##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:HPiP.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings HPiP_1.19.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.24-bioc/meat/HPiP.Rcheck’
* using R version 4.6.0 Patched (2026-05-01 r89994)
* using platform: aarch64-apple-darwin23
* R was compiled by
    Apple clang version 17.0.0 (clang-1700.3.19.1)
    GNU Fortran (GCC) 14.2.0
* running under: macOS Tahoe 26.3.1
* using session charset: UTF-8
* current time: 2026-05-25 23:58:01 UTC
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.19.0’
* 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 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
corr_plot     16.935  0.085  17.060
var_imp       16.849  0.088  16.950
FSmethod      16.816  0.061  17.090
pred_ensembel  6.050  0.142   5.469
enrichfindP    0.199  0.034   8.509
* 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 running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 2 NOTEs
See
  ‘/Users/biocbuild/bbs-3.24-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.6/Resources/library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.19.0’
** 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 4.6.0 Patched (2026-05-01 r89994) -- "Because it was There"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin23

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
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 98.860099 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.622261 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.872274 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.529148 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.383619 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.848714 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.526201 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.116656 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 113.099794 
final  value 94.473118 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.098092 
final  value 94.473118 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.557299 
iter  10 value 91.183048
iter  20 value 83.961804
iter  30 value 79.129510
iter  40 value 77.917928
iter  50 value 77.171028
final  value 77.171017 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.066291 
iter  10 value 94.479198
final  value 94.473118 
converged
Fitting Repeat 3 

# weights:  507
initial  value 108.680104 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 116.767224 
iter  10 value 94.266710
iter  20 value 87.826183
iter  30 value 86.922650
iter  40 value 85.095636
iter  50 value 83.864579
final  value 83.864577 
converged
Fitting Repeat 5 

