##############################################################################
##############################################################################
###
### 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: 2026-04-11 00:37:16 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
var_imp       17.256  0.209  17.688
corr_plot     17.157  0.115  17.344
FSmethod      16.652  0.098  17.052
pred_ensembel  6.137  0.160   5.560
enrichfindP    0.203  0.045  15.299
* 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 96.806503 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 113.829836 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.867211 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.619101 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.178680 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.563527 
iter  10 value 91.444230
iter  20 value 86.619464
iter  30 value 86.579886
iter  40 value 86.405595
iter  50 value 86.399664
final  value 86.399659 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.650963 
iter  10 value 94.484309
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.905535 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.392844 
iter  10 value 93.198667
iter  20 value 91.326767
final  value 91.322383 
converged
Fitting Repeat 5 

# weights:  305
initial  value 112.823833 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.039802 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.807119 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.156948 
iter  10 value 94.122408
iter  20 value 94.102129
final  value 94.102127 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.282233 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.433615 
final  value 94.400000 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.691807 
iter  10 value 94.479585
iter  20 value 87.512230
iter  30 value 86.913346
iter  40 value 84.926707
iter  50 value 84.592689
iter  60 value 84.537681
iter  70 value 84.479597
iter  80 value 84.260510
iter  90 value 84.065893
iter 100 value 84.032113
final  value 84.032113 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.714503 
iter  10 value 94.517564
iter  20 value 94.465602
iter  30 value 94.203141
iter  40 value 85.235637
iter  50 value 84.700867
iter  60 value 83.895224
iter  70 value 83.318702
iter  80 value 83.122143
iter  90 value 83.098924
final  value 83.097258 
converged
Fitting Repeat 3 

# weights:  103
initial  value 117.560659 
iter  10 value 94.639490
iter  20 value 93.727819
iter  30 value 85.203593
iter  40 value 84.564582
iter  50 value 84.471342
iter  60 value 84.454520
iter  70 value 84.142501
iter  80 value 84.046805
iter  90 value 84.012257
final  value 84.012240 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.005340 
iter  10 value 94.478363
iter  20 value 92.609272
iter  30 value 88.545072
iter  40 value 88.328065
iter  50 value 84.600729
iter  60 value 83.166363
iter  70 value 82.558395
iter  80 value 81.335248
iter  90 value 81.092542
iter 100 value 80.796020
final  value 80.796020 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 106.368427 
iter  10 value 94.487497
iter  20 value 94.409795
iter  30 value 91.509791
iter  40 value 88.908310
iter  50 value 86.346586
iter  60 value 85.025003
iter  70 value 84.682132
iter  80 value 84.212650
iter  90 value 83.520389
iter 100 value 83.151919
final  value 83.151919 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 112.850854 
iter  10 value 93.741475
iter  20 value 87.570159
iter  30 value 86.409423
iter  40 value 85.464244
iter  50 value 84.106354
iter  60 value 83.479418
iter  70 value 83.344886
iter  80 value 83.230502
iter  90 value 81.938435
iter 100 value 80.574786
final  value 80.574786 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.877750 
iter  10 value 94.388547
iter  20 value 88.555822
iter  30 value 82.576990
iter  40 value 80.667723
iter  50 value 80.061577
iter  60 value 79.899151
iter  70 value 79.796226
iter  80 value 79.728580
iter  90 value 79.355141
iter 100 value 78.996360
final  value 78.996360 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 124.192540 
iter  10 value 94.495324
iter  20 value 93.301333
iter  30 value 87.177027
iter  40 value 83.914443
iter  50 value 83.684987
iter  60 value 83.491624
iter  70 value 83.059954
iter  80 value 82.259076
iter  90 value 82.056589
iter 100 value 82.051774
final  value 82.051774 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.634450 
iter  10 value 94.539285
iter  20 value 93.999321
iter  30 value 86.840239
iter  40 value 85.864832
iter  50 value 84.321863
iter  60 value 83.009374
iter  70 value 81.966094
