##############################################################################
##############################################################################
###
### 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 version 4.6.0 alpha (2026-04-08 r89818)
* 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: 2026-04-21 00:17:01 UTC
* 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
corr_plot     17.238  0.123  17.480
var_imp       17.168  0.192  17.569
FSmethod      17.080  0.093  17.240
pred_ensembel  6.457  0.218   5.920
enrichfindP    0.211  0.037  15.393
* 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/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 version 4.6.0 alpha (2026-04-08 r89818)
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
avNNet
Loading required package: ggplot2
Loading required package: lattice
Fitting Repeat 1 

# weights:  103
initial  value 108.029869 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.278075 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.667910 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.907378 
final  value 94.038251 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.563352 
iter  10 value 88.198879
iter  20 value 87.577781
iter  30 value 87.305713
iter  40 value 87.299964
final  value 87.299945 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.791728 
final  value 94.052911 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.521922 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.754036 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.364670 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.033385 
final  value 93.482759 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.695185 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.373267 
iter  10 value 93.936263
iter  20 value 93.933346
final  value 93.933335 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.167587 
iter  10 value 89.772535
iter  20 value 83.521261
iter  30 value 82.976614
iter  40 value 82.882840
final  value 82.882838 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.891850 
iter  10 value 92.935734
iter  20 value 92.866141
iter  20 value 92.866141
iter  20 value 92.866141
final  value 92.866141 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.164719 
iter  10 value 92.224606
iter  20 value 91.782421
iter  30 value 91.741274
final  value 91.741245 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.733211 
iter  10 value 93.522585
iter  20 value 93.187932
iter  30 value 93.142806
iter  40 value 92.876964
iter  50 value 92.464115
iter  60 value 87.706250
iter  70 value 87.145202
iter  80 value 86.020478
iter  90 value 85.560707
iter 100 value 85.235529
final  value 85.235529 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 112.432280 
iter  10 value 94.051898
iter  20 value 93.150541
iter  30 value 86.534734
iter  40 value 85.135278
iter  50 value 84.650449
iter  60 value 84.109738
iter  70 value 83.255447
iter  80 value 82.141014
iter  90 value 81.837353
iter 100 value 81.832521
final  value 81.832521 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.575472 
iter  10 value 94.056692
iter  20 value 93.325245
iter  30 value 93.276786
iter  40 value 93.248369
iter  50 value 93.242767
iter  60 value 92.917396
iter  70 value 87.364090
iter  80 value 87.103023
iter  90 value 86.509902
iter 100 value 86.319389
final  value 86.319389 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.550789 
iter  10 value 93.816769
iter  20 value 93.319862
iter  30 value 93.141401
iter  40 value 87.527898
iter  50 value 84.981088
iter  60 value 84.366453
iter  70 value 84.021392
iter  80 value 82.693563
iter  90 value 82.379451
iter 100 value 82.377601
final  value 82.377601 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 101.364441 
iter  10 value 94.113867
iter  20 value 93.525236
iter  30 value 88.576590
iter  40 value 87.840302
iter  50 value 87.488541
iter  60 value 84.204238
iter  70 value 84.159058
iter  80 value 84.146268
final  value 84.146231 
converged
Fitting Repeat 1 