# weights:  507
initial  value 146.597918 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.877982 
iter  10 value 94.037388
iter  20 value 90.284139
iter  30 value 89.562721
iter  40 value 89.541872
final  value 89.541867 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.189587 
iter  10 value 94.267690
iter  20 value 87.307367
iter  30 value 82.945381
iter  40 value 81.846519
iter  50 value 81.468415
iter  60 value 79.684428
iter  70 value 78.855804
iter  80 value 78.475349
iter  90 value 78.230997
iter 100 value 78.203195
final  value 78.203195 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.952057 
iter  10 value 94.488555
iter  20 value 93.984346
iter  30 value 93.841753
iter  40 value 93.821868
iter  50 value 83.039931
iter  60 value 82.103316
iter  70 value 81.813228
iter  80 value 81.403245
iter  90 value 81.389394
final  value 81.389380 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.701941 
iter  10 value 94.489190
iter  20 value 94.047069
iter  30 value 93.862616
iter  40 value 93.517007
iter  50 value 93.505802
iter  60 value 93.171810
iter  70 value 87.495174
iter  80 value 80.764687
iter  90 value 79.436950
iter 100 value 78.646374
final  value 78.646374 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 104.202894 
iter  10 value 94.488545
iter  20 value 94.154621
iter  30 value 93.907351
iter  40 value 90.731483
iter  50 value 81.475388
iter  60 value 80.515983
iter  70 value 80.218228
iter  80 value 78.583576
iter  90 value 78.245763
iter 100 value 77.998424
final  value 77.998424 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 108.789454 
iter  10 value 93.147096
iter  20 value 85.481228
iter  30 value 84.506972
iter  40 value 80.693867
iter  50 value 79.697175
iter  60 value 79.212671
iter  70 value 78.871481
iter  80 value 78.359280
iter  90 value 78.235285
iter 100 value 78.033668
final  value 78.033668 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.059047 
iter  10 value 94.588710
iter  20 value 94.101107
iter  30 value 93.652126
iter  40 value 86.204085
iter  50 value 85.673027
iter  60 value 84.838568
iter  70 value 82.266782
iter  80 value 78.181241
iter  90 value 77.690429
iter 100 value 77.523059
final  value 77.523059 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.343344 
iter  10 value 94.383292
iter  20 value 92.775734
iter  30 value 92.272513
iter  40 value 90.712770
iter  50 value 81.109546
iter  60 value 79.154741
iter  70 value 78.718542
iter  80 value 78.459417
iter  90 value 78.145585
iter 100 value 77.951942
final  value 77.951942 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.641860 
iter  10 value 94.416882
iter  20 value 94.053962
iter  30 value 91.759048
iter  40 value 82.657551
iter  50 value 81.659582
iter  60 value 80.785398
iter  70 value 78.459153
iter  80 value 77.872608
iter  90 value 77.752504
iter 100 value 77.683830
final  value 77.683830 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.541322 
iter  10 value 94.505014
iter  20 value 94.313929
iter  30 value 84.177046
iter  40 value 80.549891
iter  50 value 79.955513
iter  60 value 77.874335
iter  70 value 76.365995
iter  80 value 76.180759
iter  90 value 76.115757
iter 100 value 76.073138
final  value 76.073138 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 124.842253 
iter  10 value 93.505019
iter  20 value 83.792829
iter  30 value 82.552125
iter  40 value 81.111828
iter  50 value 77.433877
iter  60 value 76.779889
iter  70 value 76.323166
iter  80 value 76.248055
iter  90 value 76.064488
iter 100 value 75.940895
final  value 75.940895 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 114.604129 
iter  10 value 95.007113
iter  20 value 94.500937
iter  30 value 87.902168
iter  40 value 86.670456
iter  50 value 84.685701
iter  60 value 80.414551
iter  70 value 78.081064
iter  80 value 77.115143
iter  90 value 76.918433
iter 100 value 76.812321
final  value 76.812321 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 117.034919 
iter  10 value 94.916363
iter  20 value 86.265349
iter  30 value 82.050185
iter  40 value 81.884913
iter  50 value 81.748904
iter  60 value 79.380895
iter  70 value 78.524220
iter  80 value 78.026888
iter  90 value 77.843573
iter 100 value 77.393091
final  value 77.393091 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 116.330862 
iter  10 value 94.468984
iter  20 value 92.983573
iter  30 value 91.321754
iter  40 value 85.540125
iter  50 value 83.435846
iter  60 value 81.649880
iter  70 value 81.033643
iter  80 value 80.166686
iter  90 value 79.781473
iter 100 value 79.370757
final  value 79.370757 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.087339 
iter  10 value 94.656905
iter  20 value 94.479019
iter  30 value 88.056873
iter  40 value 87.379116
iter  50 value 86.768488
iter  60 value 84.181841
iter  70 value 79.359197
iter  80 value 78.571126
iter  90 value 78.493489
iter 100 value 78.354352
final  value 78.354352 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.360400 
final  value 94.486157 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.740099 
final  value 94.145963 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.077870 
iter  10 value 94.485900
iter  20 value 94.483963
iter  30 value 93.309401
iter  40 value 87.268138
iter  50 value 82.425902
iter  60 value 82.362344
iter  70 value 82.314653
iter  80 value 82.313605
iter  90 value 81.030350
iter 100 value 80.348386
final  value 80.348386 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 100.055944 
iter  10 value 94.485933
iter  20 value 94.480756
iter  30 value 94.075917
final  value 94.057507 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.674545 
final  value 94.486321 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.494902 
iter  10 value 94.488686
iter  20 value 94.484406
final  value 94.484368 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.320591 
iter  10 value 94.055837
iter  20 value 94.040994
iter  30 value 94.038243
iter  40 value 94.036758
iter  50 value 94.032106
final  value 94.031501 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.958582 
iter  10 value 94.489126
iter  20 value 94.484632
iter  30 value 82.851711
iter  40 value 81.441542
iter  50 value 81.435080
iter  60 value 81.433375
iter  70 value 81.433319
final  value 81.433229 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.733001 
iter  10 value 94.489065
iter  20 value 94.484228
iter  30 value 92.680012
iter  40 value 87.046323
iter  50 value 87.036189
iter  60 value 86.640859
iter  70 value 86.563771
iter  80 value 85.760159
iter  90 value 85.755478
iter 100 value 85.570293
final  value 85.570293 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.687231 
iter  10 value 94.478141
iter  20 value 94.473527
iter  30 value 93.644311
iter  40 value 86.701516
final  value 86.699216 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.064111 
iter  10 value 94.146311
iter  20 value 94.142020
iter  30 value 94.138836
final  value 94.138507 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.318162 
iter  10 value 94.491252
iter  20 value 94.433412
iter  30 value 87.738686
iter  40 value 85.380731
iter  50 value 83.493231
iter  60 value 83.488593
iter  70 value 82.832411
iter  80 value 82.827674
iter  90 value 81.726552
iter 100 value 80.501926
final  value 80.501926 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 95.651318 
iter  10 value 94.491583
iter  20 value 94.414099
iter  30 value 82.005811
iter  40 value 81.520568
iter  50 value 81.500531
iter  60 value 80.401251
iter  70 value 80.365999
iter  80 value 79.679979
iter  90 value 77.673095
iter 100 value 77.507868
final  value 77.507868 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 97.290298 
iter  10 value 94.481619
iter  20 value 94.477699
iter  30 value 94.453516
iter  40 value 92.929908
iter  50 value 90.158001
iter  60 value 89.688468
iter  70 value 84.806808
iter  80 value 78.707628
iter  90 value 77.059425
iter 100 value 77.056869
final  value 77.056869 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.273262 
iter  10 value 94.489738
iter  20 value 87.893121
iter  30 value 84.313575
final  value 84.313291 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.161033 
final  value 94.011429 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.885524 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.484680 
final  value 93.836066 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.969139 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.685295 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.737123 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 116.930051 
final  value 93.836066 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.858447 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.680349 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.970452 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.789109 
iter  10 value 92.642428
final  value 92.211111 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.364461 
iter  10 value 93.826302
iter  20 value 93.818736
final  value 93.818714 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.399760 
iter  10 value 93.836069
final  value 93.836066 
converged
Fitting Repeat 4 

# weights:  507
initial  value 108.595245 
final  value 93.836065 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.296981 
final  value 93.836066 
converged
Fitting Repeat 1 

# weights:  103
initial  value 108.380302 
iter  10 value 94.072964
iter  20 value 92.282421
iter  30 value 90.887691
iter  40 value 86.689399
iter  50 value 84.990487
iter  60 value 83.386382
iter  70 value 83.146182
iter  80 value 83.081975
iter  90 value 83.064488
iter 100 value 83.036283
final  value 83.036283 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.833592 
iter  10 value 94.047649
iter  20 value 93.901168
iter  30 value 93.894244
iter  40 value 93.889829
iter  50 value 90.337516
iter  60 value 88.429604
iter  70 value 88.103043
iter  80 value 82.718916
iter  90 value 81.600803
iter 100 value 81.479170
final  value 81.479170 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.351221 
iter  10 value 93.970165
iter  20 value 93.727967
iter  30 value 93.662710
iter  40 value 91.088463
iter  50 value 84.145212
iter  60 value 83.202696
iter  70 value 82.785162
iter  80 value 82.668282
iter  90 value 81.887051
iter 100 value 81.204233
final  value 81.204233 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.181988 
iter  10 value 94.056715
iter  20 value 93.670092
iter  30 value 93.508192
iter  40 value 86.970543
iter  50 value 86.544199
iter  60 value 83.833613
iter  70 value 83.117509
iter  80 value 83.070540
iter  90 value 83.061723
iter 100 value 83.036291
final  value 83.036291 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 108.398275 
iter  10 value 94.162981
iter  20 value 94.056694
iter  30 value 85.858802
iter  40 value 84.513135
iter  50 value 84.384200
iter  60 value 84.308217
final  value 84.307393 
converged
Fitting Repeat 1 