iter  80 value 81.652960
iter  90 value 81.540653
iter 100 value 81.473924
final  value 81.473924 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.721098 
iter  10 value 94.389937
iter  20 value 87.132758
iter  30 value 85.060374
iter  40 value 83.964984
iter  50 value 82.860573
iter  60 value 80.973298
iter  70 value 80.871135
iter  80 value 80.855768
iter  90 value 80.582074
iter 100 value 80.436986
final  value 80.436986 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 131.061790 
iter  10 value 97.552279
iter  20 value 91.819699
iter  30 value 87.914960
iter  40 value 84.587049
iter  50 value 83.419968
iter  60 value 81.523679
iter  70 value 81.263655
iter  80 value 80.624178
iter  90 value 80.198182
iter 100 value 79.949819
final  value 79.949819 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.438994 
iter  10 value 94.556315
iter  20 value 90.488665
iter  30 value 83.713333
iter  40 value 81.909601
iter  50 value 81.335474
iter  60 value 80.896685
iter  70 value 80.746283
iter  80 value 80.270098
iter  90 value 79.750033
iter 100 value 79.601294
final  value 79.601294 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.348255 
iter  10 value 93.108902
iter  20 value 86.317664
iter  30 value 81.374498
iter  40 value 80.044130
iter  50 value 79.525745
iter  60 value 78.851275
iter  70 value 78.739689
iter  80 value 78.603908
iter  90 value 78.516124
iter 100 value 78.488620
final  value 78.488620 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.397021 
iter  10 value 99.280878
iter  20 value 90.147372
iter  30 value 85.999205
iter  40 value 82.281494
iter  50 value 82.025573
iter  60 value 80.875056
iter  70 value 80.669609
iter  80 value 80.443164
iter  90 value 80.095302
iter 100 value 79.737599
final  value 79.737599 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.040666 
iter  10 value 94.613768
iter  20 value 94.160516
iter  30 value 86.804670
iter  40 value 84.605939
iter  50 value 83.946888
iter  60 value 82.678152
iter  70 value 82.378478
iter  80 value 82.051479
iter  90 value 81.637169
iter 100 value 80.917013
final  value 80.917013 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.356431 
final  value 94.485979 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.531291 
final  value 94.485588 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.446794 
iter  10 value 94.486190
iter  20 value 94.483838
iter  30 value 84.894694
iter  40 value 83.745276
iter  50 value 83.518939
iter  60 value 83.513611
iter  70 value 83.507301
iter  80 value 83.472480
iter  90 value 83.471193
final  value 83.470772 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.962467 
final  value 94.485578 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.768535 
iter  10 value 94.485843
iter  20 value 94.484303
iter  30 value 94.370263
iter  40 value 94.063374
final  value 94.063369 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.256993 
iter  10 value 94.489251
iter  20 value 94.484258
final  value 94.484241 
converged
Fitting Repeat 2 

# weights:  305
initial  value 110.563579 
iter  10 value 94.489379
iter  20 value 94.484482
iter  30 value 94.096724
iter  40 value 93.860058
iter  50 value 89.843631
iter  60 value 89.808150
iter  70 value 88.004467
iter  80 value 87.953678
iter  90 value 87.952445
iter 100 value 87.911491
final  value 87.911491 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.727101 
iter  10 value 94.489107
iter  20 value 94.189208
iter  30 value 92.092917
iter  40 value 92.087527
final  value 92.087513 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.374979 
iter  10 value 94.390390
iter  20 value 94.131623
iter  30 value 92.546688
iter  40 value 92.442202
iter  50 value 88.105204
iter  60 value 78.807923
iter  70 value 78.320921
iter  80 value 78.219859
iter  90 value 77.972441
iter 100 value 77.823983
final  value 77.823983 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.955066 
iter  10 value 94.283085
iter  20 value 93.606405
iter  30 value 93.604487
iter  40 value 93.602764
iter  50 value 91.311695
iter  60 value 84.366742
iter  70 value 83.555868
iter  80 value 83.032387
iter  90 value 83.032261
final  value 83.032221 
converged
Fitting Repeat 1 

# weights:  507
initial  value 110.953029 
iter  10 value 94.175622
iter  20 value 93.637857
iter  30 value 90.358345
iter  40 value 90.330018
iter  50 value 90.322006
iter  60 value 87.633786
iter  70 value 87.295433
iter  80 value 82.930057
iter  90 value 81.121952
iter 100 value 81.015703
final  value 81.015703 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.732102 
iter  10 value 93.585649
iter  20 value 92.925942