# weights:  305
initial  value 121.012773 
iter  10 value 93.382735
iter  20 value 86.188346
iter  30 value 84.786555
iter  40 value 84.530415
iter  50 value 83.187973
iter  60 value 82.827049
iter  70 value 81.660878
iter  80 value 80.977058
iter  90 value 80.642171
iter 100 value 80.510560
final  value 80.510560 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 113.349122 
iter  10 value 94.079139
iter  20 value 90.167008
iter  30 value 88.925727
iter  40 value 85.713409
iter  50 value 82.800858
iter  60 value 82.288663
iter  70 value 81.925278
iter  80 value 81.620418
iter  90 value 81.369273
iter 100 value 81.091083
final  value 81.091083 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.757343 
iter  10 value 93.888974
iter  20 value 88.507681
iter  30 value 85.021084
iter  40 value 83.946377
iter  50 value 83.725191
iter  60 value 83.622613
iter  70 value 82.324967
iter  80 value 80.987971
iter  90 value 80.633170
iter 100 value 80.536911
final  value 80.536911 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.076054 
iter  10 value 94.077046
iter  20 value 86.068798
iter  30 value 85.915046
iter  40 value 83.421368
iter  50 value 83.211229
iter  60 value 83.031105
iter  70 value 82.639982
iter  80 value 81.898087
iter  90 value 80.839663
iter 100 value 80.771195
final  value 80.771195 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.707926 
iter  10 value 93.314756
iter  20 value 85.411142
iter  30 value 83.722438
iter  40 value 81.268641
iter  50 value 81.067836
iter  60 value 80.716582
iter  70 value 80.628416
iter  80 value 80.456160
iter  90 value 80.288697
iter 100 value 80.229357
final  value 80.229357 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 118.654938 
iter  10 value 93.544177
iter  20 value 91.985000
iter  30 value 84.390355
iter  40 value 82.427040
iter  50 value 81.286608
iter  60 value 81.135323
iter  70 value 80.926358
iter  80 value 80.640448
iter  90 value 80.578064
iter 100 value 80.539904
final  value 80.539904 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 124.266309 
iter  10 value 95.714039
iter  20 value 93.706656
iter  30 value 93.401278
iter  40 value 93.086357
iter  50 value 92.986369
iter  60 value 87.189271
iter  70 value 83.518537
iter  80 value 82.625666
iter  90 value 81.778505
iter 100 value 81.175521
final  value 81.175521 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 122.877731 
iter  10 value 94.000811
iter  20 value 93.190292
iter  30 value 93.104973
iter  40 value 87.382742
iter  50 value 85.110292
iter  60 value 83.824868
iter  70 value 83.013292
iter  80 value 81.740926
iter  90 value 80.791463
iter 100 value 80.652576
final  value 80.652576 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.939912 
iter  10 value 95.154882
iter  20 value 85.899046
iter  30 value 85.322198
iter  40 value 85.027777
iter  50 value 84.152348
iter  60 value 83.345503
iter  70 value 82.419737
iter  80 value 80.998116
iter  90 value 80.718544
iter 100 value 80.633503
final  value 80.633503 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 119.086907 
iter  10 value 94.185444
iter  20 value 90.777194
iter  30 value 86.458882
iter  40 value 85.414863
iter  50 value 84.087852
iter  60 value 83.749948
iter  70 value 83.680013
iter  80 value 83.174775
iter  90 value 83.053056
iter 100 value 82.542529
final  value 82.542529 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.644874 
iter  10 value 92.935250
final  value 92.935246 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.559414 
final  value 94.054444 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.147944 
iter  10 value 94.054805
iter  20 value 94.052966
iter  30 value 93.739021
final  value 93.421841 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.491910 
final  value 94.054400 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.589947 
final  value 94.054526 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.305402 
iter  10 value 94.003568
iter  20 value 94.000397
iter  30 value 93.999460
iter  40 value 93.996494
iter  50 value 93.995794
iter  50 value 93.995794
iter  50 value 93.995794
final  value 93.995794 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.790839 
iter  10 value 94.055240
iter  20 value 94.050377
iter  30 value 88.202855
iter  40 value 87.962993
iter  50 value 87.961276
iter  60 value 87.959242
iter  70 value 87.956871
iter  80 value 87.953955
iter  90 value 87.950386
iter 100 value 87.945735
final  value 87.945735 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 94.684961 
iter  10 value 94.058197
iter  20 value 94.053547
iter  30 value 93.971503
iter  40 value 90.234273
iter  50 value 83.821985
iter  60 value 83.747006
iter  70 value 83.745277
iter  80 value 82.803518
iter  90 value 82.391002
iter  90 value 82.391002
iter  90 value 82.391002
final  value 82.391002 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.830379 
iter  10 value 94.057287
iter  20 value 94.052952
iter  30 value 86.832812
iter  40 value 85.942200
iter  50 value 85.930869
iter  60 value 85.929728
iter  70 value 85.928532
iter  80 value 84.567340
final  value 84.452446 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.024268 
iter  10 value 94.000552
iter  20 value 93.996372
iter  30 value 92.127603
iter  40 value 88.184997
iter  50 value 84.277745
iter  60 value 84.220827
iter  70 value 84.077126
iter  80 value 83.745805
iter  90 value 83.730126
iter 100 value 83.173774
final  value 83.173774 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 96.198770 
iter  10 value 94.046659
iter  20 value 94.040325
iter  30 value 92.283818
iter  40 value 87.405234
iter  50 value 84.113187
iter  60 value 83.770491
iter  70 value 83.259385
iter  80 value 81.680718
iter  90 value 81.117473
iter 100 value 81.098967
final  value 81.098967 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 134.623558 
iter  10 value 94.061244
iter  20 value 94.053680
iter  30 value 93.977475
iter  40 value 93.327272
final  value 93.327089 
converged
Fitting Repeat 3 

# weights:  507
initial  value 93.986606 
iter  10 value 88.592140
iter  20 value 86.140093
iter  30 value 85.330658
iter  40 value 85.056500
iter  50 value 85.044977
iter  60 value 85.029730
iter  70 value 85.027553
iter  80 value 84.604031
iter  90 value 84.584618
iter 100 value 84.584446
final  value 84.584446 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.055271 
iter  10 value 94.059031
iter  20 value 93.868955
iter  30 value 88.857867
iter  40 value 85.750268
iter  50 value 85.191716
iter  60 value 85.191021
iter  70 value 85.190332
iter  80 value 84.480159
iter  90 value 84.261776
iter 100 value 82.902852
final  value 82.902852 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 97.687663 
iter  10 value 94.045152
iter  20 value 88.407327
iter  30 value 86.346189
final  value 86.346146 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.397939 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.561040 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.647834 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.481656 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.950538 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.461349 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.693504 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.122761 
final  value 93.915746 
converged
Fitting Repeat 4 

