##############################################################################
##############################################################################
###
### 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: 2026-04-20 00:13:02 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     17.197  0.099  17.330
var_imp       17.038  0.157  17.360
FSmethod      17.082  0.085  17.418
pred_ensembel  6.420  0.195   5.878
enrichfindP    0.205  0.043  10.816
* 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 94.639731 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.059457 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.974437 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.478024 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.310445 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.560825 
final  value 93.454900 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.621170 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.788866 
iter  10 value 93.035243
iter  20 value 91.938808
iter  30 value 91.938121
final  value 91.938092 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.095468 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.681886 
final  value 93.582418 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.335743 
final  value 93.582418 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.786324 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.714936 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.733560 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 126.323389 
final  value 93.582418 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.382606 
iter  10 value 94.050998
iter  20 value 85.028127
iter  30 value 83.022225
iter  40 value 81.746968
iter  50 value 81.283446
iter  60 value 80.529419
iter  70 value 80.431208
final  value 80.431197 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.612529 
iter  10 value 94.051160
iter  20 value 92.184980
iter  30 value 90.596759
iter  40 value 90.246348
iter  50 value 90.184927
final  value 90.184896 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.669416 
iter  10 value 94.065353
iter  20 value 92.737995
iter  30 value 91.281590
iter  40 value 86.808609
iter  50 value 82.542664
iter  60 value 81.587567
iter  70 value 81.457361
iter  80 value 81.271467
iter  90 value 80.966947
iter 100 value 80.305626
final  value 80.305626 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.866772 
iter  10 value 93.568926
iter  20 value 89.720416
iter  30 value 88.882158
iter  40 value 82.943718
iter  50 value 82.324619
iter  60 value 82.031147
iter  70 value 81.499774
iter  80 value 81.111491
iter  90 value 81.087570
iter 100 value 81.052562
final  value 81.052562 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 100.057310 
iter  10 value 94.010191
iter  20 value 92.130172
iter  30 value 85.439010
iter  40 value 84.158662
iter  50 value 83.690615
iter  60 value 83.442243
iter  70 value 81.735613
iter  80 value 80.505467
iter  90 value 79.900513
iter 100 value 79.869727
final  value 79.869727 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 101.901255 
iter  10 value 94.094428
iter  20 value 85.435619
iter  30 value 83.051850
iter  40 value 82.898528
iter  50 value 82.560181
iter  60 value 82.217758
iter  70 value 81.685309
iter  80 value 80.510017
iter  90 value 79.993065
iter 100 value 78.804302
final  value 78.804302 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.936194 
iter  10 value 94.066192
iter  20 value 86.817518
iter  30 value 85.047556
iter  40 value 84.457567
iter  50 value 82.975006
iter  60 value 82.224577
iter  70 value 81.491013
iter  80 value 79.997757
iter  90 value 79.419409
iter 100 value 78.585838
final  value 78.585838 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.212581 
iter  10 value 92.482609
iter  20 value 90.891657
iter  30 value 88.549402
iter  40 value 84.901146
iter  50 value 84.214025
iter  60 value 82.936238
iter  70 value 82.400223
iter  80 value 81.886555
iter  90 value 81.205473
iter 100 value 79.685264
final  value 79.685264 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.205936 
iter  10 value 93.993593
iter  20 value 91.660144
iter  30 value 83.681305
iter  40 value 82.516610
iter  50 value 81.958120
iter  60 value 81.791578
iter  70 value 80.738242
iter  80 value 79.750880
iter  90 value 78.537883
iter 100 value 78.336637
final  value 78.336637 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.019270 
iter  10 value 95.533691
iter  20 value 85.100563
iter  30 value 82.911591
iter  40 value 80.110299
iter  50 value 78.764407
iter  60 value 78.212910
iter  70 value 78.116774
iter  80 value 78.063017
iter  90 value 77.948445
iter 100 value 77.817003
final  value 77.817003 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 133.976010 
iter  10 value 94.882846
iter  20 value 84.083361
iter  30 value 82.976257
iter  40 value 80.830460
iter  50 value 79.727412
iter  60 value 79.285541
iter  70 value 78.565319
iter  80 value 78.099817
iter  90 value 78.022546
iter 100 value 77.972677
final  value 77.972677 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.811019 
iter  10 value 94.055334
iter  20 value 86.012645
iter  30 value 84.022683
iter  40 value 83.304330
iter  50 value 83.046497
iter  60 value 82.683674
iter  70 value 82.227815
iter  80 value 82.102926
iter  90 value 80.310815
iter 100 value 79.368903
final  value 79.368903 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 112.264556 
iter  10 value 94.064337
iter  20 value 90.900529
iter  30 value 84.052321
iter  40 value 83.504998
iter  50 value 82.830489
iter  60 value 80.084835
iter  70 value 78.418634
iter  80 value 77.893685
iter  90 value 77.796307
iter 100 value 77.751861
final  value 77.751861 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.776700 
iter  10 value 94.078382
iter  20 value 86.073970
iter  30 value 85.234786
iter  40 value 84.388354
iter  50 value 82.723242
iter  60 value 79.547877
iter  70 value 78.872926
iter  80 value 78.435647
iter  90 value 78.017815
iter 100 value 77.915060
final  value 77.915060 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.807877 
iter  10 value 94.215964
iter  20 value 93.878050
iter  30 value 93.673006
iter  40 value 89.257113
iter  50 value 88.188819
iter  60 value 87.425529
iter  70 value 86.686854
iter  80 value 82.399236
iter  90 value 80.734640
iter 100 value 80.167614
final  value 80.167614 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.156072 
final  value 94.054831 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.432812 
final  value 93.584045 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.725703 
iter  10 value 93.584080
iter  20 value 93.583130
iter  30 value 93.582738
final  value 93.582734 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.875714 
iter  10 value 90.312423
iter  20 value 90.207543
final  value 90.207512 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.117454 
final  value 94.054401 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.674087 
iter  10 value 91.697153
iter  20 value 91.693878
iter  30 value 91.265813
iter  40 value 89.773375
iter  50 value 85.612533
iter  60 value 85.439584
iter  70 value 85.177436
iter  80 value 85.172960
iter  90 value 82.339078
iter 100 value 81.366484
final  value 81.366484 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.160637 
iter  10 value 93.587967
iter  20 value 93.584926
iter  30 value 93.582649
iter  30 value 93.582649
iter  30 value 93.582649
final  value 93.582649 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.765139 
iter  10 value 94.051868
iter  20 value 93.998160
iter  30 value 93.583516
final  value 93.582629 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.226727 
iter  10 value 93.587379
iter  20 value 87.541713
iter  30 value 86.460018
iter  40 value 85.168666
iter  50 value 85.153339
iter  60 value 84.846206
iter  70 value 84.752942
final  value 84.752852 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.312631 
iter  10 value 94.057721
iter  20 value 93.801430
iter  30 value 93.583058
final  value 93.582667 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.302297 
iter  10 value 94.052059
iter  20 value 94.046320
final  value 94.044901 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.789139 
iter  10 value 94.051440
iter  20 value 94.044255
iter  30 value 87.520200
iter  40 value 87.059691
iter  50 value 87.052820
iter  60 value 85.508494
iter  70 value 81.882646
iter  80 value 81.611538
iter  90 value 79.224441
iter 100 value 79.207971
final  value 79.207971 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.622933 
iter  10 value 94.061233
iter  20 value 93.801100
iter  30 value 93.583404
iter  30 value 93.583403
iter  30 value 93.583403
final  value 93.583403 
converged
Fitting Repeat 4 