iter  30 value 92.919825
iter  40 value 92.900060
iter  50 value 92.898971
iter  60 value 92.897821
iter  70 value 92.841597
iter  80 value 92.809988
iter  90 value 92.744059
iter 100 value 92.618345
final  value 92.618345 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 118.316526 
iter  10 value 94.474616
iter  20 value 94.208208
iter  30 value 82.240447
iter  40 value 79.351497
iter  50 value 78.394429
iter  60 value 78.231267
iter  70 value 78.175303
iter  80 value 78.163380
iter  90 value 78.162925
final  value 78.162909 
converged
Fitting Repeat 4 

# weights:  507
initial  value 110.541254 
iter  10 value 94.491927
iter  20 value 94.482934
iter  30 value 85.979645
iter  40 value 82.501688
iter  50 value 79.874361
iter  60 value 78.256360
iter  70 value 78.239561
iter  80 value 78.238654
iter  90 value 78.238045
iter 100 value 78.237540
final  value 78.237540 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 102.138885 
iter  10 value 94.492622
iter  20 value 88.556895
iter  30 value 84.829123
final  value 84.824280 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.138995 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.262641 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.549823 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.192866 
final  value 93.935065 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.345145 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.819430 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.207323 
final  value 93.582418 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.257754 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.759371 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 92.434373 
iter  10 value 85.665181
iter  20 value 80.534165
final  value 80.533303 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.725298 
iter  10 value 90.717155
iter  20 value 89.372542
iter  30 value 89.060709
iter  40 value 88.669663
iter  50 value 88.590902
iter  60 value 88.534068
iter  70 value 86.137834
iter  80 value 85.428222
final  value 85.364013 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.083067 
final  value 93.582418 
converged
Fitting Repeat 3 

# weights:  507
initial  value 122.776755 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 114.584630 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.842900 
final  value 94.025289 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.416887 
iter  10 value 93.937708
iter  20 value 93.446840
iter  30 value 85.715602
iter  40 value 84.027461
iter  50 value 83.376766
iter  60 value 81.755116
iter  70 value 79.837764
iter  80 value 79.105958
iter  90 value 78.991263
iter 100 value 78.609481
final  value 78.609481 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.609395 
iter  10 value 94.056681
iter  20 value 93.404544
iter  30 value 85.049762
iter  40 value 82.580424
iter  50 value 82.142629
iter  60 value 81.831613
iter  70 value 81.664200
iter  80 value 81.381456
final  value 81.379342 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.922796 
iter  10 value 94.342220
iter  20 value 88.239099
iter  30 value 85.416149
iter  40 value 83.594468
iter  50 value 83.251603
iter  60 value 83.242690
iter  70 value 83.234138
iter  80 value 83.058966
iter  90 value 82.683662
iter 100 value 80.328699
final  value 80.328699 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 104.040145 
iter  10 value 94.027981
iter  20 value 93.547761
iter  30 value 93.508810
iter  40 value 93.482746
iter  50 value 90.034036
iter  60 value 82.477846
iter  70 value 81.761179
iter  80 value 81.194470
iter  90 value 81.080961
iter 100 value 80.928357
final  value 80.928357 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 105.883305 
iter  10 value 94.055718
iter  20 value 93.614825
iter  30 value 93.458861
iter  40 value 84.775935
iter  50 value 83.982942
iter  60 value 83.074705
iter  70 value 82.312486
iter  80 value 82.169041
iter  90 value 82.103521
iter 100 value 82.073269
final  value 82.073269 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 125.197123 
iter  10 value 93.936960
iter  20 value 93.472099
iter  30 value 93.408565
iter  40 value 92.742277
iter  50 value 84.090635
iter  60 value 83.046889
iter  70 value 81.950920
iter  80 value 81.389645
iter  90 value 81.296536
iter 100 value 81.062707
final  value 81.062707 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.085741 
iter  10 value 94.124587
iter  20 value 91.204261
iter  30 value 83.919700
iter  40 value 83.613289
iter  50 value 81.384436
iter  60 value 79.182194
iter  70 value 78.165982
iter  80 value 77.575262
iter  90 value 77.273535