# weights:  305
initial  value 113.319180 
final  value 94.052911 
converged
Fitting Repeat 5 

# weights:  305
initial  value 113.601718 
final  value 93.915746 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.695040 
final  value 93.900000 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.825537 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 111.771298 
iter  10 value 93.915746
iter  10 value 93.915746
iter  10 value 93.915746
final  value 93.915746 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.743045 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.024405 
iter  10 value 94.052912
iter  10 value 94.052911
iter  10 value 94.052911
final  value 94.052911 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.271088 
iter  10 value 93.496492
iter  20 value 88.507641
iter  30 value 85.600471
iter  40 value 84.504363
iter  50 value 83.383080
iter  60 value 82.968196
iter  70 value 82.937028
iter  80 value 81.126549
iter  90 value 80.343574
iter 100 value 80.275113
final  value 80.275113 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 98.736691 
iter  10 value 94.655282
iter  20 value 94.014754
iter  30 value 92.356035
iter  40 value 84.703903
iter  50 value 84.180968
iter  60 value 83.649242
iter  70 value 82.833041
iter  80 value 82.666507
iter  90 value 82.367541
iter 100 value 82.297580
final  value 82.297580 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 99.446967 
iter  10 value 94.056599
iter  20 value 91.687612
iter  30 value 91.091469
iter  40 value 88.790166
iter  50 value 88.262786
iter  60 value 87.565103
iter  70 value 84.000102
iter  80 value 83.015194
iter  90 value 82.960956
iter 100 value 82.946508
final  value 82.946508 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.275705 
iter  10 value 94.056214
iter  20 value 93.829920
iter  30 value 93.744098
iter  40 value 93.738347
iter  50 value 86.388359
iter  60 value 84.248842
iter  70 value 84.080862
iter  80 value 83.584349
iter  90 value 82.969098
iter 100 value 82.550019
final  value 82.550019 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.689613 
iter  10 value 94.057565
iter  20 value 93.970637
iter  30 value 93.947159
iter  40 value 93.565012
iter  50 value 85.785626
iter  60 value 85.186813
iter  70 value 84.258806
iter  80 value 83.554223
iter  90 value 83.131836
iter 100 value 82.967446
final  value 82.967446 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 103.893134 
iter  10 value 94.064609
iter  20 value 93.312918
iter  30 value 90.882640
iter  40 value 89.252431
iter  50 value 83.202485
iter  60 value 82.654078
iter  70 value 82.023191
iter  80 value 80.661202
iter  90 value 79.761374
iter 100 value 79.475093
final  value 79.475093 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.353672 
iter  10 value 93.148523
iter  20 value 86.575628
iter  30 value 83.733698
iter  40 value 83.598328
iter  50 value 82.133836
iter  60 value 80.848666
iter  70 value 80.687365
iter  80 value 80.568743
iter  90 value 80.477547
iter 100 value 80.269937
final  value 80.269937 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.591518 
iter  10 value 89.841571
iter  20 value 84.799574
iter  30 value 84.379535
iter  40 value 83.297440
iter  50 value 82.964859
iter  60 value 82.940458
iter  70 value 82.552279
iter  80 value 80.319787
iter  90 value 79.967706
iter 100 value 79.437274
final  value 79.437274 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 119.934353 
iter  10 value 94.391984
iter  20 value 92.078910
iter  30 value 91.218540
iter  40 value 86.955601
iter  50 value 85.672361
iter  60 value 84.974848
iter  70 value 83.777374
iter  80 value 82.188629
iter  90 value 81.636480
iter 100 value 81.125542
final  value 81.125542 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.154079 
iter  10 value 94.048159
iter  20 value 86.306339
iter  30 value 84.904183
iter  40 value 81.329011
iter  50 value 80.383224
iter  60 value 79.791552
iter  70 value 79.377618
iter  80 value 79.008382
iter  90 value 78.865953
iter 100 value 78.771357
final  value 78.771357 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.262236 
iter  10 value 91.811047
iter  20 value 84.022523
iter  30 value 82.414348
iter  40 value 81.797168
iter  50 value 80.980008
iter  60 value 80.079827
iter  70 value 79.981993
iter  80 value 79.824924
iter  90 value 79.322659
iter 100 value 79.009644
final  value 79.009644 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.958478 
iter  10 value 94.567665
iter  20 value 87.636121
iter  30 value 84.324664
iter  40 value 81.529899
iter  50 value 80.449020
iter  60 value 79.920592
iter  70 value 78.948174
iter  80 value 78.716305
iter  90 value 78.667231
iter 100 value 78.559102
final  value 78.559102 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.494342 
iter  10 value 94.319103
iter  20 value 92.054521
iter  30 value 83.307517
iter  40 value 81.528271
iter  50 value 80.341022
iter  60 value 79.839453
iter  70 value 79.535523
iter  80 value 79.447223
iter  90 value 79.367024
iter 100 value 79.132889
final  value 79.132889 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.590742 
iter  10 value 93.988700
iter  20 value 92.788326
iter  30 value 85.093275
iter  40 value 84.613944
iter  50 value 83.926896
iter  60 value 82.855543
iter  70 value 80.951768
iter  80 value 80.451957
iter  90 value 79.460928
iter 100 value 79.083559
final  value 79.083559 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 116.495222 
iter  10 value 101.315652
iter  20 value 89.205567
iter  30 value 85.539647
iter  40 value 82.995848
iter  50 value 82.723662
iter  60 value 81.461193
iter  70 value 80.305818
iter  80 value 79.534997
iter  90 value 79.405936
iter 100 value 79.226764
final  value 79.226764 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.018896 
final  value 94.054686 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.243505 
final  value 94.054412 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.158667 
final  value 94.054594 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.361025 
final  value 94.054227 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.275217 
final  value 94.054484 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.437437 
iter  10 value 94.056109
iter  20 value 92.241201
final  value 91.227566 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.234047 
iter  10 value 92.946002
iter  20 value 92.202222
iter  30 value 92.195106
iter  40 value 85.790080
iter  50 value 84.107412
iter  60 value 83.773818
iter  70 value 83.567741
iter  80 value 83.564626
iter  90 value 83.555411
iter 100 value 80.407023
final  value 80.407023 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.176303 
iter  10 value 94.057210
iter  20 value 94.056968
iter  30 value 94.053817
final  value 94.053340 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.158871 
iter  10 value 89.193252
iter  20 value 88.363735
iter  30 value 88.361305
iter  40 value 88.355056
iter  50 value 86.937720
iter  60 value 86.904060
iter  70 value 82.623382
iter  80 value 82.051616
final  value 82.051613 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.815117 
iter  10 value 94.057489
iter  20 value 94.052933
iter  30 value 92.100389
iter  40 value 89.455548
iter  40 value 89.455548
iter  40 value 89.455548
final  value 89.455548 
converged
Fitting Repeat 1 

