##############################################################################
##############################################################################
###
### 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_1.17.2.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2026-01-15 r89304)
* using platform: aarch64-apple-darwin20
* R was compiled by
    Apple clang version 16.0.0 (clang-1600.0.26.6)
    GNU Fortran (GCC) 14.2.0
* running under: macOS Sonoma 14.8.3
* using session charset: UTF-8
* using option ‘--no-vignettes’
* 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 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
FSmethod      19.185  0.938  21.217
corr_plot     18.974  0.941  20.695
var_imp       18.602  1.037  20.791
pred_ensembel  6.570  0.119   6.280
enrichfindP    0.204  0.039  12.503
* 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-3.23-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-arm64/Resources/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) (2026-01-15 r89304) -- "Unsuffered Consequences"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20

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 95.613701 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.891737 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.281044 
iter  10 value 93.946239
final  value 93.946237 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.285316 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.319254 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.617735 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.635918 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 109.235618 
iter  10 value 93.946241
final  value 93.946237 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.560114 
final  value 94.052911 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.404930 
iter  10 value 93.946247
final  value 93.946237 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.957907 
final  value 91.824176 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.993015 
iter  10 value 93.983250
final  value 93.946237 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.005099 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 110.308326 
iter  10 value 93.946264
final  value 93.946237 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.370123 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.374796 
iter  10 value 94.055687
iter  20 value 93.178521
iter  30 value 86.065650
iter  40 value 84.744730
iter  50 value 83.886072
iter  60 value 83.337499
iter  70 value 83.254805
final  value 83.254766 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.700012 
iter  10 value 94.027211
iter  20 value 92.723806
iter  30 value 92.364213
iter  40 value 90.118800
iter  50 value 89.758367
iter  60 value 89.696850
iter  70 value 84.438714
iter  80 value 82.467630
iter  90 value 81.999054
iter 100 value 81.886402
final  value 81.886402 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.425449 
iter  10 value 93.802394
iter  20 value 86.446143
iter  30 value 84.915022
iter  40 value 84.736684
iter  50 value 84.429468
iter  60 value 83.510180
iter  70 value 83.109059
iter  80 value 82.940831
final  value 82.940817 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.967305 
iter  10 value 94.040247
iter  20 value 91.108680
iter  30 value 84.590720
iter  40 value 83.888238
iter  50 value 83.868517
iter  60 value 83.730995
iter  70 value 83.461055
iter  80 value 83.448555
iter  90 value 83.447953
final  value 83.447914 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.342479 
iter  10 value 93.954131
iter  20 value 86.825150
iter  30 value 85.866083
iter  40 value 84.899413
iter  50 value 84.713663
iter  60 value 84.558849
iter  70 value 83.619399
iter  80 value 82.951024
iter  90 value 82.940933
final  value 82.940824 
converged
Fitting Repeat 1 

