10 value 93.975334
iter  20 value 87.317473
iter  30 value 81.974842
iter  40 value 79.838162
iter  50 value 79.065541
iter  60 value 78.637029
iter  70 value 78.569810
iter  80 value 78.380938
iter  90 value 78.027362
iter 100 value 77.697599
final  value 77.697599 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.805748 
final  value 94.486186 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.615492 
final  value 94.486764 
converged
Fitting Repeat 3 

# weights:  103
initial  value 110.690346 
final  value 94.485737 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.724758 
final  value 94.486047 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.021387 
final  value 94.485955 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.530884 
iter  10 value 94.489123
iter  20 value 90.627717
iter  30 value 89.913115
final  value 89.913060 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.655641 
iter  10 value 94.489355
iter  20 value 94.459279
iter  30 value 86.939706
iter  40 value 80.738608
iter  50 value 79.761438
iter  60 value 79.257237
iter  70 value 78.988057
iter  80 value 78.981935
iter  90 value 78.972179
iter 100 value 78.435580
final  value 78.435580 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.049028 
iter  10 value 94.484160
iter  20 value 94.360920
iter  30 value 91.946940
iter  40 value 91.943293
iter  50 value 91.939706
iter  60 value 91.938527
iter  70 value 91.419342
iter  80 value 83.371747
iter  90 value 79.907080
iter 100 value 77.935635
final  value 77.935635 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.280115 
iter  10 value 94.472285
iter  20 value 94.467847
iter  30 value 94.397724
iter  40 value 82.975646
iter  50 value 81.297316
iter  60 value 81.246166
iter  70 value 80.423858
iter  80 value 78.463846
iter  90 value 76.499554
iter 100 value 75.985797
final  value 75.985797 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 98.896043 
iter  10 value 94.135094
iter  20 value 94.030339
iter  30 value 94.027461
iter  40 value 93.470466
iter  50 value 84.341346
iter  60 value 81.655329
iter  70 value 81.446747
iter  80 value 81.439727
iter  90 value 81.431053
iter 100 value 81.361501
final  value 81.361501 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 100.239372 
iter  10 value 94.492247
iter  20 value 94.282596
iter  30 value 89.909686
iter  40 value 89.906410
iter  50 value 81.453641
iter  60 value 80.584896
iter  70 value 80.569158
iter  80 value 80.390880
iter  90 value 78.602504
iter 100 value 77.661104
final  value 77.661104 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.737892 
iter  10 value 94.475729
iter  20 value 94.467900
iter  30 value 94.438349
iter  40 value 92.901744
iter  50 value 81.942508
iter  60 value 81.326557
iter  70 value 81.321602
iter  80 value 80.984855
final  value 80.983823 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.765975 
iter  10 value 94.492830
iter  20 value 94.483517
iter  30 value 94.354810
iter  40 value 88.115872
iter  50 value 88.013350
iter  60 value 83.328570
iter  70 value 80.718333
iter  80 value 80.355867
iter  90 value 79.935379
iter 100 value 79.845775
final  value 79.845775 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 99.424638 
iter  10 value 94.408263
iter  20 value 94.400893
iter  30 value 94.387649
iter  40 value 94.351057
iter  50 value 94.301587
iter  60 value 90.629877
iter  70 value 89.721448
iter  80 value 86.393705
iter  90 value 86.328521
iter 100 value 86.304359
final  value 86.304359 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 96.473549 
iter  10 value 94.492961
iter  20 value 94.484964
iter  30 value 94.104209
iter  40 value 88.482495
iter  50 value 84.015479
iter  60 value 81.758123
iter  70 value 79.190024
iter  80 value 79.039939
iter  90 value 78.705016
iter 100 value 78.651539
final  value 78.651539 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 122.966766 
iter  10 value 117.749231
iter  20 value 117.684375
iter  30 value 117.554498
iter  40 value 117.553009
iter  50 value 117.514395
iter  60 value 117.508084
final  value 117.501326 
converged
Fitting Repeat 2 

# weights:  305
initial  value 118.854240 
iter  10 value 117.763721
iter  20 value 117.288678
iter  30 value 110.505355
iter  40 value 110.417210
final  value 110.417182 
converged
Fitting Repeat 3 

# weights:  305
initial  value 146.560243 
iter  10 value 117.847411
iter  20 value 117.532918
iter  30 value 117.516501
iter  40 value 117.473646
iter  50 value 117.471407
iter  60 value 117.459731
iter  70 value 117.456355
iter  80 value 109.895121
iter  90 value 109.412636
final  value 109.412632 
converged
Fitting Repeat 4 

# weights:  305
initial  value 131.952704 
iter  10 value 117.763694
iter  20 value 117.760009
final  value 117.729436 
converged
Fitting Repeat 5 

# weights:  305
initial  value 120.029537 
iter  10 value 117.894196
iter  20 value 117.664016
final  value 117.549773 
converged
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 -- Sat Mar 14 00:31:22 2026 
*********************************************** 
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 
 39.940   1.135  93.773