# weights:  507
initial  value 111.233940 
iter  10 value 93.923644
iter  20 value 93.916756
iter  30 value 93.716884
iter  40 value 93.693282
iter  50 value 93.179566
iter  60 value 87.317996
iter  70 value 86.990736
iter  80 value 86.677815
iter  90 value 86.581500
iter 100 value 86.546032
final  value 86.546032 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.601622 
iter  10 value 93.776884
iter  20 value 91.537594
iter  30 value 91.287429
iter  40 value 91.180904
iter  50 value 91.069351
iter  60 value 90.175983
final  value 90.133145 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.525703 
iter  10 value 93.923717
iter  20 value 93.809338
iter  30 value 82.097801
iter  40 value 80.545562
iter  50 value 80.520890
iter  60 value 80.509735
iter  70 value 80.508410
iter  80 value 80.420250
iter  90 value 80.412711
iter 100 value 80.407028
final  value 80.407028 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 99.233989 
iter  10 value 94.060900
iter  20 value 94.043392
iter  30 value 93.444679
iter  40 value 86.958221
iter  50 value 83.043477
iter  60 value 81.751992
iter  70 value 79.718738
iter  80 value 77.877129
iter  90 value 77.465411
iter 100 value 77.448839
final  value 77.448839 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 123.687156 
iter  10 value 93.923975
iter  20 value 93.916101
iter  30 value 93.023296
iter  40 value 86.199974
iter  50 value 84.848985
iter  60 value 82.388347
iter  70 value 80.112032
iter  80 value 79.896748
iter  90 value 79.787911
iter 100 value 79.766179
final  value 79.766179 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.638372 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.126381 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.616480 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.868453 
final  value 94.449438 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.021849 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.244813 
iter  10 value 93.394958
final  value 93.394928 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.539652 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.695897 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.796715 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 116.111969 
iter  10 value 93.376008
final  value 93.375969 
converged
Fitting Repeat 1 

# weights:  507
initial  value 111.813624 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.317409 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.444973 
iter  10 value 93.742596
iter  20 value 91.441725
iter  30 value 91.207563
iter  40 value 90.548046
iter  50 value 90.345525
iter  60 value 90.309613
iter  70 value 89.147455
iter  80 value 89.062586
iter  90 value 89.056727
iter 100 value 89.056615
final  value 89.056615 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 93.681587 
iter  10 value 86.141172
iter  20 value 84.435171
iter  30 value 83.896005
iter  40 value 83.894773
final  value 83.894595 
converged
Fitting Repeat 5 

# weights:  507
initial  value 109.623882 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.241393 
iter  10 value 94.449841
iter  20 value 88.203587
iter  30 value 87.837152
iter  40 value 85.548190
iter  50 value 85.276310
iter  60 value 85.176650
final  value 85.176542 
converged
Fitting Repeat 2 

# weights:  103
initial  value 116.562174 
iter  10 value 94.446368
iter  20 value 93.809612
iter  30 value 93.609705
iter  40 value 86.087065
iter  50 value 84.187786
iter  60 value 82.771641
iter  70 value 81.904357
iter  80 value 81.648812
final  value 81.643003 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.076356 
iter  10 value 94.522753
iter  20 value 93.710088
iter  30 value 93.400575
iter  40 value 91.340366
iter  50 value 86.972015
iter  60 value 85.092175
iter  70 value 83.194958
iter  80 value 82.848088
iter  90 value 82.666913
iter 100 value 82.390696
final  value 82.390696 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.235296 
iter  10 value 94.494272
iter  20 value 94.315275
iter  30 value 91.729346
iter  40 value 86.245914
iter  50 value 83.292873
iter  60 value 83.096026
iter  70 value 82.077762
iter  80 value 81.881543
iter  90 value 81.643362
final  value 81.643003 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.211968 
iter  10 value 93.660330
iter  20 value 86.208853
iter  30 value 85.537623
iter  40 value 83.801581
iter  50 value 82.711428
iter  60 value 82.255759
iter  70 value 81.964869
iter  80 value 81.646615
final  value 81.643004 
converged
Fitting Repeat 1 