# weights:  507
initial  value 116.963409 
iter  10 value 93.912147
iter  20 value 93.806417
iter  30 value 91.303490
iter  40 value 90.711743
iter  50 value 90.676850
iter  60 value 90.344183
final  value 90.344121 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.525567 
iter  10 value 94.054674
iter  20 value 83.113852
iter  30 value 82.555167
iter  40 value 82.413154
final  value 82.412582 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.753692 
iter  10 value 92.115469
iter  20 value 91.935632
iter  30 value 91.142632
iter  40 value 90.970149
final  value 90.970130 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.814103 
final  value 94.043244 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.223242 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.911422 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 112.366666 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.807924 
final  value 94.043243 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.237578 
iter  10 value 93.887527
iter  20 value 91.396866
final  value 91.346308 
converged
Fitting Repeat 3 

# weights:  305
initial  value 127.553670 
iter  10 value 94.043243
iter  10 value 94.043243
iter  10 value 94.043243
final  value 94.043243 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.640415 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.565302 
iter  10 value 93.669808
iter  10 value 93.669808
iter  10 value 93.669808
final  value 93.669808 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.212582 
final  value 93.720939 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.999811 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 113.130264 
final  value 94.043243 
converged
Fitting Repeat 4 

# weights:  507
initial  value 109.870261 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.798594 
final  value 94.043243 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.575825 
iter  10 value 94.050788
iter  20 value 91.755177
iter  30 value 90.262302
iter  40 value 90.105728
iter  50 value 90.029821
iter  60 value 85.222757
iter  70 value 84.839214
iter  80 value 81.471485
iter  90 value 81.263336
iter 100 value 80.441962
final  value 80.441962 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 95.816012 
iter  10 value 94.056751
iter  20 value 93.988843
iter  30 value 87.297514
iter  40 value 86.681366
iter  50 value 86.385260
iter  60 value 86.295545
iter  70 value 86.276762
iter  80 value 84.538726
iter  90 value 84.249800
iter 100 value 84.246869
final  value 84.246869 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.189270 
iter  10 value 94.082346
iter  20 value 94.057009
iter  30 value 93.992168
iter  40 value 86.620921
iter  50 value 84.355930
iter  60 value 83.119255
iter  70 value 82.957287
iter  80 value 82.773650
iter  90 value 81.529680
iter 100 value 80.521383
final  value 80.521383 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 105.157999 
iter  10 value 94.084810
iter  20 value 94.053892
iter  30 value 93.546357
iter  40 value 92.567225
iter  50 value 92.546213
iter  60 value 87.029258
iter  70 value 86.916126
iter  80 value 86.755177
iter  90 value 86.668530
iter 100 value 85.104264
final  value 85.104264 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 101.388474 
iter  10 value 94.040217
iter  20 value 92.665576
iter  30 value 92.551569
iter  40 value 91.747340
iter  40 value 91.747340
iter  50 value 84.105709
iter  60 value 83.438746
iter  70 value 83.231020
iter  80 value 82.889888
iter  90 value 82.665867
iter 100 value 80.313622
final  value 80.313622 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 104.671690 
iter  10 value 94.003085
iter  20 value 89.598414
iter  30 value 85.719161
iter  40 value 82.802154
iter  50 value 82.078101
iter  60 value 81.412802
iter  70 value 81.193820
iter  80 value 80.344749
iter  90 value 80.211078
iter 100 value 79.543696
final  value 79.543696 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 109.327612 
iter  10 value 93.595228
iter  20 value 90.171017
iter  30 value 88.731251
iter  40 value 88.580449
iter  50 value 88.536590
iter  60 value 88.512790
iter  70 value 88.307485
iter  80 value 85.103025
iter  90 value 83.441824
iter 100 value 83.192393
final  value 83.192393 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 117.307938 
iter  10 value 94.072839
iter  20 value 92.277062
iter  30 value 88.674875
iter  40 value 85.820107
iter  50 value 81.269098
iter  60 value 80.512842
iter  70 value 80.047538
iter  80 value 79.445209
iter  90 value 79.204064
iter 100 value 78.929093
final  value 78.929093 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.317702 
iter  10 value 94.065663
iter  20 value 93.925302
iter  30 value 93.155947
iter  40 value 84.609441
iter  50 value 81.722527
iter  60 value 81.144043
iter  70 value 80.603465
iter  80 value 79.698056
iter  90 value 79.540702
iter 100 value 79.521912
final  value 79.521912 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.655032 
iter  10 value 88.469621
iter  20 value 87.165312
iter  30 value 84.304873
iter  40 value 81.222498
iter  50 value 80.145511
iter  60 value 79.166862
iter  70 value 79.137191
iter  80 value 78.879915
iter  90 value 78.705575
iter 100 value 78.651622
final  value 78.651622 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.406684 
iter  10 value 94.553143
iter  20 value 88.948689
iter  30 value 85.929845
iter  40 value 85.693666
iter  50 value 85.611322
iter  60 value 84.965716
iter  70 value 83.370648
iter  80 value 80.945593
iter  90 value 80.215463
iter 100 value 79.385744
final  value 79.385744 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 122.531826 
iter  10 value 94.042832
iter  20 value 85.927096
iter  30 value 85.168937
iter  40 value 84.859430
iter  50 value 81.618902
iter  60 value 80.631931
iter  70 value 79.455449
iter  80 value 79.379339
iter  90 value 79.164766
iter 100 value 79.005454
final  value 79.005454 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 125.802220 
iter  10 value 94.031781
iter  20 value 90.673907
iter  30 value 88.619411
iter  40 value 82.275941
iter  50 value 80.955993
iter  60 value 80.758866
iter  70 value 80.513758
iter  80 value 80.168777
iter  90 value 79.738573
iter 100 value 79.547047