# weights:  305
initial  value 120.156603 
iter  10 value 94.038106
iter  20 value 92.598478
iter  30 value 88.794309
iter  40 value 85.484586
iter  50 value 82.210314
iter  60 value 81.934664
iter  70 value 81.140352
iter  80 value 80.790223
iter  90 value 80.333271
iter 100 value 80.099116
final  value 80.099116 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 113.069374 
iter  10 value 92.395281
iter  20 value 84.725401
iter  30 value 83.433886
iter  40 value 83.363636
iter  50 value 83.038457
iter  60 value 82.916330
iter  70 value 82.759492
iter  80 value 82.703834
iter  90 value 82.370593
iter 100 value 80.779459
final  value 80.779459 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 113.769819 
iter  10 value 93.901192
iter  20 value 89.384427
iter  30 value 86.590473
iter  40 value 84.074422
iter  50 value 83.205347
iter  60 value 82.874629
iter  70 value 82.828375
iter  80 value 82.723700
iter  90 value 82.422763
iter 100 value 81.499863
final  value 81.499863 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 126.668114 
iter  10 value 94.549677
iter  20 value 94.062656
iter  30 value 93.849924
iter  40 value 93.755767
iter  50 value 91.947474
iter  60 value 89.835641
iter  70 value 84.644544
iter  80 value 83.285177
iter  90 value 83.213560
iter 100 value 82.799459
final  value 82.799459 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 128.091219 
iter  10 value 94.005941
iter  20 value 92.808492
iter  30 value 86.808027
iter  40 value 84.549817
iter  50 value 82.747611
iter  60 value 81.559939
iter  70 value 80.377937
iter  80 value 80.044081
iter  90 value 79.941162
iter 100 value 79.885429
final  value 79.885429 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.919367 
iter  10 value 93.784295
iter  20 value 86.465922
iter  30 value 83.141792
iter  40 value 81.213758
iter  50 value 80.801092
iter  60 value 80.746106
iter  70 value 80.592849
iter  80 value 80.117331
iter  90 value 79.800310
iter 100 value 79.782689
final  value 79.782689 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.522674 
iter  10 value 94.135845
iter  20 value 86.522159
iter  30 value 85.147701
iter  40 value 82.944224
iter  50 value 81.543083
iter  60 value 80.746957
iter  70 value 80.368586
iter  80 value 80.135847
iter  90 value 80.044391
iter 100 value 79.861614
final  value 79.861614 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.945510 
iter  10 value 93.887896
iter  20 value 88.215248
iter  30 value 86.250224
iter  40 value 81.309959
iter  50 value 80.536791
iter  60 value 80.371239
iter  70 value 80.326478
iter  80 value 80.287897
iter  90 value 80.251149
iter 100 value 79.954901
final  value 79.954901 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 120.074281 
iter  10 value 94.054683
iter  20 value 92.278129
iter  30 value 85.474430
iter  40 value 84.270903
iter  50 value 82.999466
iter  60 value 82.732847
iter  70 value 82.308532
iter  80 value 82.186207
iter  90 value 82.135100
iter 100 value 81.929443
final  value 81.929443 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.733764 
iter  10 value 94.185553
iter  20 value 93.050083
iter  30 value 89.691629
iter  40 value 86.854063
iter  50 value 85.058521
iter  60 value 84.162946
iter  70 value 83.497239
iter  80 value 81.158564
iter  90 value 80.585525
iter 100 value 80.372472
final  value 80.372472 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.614463 
final  value 94.054855 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.550956 
final  value 94.054543 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.501995 
final  value 94.054406 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.035059 
final  value 94.054628 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.179334 
final  value 94.054652 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.352769 
iter  10 value 93.415584
iter  20 value 93.413528
iter  30 value 93.409164
iter  40 value 87.668006
iter  50 value 85.137977
iter  60 value 81.243595
iter  70 value 81.223804
iter  80 value 81.144427
iter  90 value 81.086642
iter 100 value 81.038893
final  value 81.038893 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.329972 
iter  10 value 94.057320
iter  20 value 93.889724
iter  30 value 93.521518
iter  40 value 87.664362
iter  50 value 87.235847
iter  60 value 85.185278
iter  70 value 83.946898
iter  80 value 83.935663
iter  90 value 83.860060
iter 100 value 83.721180
final  value 83.721180 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.323768 
iter  10 value 93.843743
iter  20 value 88.465990
iter  30 value 84.129255
iter  40 value 84.102679
iter  50 value 84.093076
iter  60 value 83.502750
final  value 83.493291 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.762676 
iter  10 value 93.840288
iter  20 value 93.787371
iter  30 value 93.544555
iter  40 value 93.542974
iter  40 value 93.542974
iter  50 value 93.411636
final  value 93.411621 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.322642 
iter  10 value 93.246869
iter  20 value 93.102625
iter  30 value 93.018246
final  value 93.017667 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.771837 
iter  10 value 93.844784
iter  20 value 93.841546
iter  30 value 93.762623
iter  40 value 85.254362
iter  50 value 81.753059
iter  60 value 81.304351
iter  70 value 81.303689
iter  80 value 81.303158
iter  90 value 81.300528
iter 100 value 81.296729
final  value 81.296729 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.057074 
iter  10 value 93.844285
iter  20 value 93.837379
final  value 93.836825 
converged
Fitting Repeat 3 