# weights:  305
initial  value 123.380194 
iter  10 value 94.341354
iter  20 value 89.811814
iter  30 value 86.340773
iter  40 value 83.769812
iter  50 value 82.768484
iter  60 value 81.874867
iter  70 value 81.439187
iter  80 value 81.168669
iter  90 value 81.018581
iter 100 value 80.992778
final  value 80.992778 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.144883 
iter  10 value 94.486381
iter  20 value 94.419518
iter  30 value 93.771287
iter  40 value 92.304164
iter  50 value 88.589780
iter  60 value 87.884960
iter  70 value 85.705122
iter  80 value 85.425775
iter  90 value 84.947772
iter 100 value 81.602227
final  value 81.602227 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.870189 
iter  10 value 93.475362
iter  20 value 86.761774
iter  30 value 85.995803
iter  40 value 84.990561
iter  50 value 83.335876
iter  60 value 81.044282
iter  70 value 80.285724
iter  80 value 80.176168
iter  90 value 79.934550
iter 100 value 79.870269
final  value 79.870269 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.624886 
iter  10 value 94.395481
iter  20 value 93.467163
iter  30 value 89.946846
iter  40 value 89.372127
iter  50 value 84.320822
iter  60 value 82.573993
iter  70 value 82.122788
iter  80 value 81.468621
iter  90 value 81.065390
iter 100 value 80.484354
final  value 80.484354 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 138.465334 
iter  10 value 94.019830
iter  20 value 93.767994
iter  30 value 89.134643
iter  40 value 88.426197
iter  50 value 83.535675
iter  60 value 81.611307
iter  70 value 81.086244
iter  80 value 80.683241
iter  90 value 80.470733
iter 100 value 80.319285
final  value 80.319285 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.788327 
iter  10 value 94.585211
iter  20 value 89.264041
iter  30 value 85.698238
iter  40 value 85.034267
iter  50 value 83.463460
iter  60 value 82.224475
iter  70 value 81.654512
iter  80 value 80.925180
iter  90 value 80.153627
iter 100 value 79.885769
final  value 79.885769 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.621799 
iter  10 value 96.347939
iter  20 value 91.741665
iter  30 value 86.861382
iter  40 value 84.943668
iter  50 value 84.519637
iter  60 value 82.654835
iter  70 value 82.141433
iter  80 value 81.739651
iter  90 value 81.465830
iter 100 value 81.092238
final  value 81.092238 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.779514 
iter  10 value 93.952557
iter  20 value 92.106997
iter  30 value 88.689766
iter  40 value 88.092279
iter  50 value 86.800989
iter  60 value 83.298673
iter  70 value 81.623180
iter  80 value 81.290258
iter  90 value 81.039295
iter 100 value 80.851403
final  value 80.851403 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.727961 
iter  10 value 95.121496
iter  20 value 92.816060
iter  30 value 86.230630
iter  40 value 84.646988
iter  50 value 83.583895
iter  60 value 82.872058
iter  70 value 82.169555
iter  80 value 81.089907
iter  90 value 80.415388
iter 100 value 80.104899
final  value 80.104899 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.572688 
iter  10 value 98.020607
iter  20 value 91.333453
iter  30 value 84.237590
iter  40 value 82.754874
iter  50 value 82.239435
iter  60 value 81.720754
iter  70 value 81.592449
iter  80 value 81.436648
iter  90 value 81.402298
iter 100 value 81.345788
final  value 81.345788 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.556554 
final  value 94.485920 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.409092 
final  value 94.450780 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.875048 
final  value 94.485597 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.347213 
final  value 94.485851 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.088771 
final  value 94.485956 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.247661 
iter  10 value 93.403417
iter  20 value 93.400025
iter  30 value 93.395473
iter  40 value 91.901417
iter  50 value 90.000640
iter  60 value 89.939364
iter  70 value 88.943097
iter  80 value 88.671317
iter  90 value 88.668027
iter 100 value 88.070609
final  value 88.070609 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 95.536460 
iter  10 value 93.255309
iter  20 value 86.667994
iter  30 value 86.630060
iter  40 value 86.629640
iter  50 value 86.628876
iter  60 value 86.211463
iter  70 value 84.117282
iter  80 value 84.085928
iter  90 value 84.081799
final  value 84.081670 
converged
Fitting Repeat 3 

# weights:  305
initial  value 118.185971 
iter  10 value 94.489383
iter  20 value 94.484673
iter  30 value 93.400743
iter  40 value 93.396317
final  value 93.395789 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.085361 
iter  10 value 92.309595
iter  20 value 92.308958
iter  30 value 92.304558
iter  40 value 89.203106
iter  50 value 86.828482
iter  60 value 86.735796
final  value 86.734953 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.029034 
iter  10 value 90.959221
iter  20 value 90.584336
iter  30 value 90.574877
final  value 90.574794 
converged
Fitting Repeat 1 

# weights:  507
initial  value 114.264498 
iter  10 value 94.493282
iter  20 value 94.401564
iter  30 value 93.290938
iter  40 value 93.158810
iter  50 value 93.124780
iter  60 value 86.781392
iter  70 value 86.503133
final  value 86.502756 
converged
Fitting Repeat 2 

# weights:  507
initial  value 112.478537 
iter  10 value 94.492349
iter  20 value 94.483784
iter  30 value 90.251780
iter  40 value 90.124563
iter  50 value 86.935420
iter  60 value 83.340824
iter  70 value 82.974016
iter  80 value 82.266160
iter  90 value 81.780010
iter 100 value 81.772706
final  value 81.772706 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 96.342617 
iter  10 value 94.492371
iter  20 value 93.139904
iter  30 value 90.728460
iter  40 value 88.852110
iter  50 value 87.507713
iter  60 value 86.382687
iter  70 value 85.980871
iter  80 value 85.980684
iter  90 value 85.980319
iter 100 value 85.979784
final  value 85.979784 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 121.338535 
iter  10 value 94.493605
iter  20 value 93.765120
iter  30 value 90.364986
iter  40 value 90.348165
iter  50 value 90.345155
iter  60 value 90.342655
iter  70 value 90.151510
final  value 90.150510 
converged
Fitting Repeat 5 