final  value 79.547047 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.727705 
iter  10 value 93.971597
iter  20 value 90.738735
iter  30 value 86.090312
iter  40 value 83.872849
iter  50 value 83.314189
iter  60 value 82.518757
iter  70 value 81.923322
iter  80 value 80.651990
iter  90 value 80.097697
iter 100 value 79.908842
final  value 79.908842 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.946799 
iter  10 value 94.388294
iter  20 value 86.976046
iter  30 value 85.170272
iter  40 value 83.262875
iter  50 value 82.200213
iter  60 value 80.826506
iter  70 value 80.499000
iter  80 value 79.683089
iter  90 value 78.976986
iter 100 value 78.625964
final  value 78.625964 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 106.358130 
iter  10 value 84.739156
iter  20 value 84.590709
final  value 84.590456 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.168796 
final  value 94.054897 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.042499 
final  value 94.054509 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.246232 
final  value 94.054649 
converged
Fitting Repeat 5 

# weights:  103
initial  value 114.764683 
final  value 94.055901 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.592970 
iter  10 value 94.057912
iter  20 value 94.043014
iter  30 value 89.380618
final  value 88.197732 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.774528 
iter  10 value 94.048250
iter  20 value 93.922225
iter  30 value 91.550645
final  value 91.542331 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.608311 
iter  10 value 94.086670
iter  20 value 94.079967
iter  30 value 87.403647
iter  40 value 83.836447
iter  50 value 83.686768
iter  60 value 83.616041
iter  70 value 83.406972
final  value 83.406177 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.930108 
iter  10 value 94.057360
iter  20 value 94.051052
iter  30 value 93.975195
iter  40 value 89.405749
iter  50 value 88.304274
iter  60 value 86.961801
iter  70 value 86.635038
iter  80 value 85.821705
iter  90 value 85.627505
iter 100 value 85.451768
final  value 85.451768 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.071106 
iter  10 value 94.071671
iter  20 value 94.065679
iter  30 value 91.856580
iter  40 value 91.846421
iter  50 value 91.840866
iter  60 value 91.839784
iter  70 value 91.813747
iter  80 value 85.664129
iter  90 value 85.383280
iter 100 value 85.380046
final  value 85.380046 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.102210 
iter  10 value 94.061064
iter  20 value 92.489614
iter  30 value 90.398362
iter  30 value 90.398361
iter  30 value 90.398361
final  value 90.398361 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.382050 
iter  10 value 92.710676
iter  20 value 85.439641
iter  30 value 84.663955
iter  40 value 84.492026
iter  50 value 84.424442
iter  60 value 84.423657
iter  70 value 84.093811
iter  80 value 83.392168
iter  90 value 83.342390
iter 100 value 83.340397
final  value 83.340397 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 98.228952 
iter  10 value 92.026007
iter  20 value 89.606085
iter  30 value 87.819990
iter  40 value 87.735554
iter  50 value 87.731699
iter  60 value 87.722683
iter  70 value 87.714393
iter  80 value 87.706828
iter  90 value 87.705784
iter 100 value 87.683505
final  value 87.683505 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.240097 
iter  10 value 94.060498
iter  20 value 94.052944
iter  30 value 93.966621
iter  40 value 93.953093
iter  50 value 92.457006
iter  60 value 90.532311
iter  70 value 90.471005
iter  80 value 89.590557
iter  90 value 88.336047
iter 100 value 88.335694
final  value 88.335694 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 98.350185 
iter  10 value 94.060762
iter  20 value 93.904087
iter  30 value 84.606052
iter  40 value 83.880593
iter  50 value 83.876817
iter  60 value 83.876326
iter  70 value 83.875225
iter  80 value 83.872797
iter  90 value 83.407177
iter 100 value 81.948432
final  value 81.948432 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.175920 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.901123 
final  value 94.467391 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.197947 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.010174 
iter  10 value 93.684377
final  value 93.683142 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.113624 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.709821 
final  value 94.467391 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.599436 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.361418 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.936021 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.656520 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.516839 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.597877 
iter  10 value 91.743806
iter  20 value 85.965967
iter  30 value 85.879872
iter  40 value 85.864582
final  value 85.864393 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.695526 
final  value 94.467391 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.420684 
iter  10 value 92.617939
final  value 92.613874 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.748179 
iter  10 value 94.105263
iter  10 value 94.105262
iter  10 value 94.105262
final  value 94.105262 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.312630 
iter  10 value 94.870309
iter  20 value 90.635069
iter  30 value 85.286345
iter  40 value 83.669799
iter  50 value 82.348061
iter  60 value 81.871150
iter  70 value 81.620466
final  value 81.620459 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.510657 
iter  10 value 94.485805
iter  20 value 87.229488
iter  30 value 84.010309
iter  40 value 83.553622
iter  50 value 82.998823
iter  60 value 82.959054
iter  70 value 82.754298
iter  80 value 82.727497
iter  80 value 82.727497
iter  80 value 82.727497
final  value 82.727497 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.846784 
iter  10 value 94.479701
iter  20 value 86.017817
iter  30 value 84.967424
iter  40 value 84.161057
iter  50 value 83.503941
iter  60 value 82.135296
iter  70 value 81.717050
iter  80 value 81.381863
iter  90 value 81.378620
final  value 81.378618 
converged
Fitting Repeat 4 