# weights:  507
initial  value 121.128281 
iter  10 value 94.061439
iter  20 value 94.052843
iter  30 value 91.249964
iter  40 value 86.879104
iter  50 value 86.057065
iter  60 value 84.256175
iter  70 value 84.251559
final  value 84.249423 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.686023 
iter  10 value 94.061501
iter  20 value 94.007144
iter  30 value 93.858398
iter  40 value 93.141044
iter  50 value 85.832412
final  value 85.732941 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.624071 
iter  10 value 93.223775
iter  20 value 87.752770
iter  30 value 85.045298
iter  40 value 84.743461
iter  50 value 84.222995
iter  60 value 84.220167
iter  70 value 83.801340
iter  80 value 82.297817
iter  90 value 82.224019
iter 100 value 82.130775
final  value 82.130775 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.716304 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.856856 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.341809 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.503313 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.062962 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.205441 
iter  10 value 93.109984
final  value 93.109890 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.775660 
final  value 94.436782 
converged
Fitting Repeat 3 

# weights:  305
initial  value 127.972693 
iter  10 value 94.275363
iter  10 value 94.275362
iter  10 value 94.275362
final  value 94.275362 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.108780 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 109.079634 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.189642 
final  value 94.275362 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.291078 
final  value 94.275362 
converged
Fitting Repeat 3 

# weights:  507
initial  value 113.117914 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.487936 
iter  10 value 94.275371
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.829499 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.945311 
iter  10 value 94.478612
iter  20 value 88.156665
iter  30 value 85.885143
iter  40 value 85.847738
iter  50 value 85.628435
iter  60 value 85.356652
iter  70 value 84.105794
iter  80 value 83.888847
iter  90 value 83.852541
iter 100 value 83.772182
final  value 83.772182 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 117.407977 
iter  10 value 94.239500
iter  20 value 93.987773
iter  30 value 93.057088
iter  40 value 92.999297
iter  50 value 89.147357
iter  60 value 86.446058
iter  70 value 85.119974
iter  80 value 84.910933
iter  90 value 84.160087
iter 100 value 83.796196
final  value 83.796196 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 103.999351 
iter  10 value 94.408700
iter  20 value 86.350930
iter  30 value 85.822989
iter  40 value 85.330268
iter  50 value 84.332579
iter  60 value 83.230282
iter  70 value 83.220738
final  value 83.220712 
converged
Fitting Repeat 4 