# weights:  305
initial  value 145.986896 
iter  10 value 93.922759
iter  20 value 91.508888
iter  30 value 85.946274
iter  40 value 84.774108
iter  50 value 84.460841
iter  60 value 83.951022
iter  70 value 83.308722
iter  80 value 82.357304
iter  90 value 81.440060
iter 100 value 80.677174
final  value 80.677174 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.034151 
iter  10 value 94.075344
iter  20 value 94.035052
iter  30 value 89.098177
iter  40 value 84.915281
iter  50 value 84.324063
iter  60 value 84.038535
iter  70 value 83.758124
iter  80 value 83.545108
iter  90 value 82.928557
iter 100 value 81.017577
final  value 81.017577 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 107.322360 
iter  10 value 94.075634
iter  20 value 90.646015
iter  30 value 84.910658
iter  40 value 84.796601
iter  50 value 84.593630
iter  60 value 83.634676
iter  70 value 82.706021
iter  80 value 80.836738
iter  90 value 80.386898
iter 100 value 80.348303
final  value 80.348303 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.761848 
iter  10 value 93.296156
iter  20 value 88.741188
iter  30 value 85.781636
iter  40 value 83.509873
iter  50 value 82.469632
iter  60 value 81.016025
iter  70 value 80.477611
iter  80 value 80.281124
iter  90 value 80.242347
iter 100 value 80.219842
final  value 80.219842 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.809782 
iter  10 value 94.072530
iter  20 value 87.321948
iter  30 value 86.873332
iter  40 value 86.199021
iter  50 value 84.352091
iter  60 value 83.853477
iter  70 value 82.581434
iter  80 value 81.260597
iter  90 value 80.904148
iter 100 value 80.511262
final  value 80.511262 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 111.938221 
iter  10 value 98.624662
iter  20 value 95.849222
iter  30 value 92.894853
iter  40 value 86.189377
iter  50 value 82.954063
iter  60 value 81.868104
iter  70 value 81.522848
iter  80 value 81.478286
iter  90 value 81.445826
iter 100 value 81.391430
final  value 81.391430 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 114.074945 
iter  10 value 93.975030
iter  20 value 90.241167
iter  30 value 86.113265
iter  40 value 83.732299
iter  50 value 82.232469
iter  60 value 81.911357
iter  70 value 81.160292
iter  80 value 80.361189
iter  90 value 80.114014
iter 100 value 79.965523
final  value 79.965523 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 112.716954 
iter  10 value 94.159971
iter  20 value 93.861402
iter  30 value 86.487235
iter  40 value 85.712228
iter  50 value 84.345638
iter  60 value 82.384851
iter  70 value 81.878521
iter  80 value 81.644163
iter  90 value 81.011827
iter 100 value 80.748991
final  value 80.748991 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.994329 
iter  10 value 94.812921
iter  20 value 86.063735
iter  30 value 83.695775
iter  40 value 81.445590
iter  50 value 80.554635
iter  60 value 80.244093
iter  70 value 80.093565
iter  80 value 80.008999
iter  90 value 79.875649
iter 100 value 79.773885
final  value 79.773885 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.590183 
iter  10 value 91.819602
iter  20 value 84.124258
iter  30 value 82.343241
iter  40 value 81.684823
iter  50 value 81.347287
iter  60 value 80.519007
iter  70 value 80.197978
iter  80 value 80.140304
iter  90 value 80.060811
iter 100 value 80.007781
final  value 80.007781 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.801463 
final  value 94.054278 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.081840 
final  value 94.054390 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.342918 
iter  10 value 94.054712
iter  20 value 94.052939
final  value 94.052920 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.616065 
final  value 94.054666 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.624195 
iter  10 value 93.947883
iter  20 value 93.947192
final  value 93.946426 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.284942 
iter  10 value 92.820582
iter  20 value 92.815261
iter  30 value 85.452717
iter  40 value 85.217801
iter  50 value 85.197082
iter  60 value 84.582015
iter  70 value 83.553878
final  value 83.433390 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.977943 
iter  10 value 94.057929
iter  20 value 93.958055
final  value 93.915836 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.316586 
iter  10 value 93.951198
iter  20 value 93.946814
iter  30 value 85.498379
iter  40 value 81.757187
iter  50 value 81.558982
iter  60 value 81.522751
iter  70 value 81.407262
iter  80 value 80.928014
iter  90 value 80.418526
iter 100 value 79.938103
final  value 79.938103 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 94.224424 
iter  10 value 94.055400
iter  20 value 93.651562
iter  30 value 87.082620
iter  40 value 83.586280
iter  50 value 83.553531
iter  60 value 83.504888
iter  70 value 83.451498
iter  80 value 83.417748
iter  90 value 83.224269
iter 100 value 82.809130
final  value 82.809130 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.809348 
iter  10 value 94.056536
iter  20 value 93.973407
iter  30 value 91.878810
iter  40 value 88.876587
iter  50 value 88.758897
iter  60 value 88.734986
iter  70 value 88.734316
iter  80 value 88.733544
iter  90 value 88.732928
iter 100 value 88.731630
final  value 88.731630 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.916078 
iter  10 value 93.954291
iter  20 value 93.951937
iter  30 value 93.906341
iter  40 value 91.826194
final  value 91.826179 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.112380 
iter  10 value 93.399319
iter  20 value 93.267278
iter  30 value 93.260279
iter  40 value 93.224016
iter  50 value 93.221742
iter  60 value 92.841212
iter  70 value 89.731461
iter  80 value 89.454896
iter  90 value 89.071228
iter 100 value 89.020185
final  value 89.020185 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 98.139065 
iter  10 value 94.061168
iter  20 value 93.764821
iter  30 value 91.826684
iter  40 value 91.825841
iter  50 value 91.379238
iter  60 value 90.322198
final  value 90.240886 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.877959 
iter  10 value 94.061783
iter  20 value 94.051011
iter  30 value 85.547565
iter  40 value 84.768338
iter  50 value 84.692001
iter  60 value 84.687689
iter  70 value 84.653512
iter  80 value 84.611453
iter  90 value 84.027107
iter 100 value 80.792251
final  value 80.792251 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.772960 
iter  10 value 94.060925
iter  20 value 94.031153
iter  30 value 87.055650
iter  40 value 86.988342
iter  50 value 86.244806
iter  60 value 84.749855
iter  70 value 84.514954
iter  80 value 84.489362
iter  90 value 84.482529
iter  90 value 84.482528
final  value 84.481936 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.997161 
final  value 94.480519 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.419393 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 110.294702 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.725916 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.701738 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.750059 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.406238 
iter  10 value 93.637386
iter  10 value 93.637385
final  value 93.637381 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.805889 
iter  10 value 94.497478
iter  20 value 93.046565
iter  30 value 90.471661
iter  40 value 87.081990
iter  50 value 87.061997
final  value 87.061743 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.914460 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.317305 
iter  10 value 94.484221
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 113.814612 
final  value 93.637379 
converged
Fitting Repeat 2 

# weights:  507
initial  value 114.681438 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.238544 
iter  10 value 93.628520
iter  20 value 93.626826
final  value 93.626795 
converged
Fitting Repeat 4 

# weights:  507
initial  value 133.117294 
iter  10 value 94.484293
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.084308 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.341480 
iter  10 value 94.488552
iter  20 value 93.983346
iter  30 value 93.893003
iter  40 value 93.652167
iter  50 value 93.620532
iter  60 value 90.804896
iter  70 value 88.585350
iter  80 value 85.784729
iter  90 value 84.484530
iter 100 value 84.057142
final  value 84.057142 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 102.813612 
iter  10 value 94.301342
iter  20 value 89.788327
iter  30 value 87.878448
iter  40 value 84.477760
iter  50 value 84.454879
iter  60 value 83.872898
iter  70 value 82.196977
iter  80 value 81.815998
iter  90 value 81.704132
final  value 81.704131 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.152786 
iter  10 value 94.576562
iter  20 value 94.486014
iter  30 value 93.784096
iter  40 value 86.919391
iter  50 value 84.793213
iter  60 value 84.630724
iter  70 value 84.412820
iter  80 value 84.339252
iter  90 value 84.284040
final  value 84.284032 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.715975 
iter  10 value 94.493941
iter  20 value 93.871347
iter  30 value 89.243475
iter  40 value 84.396572
iter  50 value 83.718658
iter  60 value 82.634977
iter  70 value 81.733549
iter  80 value 81.704218
final  value 81.704131 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.758495 
iter  10 value 94.487948
iter  20 value 93.517464
iter  30 value 93.355246
iter  40 value 89.520180
iter  50 value 86.120060
iter  60 value 85.565305
iter  70 value 85.006135
iter  80 value 84.674304
final  value 84.658791 
converged
Fitting Repeat 1 