# weights:  103
initial  value 115.897618 
iter  10 value 94.421076
iter  20 value 91.342628
iter  30 value 90.196165
iter  40 value 88.114966
iter  50 value 86.966352
iter  60 value 83.811160
iter  70 value 82.689017
iter  80 value 82.311071
iter  90 value 82.178955
iter 100 value 81.506995
final  value 81.506995 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 108.935288 
iter  10 value 94.365602
iter  20 value 91.796870
iter  30 value 90.198513
iter  40 value 89.576822
iter  50 value 84.170318
iter  60 value 84.014734
iter  70 value 83.631999
iter  80 value 82.438988
iter  90 value 81.627487
final  value 81.620459 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.068544 
iter  10 value 94.501698
iter  20 value 94.277242
iter  30 value 92.208875
iter  40 value 90.959941
iter  50 value 86.297021
iter  60 value 82.892833
iter  70 value 81.621548
iter  80 value 80.605949
iter  90 value 80.436466
iter 100 value 80.217474
final  value 80.217474 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 111.405867 
iter  10 value 94.656742
iter  20 value 94.439025
iter  30 value 87.439400
iter  40 value 87.098328
iter  50 value 83.726975
iter  60 value 82.905790
iter  70 value 82.100206
iter  80 value 81.322297
iter  90 value 81.025524
iter 100 value 80.446246
final  value 80.446246 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.385910 
iter  10 value 94.509634
iter  20 value 93.848040
iter  30 value 89.756372
iter  40 value 87.397074
iter  50 value 84.382645
iter  60 value 83.878130
iter  70 value 83.331098
iter  80 value 82.837800
iter  90 value 81.117638
iter 100 value 80.879518
final  value 80.879518 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.240035 
iter  10 value 94.361927
iter  20 value 89.018583
iter  30 value 85.633657
iter  40 value 85.160486
iter  50 value 85.050438
iter  60 value 84.698702
iter  70 value 84.358957
iter  80 value 83.482483
iter  90 value 83.074594
iter 100 value 82.446974
final  value 82.446974 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.789373 
iter  10 value 94.494640
iter  20 value 93.493046
iter  30 value 88.637459
iter  40 value 86.669953
iter  50 value 85.118583
iter  60 value 83.829987
iter  70 value 83.117256
iter  80 value 81.672344
iter  90 value 80.824019
iter 100 value 80.657156
final  value 80.657156 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 123.683676 
iter  10 value 94.724804
iter  20 value 94.113788
iter  30 value 87.068093
iter  40 value 84.569383
iter  50 value 82.442288
iter  60 value 81.892584
iter  70 value 81.584059
iter  80 value 81.047515
iter  90 value 80.623240
iter 100 value 80.260349
final  value 80.260349 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.242488 
iter  10 value 94.706067
iter  20 value 92.897676
iter  30 value 84.594573
iter  40 value 82.580996
iter  50 value 81.829434
iter  60 value 81.519740
iter  70 value 80.857249
iter  80 value 80.814847
iter  90 value 80.568683
iter 100 value 80.205640
final  value 80.205640 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 117.490825 
iter  10 value 94.736650
iter  20 value 89.254069
iter  30 value 86.326018
iter  40 value 84.071544
iter  50 value 82.903677
iter  60 value 82.431628
iter  70 value 81.854275
iter  80 value 81.247471
iter  90 value 80.639771
iter 100 value 80.503192
final  value 80.503192 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.212487 
iter  10 value 95.038281
iter  20 value 94.468094
iter  30 value 92.314617
iter  40 value 88.690651
iter  50 value 85.713650
iter  60 value 82.849894
iter  70 value 81.053694
iter  80 value 80.803405
iter  90 value 80.548624
iter 100 value 80.471684
final  value 80.471684 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 144.624049 
iter  10 value 95.346150
iter  20 value 94.518559
iter  30 value 91.931019
iter  40 value 87.075400
iter  50 value 83.759932
iter  60 value 82.759489
iter  70 value 81.803690
iter  80 value 81.414583
iter  90 value 81.003237
iter 100 value 80.557736
final  value 80.557736 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.725195 
iter  10 value 94.114807
iter  20 value 94.114293
iter  30 value 94.113532
final  value 94.113415 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.715030 
iter  10 value 94.485754
iter  20 value 94.371219
iter  30 value 93.220432
iter  30 value 93.220431
iter  30 value 93.220431
final  value 93.220431 
converged
Fitting Repeat 3 