# weights:  103
initial  value 116.445327 
iter  10 value 91.190830
iter  20 value 86.983416
iter  30 value 85.398221
iter  40 value 83.680092
iter  50 value 83.447117
iter  60 value 83.421826
final  value 83.421758 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.193275 
iter  10 value 94.481938
iter  20 value 94.152979
iter  30 value 94.113876
iter  40 value 88.627051
iter  50 value 83.158112
iter  60 value 82.026266
iter  70 value 81.996007
iter  80 value 81.801635
iter  90 value 81.638266
iter 100 value 81.544593
final  value 81.544593 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 100.306732 
iter  10 value 94.598171
iter  20 value 94.372237
iter  30 value 93.067561
iter  40 value 92.686871
iter  50 value 89.172773
iter  60 value 85.499913
iter  70 value 80.995786
iter  80 value 80.758650
iter  90 value 80.219198
iter 100 value 80.008515
final  value 80.008515 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.446277 
iter  10 value 95.099737
iter  20 value 85.205817
iter  30 value 84.108176
iter  40 value 83.378967
iter  50 value 81.713517
iter  60 value 80.938558
iter  70 value 80.769076
iter  80 value 80.609423
iter  90 value 80.543473
iter 100 value 80.158025
final  value 80.158025 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.759681 
iter  10 value 95.634997
iter  20 value 91.487991
iter  30 value 86.313662
iter  40 value 83.625185
iter  50 value 81.981592
iter  60 value 81.512723
iter  70 value 81.396585
iter  80 value 81.236120
iter  90 value 81.180278
iter 100 value 80.786135
final  value 80.786135 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 118.039575 
iter  10 value 93.002547
iter  20 value 86.211171
iter  30 value 83.876284
iter  40 value 82.820559
iter  50 value 81.790686
iter  60 value 80.113432
iter  70 value 79.671056
iter  80 value 79.649414
iter  90 value 79.643406
iter 100 value 79.639510
final  value 79.639510 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 112.394079 
iter  10 value 84.769870
iter  20 value 83.807857
iter  30 value 83.605365
iter  40 value 83.389754
iter  50 value 82.313868
iter  60 value 81.207667
iter  70 value 80.491276
iter  80 value 80.286449
iter  90 value 80.010529
iter 100 value 79.869014
final  value 79.869014 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 130.577677 
iter  10 value 95.660571
iter  20 value 94.533824
iter  30 value 91.902325
iter  40 value 85.740141
iter  50 value 85.414737
iter  60 value 84.780914
iter  70 value 83.485274
iter  80 value 82.299841
iter  90 value 81.556605
iter 100 value 81.228472
final  value 81.228472 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 110.840631 
iter  10 value 94.422819
iter  20 value 93.281684
iter  30 value 84.373513
iter  40 value 83.238540
iter  50 value 82.749846
iter  60 value 81.058048
iter  70 value 80.260004
iter  80 value 79.934194
iter  90 value 79.884548
iter 100 value 79.703602
final  value 79.703602 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 117.140330 
iter  10 value 96.842639
iter  20 value 91.323566
iter  30 value 87.741381
iter  40 value 87.045967
iter  50 value 86.282644
iter  60 value 84.767085
iter  70 value 83.921526
iter  80 value 82.241312
iter  90 value 81.898858
iter 100 value 80.799968
final  value 80.799968 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 115.236991 
iter  10 value 94.546416
iter  20 value 93.415449
iter  30 value 93.074144
iter  40 value 88.554371
iter  50 value 85.966904
iter  60 value 83.332516
iter  70 value 81.146477
iter  80 value 80.480435
iter  90 value 80.201655
iter 100 value 79.879251
final  value 79.879251 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.258674 
iter  10 value 96.076456
iter  20 value 87.234296
iter  30 value 86.665280
iter  40 value 84.963388
iter  50 value 83.542927
iter  60 value 82.289031
iter  70 value 81.995403
iter  80 value 81.595515
iter  90 value 81.547171
iter 100 value 81.544164
final  value 81.544164 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.603508 
iter  10 value 94.485711
iter  20 value 94.484221
iter  20 value 94.484221
iter  20 value 94.484221
final  value 94.484221 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.264357 
iter  10 value 94.485867
iter  20 value 94.484246
iter  30 value 89.469411
iter  40 value 82.856857
iter  50 value 82.823443
iter  60 value 82.823235
final  value 82.822941 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.284831 
final  value 94.485868 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.970597 
iter  10 value 94.276892
iter  20 value 94.275496
final  value 94.275429 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.807237 
iter  10 value 94.485918
final  value 94.484214 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.715392 
iter  10 value 94.281351
iter  20 value 94.278546
iter  30 value 94.277401
iter  40 value 94.194752
iter  50 value 87.433461
iter  60 value 86.953552
iter  70 value 86.294495
iter  80 value 85.986784
iter  90 value 85.755057
final  value 85.742634 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.444583 
iter  10 value 94.488604
iter  20 value 94.388226
iter  30 value 86.087686
iter  40 value 85.388479
iter  50 value 85.370701
iter  60 value 85.370259
iter  70 value 83.001137
iter  80 value 81.233913
iter  90 value 80.694723
iter 100 value 80.193275
final  value 80.193275 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 96.237145 
iter  10 value 94.280654
iter  20 value 91.053109
iter  30 value 90.693776
iter  40 value 90.691324
iter  50 value 89.502891
iter  60 value 84.173899
iter  70 value 81.740260
iter  80 value 81.740063
iter  90 value 81.584103
iter 100 value 81.563161
final  value 81.563161 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 112.153068 
iter  10 value 94.489184
iter  20 value 94.457536
final  value 94.052550 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.492308 
iter  10 value 94.482990
iter  20 value 94.479262
iter  30 value 94.396179
iter  40 value 94.053773
iter  50 value 94.052786
iter  60 value 84.530148
iter  70 value 82.524288
iter  80 value 81.990414
iter  90 value 81.554630
iter 100 value 80.658515
final  value 80.658515 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 94.697452 
iter  10 value 89.400212
iter  20 value 86.499490
iter  30 value 86.492190
iter  40 value 86.490414
iter  50 value 86.472219
iter  60 value 86.151464
iter  70 value 84.708106
iter  80 value 80.685625
iter  90 value 80.148570
iter 100 value 79.087124
final  value 79.087124 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.585613 
iter  10 value 94.074424
iter  20 value 87.558681
iter  30 value 82.322210
iter  40 value 81.564986
iter  50 value 81.122350
iter  60 value 79.992884
iter  70 value 79.991982
iter  80 value 79.988966
iter  90 value 79.717448
iter 100 value 79.678192
final  value 79.678192 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 92.768649 
iter  10 value 86.685509
iter  20 value 86.641645
iter  30 value 85.450438
iter  40 value 85.423233
iter  50 value 85.358251
iter  60 value 84.468204
final  value 84.449523 
converged
Fitting Repeat 4 

# weights:  507
initial  value 108.136219 
iter  10 value 94.283097
iter  20 value 94.260814
iter  30 value 86.595261
iter  40 value 86.430647
iter  50 value 86.430233
iter  60 value 86.067840
final  value 86.065710 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.538474 
iter  10 value 94.492466
iter  20 value 94.468413
iter  30 value 90.794613
iter  40 value 90.414420
iter  40 value 90.414420
iter  40 value 90.414420
final  value 90.414420 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.122550 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.472068 
final  value 94.354396 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.036805 
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.333937 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.720012 
final  value 94.354395 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.898090 
iter  10 value 94.307176
final  value 94.305883 
converged
Fitting Repeat 2 

# weights:  305
initial  value 106.324133 
final  value 94.354396 
converged
Fitting Repeat 3 

# weights:  305
initial  value 109.553886 
iter  10 value 94.442082
final  value 94.442073 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.823129 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.082249 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.225543 
iter  10 value 87.302761
final  value 87.283812 
converged
Fitting Repeat 2 