# weights:  305
initial  value 126.461762 
iter  10 value 91.529474
iter  20 value 85.908268
iter  30 value 85.536581
iter  40 value 85.363953
iter  50 value 85.231053
iter  60 value 85.085256
iter  70 value 81.489414
iter  80 value 80.533041
iter  90 value 80.459346
iter 100 value 80.429183
final  value 80.429183 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.475499 
iter  10 value 95.373638
iter  20 value 88.688905
iter  30 value 87.150963
iter  40 value 86.144935
iter  50 value 85.520777
iter  60 value 84.634625
iter  70 value 84.441651
iter  80 value 83.866704
iter  90 value 81.922074
iter 100 value 81.841768
final  value 81.841768 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.060947 
iter  10 value 94.494623
iter  20 value 86.473251
iter  30 value 84.463735
iter  40 value 84.018828
iter  50 value 82.844111
iter  60 value 81.967305
iter  70 value 81.856733
iter  80 value 81.678509
iter  90 value 81.130616
iter 100 value 80.657365
final  value 80.657365 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.072124 
iter  10 value 94.036231
iter  20 value 86.916313
iter  30 value 84.737521
iter  40 value 84.572335
iter  50 value 84.527923
iter  60 value 84.335063
iter  70 value 84.212780
iter  80 value 84.080296
iter  90 value 83.729128
iter 100 value 80.729736
final  value 80.729736 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.428154 
iter  10 value 94.549169
iter  20 value 90.720006
iter  30 value 87.088195
iter  40 value 84.988553
iter  50 value 84.262987
iter  60 value 84.094998
iter  70 value 83.874975
iter  80 value 82.586171
iter  90 value 81.059561
iter 100 value 80.434010
final  value 80.434010 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 119.873231 
iter  10 value 94.497408
iter  20 value 89.162966
iter  30 value 85.633518
iter  40 value 85.354440
iter  50 value 85.018733
iter  60 value 85.004376
iter  70 value 84.711894
iter  80 value 83.172056
iter  90 value 81.834464
iter 100 value 80.909758
final  value 80.909758 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.196882 
iter  10 value 94.409040
iter  20 value 87.718055
iter  30 value 85.163651
iter  40 value 84.193473
iter  50 value 83.942901
iter  60 value 83.132034
iter  70 value 81.616433
iter  80 value 80.832295
iter  90 value 80.762218
iter 100 value 80.738178
final  value 80.738178 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 115.192417 
iter  10 value 94.006740
iter  20 value 88.434291
iter  30 value 84.294604
iter  40 value 83.501125
iter  50 value 82.500203
iter  60 value 80.750239
iter  70 value 80.212315
iter  80 value 80.093411
iter  90 value 80.032805
iter 100 value 79.907258
final  value 79.907258 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.818355 
iter  10 value 94.958586
iter  20 value 94.081326
iter  30 value 91.805016
iter  40 value 87.502273
iter  50 value 85.654019
iter  60 value 84.219165
iter  70 value 83.064546
iter  80 value 81.108664
iter  90 value 80.613185
iter 100 value 80.360979
final  value 80.360979 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 125.722517 
iter  10 value 94.604432
iter  20 value 94.288290
iter  30 value 91.396488
iter  40 value 88.036210
iter  50 value 84.529863
iter  60 value 83.953596
iter  70 value 83.790825
iter  80 value 82.819759
iter  90 value 82.194591
iter 100 value 81.731274
final  value 81.731274 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.741263 
final  value 94.485780 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.199916 
iter  10 value 94.468238
iter  20 value 94.466930
final  value 94.466863 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.096688 
final  value 94.485705 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.640529 
final  value 94.485670 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.067569 
iter  10 value 94.485856
iter  20 value 94.484225
final  value 94.484214 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.557534 
iter  10 value 94.488683
iter  20 value 94.396204
iter  30 value 93.617648
iter  40 value 86.879158
iter  50 value 83.869713
iter  60 value 81.736282
iter  70 value 79.647266
iter  80 value 79.542095
iter  90 value 79.541390
final  value 79.541122 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.243674 
iter  10 value 94.090839
iter  20 value 94.085203
iter  30 value 94.084363
iter  40 value 93.670264
iter  50 value 86.915624
iter  60 value 86.705706
iter  70 value 86.681132
iter  80 value 83.675897
iter  90 value 81.987284
iter 100 value 81.679948
final  value 81.679948 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 97.430388 
iter  10 value 94.414807
iter  20 value 94.248601
iter  30 value 94.091011
iter  40 value 94.089254
iter  50 value 94.017069
iter  60 value 90.310203
iter  70 value 85.193630
iter  80 value 85.005508
final  value 85.002559 
converged
Fitting Repeat 4 