iter 100 value 77.154358
final  value 77.154358 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.644655 
iter  10 value 93.835587
iter  20 value 81.895330
iter  30 value 81.296948
iter  40 value 80.384730
iter  50 value 79.398657
iter  60 value 78.617213
iter  70 value 78.029836
iter  80 value 77.734454
iter  90 value 77.445186
iter 100 value 77.205113
final  value 77.205113 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.769430 
iter  10 value 94.184341
iter  20 value 93.495667
iter  30 value 93.363672
iter  40 value 85.878926
iter  50 value 85.749086
iter  60 value 85.554239
iter  70 value 81.225204
iter  80 value 79.800319
iter  90 value 79.292389
iter 100 value 79.075992
final  value 79.075992 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 116.145823 
iter  10 value 91.978656
iter  20 value 82.065416
iter  30 value 81.363521
iter  40 value 81.158660
iter  50 value 80.141241
iter  60 value 79.270403
iter  70 value 78.738326
iter  80 value 77.897850
iter  90 value 77.446024
iter 100 value 77.336260
final  value 77.336260 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.728765 
iter  10 value 94.109556
iter  20 value 93.816066
iter  30 value 92.253736
iter  40 value 85.276479
iter  50 value 82.648027
iter  60 value 79.002115
iter  70 value 77.576706
iter  80 value 77.212073
iter  90 value 77.064213
iter 100 value 76.983204
final  value 76.983204 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.048222 
iter  10 value 93.598195
iter  20 value 84.294731
iter  30 value 81.959006
iter  40 value 81.466718
iter  50 value 80.016960
iter  60 value 77.280248
iter  70 value 76.358015
iter  80 value 76.109816
iter  90 value 75.959128
iter 100 value 75.929877
final  value 75.929877 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.613909 
iter  10 value 94.091776
iter  20 value 85.988658
iter  30 value 84.490327
iter  40 value 83.272899
iter  50 value 82.135905
iter  60 value 80.337932
iter  70 value 79.467592
iter  80 value 79.413550
iter  90 value 79.159816
iter 100 value 78.396026
final  value 78.396026 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.940036 
iter  10 value 93.939004
iter  20 value 92.028370
iter  30 value 85.860324
iter  40 value 81.411803
iter  50 value 81.078255
iter  60 value 79.260983
iter  70 value 78.635953
iter  80 value 78.201027
iter  90 value 78.018596
iter 100 value 77.853372
final  value 77.853372 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.639846 
iter  10 value 94.122471
iter  20 value 89.052433
iter  30 value 82.962651
iter  40 value 80.813086
iter  50 value 78.803682
iter  60 value 78.468771
iter  70 value 77.739479
iter  80 value 77.529265
iter  90 value 77.272617
iter 100 value 77.200192
final  value 77.200192 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.611363 
iter  10 value 93.584174
iter  20 value 93.582711
iter  30 value 93.314118
iter  40 value 93.286520
final  value 93.286491 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.548445 
final  value 94.054491 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.733094 
final  value 94.054893 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.316905 
final  value 94.054712 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.031088 
iter  10 value 93.584182
iter  20 value 93.582682
iter  30 value 93.253991
iter  40 value 90.092262
iter  50 value 90.051255
final  value 90.051135 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.550358 
iter  10 value 93.352050
iter  20 value 93.306313
iter  30 value 93.261090
iter  40 value 93.161502
final  value 93.160352 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.420788 
iter  10 value 94.057399
iter  20 value 93.752781
iter  30 value 81.219470
iter  40 value 80.905938
iter  50 value 80.627038
iter  60 value 80.564089
iter  70 value 80.386471
iter  80 value 79.900053
iter  90 value 79.794927
iter 100 value 78.932759
final  value 78.932759 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 95.705995 
iter  10 value 94.057943
iter  20 value 94.053291
iter  30 value 82.604354
iter  40 value 80.585766
final  value 80.584278 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.068362 
iter  10 value 94.057413
iter  20 value 93.298588
iter  30 value 84.265923
iter  40 value 84.263810
final  value 84.261830 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.600172 
iter  10 value 94.057219
iter  20 value 93.455746
final  value 93.342264 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.500315 
iter  10 value 93.590871
iter  20 value 93.350622
iter  30 value 93.343402
iter  40 value 93.340874
iter  50 value 93.305810
iter  60 value 92.025380
iter  70 value 90.945691