# weights:  103
initial  value 117.707029 
iter  10 value 94.485716
iter  20 value 94.474768
final  value 94.467415 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.100125 
iter  10 value 94.485976
iter  20 value 94.484229
iter  30 value 94.138832
final  value 94.138684 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.880910 
final  value 94.485661 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.465055 
iter  10 value 94.488912
iter  20 value 91.842073
iter  30 value 91.024363
iter  40 value 88.650594
iter  50 value 87.613110
iter  60 value 87.569683
final  value 87.569554 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.231488 
iter  10 value 93.356472
iter  20 value 93.330211
iter  30 value 91.727787
iter  40 value 90.882213
iter  50 value 90.875594
iter  60 value 90.658344
iter  70 value 90.386653
iter  80 value 90.344589
iter  90 value 90.343130
final  value 90.343129 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.243675 
iter  10 value 94.489081
iter  20 value 94.415570
iter  30 value 84.866188
iter  40 value 84.764167
final  value 84.764150 
converged
Fitting Repeat 4 

# weights:  305
initial  value 121.855684 
iter  10 value 94.488785
iter  20 value 94.468473
final  value 93.874709 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.289521 
iter  10 value 94.472415
iter  20 value 94.440697
iter  30 value 92.836492
iter  40 value 83.152549
iter  50 value 83.027244
final  value 83.025906 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.525773 
iter  10 value 94.491745
iter  20 value 94.385746
iter  30 value 92.473062
iter  40 value 88.316124
iter  50 value 82.950648
iter  60 value 80.742261
iter  70 value 80.186701
iter  80 value 80.127694
iter  90 value 80.105249
iter 100 value 80.005048
final  value 80.005048 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.798058 
iter  10 value 94.475508
iter  20 value 94.470788
iter  30 value 92.993623
iter  40 value 92.365995
iter  50 value 92.363880
iter  50 value 92.363879
iter  50 value 92.363879
final  value 92.363879 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.764414 
iter  10 value 83.175347
iter  20 value 82.731806
iter  30 value 82.720432
iter  40 value 82.667822
final  value 82.666711 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.623675 
iter  10 value 94.489155
iter  20 value 94.476582
iter  30 value 86.144158
iter  40 value 84.193913
iter  50 value 83.185637
iter  60 value 83.012487
iter  70 value 83.009768
iter  80 value 83.008875
iter  90 value 83.007552
final  value 83.007508 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.078580 
iter  10 value 94.478310
iter  20 value 93.692560
iter  30 value 93.674967
iter  40 value 92.259148
iter  50 value 91.490908
iter  60 value 81.008655
iter  70 value 80.456114
iter  80 value 80.267729
iter  90 value 80.006939
iter 100 value 79.999978
final  value 79.999978 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.224063 
final  value 94.026542 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.675357 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.302006 
iter  10 value 93.320226
final  value 93.320225 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.487087 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.758405 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.262156 
final  value 94.039474 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.462867 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 108.475782 
final  value 94.026542 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.635263 
iter  10 value 93.809655
final  value 93.809648 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.570314 
iter  10 value 92.552732
final  value 92.552727 
converged
Fitting Repeat 1 