# weights:  305
initial  value 110.756801 
iter  10 value 94.485231
iter  20 value 94.290619
iter  30 value 93.861133
iter  40 value 92.871386
iter  50 value 92.404799
final  value 92.379186 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.747565 
iter  10 value 94.486927
iter  20 value 93.901588
iter  30 value 93.636109
iter  40 value 93.635815
iter  50 value 93.621723
iter  60 value 87.816540
iter  70 value 87.021927
iter  80 value 82.827316
iter  90 value 82.821850
iter 100 value 82.650172
final  value 82.650172 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 122.102716 
iter  10 value 94.475379
iter  20 value 94.186962
iter  30 value 93.461812
iter  40 value 93.119880
iter  50 value 92.515275
iter  60 value 83.757131
iter  70 value 81.860940
iter  80 value 81.414267
iter  90 value 81.413989
iter 100 value 81.363425
final  value 81.363425 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.185720 
iter  10 value 92.954467
iter  20 value 87.705453
iter  30 value 86.654868
iter  40 value 86.650479
iter  50 value 86.638278
iter  60 value 86.634068
iter  70 value 86.484869
final  value 86.484377 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.064089 
iter  10 value 94.492247
iter  20 value 94.484348
iter  30 value 93.458646
iter  40 value 89.995393
iter  50 value 83.066688
iter  60 value 82.849444
iter  70 value 82.848264
iter  80 value 82.841643
iter  90 value 82.372792
iter 100 value 81.125821
final  value 81.125821 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 101.223909 
iter  10 value 94.474814
iter  20 value 93.008417
iter  30 value 90.342790
iter  40 value 89.156933
iter  50 value 88.360768
iter  60 value 83.181776
iter  70 value 81.769833
iter  80 value 81.730956
iter  90 value 81.728131
final  value 81.726941 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.760505 
iter  10 value 94.475131
iter  20 value 94.461117
iter  30 value 84.950937
iter  40 value 83.743544
iter  50 value 83.642212
iter  60 value 83.486561
iter  70 value 83.238043
iter  80 value 83.185696
iter  90 value 83.184295
iter 100 value 83.119688
final  value 83.119688 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.844073 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.176419 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.464945 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.227141 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.518899 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.425715 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.271139 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.881174 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.790847 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.816084 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.855366 
iter  10 value 89.803503
final  value 89.767560 
converged
Fitting Repeat 2 

# weights:  507
initial  value 114.331010 
iter  10 value 93.486777
iter  20 value 93.420265
final  value 93.420115 
converged
Fitting Repeat 3 

# weights:  507
initial  value 112.298165 
final  value 94.032967 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.055091 
iter  10 value 93.881872
iter  20 value 93.869772
final  value 93.869756 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.709723 
iter  10 value 94.070337
iter  20 value 94.021237
final  value 94.020799 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.224132 
iter  10 value 94.047053
iter  20 value 93.119556
iter  30 value 91.599714
iter  40 value 91.109595
iter  50 value 87.069077
iter  60 value 84.862966
iter  70 value 84.434900
iter  80 value 84.298528
iter  90 value 83.970330
iter 100 value 82.417677
final  value 82.417677 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 103.765398 
iter  10 value 93.844212
iter  20 value 93.693920
iter  30 value 93.690675
iter  40 value 91.466097
iter  50 value 85.921412
iter  60 value 85.562203
iter  70 value 83.940095
iter  80 value 83.664603
iter  90 value 83.435048
iter 100 value 83.364849
final  value 83.364849 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.178314 
iter  10 value 94.121394
iter  20 value 94.050604
iter  30 value 84.704408
iter  40 value 83.744833
iter  50 value 83.603977
iter  60 value 83.561490
iter  70 value 83.400412
iter  80 value 83.335446
iter  90 value 83.125160
iter 100 value 82.864564
final  value 82.864564 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 102.608888 
iter  10 value 93.888592
iter  20 value 85.109549
iter  30 value 83.576173
iter  40 value 83.371570
iter  50 value 83.325630
iter  60 value 83.197584
iter  70 value 83.102650
iter  80 value 82.596426
iter  90 value 82.443423
iter 100 value 82.436974
final  value 82.436974 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 100.876804 
iter  10 value 96.992187
iter  20 value 94.009647
iter  30 value 93.697386
iter  40 value 84.434141
iter  50 value 83.239873
iter  60 value 82.942217
iter  70 value 82.899798
iter  80 value 82.882104
iter  90 value 82.845271
iter 100 value 82.839902
final  value 82.839902 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 111.685711 
iter  10 value 94.074980
iter  20 value 92.679078
iter  30 value 86.850765
iter  40 value 85.369335
iter  50 value 84.719185
iter  60 value 82.551942
iter  70 value 82.172995
iter  80 value 81.578928
iter  90 value 81.431026
iter 100 value 81.272146
final  value 81.272146 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.177398 
iter  10 value 94.675022
iter  20 value 92.353787
iter  30 value 84.485143
iter  40 value 83.967549
iter  50 value 83.442812
iter  60 value 82.972175
iter  70 value 82.821597
iter  80 value 82.643916
iter  90 value 82.589349
iter 100 value 82.439655
final  value 82.439655 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 112.017664 
iter  10 value 94.066477
iter  20 value 85.902020
iter  30 value 84.229037
iter  40 value 83.673991
iter  50 value 82.967279
iter  60 value 81.749676
iter  70 value 81.285574
iter  80 value 81.072804
iter  90 value 81.026310
iter 100 value 80.981451
final  value 80.981451 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.780403 
iter  10 value 94.359724
iter  20 value 91.687862
iter  30 value 86.895879
iter  40 value 83.795523
iter  50 value 83.158625
iter  60 value 83.081041
iter  70 value 82.815877
iter  80 value 82.644096
iter  90 value 82.542414
iter 100 value 82.156316
final  value 82.156316 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.501695 
iter  10 value 94.081800
iter  20 value 90.363989
iter  30 value 85.545235
iter  40 value 84.353291
iter  50 value 82.896832
iter  60 value 82.618447
iter  70 value 82.600612
iter  80 value 82.549026
iter  90 value 82.535718
iter 100 value 82.522684
final  value 82.522684 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.051996 
iter  10 value 96.625052
iter  20 value 93.925696
iter  30 value 86.103873
iter  40 value 85.261084
iter  50 value 84.311257
iter  60 value 82.759390
iter  70 value 81.999401
iter  80 value 81.313429
iter  90 value 80.990724
iter 100 value 80.764461
final  value 80.764461 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.340335 
iter  10 value 93.655697
iter  20 value 91.098075
iter  30 value 89.266314
iter  40 value 86.853985
iter  50 value 84.128483
iter  60 value 82.454835
iter  70 value 81.977999
iter  80 value 81.586030
iter  90 value 81.136979
iter 100 value 80.870188
final  value 80.870188 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 130.974913 
iter  10 value 94.413675
iter  20 value 83.558332
iter  30 value 82.484625
iter  40 value 82.352093
iter  50 value 81.867785
iter  60 value 81.518966
iter  70 value 81.377379
iter  80 value 81.153978
iter  90 value 80.901324
iter 100 value 80.872982
final  value 80.872982 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 115.407878 
iter  10 value 93.888488
iter  20 value 93.277659
iter  30 value 88.698418
iter  40 value 85.681099
iter  50 value 84.852356
iter  60 value 83.778256
iter  70 value 82.775259
iter  80 value 82.175138
iter  90 value 81.509806
iter 100 value 81.317978
final  value 81.317978 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 126.641509 
iter  10 value 92.616635
iter  20 value 88.660510
iter  30 value 87.159668
iter  40 value 84.546467
iter  50 value 83.366849
iter  60 value 82.706599
iter  70 value 82.173386
iter  80 value 81.988137
iter  90 value 81.808865
iter 100 value 81.268619
final  value 81.268619 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.338221 
final  value 94.054461 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.974027 
final  value 94.054584 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.357579 
final  value 94.054616 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.944758 
final  value 94.054460 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.428929 
final  value 94.054417 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.780326 
iter  10 value 94.037563
iter  20 value 84.847067
iter  30 value 82.465836
iter  40 value 82.465361
final  value 82.464844 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.362288 
iter  10 value 94.057168
iter  20 value 94.039197
iter  30 value 85.067299
iter  40 value 80.687415
iter  50 value 80.624918
iter  60 value 80.622095
iter  70 value 80.619403
iter  80 value 80.333731
iter  90 value 80.211778
iter 100 value 80.204731
final  value 80.204731 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 112.422272 
iter  10 value 91.966212
iter  20 value 84.144097
iter  30 value 82.642699
iter  40 value 82.639593
iter  50 value 82.423728
iter  60 value 82.268608
iter  70 value 82.227151
iter  80 value 82.224742
final  value 82.222462 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.053760 
iter  10 value 94.058148
iter  20 value 93.924865
iter  30 value 93.658537
iter  40 value 93.658159
iter  50 value 93.657837
iter  60 value 93.653232
iter  70 value 89.230910
iter  80 value 84.068177
iter  90 value 83.397087
iter 100 value 83.392278
final  value 83.392278 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 98.378494 
iter  10 value 94.037919
iter  20 value 93.583665
iter  30 value 85.629850
iter  40 value 85.587987
iter  50 value 85.082040
iter  60 value 83.724508
iter  70 value 83.636593
iter  80 value 83.632321
iter  90 value 83.396814
iter 100 value 82.980225
final  value 82.980225 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 101.893800 
iter  10 value 94.060238
iter  20 value 93.781781
iter  30 value 86.881934
iter  40 value 84.348458
iter  50 value 82.579173
iter  60 value 82.463193
iter  70 value 82.321102
iter  80 value 82.320531
iter  80 value 82.320531
final  value 82.320531 
converged
Fitting Repeat 2 