iter  80 value 90.940735
iter  90 value 90.940439
iter 100 value 90.939878
final  value 90.939878 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 100.793792 
iter  10 value 93.884926
iter  20 value 93.881693
iter  30 value 92.733629
iter  40 value 92.504264
iter  50 value 92.502862
iter  60 value 91.439431
final  value 90.946631 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.796769 
iter  10 value 94.060136
iter  20 value 91.826281
iter  30 value 80.621126
iter  40 value 80.613960
iter  50 value 80.603817
iter  60 value 80.593627
iter  70 value 80.589764
iter  80 value 80.585413
iter  90 value 80.580735
iter 100 value 80.535606
final  value 80.535606 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 99.234392 
iter  10 value 91.739119
iter  20 value 83.854151
iter  30 value 83.836909
iter  40 value 83.088311
iter  50 value 83.087414
iter  60 value 83.076405
iter  70 value 82.989784
iter  80 value 82.989292
iter  90 value 82.988469
iter 100 value 82.943303
final  value 82.943303 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.869429 
iter  10 value 93.560330
iter  20 value 93.554013
final  value 93.552937 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.286139 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.823052 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.066457 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.014046 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.876422 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.978411 
final  value 94.428839 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.242430 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.617680 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.476342 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  305
initial  value 137.828235 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.638360 
iter  10 value 94.391656
iter  20 value 85.275964
final  value 85.275868 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.457129 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.154510 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 118.266028 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.160051 
iter  10 value 94.106294
iter  20 value 86.736774
iter  30 value 86.734345
final  value 86.733937 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.752756 
iter  10 value 94.480581
iter  20 value 93.293420
iter  30 value 91.557615
iter  40 value 91.496478
iter  50 value 91.428570
iter  60 value 86.741137
iter  70 value 86.135397
iter  80 value 85.468048
iter  90 value 84.928203
iter 100 value 84.820958
final  value 84.820958 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 108.996860 
iter  10 value 94.364731
iter  20 value 92.035994
iter  30 value 88.868735
iter  40 value 86.782262
iter  50 value 86.516633
iter  60 value 84.854114
iter  70 value 84.790858
final  value 84.784275 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.166421 
iter  10 value 94.484989
iter  20 value 93.758807
iter  30 value 90.591878
iter  40 value 89.903700
iter  50 value 87.007299
iter  60 value 86.107760
iter  70 value 85.629597
iter  80 value 84.787453
iter  90 value 84.613834
iter 100 value 84.590472
final  value 84.590472 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 101.244084 
iter  10 value 94.488257
iter  20 value 94.331440
iter  30 value 87.036844
iter  40 value 85.933687
iter  50 value 85.854754
iter  60 value 85.249429
iter  70 value 85.106025
iter  80 value 84.830073
iter  90 value 84.794233
iter 100 value 84.784916
final  value 84.784916 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.872302 
iter  10 value 93.305165
iter  20 value 86.059223
iter  30 value 85.826740
iter  40 value 85.302467
iter  50 value 85.128249
iter  60 value 84.943105
iter  70 value 84.834772
iter  80 value 84.785287
final  value 84.784275 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.111939 
iter  10 value 94.487437
iter  20 value 92.630961
iter  30 value 90.090805
iter  40 value 89.788383
iter  50 value 87.935987
iter  60 value 86.462053
iter  70 value 83.455414
iter  80 value 81.532289
iter  90 value 81.227025
iter 100 value 80.856805
final  value 80.856805 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.372010 
iter  10 value 94.513874
iter  20 value 94.400965
iter  30 value 89.550889
iter  40 value 87.467233
iter  50 value 86.725990
iter  60 value 86.301303
iter  70 value 85.856742
iter  80 value 83.490221
iter  90 value 82.603601
iter 100 value 82.362381
final  value 82.362381 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.279427 
iter  10 value 94.498107
iter  20 value 94.329902