# weights:  507
initial  value 123.887485 
final  value 93.783647 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.250279 
iter  10 value 94.289319
final  value 94.289216 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.448320 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 113.021010 
iter  10 value 94.354740
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.730393 
iter  10 value 93.345305
iter  20 value 86.611919
iter  30 value 85.200566
iter  40 value 84.999687
iter  50 value 84.601697
iter  60 value 84.556739
final  value 84.556728 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.241241 
iter  10 value 94.488618
iter  20 value 89.881122
iter  30 value 88.309180
iter  40 value 87.085722
iter  50 value 86.085103
iter  60 value 85.632778
iter  70 value 85.321651
iter  80 value 85.048549
final  value 85.048030 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.440594 
iter  10 value 94.487773
iter  20 value 94.453607
iter  30 value 94.123314
iter  40 value 94.067991
iter  50 value 90.556496
iter  60 value 87.935468
iter  70 value 87.670571
iter  80 value 87.530636
iter  90 value 86.862888
iter 100 value 85.277267
final  value 85.277267 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.466734 
iter  10 value 94.490668
iter  20 value 94.328767
iter  30 value 92.209982
iter  40 value 91.108109
iter  50 value 87.402813
iter  60 value 86.427711
iter  70 value 85.935185
iter  80 value 85.027279
iter  90 value 84.944127
iter 100 value 84.940652
final  value 84.940652 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 106.809982 
iter  10 value 94.162480
iter  20 value 89.490150
iter  30 value 88.370048
iter  40 value 88.130832
iter  50 value 86.339822
iter  60 value 86.095703
iter  70 value 85.468989
final  value 85.443703 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.696381 
iter  10 value 94.518607
iter  20 value 87.017019
iter  30 value 86.744508
iter  40 value 84.899111
iter  50 value 83.333813
iter  60 value 82.559673
iter  70 value 81.982202
iter  80 value 81.886430
iter  90 value 81.736371
iter 100 value 81.668823
final  value 81.668823 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.813901 
iter  10 value 94.489551
iter  20 value 93.877283
iter  30 value 87.130992
iter  40 value 85.832091
iter  50 value 85.734094
iter  60 value 83.468874
iter  70 value 82.777456
iter  80 value 82.336360
iter  90 value 82.233820
iter 100 value 82.189284
final  value 82.189284 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.319093 
iter  10 value 94.499812
iter  20 value 93.920008
iter  30 value 93.797569
iter  40 value 93.319028
iter  50 value 87.466966
iter  60 value 86.893632
iter  70 value 86.752624
iter  80 value 86.723437
iter  90 value 85.767742
iter 100 value 84.543021
final  value 84.543021 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 120.756718 
iter  10 value 94.707275
iter  20 value 94.392583
iter  30 value 89.384046
iter  40 value 87.489166
iter  50 value 86.080513
iter  60 value 85.534868
iter  70 value 85.272215
iter  80 value 85.215955
iter  90 value 84.115468
iter 100 value 82.358412
final  value 82.358412 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.842597 
iter  10 value 94.501300
iter  20 value 88.419921
iter  30 value 86.481407
iter  40 value 85.626848
iter  50 value 85.025741
iter  60 value 84.987235
iter  70 value 84.798781
iter  80 value 83.036374
iter  90 value 82.087541
iter 100 value 81.787761
final  value 81.787761 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 116.446391 
iter  10 value 94.675986
iter  20 value 93.438178
iter  30 value 89.336523
iter  40 value 87.370125
iter  50 value 86.906940
iter  60 value 84.841100
iter  70 value 83.309106
iter  80 value 82.801315
iter  90 value 82.253271
iter 100 value 81.946519
final  value 81.946519 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.558221 
iter  10 value 94.521318
iter  20 value 90.481898
iter  30 value 87.442200
iter  40 value 86.442317
iter  50 value 84.061751
iter  60 value 83.715067
iter  70 value 83.489568
iter  80 value 82.425243
iter  90 value 81.962705
iter 100 value 81.794330
final  value 81.794330 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 112.816096 
iter  10 value 94.305126
iter  20 value 86.294323
iter  30 value 85.737047
iter  40 value 85.295620
iter  50 value 84.526659
iter  60 value 82.878478
iter  70 value 82.609018
iter  80 value 82.166618
iter  90 value 82.079774
iter 100 value 81.989115
final  value 81.989115 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 124.978599 
iter  10 value 94.413682
iter  20 value 88.128084
iter  30 value 87.175397
iter  40 value 84.429083
iter  50 value 82.520358
iter  60 value 81.824267
iter  70 value 81.465817
iter  80 value 81.267966
iter  90 value 81.236621
iter 100 value 81.102548
final  value 81.102548 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.126931 
iter  10 value 94.788280
iter  20 value 94.392735
iter  30 value 94.313331
iter  40 value 88.049482
iter  50 value 87.118990
iter  60 value 86.011083
iter  70 value 84.921924
iter  80 value 83.688499
iter  90 value 82.773352
iter 100 value 82.172677
final  value 82.172677 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.664328 
final  value 94.486171 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.557747 
final  value 94.485944 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.487271 
iter  10 value 93.111790
iter  20 value 93.111218
iter  30 value 93.110641
final  value 93.110576 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.305496 
final  value 94.485871 
converged
Fitting Repeat 5 