# weights:  507
initial  value 94.043676 
iter  10 value 92.071899
iter  20 value 90.635497
iter  30 value 90.539578
iter  40 value 90.403747
iter  50 value 90.169224
iter  60 value 90.166468
iter  70 value 90.166266
iter  80 value 90.164666
iter  90 value 90.135362
iter 100 value 89.821895
final  value 89.821895 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 93.884574 
iter  10 value 93.628495
iter  20 value 93.620693
iter  30 value 83.256395
iter  40 value 82.993557
iter  50 value 82.924193
iter  60 value 81.500047
iter  70 value 81.338987
iter  80 value 81.331307
iter  90 value 81.330442
iter 100 value 81.326700
final  value 81.326700 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.962124 
iter  10 value 90.750553
iter  20 value 89.995387
iter  30 value 89.993974
iter  40 value 89.781544
iter  50 value 89.772883
iter  60 value 89.695591
iter  70 value 89.638180
iter  80 value 89.638108
final  value 89.638095 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.874906 
iter  10 value 94.030022
iter  20 value 89.932929
final  value 89.932387 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.454182 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.626299 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.202794 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.797408 
final  value 94.354396 
converged
Fitting Repeat 5 

# weights:  103
initial  value 110.190912 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.034235 
final  value 94.423530 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.891750 
final  value 94.354396 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.067339 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.887238 
final  value 94.354396 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.333391 
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  507
initial  value 117.428626 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.089166 
final  value 94.354396 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.807944 
final  value 94.350744 
converged
Fitting Repeat 4 

# weights:  507
initial  value 125.589507 
iter  10 value 92.043326
iter  20 value 91.855510
final  value 91.854060 
converged
Fitting Repeat 5 