# weights:  507
initial  value 126.752359 
iter  10 value 93.384506
iter  20 value 93.379372
iter  30 value 93.277771
iter  40 value 87.723534
iter  50 value 87.585890
iter  60 value 87.582622
final  value 87.582604 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.603893 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.820642 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.037718 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.408443 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.306348 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.766552 
final  value 93.701657 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.887748 
final  value 94.484212 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.851105 
iter  10 value 94.484196
iter  20 value 94.476311
final  value 94.473118 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.071428 
iter  10 value 93.110350
final  value 93.109890 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.092667 
iter  10 value 94.138444
iter  20 value 93.747397
final  value 93.683616 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.915485 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.254829 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 123.725913 
iter  10 value 94.473070
iter  20 value 93.837674
iter  30 value 93.830455
final  value 93.830390 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.533131 
iter  10 value 88.801019
iter  20 value 83.964008
iter  30 value 81.679593
iter  40 value 81.479142
iter  50 value 81.475646
final  value 81.475568 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.373584 
final  value 94.473118 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.141972 
iter  10 value 94.278261
iter  20 value 84.337037
iter  30 value 83.307152
iter  40 value 82.514205
iter  50 value 81.572128
iter  60 value 81.131137
iter  70 value 80.976009
final  value 80.976000 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.394719 
iter  10 value 94.259608
iter  20 value 86.222573
iter  30 value 83.104149
iter  40 value 82.446055
iter  50 value 82.012045
iter  60 value 81.588680
iter  70 value 81.437499
iter  80 value 81.405227
iter  90 value 81.103007
iter 100 value 80.976042
final  value 80.976042 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.271398 
iter  10 value 94.477944
iter  20 value 91.661112
iter  30 value 91.335230
iter  40 value 87.334170
iter  50 value 82.162804
iter  60 value 81.310428
iter  70 value 80.934773
iter  80 value 80.809203
iter  90 value 80.682679
iter 100 value 80.448817
final  value 80.448817 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 102.282125 
iter  10 value 94.511878
iter  20 value 93.556607
iter  30 value 86.064720
iter  40 value 84.212730
iter  50 value 82.681296
iter  60 value 81.348689
iter  70 value 79.942217
iter  80 value 79.735595
iter  90 value 78.704951
iter 100 value 77.709488
final  value 77.709488 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 98.681630 
iter  10 value 94.481404
iter  20 value 93.903313
iter  30 value 93.867063
iter  40 value 85.337079
iter  50 value 82.201162
iter  60 value 82.162024
iter  70 value 81.847545
iter  80 value 81.602267
iter  90 value 81.181605
iter 100 value 81.109273
final  value 81.109273 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 105.086206 
iter  10 value 96.502914
iter  20 value 91.567478
iter  30 value 90.977259
iter  40 value 86.318808
iter  50 value 80.837320
iter  60 value 78.656004
iter  70 value 78.354732
iter  80 value 77.731130
iter  90 value 77.608048
iter 100 value 77.279497
final  value 77.279497 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 113.418042 
iter  10 value 92.912128
iter  20 value 85.896715
iter  30 value 82.420106
iter  40 value 81.831528
iter  50 value 81.278798
iter  60 value 80.809435
iter  70 value 80.673036
iter  80 value 80.355885
iter  90 value 78.641315
iter 100 value 77.301205
final  value 77.301205 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.909483 
iter  10 value 94.464040
iter  20 value 93.723753
iter  30 value 88.519627
iter  40 value 85.417638
iter  50 value 80.757826
iter  60 value 80.498718
iter  70 value 78.901643
iter  80 value 78.432682
iter  90 value 78.263257
iter 100 value 77.956474
final  value 77.956474 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.525492 
iter  10 value 89.397362
iter  20 value 84.068079
iter  30 value 83.729472
iter  40 value 79.514978
iter  50 value 78.649530
iter  60 value 78.103098
iter  70 value 77.626476
iter  80 value 77.090657
iter  90 value 76.949481
iter 100 value 76.761832
final  value 76.761832 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.329084 
iter  10 value 94.962160
iter  20 value 94.571866
iter  30 value 94.453373
iter  40 value 86.847564
iter  50 value 83.259268
iter  60 value 82.404643
iter  70 value 81.220703
iter  80 value 80.697642
iter  90 value 80.612205
iter 100 value 80.284920
final  value 80.284920 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.674320 
iter  10 value 94.984084
iter  20 value 93.493067
iter  30 value 88.051541
iter  40 value 83.329471
iter  50 value 81.824105
iter  60 value 79.677151
iter  70 value 78.838688
iter  80 value 77.695784
iter  90 value 77.135758
iter 100 value 76.841667
final  value 76.841667 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.723899 
iter  10 value 95.004671
iter  20 value 92.520925
iter  30 value 86.322367
iter  40 value 82.326008
iter  50 value 80.394154
iter  60 value 78.494468
iter  70 value 78.124000
iter  80 value 77.862526
iter  90 value 77.760337
iter 100 value 77.632086
final  value 77.632086 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 127.149707 
iter  10 value 92.905177
iter  20 value 84.891173
iter  30 value 82.567996
iter  40 value 81.871269
iter  50 value 78.850776
iter  60 value 77.867854
iter  70 value 76.950358
iter  80 value 76.646934
iter  90 value 76.498823
iter 100 value 76.315790
final  value 76.315790 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 116.375379 
iter  10 value 88.043274
iter  20 value 86.288998
iter  30 value 83.173295
iter  40 value 82.925761
iter  50 value 80.723487
iter  60 value 79.637139
iter  70 value 78.616732
iter  80 value 78.532888
iter  90 value 78.485556
iter 100 value 78.320048
final  value 78.320048 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 114.964886 
iter  10 value 94.533377
iter  20 value 88.441265
iter  30 value 87.181319
iter  40 value 81.533151
iter  50 value 80.207162
iter  60 value 78.946517
iter  70 value 78.491982
iter  80 value 77.240989
iter  90 value 77.124443
iter 100 value 76.996023
final  value 76.996023 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.630637 
final  value 94.485786 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.678016 
final  value 94.485642 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.488158 
final  value 93.703348 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.761176 
final  value 94.486596 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.123977 
final  value 94.486071 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.776586 
iter  10 value 92.047235
iter  20 value 86.741544
iter  30 value 82.666721
iter  40 value 80.420336
iter  50 value 80.264543
iter  60 value 79.968438
iter  70 value 79.965361
iter  80 value 79.963542
final  value 79.957554 
converged
Fitting Repeat 2 