# weights:  103
initial  value 108.283851 
final  value 94.485725 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.271246 
iter  10 value 94.488650
iter  20 value 94.484235
iter  30 value 90.939023
iter  40 value 90.867040
iter  50 value 88.212928
iter  60 value 86.565934
final  value 86.565213 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.229766 
iter  10 value 94.508151
iter  20 value 94.458696
iter  30 value 88.547321
iter  40 value 87.370502
iter  50 value 87.303955
iter  60 value 87.289942
final  value 87.286201 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.577407 
iter  10 value 94.486038
iter  20 value 92.898335
iter  30 value 85.023158
iter  40 value 84.067023
iter  50 value 84.003053
iter  50 value 84.003052
iter  50 value 84.003052
final  value 84.003052 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.534715 
iter  10 value 86.507709
iter  20 value 85.430876
iter  30 value 85.164398
iter  40 value 85.128402
iter  50 value 85.121365
iter  60 value 85.119560
final  value 85.119055 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.134131 
iter  10 value 94.489415
iter  20 value 94.484463
final  value 94.484284 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.599082 
iter  10 value 94.492721
iter  20 value 93.850838
iter  30 value 87.671035
final  value 87.669857 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.439644 
iter  10 value 94.492260
iter  20 value 94.447083
iter  30 value 94.287255
iter  40 value 92.491213
iter  50 value 92.381688
iter  60 value 92.353803
final  value 92.353757 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.163698 
iter  10 value 94.362751
iter  20 value 94.342841
iter  30 value 89.418376
iter  40 value 89.329345
final  value 89.329269 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.444312 
iter  10 value 94.423326
iter  20 value 93.982332
iter  30 value 93.972762
iter  40 value 93.971308
iter  50 value 93.967279
iter  60 value 90.855405
iter  70 value 87.992400
iter  80 value 86.051412
iter  90 value 85.884231
iter 100 value 84.286077
final  value 84.286077 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 98.752417 
iter  10 value 94.362473
iter  20 value 94.355198
final  value 94.355134 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.008814 
final  value 93.915746 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.746317 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.967902 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.140571 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.521890 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.427109 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.066476 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 123.387123 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.796871 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.126879 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.116898 
iter  10 value 88.559971
final  value 88.332628 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.902155 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.419508 
final  value 93.915746 
converged
Fitting Repeat 4 

# weights:  507
initial  value 118.427425 
final  value 93.915746 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.655383 
final  value 94.011429 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.169708 
iter  10 value 94.035524
iter  20 value 93.563232
iter  30 value 93.387829
iter  40 value 92.879351
iter  50 value 87.111521
iter  60 value 85.474995
iter  70 value 84.893299
iter  80 value 84.822912
final  value 84.822252 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.255177 
iter  10 value 94.088871
iter  20 value 93.965643
iter  30 value 93.458829
iter  40 value 93.382860
iter  50 value 91.416291
iter  60 value 88.778425
iter  70 value 87.454751
iter  80 value 85.309072
iter  90 value 84.931606
iter 100 value 84.822254
final  value 84.822254 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 101.203019 
iter  10 value 93.803232
iter  20 value 87.596682
iter  30 value 85.550398
iter  40 value 85.415686
iter  50 value 85.289950
iter  60 value 85.284391
iter  70 value 85.281358
final  value 85.281348 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.162336 
iter  10 value 94.052627
iter  20 value 93.529236
iter  30 value 88.446852
iter  40 value 86.922338
iter  50 value 85.277125
iter  60 value 84.914183
iter  70 value 84.859754
iter  80 value 84.840599
iter  90 value 84.822253
final  value 84.822251 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.949081 
iter  10 value 94.038539
iter  20 value 91.483955
iter  30 value 88.434088
iter  40 value 87.703052
iter  50 value 87.086050
iter  60 value 84.997835
iter  70 value 83.219703
iter  80 value 82.654833
iter  90 value 82.569730
iter 100 value 82.380979
final  value 82.380979 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 100.943848 
iter  10 value 93.850660
iter  20 value 89.582023
iter  30 value 86.065972
iter  40 value 85.870884
iter  50 value 85.177407
iter  60 value 85.072915
iter  70 value 84.938633
iter  80 value 83.247464
iter  90 value 81.498181
iter 100 value 81.229699
final  value 81.229699 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.058608 
iter  10 value 94.318023
iter  20 value 94.005363
iter  30 value 87.415037
iter  40 value 86.741558
iter  50 value 85.857125
iter  60 value 84.397081
iter  70 value 83.020533
iter  80 value 82.705126
iter  90 value 82.405573
iter 100 value 81.779691
final  value 81.779691 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 112.883318 
iter  10 value 96.760042
iter  20 value 93.519248
iter  30 value 92.176980
iter  40 value 86.032794
iter  50 value 85.734799
iter  60 value 84.726619
iter  70 value 84.243578
iter  80 value 84.171609
iter  90 value 84.119168
iter 100 value 83.231057
final  value 83.231057 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.310305 
iter  10 value 94.198627
iter  20 value 89.418195
iter  30 value 88.289220
iter  40 value 85.192455
iter  50 value 83.675285
iter  60 value 83.296008
iter  70 value 81.965046
iter  80 value 81.640213
iter  90 value 81.357977
iter 100 value 81.350526
final  value 81.350526 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.744358 
iter  10 value 94.038999
iter  20 value 93.764204
iter  30 value 93.479625
iter  40 value 92.053558
iter  50 value 89.247622
iter  60 value 86.476245
iter  70 value 85.372376
iter  80 value 84.095854
iter  90 value 82.671144
iter 100 value 82.076138
final  value 82.076138 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.547668 
iter  10 value 93.143187
iter  20 value 88.557853
iter  30 value 85.858823
iter  40 value 83.262374
iter  50 value 82.835320
iter  60 value 81.914699
iter  70 value 81.303257
iter  80 value 80.981153
iter  90 value 80.722654
iter 100 value 80.561117
final  value 80.561117 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 116.202753 
iter  10 value 94.032375
iter  20 value 89.557673
iter  30 value 87.773769
iter  40 value 86.334124
iter  50 value 85.950198
iter  60 value 84.081633
iter  70 value 82.136888
iter  80 value 81.569976
iter  90 value 81.340841
iter 100 value 81.200791
final  value 81.200791 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 117.675785 
iter  10 value 93.504211
iter  20 value 86.408235
iter  30 value 85.867468
iter  40 value 84.145037
iter  50 value 83.044330
iter  60 value 82.489137
iter  70 value 81.782024
iter  80 value 81.327974
iter  90 value 81.058470
iter 100 value 80.967188
final  value 80.967188 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 116.024662 
iter  10 value 93.896412
iter  20 value 89.914036
iter  30 value 87.103518
iter  40 value 85.317686
iter  50 value 84.629866
iter  60 value 84.347321
iter  70 value 84.094128
iter  80 value 83.247579
iter  90 value 82.473545
iter 100 value 81.768857
final  value 81.768857 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.542697 
iter  10 value 94.601622
iter  20 value 91.799593
iter  30 value 89.486904
iter  40 value 86.324746
iter  50 value 85.405080
iter  60 value 84.880881
iter  70 value 84.583974
iter  80 value 82.379701
iter  90 value 81.262378
iter 100 value 80.970381
final  value 80.970381 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.328063 
final  value 94.054468 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.032858 
iter  10 value 93.729767
iter  20 value 93.374182
iter  30 value 93.247287
iter  40 value 92.406423
iter  50 value 91.980993
final  value 91.917297 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.579433 
iter  10 value 93.917506
iter  10 value 93.917506
iter  10 value 93.917506
final  value 93.917506 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.420456 
final  value 94.054616 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.405570 
final  value 94.054572 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.765696 
iter  10 value 93.983611
iter  20 value 88.478558
iter  30 value 84.964427
iter  40 value 84.550603
iter  50 value 84.548395
iter  60 value 84.544429
iter  70 value 84.145454
iter  80 value 83.096163
iter  90 value 82.904554
iter 100 value 82.899230
final  value 82.899230 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 135.146922 
iter  10 value 94.058052
iter  20 value 94.050450
iter  30 value 93.511599
iter  40 value 93.202297
iter  50 value 89.889957
iter  60 value 85.051533
iter  70 value 84.458511
iter  80 value 84.408705
final  value 84.408648 
converged
Fitting Repeat 3 