# weights:  507
initial  value 118.375319 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.031144 
iter  10 value 94.198296
iter  20 value 87.656361
iter  30 value 86.669994
iter  40 value 86.464932
iter  50 value 86.281843
iter  60 value 85.464855
iter  70 value 85.364541
iter  80 value 85.348010
iter  80 value 85.348009
iter  80 value 85.348009
final  value 85.348009 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.036242 
iter  10 value 94.487131
iter  20 value 94.354491
iter  30 value 94.186635
iter  40 value 93.719944
iter  50 value 88.764941
iter  60 value 87.697156
iter  70 value 87.052002
iter  80 value 84.709220
iter  90 value 83.492549
iter 100 value 83.273444
final  value 83.273444 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.640107 
iter  10 value 94.430019
iter  20 value 90.095539
iter  30 value 88.897799
iter  40 value 88.414098
iter  50 value 85.726529
iter  60 value 85.357684
iter  70 value 85.348502
final  value 85.348009 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.241382 
iter  10 value 94.523528
iter  20 value 94.247334
iter  30 value 88.930176
iter  40 value 87.444022
iter  50 value 85.144679
iter  60 value 85.011920
iter  70 value 84.975199
iter  80 value 84.973255
final  value 84.973251 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.230388 
iter  10 value 94.454301
iter  20 value 89.473665
iter  30 value 88.764731
iter  40 value 86.497854
iter  50 value 86.081027
iter  60 value 85.496159
iter  70 value 85.368033
iter  80 value 85.348011
final  value 85.348009 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.548637 
iter  10 value 94.612714
iter  20 value 94.486377
iter  30 value 94.287212
iter  40 value 93.150900
iter  50 value 87.366262
iter  60 value 85.343394
iter  70 value 83.466306
iter  80 value 82.334507
iter  90 value 81.776030
iter 100 value 81.516585
final  value 81.516585 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.826540 
iter  10 value 94.442240
iter  20 value 89.980007
iter  30 value 88.582986
iter  40 value 85.538522
iter  50 value 84.191688
iter  60 value 83.651175
iter  70 value 83.285955
iter  80 value 82.736302
iter  90 value 82.425271
iter 100 value 82.356079
final  value 82.356079 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 116.448679 
iter  10 value 94.522048
iter  20 value 93.003569
iter  30 value 88.353754
iter  40 value 86.353211
iter  50 value 85.257917
iter  60 value 84.694420
iter  70 value 84.224515
iter  80 value 83.977004
iter  90 value 83.108447
iter 100 value 82.800483
final  value 82.800483 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 98.623419 
iter  10 value 88.569846
iter  20 value 88.141051
iter  30 value 87.984862
iter  40 value 86.331690
iter  50 value 85.982084
iter  60 value 85.291328
iter  70 value 83.621669
iter  80 value 82.386947
iter  90 value 81.874799
iter 100 value 81.628035
final  value 81.628035 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.690522 
iter  10 value 94.354990
iter  20 value 86.817920
iter  30 value 86.129134
iter  40 value 85.474016
iter  50 value 84.509394
iter  60 value 83.982774
iter  70 value 83.843292
iter  80 value 83.505031
iter  90 value 82.615859
iter 100 value 82.223242
final  value 82.223242 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.420399 
iter  10 value 94.774204
iter  20 value 93.948398
iter  30 value 89.293362
iter  40 value 85.121706
iter  50 value 83.851202
iter  60 value 82.833753
iter  70 value 82.436258
iter  80 value 81.843549
iter  90 value 81.632838
iter 100 value 81.569460
final  value 81.569460 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 119.418176 
iter  10 value 94.664361
iter  20 value 94.232255
iter  30 value 87.626712
iter  40 value 85.445892
iter  50 value 85.217353
iter  60 value 85.138632
iter  70 value 85.063999
iter  80 value 84.935991
iter  90 value 83.563964
iter 100 value 82.628230
final  value 82.628230 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.876034 
iter  10 value 94.438386
iter  20 value 94.201202
iter  30 value 94.146380
iter  40 value 89.469868
iter  50 value 86.298205
iter  60 value 86.145248
iter  70 value 84.811467
iter  80 value 82.979470
iter  90 value 82.260044
iter 100 value 81.880849
final  value 81.880849 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 119.675039 
iter  10 value 94.891664
iter  20 value 90.520993
iter  30 value 86.633782
iter  40 value 85.838458
iter  50 value 84.474534
iter  60 value 84.058268
iter  70 value 83.343711
iter  80 value 82.277766
iter  90 value 81.802690
iter 100 value 81.729401
final  value 81.729401 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.174107 
iter  10 value 94.476799
iter  20 value 93.719655
iter  30 value 90.744657
iter  40 value 87.161375
iter  50 value 85.455773
iter  60 value 84.727418
iter  70 value 84.102409
iter  80 value 83.576600
iter  90 value 83.390726
iter 100 value 83.136381
final  value 83.136381 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 109.206193 
iter  10 value 94.485897
iter  20 value 94.484228
iter  30 value 92.977025
iter  40 value 92.902399
iter  50 value 92.503482
final  value 92.305646 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.748914 
final  value 94.485772 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.427873 
final  value 94.485805 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.222861 
final  value 94.485789 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.349616 
final  value 94.486022 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.652627 
iter  10 value 94.212053
iter  20 value 94.149642
iter  30 value 94.146155
iter  40 value 94.142574
iter  50 value 88.555470
iter  60 value 88.373930
final  value 88.373855 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.977121 
iter  10 value 94.489126
iter  20 value 94.484396
iter  30 value 94.166288
final  value 94.144573 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.515563 
iter  10 value 94.359310
iter  20 value 94.153869
iter  30 value 87.895593
iter  40 value 85.582238
iter  50 value 85.089089
final  value 85.089086 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.842178 
iter  10 value 94.487681
iter  20 value 93.733984
iter  30 value 88.682191
iter  40 value 86.179697
iter  50 value 84.872354
iter  60 value 84.245700
iter  70 value 84.149764
iter  80 value 84.148459
iter  90 value 84.147876
iter 100 value 83.190698
final  value 83.190698 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 96.822396 
iter  10 value 94.489077
iter  20 value 94.358302
final  value 94.354616 
converged
Fitting Repeat 1 