# weights:  305
initial  value 117.452181 
iter  10 value 94.510851
iter  20 value 94.486293
iter  30 value 93.851832
iter  40 value 92.529769
final  value 92.529594 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.703445 
iter  10 value 94.493050
iter  20 value 94.466702
iter  30 value 84.538963
iter  40 value 84.534996
iter  50 value 84.289530
final  value 84.289526 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.859008 
iter  10 value 94.488288
iter  20 value 94.411517
iter  30 value 81.193523
iter  40 value 81.189304
iter  50 value 80.416751
iter  60 value 79.628206
iter  70 value 79.422556
iter  80 value 79.339606
iter  90 value 79.338722
iter 100 value 79.336088
final  value 79.336088 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.177435 
iter  10 value 94.488884
iter  20 value 94.483876
iter  30 value 93.356957
iter  40 value 84.886786
iter  50 value 78.133983
iter  60 value 76.856188
iter  70 value 76.097426
iter  80 value 76.091616
iter  90 value 75.804641
iter 100 value 75.527205
final  value 75.527205 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.548647 
iter  10 value 94.495220
iter  20 value 94.475299
iter  30 value 94.474313
iter  40 value 94.473996
iter  50 value 94.334227
iter  60 value 82.601175
iter  70 value 81.119941
iter  80 value 80.928724
final  value 80.928701 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.803272 
iter  10 value 94.492032
iter  20 value 94.442539
iter  30 value 86.052347
iter  40 value 84.143513
iter  50 value 81.486538
iter  60 value 79.832469
iter  70 value 79.672743
final  value 79.672587 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.202994 
iter  10 value 94.491810
iter  20 value 82.957450
iter  30 value 82.595987
iter  40 value 81.107985
iter  50 value 81.106022
iter  60 value 81.103782
iter  60 value 81.103781
final  value 81.103781 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.823800 
iter  10 value 93.798292
iter  20 value 91.834676
iter  30 value 91.760762
iter  40 value 91.648899
iter  50 value 91.646614
iter  60 value 89.088945
iter  70 value 85.658661
iter  80 value 84.048233
iter  90 value 82.411865
iter 100 value 81.753675
final  value 81.753675 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 99.827699 
iter  10 value 94.492686
iter  20 value 94.478270
iter  30 value 89.573052
iter  40 value 87.899433
final  value 87.897886 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.586325 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.055951 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.785994 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.823376 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.822451 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.117814 
iter  10 value 93.809500
iter  20 value 93.429410
iter  30 value 92.999800
iter  40 value 92.987208
final  value 92.986147 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.676709 
final  value 94.052434 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.262448 
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  305
initial  value 114.137524 
final  value 94.354396 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.379945 
iter  10 value 93.136300
iter  20 value 93.135239
final  value 93.135238 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.535364 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 112.394616 
final  value 94.354396 
converged
Fitting Repeat 3 

# weights:  507
initial  value 129.515273 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 130.518168 
iter  10 value 94.354397
final  value 94.354396 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.369896 
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.604527 
iter  10 value 94.489811
iter  20 value 94.480535
iter  30 value 94.209836
iter  40 value 94.128535
iter  50 value 88.150514
iter  60 value 87.903699
iter  70 value 87.133959
iter  80 value 86.570664
iter  90 value 86.320221
iter 100 value 86.317622
final  value 86.317622 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.396197 
iter  10 value 94.489028
iter  20 value 94.338046
iter  30 value 94.182020
iter  40 value 94.109127
iter  50 value 93.687255
iter  60 value 88.469237
iter  70 value 87.245529
iter  80 value 86.668080
iter  90 value 86.590623
iter 100 value 85.328503
final  value 85.328503 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 105.467820 
iter  10 value 94.528902
iter  20 value 94.488514
iter  30 value 94.425220
iter  40 value 89.252311
iter  50 value 88.401876
iter  60 value 87.392831
iter  70 value 86.866797
iter  80 value 86.725537
iter  90 value 86.661505
iter 100 value 86.651471
final  value 86.651471 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 103.403574 
iter  10 value 92.695085
iter  20 value 87.406473
iter  30 value 86.606516
iter  40 value 86.469921
final  value 86.466615 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.751790 
iter  10 value 94.381880
iter  20 value 93.067712
iter  30 value 92.871419
iter  40 value 92.568139
iter  50 value 87.602834
iter  60 value 87.392188
iter  70 value 87.268345
iter  80 value 87.015153
iter  90 value 86.986169
iter 100 value 86.979494
final  value 86.979494 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 115.604205 
iter  10 value 94.344627
iter  20 value 93.820697
iter  30 value 90.020933
iter  40 value 89.088653
iter  50 value 88.516397
iter  60 value 88.312282
iter  70 value 87.973383
iter  80 value 85.113943
iter  90 value 84.620518
iter 100 value 83.960831
final  value 83.960831 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.142473 
iter  10 value 94.417274
iter  20 value 91.876843
iter  30 value 89.558617
iter  40 value 85.319023
iter  50 value 84.761358
iter  60 value 84.178350
iter  70 value 83.795563
iter  80 value 83.421835
iter  90 value 83.227338
iter 100 value 83.192285
final  value 83.192285 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 116.908438 
iter  10 value 94.443523
iter  20 value 92.625104
iter  30 value 87.750921
iter  40 value 85.143800
iter  50 value 84.705662
iter  60 value 84.599882
iter  70 value 84.397784
iter  80 value 84.108130
iter  90 value 83.910047
iter 100 value 83.685150
final  value 83.685150 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 118.245018 
iter  10 value 94.074785
iter  20 value 92.844688
iter  30 value 89.194606
iter  40 value 87.858982
iter  50 value 86.192988
iter  60 value 85.006698
iter  70 value 84.805724
iter  80 value 84.594573
iter  90 value 84.538492
iter 100 value 84.408078
final  value 84.408078 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.561354 
iter  10 value 95.683685
iter  20 value 93.638823
iter  30 value 93.479599
iter  40 value 93.324023
iter  50 value 87.975563
iter  60 value 87.579792
iter  70 value 86.831777
iter  80 value 86.642328
iter  90 value 86.552535
iter 100 value 86.334757
final  value 86.334757 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 122.433645 
iter  10 value 94.095519
iter  20 value 88.473216
iter  30 value 87.322891
iter  40 value 87.183287
iter  50 value 86.599150
iter  60 value 84.203274
iter  70 value 83.924298
iter  80 value 83.867250
iter  90 value 83.795062
iter 100 value 83.710354
final  value 83.710354 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.435443 
iter  10 value 94.512665
iter  20 value 90.215111
iter  30 value 89.310467
iter  40 value 88.198248
iter  50 value 87.120008
iter  60 value 86.761225
iter  70 value 86.683166
iter  80 value 86.624367
iter  90 value 85.881953
iter 100 value 84.091725
final  value 84.091725 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.809512 
iter  10 value 96.880219
iter  20 value 88.801343
iter  30 value 86.510783
iter  40 value 86.128531
iter  50 value 84.715605
iter  60 value 83.698147
iter  70 value 83.355669
iter  80 value 83.245029
iter  90 value 83.102616
iter 100 value 83.043238
final  value 83.043238 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.759437 
iter  10 value 92.959406
iter  20 value 89.058377
iter  30 value 87.381421
iter  40 value 86.901058
iter  50 value 86.814522
iter  60 value 86.741237
iter  70 value 85.521362
iter  80 value 84.342706
iter  90 value 84.173595
iter 100 value 84.020855
final  value 84.020855 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.774439 
iter  10 value 94.345873
iter  20 value 87.955765
iter  30 value 87.602465
iter  40 value 86.393510
iter  50 value 85.448939
iter  60 value 84.927580
iter  70 value 84.136449
iter  80 value 84.047135
iter  90 value 84.012573
iter 100 value 83.978873
final  value 83.978873 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.972955 
iter  10 value 94.474718
final  value 94.356005 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.398127 
final  value 94.485736 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.862986 
final  value 94.485720 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.548999 
iter  10 value 94.485819
iter  20 value 94.484214
iter  30 value 87.705118
iter  40 value 87.358738
iter  40 value 87.358738
iter  40 value 87.358738
final  value 87.358738 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.560513 
final  value 94.485923 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.009066 
iter  10 value 94.359208
iter  20 value 94.356842
iter  30 value 93.304907
iter  40 value 87.540356
iter  50 value 86.781526
iter  60 value 86.499345
iter  70 value 86.448584
iter  80 value 86.446537
iter  90 value 86.446004
iter 100 value 86.445102
final  value 86.445102 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.141027 
iter  10 value 94.489593
iter  20 value 94.357807
iter  30 value 94.069829
final  value 94.052790 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.298863 
iter  10 value 94.359071
iter  20 value 94.354589
final  value 94.354472 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.010569 
iter  10 value 94.359592
iter  20 value 94.355241
iter  30 value 88.723958
final  value 87.034544 
converged
Fitting Repeat 5 