# weights:  305
initial  value 110.331419 
iter  10 value 94.057947
iter  20 value 94.046111
iter  30 value 89.573691
iter  40 value 85.637871
iter  50 value 85.633827
iter  60 value 85.631875
iter  70 value 84.671896
iter  80 value 84.484250
final  value 84.482777 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.458221 
iter  10 value 94.057245
iter  20 value 92.657155
iter  30 value 88.129756
iter  40 value 87.022328
iter  50 value 87.021730
final  value 87.021659 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.550789 
iter  10 value 94.058142
iter  20 value 94.052955
iter  30 value 93.873582
iter  40 value 85.634451
iter  50 value 85.634074
iter  60 value 85.629879
iter  70 value 83.831827
iter  80 value 81.256236
iter  90 value 80.405543
final  value 80.404274 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.089559 
iter  10 value 93.519571
iter  20 value 93.512501
iter  30 value 85.765643
iter  40 value 85.316180
iter  50 value 85.314758
iter  60 value 85.143611
iter  70 value 84.816684
iter  80 value 83.881146
iter  90 value 81.962649
iter 100 value 79.534411
final  value 79.534411 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 95.222696 
iter  10 value 86.107513
iter  20 value 86.096746
iter  30 value 85.434034
iter  40 value 85.433640
final  value 85.430785 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.665579 
iter  10 value 93.924124
iter  20 value 93.916886
final  value 93.916713 
converged
Fitting Repeat 4 

# weights:  507
initial  value 115.270171 
iter  10 value 94.060799
iter  20 value 93.980323
iter  30 value 93.111250
iter  40 value 91.049546
iter  50 value 88.668376
iter  60 value 84.809612
iter  70 value 83.885434
iter  80 value 83.781817
final  value 83.781714 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.692471 
iter  10 value 85.174394
iter  20 value 85.074892
iter  30 value 84.419403
final  value 84.418670 
converged
Fitting Repeat 1 

# weights:  305
initial  value 121.309612 
iter  10 value 117.895192
iter  20 value 116.303446
iter  30 value 110.319674
iter  40 value 110.230453
iter  50 value 108.324895
final  value 108.324710 
converged
Fitting Repeat 2 

# weights:  305
initial  value 119.685540 
iter  10 value 117.895369
iter  20 value 117.684539
iter  30 value 117.684183
iter  40 value 117.683756
iter  50 value 117.682272
iter  60 value 117.538862
final  value 117.538856 
converged
Fitting Repeat 3 

# weights:  305
initial  value 119.802960 
iter  10 value 117.896912
iter  20 value 117.238531
iter  30 value 114.260588
iter  40 value 114.231640
iter  50 value 114.231289
iter  60 value 113.800589
iter  70 value 113.773867
iter  80 value 113.772133
iter  90 value 113.632612
final  value 113.632476 
converged
Fitting Repeat 4 

# weights:  305
initial  value 131.627063 
iter  10 value 117.894807
iter  20 value 117.890334
iter  20 value 117.890334
iter  20 value 117.890334
final  value 117.890334 
converged
Fitting Repeat 5 

# weights:  305
initial  value 119.346855 
iter  10 value 117.894648
final  value 117.890301 
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 -- Mon May 25 20:01:02 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 
 18.696   0.582  69.878