# weights:  507
initial  value 134.165524 
iter  10 value 89.329207
iter  20 value 87.292716
iter  30 value 87.282433
iter  40 value 87.277997
iter  50 value 87.271674
iter  60 value 86.904949
iter  70 value 85.251788
iter  80 value 81.021827
iter  90 value 80.613812
iter 100 value 80.600252
final  value 80.600252 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.523835 
iter  10 value 93.484293
iter  20 value 90.960495
iter  30 value 90.850954
iter  40 value 90.766106
iter  50 value 90.759724
iter  60 value 90.759223
iter  70 value 89.618758
iter  80 value 84.454269
iter  90 value 84.446374
iter 100 value 83.226080
final  value 83.226080 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.299551 
iter  10 value 94.361656
iter  20 value 94.358591
iter  30 value 94.353789
iter  40 value 94.328595
iter  50 value 93.454998
iter  60 value 89.905496
iter  60 value 89.905496
iter  60 value 89.905496
final  value 89.905496 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.336175 
iter  10 value 94.489212
iter  20 value 94.484244
final  value 94.484224 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.155633 
iter  10 value 94.492184
iter  20 value 94.430864
iter  30 value 94.142125
final  value 94.133069 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.907290 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.502997 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.884197 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.103423 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 113.339557 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.877438 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.434843 
iter  10 value 93.917688
iter  20 value 93.911782
final  value 93.911765 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.867617 
final  value 94.312038 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.149334 
iter  10 value 94.467760
iter  20 value 93.906970
iter  30 value 90.341151
iter  40 value 90.340673
final  value 90.340649 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.587454 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.229535 
iter  10 value 91.257889
iter  20 value 89.059516
iter  30 value 89.033705
iter  40 value 89.029679
final  value 89.029651 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.688034 
iter  10 value 93.791105
final  value 93.790476 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.524169 
final  value 93.624286 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.497507 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.090070 
final  value 94.342058 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.319406 
iter  10 value 94.371359
iter  20 value 93.368475
iter  30 value 93.302700
iter  40 value 92.855519
iter  50 value 88.347171
iter  60 value 87.339897
iter  70 value 82.254488
iter  80 value 81.307663
iter  90 value 81.264856
iter 100 value 81.238300
final  value 81.238300 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 100.455965 
iter  10 value 94.424587
iter  20 value 88.679273
iter  30 value 86.907445
iter  40 value 86.452022
iter  50 value 85.158735
iter  60 value 85.120079
iter  70 value 82.553524
iter  80 value 82.297055
iter  90 value 82.275162
iter  90 value 82.275162
iter  90 value 82.275162
final  value 82.275162 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.883548 
iter  10 value 94.488495
iter  20 value 94.416173
iter  30 value 93.973511
iter  40 value 92.776363
iter  50 value 83.720252
iter  60 value 82.087635
iter  70 value 81.951061
iter  80 value 81.775708
iter  90 value 80.849660
iter 100 value 79.895026
final  value 79.895026 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 106.624553 
iter  10 value 94.492440
iter  20 value 94.441754
iter  30 value 89.162200
iter  40 value 79.197456
iter  50 value 78.629866
iter  60 value 78.293773
iter  70 value 77.463164
iter  80 value 76.872286
iter  90 value 76.380455
iter 100 value 76.164180
final  value 76.164180 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 111.724821 
iter  10 value 93.968716
iter  20 value 87.082672
iter  30 value 84.474141
iter  40 value 83.763142
iter  50 value 83.239798
iter  60 value 82.283952
iter  70 value 82.007439
iter  80 value 81.767045
iter  90 value 81.756263
final  value 81.756180 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.840517 
iter  10 value 94.483873
iter  20 value 88.614012
iter  30 value 82.058293
iter  40 value 78.612573
iter  50 value 78.022394
iter  60 value 77.728471
iter  70 value 76.821493
iter  80 value 75.672364
iter  90 value 74.972544
iter 100 value 74.658353
final  value 74.658353 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.857841 
iter  10 value 94.483652
iter  20 value 93.919136
iter  30 value 88.803557
iter  40 value 87.616100
iter  50 value 84.856772
iter  60 value 83.324064
iter  70 value 82.306690
iter  80 value 78.752125
iter  90 value 77.946153
iter 100 value 77.152971
final  value 77.152971 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.044156 
iter  10 value 94.534803
iter  20 value 94.193509
iter  30 value 93.957618
iter  40 value 93.906910
iter  50 value 88.499748
iter  60 value 84.104268
iter  70 value 83.157721
iter  80 value 80.043759
iter  90 value 78.498619
iter 100 value 77.337941
final  value 77.337941 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 117.806927 
iter  10 value 94.460369
iter  20 value 92.598162
iter  30 value 90.736952
iter  40 value 90.017632
iter  50 value 82.218422
iter  60 value 79.701830
iter  70 value 77.401579
iter  80 value 76.155755
iter  90 value 75.786771
iter 100 value 75.365394
final  value 75.365394 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.875153 
iter  10 value 94.245168
iter  20 value 90.025111
iter  30 value 82.276057
iter  40 value 79.304329
iter  50 value 78.175266
iter  60 value 77.642493
iter  70 value 76.144408
iter  80 value 75.658430
iter  90 value 75.281683
iter 100 value 75.165341
final  value 75.165341 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 145.628100 
iter  10 value 95.699666
iter  20 value 95.027625
iter  30 value 86.061766
iter  40 value 82.432002
iter  50 value 81.127621
iter  60 value 80.809908
iter  70 value 78.735336
iter  80 value 77.230717
iter  90 value 75.821718
iter 100 value 75.428453
final  value 75.428453 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.414410 
iter  10 value 96.468552
iter  20 value 93.973819
iter  30 value 93.794168
iter  40 value 87.006956
iter  50 value 84.662787
iter  60 value 80.299008
iter  70 value 79.365838
iter  80 value 76.943233
iter  90 value 76.361474
iter 100 value 75.347581
final  value 75.347581 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.270672 
iter  10 value 94.509563
iter  20 value 87.215237
iter  30 value 85.026115
iter  40 value 84.625297
iter  50 value 84.108538
iter  60 value 80.740245
iter  70 value 79.341362
iter  80 value 76.612715
iter  90 value 75.830378
iter 100 value 75.517448
final  value 75.517448 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.060218 
iter  10 value 95.186290
iter  20 value 92.679946
iter  30 value 84.886333
iter  40 value 82.951639
iter  50 value 80.608216
iter  60 value 78.868958
iter  70 value 77.142199
iter  80 value 76.618283
iter  90 value 75.657598
iter 100 value 75.039735
final  value 75.039735 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 115.050360 
iter  10 value 94.102484
iter  20 value 88.299190
iter  30 value 87.215864
iter  40 value 84.981600
iter  50 value 84.582227
iter  60 value 84.445026
iter  70 value 81.295226
iter  80 value 80.198714
iter  90 value 77.936901
iter 100 value 77.196299
final  value 77.196299 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.151202 
final  value 94.485854 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.007860 
final  value 94.485718 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.013281 
iter  10 value 94.484888
final  value 94.484214 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.134264 
final  value 94.485890 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.068453 
final  value 94.485840 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.667857 
iter  10 value 94.489174
iter  20 value 94.368425
iter  30 value 84.677665
iter  40 value 84.669593
iter  50 value 84.626772
iter  60 value 81.826802
iter  70 value 81.806790
iter  80 value 81.798155
iter  90 value 81.797223
iter 100 value 78.014667
final  value 78.014667 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 96.684422 
iter  10 value 94.488214
iter  20 value 93.840206
iter  30 value 93.823066
iter  30 value 93.823066
iter  30 value 93.823066
final  value 93.823066 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.724664 
iter  10 value 92.460282
iter  20 value 83.525552
iter  30 value 83.508762
iter  40 value 83.508253
iter  50 value 82.186196
iter  60 value 81.353516
iter  70 value 81.339031
iter  80 value 81.320058
iter  90 value 81.319179
iter 100 value 81.318762
final  value 81.318762 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 118.054669 
iter  10 value 94.489260
iter  20 value 94.293547
iter  30 value 91.654657
iter  40 value 90.278357
iter  50 value 90.162713
iter  60 value 87.730911
iter  70 value 84.579920
iter  80 value 84.279321
iter  90 value 83.824818
iter 100 value 83.737286
final  value 83.737286 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 95.324345 
iter  10 value 94.489421
iter  20 value 94.478776
iter  30 value 88.517871
iter  40 value 87.340007
iter  50 value 87.323591
final  value 87.319671 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.528905 
iter  10 value 94.492805
iter  20 value 94.429004
iter  30 value 93.083587
iter  40 value 86.548634
iter  50 value 86.509610
iter  60 value 86.506680
iter  70 value 86.504707
iter  80 value 86.501096
iter  90 value 86.497227
iter 100 value 79.611355
final  value 79.611355 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 110.271423 
iter  10 value 90.847060
iter  20 value 82.048936
iter  30 value 81.277991
iter  40 value 80.192225
iter  50 value 78.801951
iter  60 value 78.796979
iter  70 value 78.787200
iter  80 value 77.403885
iter  90 value 75.855992
iter 100 value 75.650226
final  value 75.650226 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.927833 
iter  10 value 94.035612
iter  20 value 94.028466
iter  30 value 93.997277
iter  40 value 90.844009
iter  50 value 90.087609
final  value 90.080798 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.688652 
iter  10 value 94.055072
iter  20 value 86.017449
iter  30 value 85.027885
iter  40 value 85.006553
final  value 85.005015 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.954880 
iter  10 value 94.035610
iter  20 value 94.027658
iter  30 value 94.026992
final  value 94.026989 
converged
Fitting Repeat 1 