# weights:  507
initial  value 130.043142 
final  value 93.289722 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.141407 
iter  10 value 92.571959
final  value 92.552728 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.284064 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.664527 
final  value 93.294118 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.335964 
iter  10 value 86.027289
iter  20 value 82.170433
final  value 82.169463 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.171514 
iter  10 value 92.936428
iter  20 value 86.002278
iter  30 value 83.551719
iter  40 value 82.051686
iter  50 value 81.973627
iter  60 value 81.405318
iter  70 value 80.911544
final  value 80.910675 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.496665 
iter  10 value 94.425858
iter  20 value 93.375185
iter  30 value 92.732919
iter  40 value 92.705192
iter  50 value 85.128299
iter  60 value 84.381894
iter  70 value 84.173921
iter  80 value 83.504716
iter  90 value 82.745149
iter 100 value 81.804129
final  value 81.804129 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.521603 
iter  10 value 92.898001
iter  20 value 90.030641
iter  30 value 89.598168
iter  40 value 86.201271
iter  50 value 83.216432
iter  60 value 82.123832
iter  70 value 81.126018
iter  80 value 80.912102
iter  90 value 80.910707
final  value 80.910675 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.433449 
iter  10 value 93.961324
iter  20 value 92.874355
iter  30 value 89.147607
iter  40 value 89.001286
iter  50 value 88.744371
iter  60 value 83.041314
iter  70 value 82.233991
iter  80 value 82.143009
iter  90 value 81.968993
iter 100 value 81.593139
final  value 81.593139 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.845939 
iter  10 value 93.580109
iter  20 value 88.166833
iter  30 value 84.653500
iter  40 value 84.358706
iter  50 value 84.157291
final  value 84.153024 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.292083 
iter  10 value 94.474709
iter  20 value 88.965281
iter  30 value 85.182007
iter  40 value 83.376973
iter  50 value 82.856931
iter  60 value 80.653439
iter  70 value 80.143180
iter  80 value 80.061049
iter  90 value 79.965352
iter 100 value 79.888553
final  value 79.888553 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 111.978725 
iter  10 value 97.921720
iter  20 value 86.325438
iter  30 value 84.510775
iter  40 value 83.505694
iter  50 value 83.157187
iter  60 value 82.958578
iter  70 value 82.844112
iter  80 value 82.763799
iter  90 value 82.652742
iter 100 value 82.597682
final  value 82.597682 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 128.867400 
iter  10 value 94.440437
iter  20 value 85.791774
iter  30 value 84.921639
iter  40 value 83.450036
iter  50 value 82.970090
iter  60 value 81.841966
iter  70 value 81.370147
iter  80 value 80.596044
iter  90 value 79.803011
iter 100 value 79.557802
final  value 79.557802 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.027862 
iter  10 value 94.501689
iter  20 value 94.153464
iter  30 value 92.536875
iter  40 value 85.053972
iter  50 value 84.483723
iter  60 value 84.233906
iter  70 value 83.302109
iter  80 value 80.668204
iter  90 value 79.685809
iter 100 value 79.604371
final  value 79.604371 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 125.402792 
iter  10 value 94.457779
iter  20 value 86.210321
iter  30 value 83.533308
iter  40 value 81.347041
iter  50 value 80.406651
iter  60 value 79.767348
iter  70 value 79.598526
iter  80 value 79.595954
iter  90 value 79.580687
iter 100 value 79.416379
final  value 79.416379 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 111.059033 
iter  10 value 94.555929
iter  20 value 92.554245
iter  30 value 85.274334
iter  40 value 84.195779
iter  50 value 83.552543
iter  60 value 82.905064
iter  70 value 81.883081
iter  80 value 80.870533
iter  90 value 80.238874
iter 100 value 80.157723
final  value 80.157723 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.979492 
iter  10 value 94.484784
iter  20 value 92.800666
iter  30 value 92.592100
iter  40 value 86.989158
iter  50 value 83.425471
iter  60 value 82.611994
iter  70 value 81.747727
iter  80 value 81.368456
iter  90 value 81.109725
iter 100 value 80.433318
final  value 80.433318 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 124.215478 
iter  10 value 96.323065
iter  20 value 92.829628
iter  30 value 85.660428
iter  40 value 83.742344
iter  50 value 82.574905
iter  60 value 80.922490
iter  70 value 80.404445
iter  80 value 80.007866
iter  90 value 79.621428
iter 100 value 79.446250
final  value 79.446250 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 115.823091 
iter  10 value 94.858762
iter  20 value 90.775279
iter  30 value 84.664207
iter  40 value 84.288810
iter  50 value 83.422173
iter  60 value 82.014841
iter  70 value 80.843009
iter  80 value 80.435305
iter  90 value 79.990959
iter 100 value 79.910312
final  value 79.910312 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 117.298934 
iter  10 value 94.579737
iter  20 value 93.035446
iter  30 value 84.446500
iter  40 value 84.197585
iter  50 value 83.895267
iter  60 value 82.834938
iter  70 value 81.545304
iter  80 value 79.911194
iter  90 value 79.304534
iter 100 value 79.131910
final  value 79.131910 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.166506 
final  value 94.486137 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.994871 
iter  10 value 90.775518
iter  20 value 88.850019
iter  30 value 88.567530
iter  40 value 85.604403
iter  50 value 84.507268
iter  60 value 84.480268
final  value 84.480219 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.716205 
final  value 94.485598 
converged
Fitting Repeat 4 

# weights:  103
initial  value 108.182776 
final  value 93.811288 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.477544 
final  value 94.486007 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.513074 
iter  10 value 94.489578
final  value 94.485883 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.649624 
iter  10 value 94.488859
iter  20 value 94.484471
final  value 94.484281 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.652979 
iter  10 value 94.031733
iter  20 value 94.028706
final  value 94.028181 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.520842 
iter  10 value 94.492275
iter  20 value 94.305435
iter  30 value 87.086891
iter  40 value 86.110250
iter  50 value 86.102628
iter  60 value 85.761809
iter  70 value 85.061198
iter  80 value 85.058805
final  value 85.058619 
converged
Fitting Repeat 5 