# weights:  305
initial  value 120.432627 
iter  10 value 94.485959
iter  20 value 94.378297
iter  30 value 91.720449
iter  40 value 91.383070
iter  50 value 86.593329
iter  60 value 83.432640
iter  70 value 83.241692
iter  80 value 83.168039
iter  90 value 83.113382
final  value 83.111902 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.430365 
iter  10 value 94.492814
iter  20 value 94.481015
iter  30 value 93.870484
iter  40 value 88.216552
iter  50 value 88.009680
iter  60 value 86.008575
iter  70 value 85.632822
iter  80 value 85.121205
iter  90 value 85.105152
final  value 85.104634 
converged
Fitting Repeat 2 

# weights:  507
initial  value 124.391341 
iter  10 value 94.434596
iter  20 value 90.314640
iter  30 value 87.336832
iter  40 value 85.955062
iter  50 value 84.120283
iter  60 value 83.673711
iter  70 value 83.208459
iter  80 value 82.925332
iter  90 value 82.923315
iter 100 value 82.923095
final  value 82.923095 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 118.660700 
iter  10 value 94.491793
iter  20 value 94.456021
iter  30 value 94.354703
iter  30 value 94.354702
iter  30 value 94.354702
final  value 94.354702 
converged
Fitting Repeat 4 

# weights:  507
initial  value 110.135899 
iter  10 value 94.362471
iter  20 value 94.331581
iter  30 value 88.433014
iter  40 value 87.838712
final  value 87.836514 
converged
Fitting Repeat 5 

# weights:  507
initial  value 124.456611 
iter  10 value 94.492315
iter  20 value 94.484541
final  value 94.484225 
converged
Fitting Repeat 1 

# weights:  305
initial  value 145.445198 
iter  10 value 117.210663
iter  20 value 114.858741
iter  30 value 108.538784
iter  40 value 108.395777
final  value 108.395182 
converged
Fitting Repeat 2 

# weights:  305
initial  value 126.379476 
iter  10 value 117.763686
iter  20 value 117.358431
iter  30 value 115.215192
iter  40 value 109.501117
iter  50 value 108.098491
iter  60 value 107.005463
iter  70 value 106.673823
final  value 106.656300 
converged
Fitting Repeat 3 

# weights:  305
initial  value 126.799294 
iter  10 value 117.895487
iter  20 value 117.878162
final  value 117.770098 
converged
Fitting Repeat 4 

# weights:  305
initial  value 118.437123 
iter  10 value 117.892330
iter  20 value 113.048989
iter  30 value 108.428706
iter  40 value 108.322962
iter  50 value 108.174935
final  value 108.174704 
converged
Fitting Repeat 5 

# weights:  305
initial  value 127.571561 
iter  10 value 117.735860
iter  20 value 117.532815
iter  30 value 117.203955
iter  40 value 114.927260
iter  50 value 114.653000
iter  60 value 114.635707
iter  70 value 114.635508
iter  80 value 114.635052
iter  80 value 114.635052
final  value 114.635052 
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 Apr 20 20:20:26 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 
 20.047   0.779  84.092