# weights:  507
initial  value 120.823944 
iter  10 value 117.898463
iter  20 value 117.466426
iter  30 value 105.449851
iter  40 value 102.438753
iter  50 value 102.349401
iter  60 value 102.344044
iter  70 value 102.343376
final  value 102.343176 
converged
Fitting Repeat 2 

# weights:  507
initial  value 118.050122 
iter  10 value 117.892175
iter  20 value 111.798228
iter  30 value 110.170212
iter  40 value 109.935513
iter  50 value 108.274092
iter  60 value 107.188515
iter  70 value 107.166942
iter  80 value 106.898719
iter  90 value 104.611860
iter 100 value 101.458546
final  value 101.458546 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 150.306428 
iter  10 value 117.602601
iter  20 value 117.596386
iter  30 value 117.591197
iter  40 value 117.523690
iter  50 value 117.511522
final  value 117.511509 
converged
Fitting Repeat 4 

# weights:  507
initial  value 122.550301 
iter  10 value 117.897382
iter  20 value 117.808812
iter  30 value 117.507326
iter  40 value 116.881363
iter  50 value 112.988816
iter  60 value 111.349137
iter  70 value 111.295864
iter  80 value 106.229898
iter  90 value 104.849332
iter 100 value 104.798713
final  value 104.798713 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 132.042300 
iter  10 value 117.897950
iter  20 value 117.882512
iter  30 value 117.133701
iter  40 value 116.845035
final  value 116.844264 
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 -- Tue Mar  3 20:23:35 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 
 20.179   0.512  72.989