# weights:  305
initial  value 114.661102 
iter  10 value 94.489023
iter  20 value 94.484239
iter  30 value 92.348868
iter  40 value 88.815729
iter  50 value 88.721426
iter  60 value 87.355347
iter  70 value 83.130756
iter  80 value 81.824952
iter  90 value 81.650835
iter 100 value 81.563019
final  value 81.563019 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 96.341400 
iter  10 value 94.485611
iter  20 value 92.894722
final  value 92.553738 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.459239 
iter  10 value 94.034441
iter  20 value 92.612554
iter  30 value 92.552577
iter  40 value 92.147009
iter  50 value 87.833114
iter  60 value 81.358104
iter  70 value 79.922615
iter  80 value 79.901656
iter  90 value 79.856231
iter 100 value 78.816349
final  value 78.816349 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.168472 
iter  10 value 94.492545
iter  20 value 94.484024
iter  30 value 89.325710
iter  40 value 84.507687
iter  50 value 81.135421
iter  60 value 79.607194
iter  70 value 79.552684
iter  80 value 79.528957
iter  90 value 78.818913
iter 100 value 78.723931
final  value 78.723931 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.274835 
iter  10 value 93.817370
iter  20 value 93.810740
iter  30 value 93.569167
iter  40 value 92.518829
final  value 92.512086 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.264467 
iter  10 value 94.492490
iter  20 value 94.387156
iter  30 value 92.553040
iter  40 value 87.626926
iter  50 value 83.026806
iter  60 value 82.421000
iter  70 value 81.962063
iter  80 value 81.565675
iter  90 value 81.554330
iter 100 value 81.553676
final  value 81.553676 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 111.488097 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.521752 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.382358 
iter  10 value 93.720946
iter  20 value 93.720867
final  value 93.720829 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.121139 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.365532 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.918817 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.975089 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.156213 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.113573 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 110.128675 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.128759 
iter  10 value 94.480060
iter  20 value 94.381462
iter  20 value 94.381462
iter  20 value 94.381462
final  value 94.381462 
converged
Fitting Repeat 2 

# weights:  507
initial  value 112.668185 
iter  10 value 94.609264
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 128.329041 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 113.748723 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.917571 
iter  10 value 94.354396
iter  10 value 94.354396
iter  10 value 94.354396
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  103
initial  value 113.265216 
iter  10 value 94.486543
iter  20 value 94.484180
iter  30 value 94.202691
iter  40 value 90.778943
iter  50 value 88.046157
iter  60 value 87.132932
iter  70 value 84.813870
iter  80 value 84.773208
iter  90 value 84.765955
iter 100 value 84.127138
final  value 84.127138 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.605801 
iter  10 value 94.214552
iter  20 value 94.187075
iter  30 value 93.788674
iter  40 value 93.327518
iter  50 value 93.296564
iter  60 value 92.900674
iter  70 value 92.614071
iter  80 value 92.594238
final  value 92.594202 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.703719 
iter  10 value 94.469194
iter  20 value 93.567625
iter  30 value 91.848438
iter  40 value 90.271908
iter  50 value 87.135084
iter  60 value 85.813625
iter  70 value 85.273347
iter  80 value 84.420409
iter  90 value 83.717639
iter 100 value 83.701072
final  value 83.701072 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 101.693391 
iter  10 value 94.493870
iter  20 value 94.473301
iter  30 value 90.206263
iter  40 value 87.716205
iter  50 value 85.583543
iter  60 value 84.577874
iter  70 value 84.249533
iter  80 value 84.154168
iter  90 value 83.533340
final  value 83.523669 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.795057 
iter  10 value 94.483783
iter  20 value 88.703630
iter  30 value 86.319718
iter  40 value 85.287611
iter  50 value 85.219464
final  value 85.219442 
converged
Fitting Repeat 1 

# weights:  305
initial  value 132.593140 
iter  10 value 94.860640
iter  20 value 91.771906
iter  30 value 89.071804
iter  40 value 88.340954
iter  50 value 87.695667
iter  60 value 85.979064
iter  70 value 84.335168
iter  80 value 83.955855
iter  90 value 83.859472
iter 100 value 83.415139
final  value 83.415139 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.603893 
iter  10 value 94.318388
iter  20 value 86.833029
iter  30 value 85.934107
iter  40 value 85.198610
iter  50 value 84.811875
iter  60 value 84.376100
iter  70 value 84.082112
iter  80 value 83.558642
iter  90 value 83.478531
iter 100 value 83.364831
final  value 83.364831 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.046911 
iter  10 value 93.576418
iter  20 value 86.107241
iter  30 value 85.210937
iter  40 value 84.392266
iter  50 value 84.059973
iter  60 value 82.975738
iter  70 value 82.536579
iter  80 value 82.409365
iter  90 value 82.272663
iter 100 value 82.081128
final  value 82.081128 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 112.427344 
iter  10 value 94.618080
iter  20 value 88.249014
iter  30 value 86.565542
iter  40 value 86.262762
iter  50 value 84.645513
iter  60 value 83.793748
iter  70 value 83.573163
iter  80 value 83.280999
iter  90 value 83.235074
iter 100 value 83.218781
final  value 83.218781 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.870725 
iter  10 value 93.761042
iter  20 value 86.572445
iter  30 value 86.331474
iter  40 value 85.258513
iter  50 value 84.728100
iter  60 value 84.389241
iter  70 value 84.145267
iter  80 value 83.245225
iter  90 value 82.508931
iter 100 value 82.404803
final  value 82.404803 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 123.884780 
iter  10 value 91.877226
iter  20 value 86.540768
iter  30 value 86.362594
iter  40 value 85.278070
iter  50 value 84.614554
iter  60 value 83.573696
iter  70 value 83.232843
iter  80 value 83.001984
iter  90 value 82.677453
iter 100 value 82.304168
final  value 82.304168 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.249267 
iter  10 value 94.507696
iter  20 value 93.302994
iter  30 value 86.983272
iter  40 value 86.635884
iter  50 value 84.826417
iter  60 value 82.888227
iter  70 value 82.187348
iter  80 value 82.067398
iter  90 value 81.923557
iter 100 value 81.769432
final  value 81.769432 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.283868 
iter  10 value 94.491413
iter  20 value 92.924991
iter  30 value 88.966559
iter  40 value 87.235485
iter  50 value 87.101933
iter  60 value 86.869636
iter  70 value 85.877931
iter  80 value 84.516823
iter  90 value 83.513046
iter 100 value 82.649372
final  value 82.649372 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.190346 
iter  10 value 94.212064
iter  20 value 88.449212
iter  30 value 85.760303
iter  40 value 85.013706
iter  50 value 84.500366
iter  60 value 84.459088
iter  70 value 84.426143
iter  80 value 84.101276
iter  90 value 82.798944
iter 100 value 82.407330
final  value 82.407330 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 123.652583 
iter  10 value 95.784025
iter  20 value 87.189992
iter  30 value 86.665872
iter  40 value 85.035986
iter  50 value 83.570177
iter  60 value 82.726831
iter  70 value 82.412005
iter  80 value 82.284692
iter  90 value 82.203658
iter 100 value 82.027836
final  value 82.027836 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.167093 
final  value 94.485862 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.692605 
iter  10 value 94.485852
iter  20 value 94.254465
iter  30 value 86.623603
iter  40 value 85.933881
final  value 85.933664 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.528186 
iter  10 value 94.486288
iter  20 value 94.484837
iter  20 value 94.484837
iter  20 value 94.484837
final  value 94.484837 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.220876 
final  value 94.485767 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.783652 
final  value 94.486074 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.932278 
iter  10 value 94.488217
iter  20 value 94.484238
final  value 94.484225 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.988512 
iter  10 value 94.484724
iter  20 value 94.484469
final  value 94.484455 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.956808 
iter  10 value 94.489181
iter  20 value 94.294262
iter  30 value 87.981066
iter  40 value 87.101758
iter  50 value 87.038002
iter  60 value 86.915226
iter  70 value 86.498113
iter  80 value 86.496534
iter  80 value 86.496533
iter  80 value 86.496533
final  value 86.496533 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.832640 
iter  10 value 94.368786
iter  20 value 94.358558
iter  30 value 94.147569
iter  40 value 94.144682
iter  50 value 94.144185
final  value 94.142682 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.888094 
iter  10 value 94.149310
iter  20 value 94.131080
iter  30 value 94.123445
iter  40 value 94.027066
iter  50 value 94.024209
final  value 94.012007 
converged
Fitting Repeat 1 

# weights:  507
initial  value 120.014858 
iter  10 value 94.492082
iter  20 value 94.457596
iter  30 value 88.074722
iter  40 value 87.821063
iter  50 value 87.541834
iter  60 value 87.374612
iter  70 value 87.374291
iter  70 value 87.374291
iter  70 value 87.374291
final  value 87.374291 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.726668 
iter  10 value 94.487575
iter  20 value 87.980039
iter  30 value 86.494428
iter  40 value 83.136333
iter  50 value 82.933031
iter  60 value 82.915268
iter  60 value 82.915268
final  value 82.915268 
converged
Fitting Repeat 3 

# weights:  507
initial  value 118.500554 
iter  10 value 94.415223
iter  20 value 86.808596
iter  30 value 84.558849
iter  40 value 84.484172
iter  50 value 84.427128
iter  60 value 84.420009
iter  70 value 84.418429
iter  80 value 84.417151
iter  80 value 84.417151
iter  80 value 84.417151
final  value 84.417151 
converged
Fitting Repeat 4 

# weights:  507
initial  value 111.336501 
iter  10 value 94.492375
iter  20 value 94.443033
iter  30 value 87.075655
iter  40 value 86.633552
iter  50 value 86.535763
iter  60 value 85.861392
iter  70 value 85.855254
iter  80 value 85.805405
iter  90 value 83.316347
iter 100 value 82.976381
final  value 82.976381 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 98.989749 
iter  10 value 94.492397
iter  20 value 94.485160
iter  30 value 93.496237
iter  40 value 87.334639
final  value 87.334195 
converged
Fitting Repeat 1 

# weights:  103
initial  value 127.579065 
iter  10 value 118.016142
iter  20 value 117.893396
iter  30 value 116.308189
iter  40 value 111.942032
iter  50 value 109.475503
iter  60 value 108.744179
iter  70 value 105.290153
iter  80 value 105.258441
final  value 105.258333 
converged
Fitting Repeat 2 

# weights:  103
initial  value 120.991189 
iter  10 value 116.672690
iter  20 value 109.598349
iter  30 value 108.695734
iter  40 value 107.485474
iter  50 value 105.320524
iter  60 value 105.261872
iter  70 value 105.258585
final  value 105.258336 
converged
Fitting Repeat 3 

# weights:  103
initial  value 132.265720 
iter  10 value 117.436659
iter  20 value 111.532281
iter  30 value 110.639966
iter  40 value 109.979294
iter  50 value 105.844561
iter  60 value 105.372885
iter  70 value 105.259424
final  value 105.258333 
converged
Fitting Repeat 4 

# weights:  103
initial  value 122.197265 
iter  10 value 116.635003
iter  20 value 112.459970
iter  30 value 107.913438
iter  40 value 106.184709
iter  50 value 105.753781
iter  60 value 105.589883
iter  70 value 105.098219
iter  80 value 104.812565
iter  90 value 104.777171
iter 100 value 104.775472
final  value 104.775472 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 122.430202 
iter  10 value 117.892767
iter  20 value 117.813159
iter  30 value 112.581632
iter  40 value 105.161484
iter  50 value 103.131610
iter  60 value 102.670566
iter  70 value 102.326843
iter  80 value 102.325293
iter  80 value 102.325293
iter  80 value 102.325293
final  value 102.325293 
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 -- Sun Apr 19 20:16:23 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 
 19.379   0.683  85.046