iter  30 value 93.983859
iter  40 value 86.945427
iter  50 value 85.241194
iter  60 value 84.648418
iter  70 value 84.321913
iter  80 value 84.057949
iter  90 value 83.936174
iter 100 value 83.869376
final  value 83.869376 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.555656 
iter  10 value 93.305862
iter  20 value 88.042374
iter  30 value 85.792300
iter  40 value 84.833178
iter  50 value 84.067019
iter  60 value 82.609703
iter  70 value 82.299457
iter  80 value 82.126455
iter  90 value 81.968481
iter 100 value 81.687658
final  value 81.687658 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.225355 
iter  10 value 95.083697
iter  20 value 94.493593
iter  30 value 85.286560
iter  40 value 82.252256
iter  50 value 81.645931
iter  60 value 81.473128
iter  70 value 81.332588
iter  80 value 81.098224
iter  90 value 80.993508
iter 100 value 80.899958
final  value 80.899958 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 126.892791 
iter  10 value 95.000688
iter  20 value 94.326338
iter  30 value 94.225148
iter  40 value 91.468811
iter  50 value 91.386646
iter  60 value 89.750889
iter  70 value 84.704527
iter  80 value 82.224331
iter  90 value 80.995853
iter 100 value 80.816389
final  value 80.816389 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.443472 
iter  10 value 93.979027
iter  20 value 87.740397
iter  30 value 83.301244
iter  40 value 82.854408
iter  50 value 81.959411
iter  60 value 81.491449
iter  70 value 81.424473
iter  80 value 81.188259
iter  90 value 80.916643
iter 100 value 80.820458
final  value 80.820458 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.281081 
iter  10 value 94.571820
iter  20 value 94.471731
iter  30 value 92.408751
iter  40 value 87.177976
iter  50 value 84.528326
iter  60 value 84.264892
iter  70 value 84.120094
iter  80 value 83.444948
iter  90 value 82.167958
iter 100 value 81.712313
final  value 81.712313 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.025838 
iter  10 value 94.771254
iter  20 value 86.167773
iter  30 value 84.835049
iter  40 value 84.780009
iter  50 value 84.300955
iter  60 value 84.148673
iter  70 value 84.022121
iter  80 value 83.919334
iter  90 value 83.899101
iter 100 value 83.640777
final  value 83.640777 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.703716 
iter  10 value 95.482327
iter  20 value 89.682707
iter  30 value 85.799343
iter  40 value 84.481450
iter  50 value 82.702454
iter  60 value 81.935160
iter  70 value 81.379256
iter  80 value 80.848620
iter  90 value 80.627681
iter 100 value 80.569160
final  value 80.569160 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.800094 
final  value 94.485662 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.433426 
final  value 94.486171 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.611531 
iter  10 value 94.485800
iter  20 value 94.484211
iter  30 value 88.757663
iter  40 value 85.511359
iter  50 value 85.509285
iter  60 value 85.096552
iter  70 value 85.077416
final  value 85.077401 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.251233 
final  value 94.485918 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.244234 
final  value 94.313599 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.383487 
iter  10 value 88.762465
iter  20 value 86.328984
iter  30 value 84.522986
iter  40 value 84.521938
final  value 84.521839 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.246963 
iter  10 value 94.435857
iter  20 value 94.418586
iter  30 value 86.668734
iter  40 value 85.293983
iter  50 value 85.289904
iter  60 value 81.848331
iter  70 value 81.097691
iter  80 value 80.910918
iter  90 value 80.815927
iter 100 value 80.808696
final  value 80.808696 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 96.298928 
iter  10 value 94.386951
iter  20 value 94.148953
iter  30 value 94.133502
iter  40 value 94.129339
iter  50 value 94.128928
iter  60 value 93.339027
iter  70 value 93.089402
final  value 93.089396 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.064006 
iter  10 value 94.489087
iter  20 value 94.484224
final  value 94.484214 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.904509 
iter  10 value 94.489131
iter  20 value 94.482786
iter  30 value 84.780112
iter  40 value 84.304174
iter  50 value 84.225089
iter  60 value 84.219834
iter  70 value 82.972585
iter  80 value 82.906696
iter  90 value 82.869954
final  value 82.869746 
converged
Fitting Repeat 1 

# weights:  507
initial  value 112.053891 
iter  10 value 92.496106
iter  20 value 86.283508
iter  30 value 86.280186
iter  40 value 84.928880
iter  50 value 84.662927
iter  60 value 84.652223
final  value 84.652134 
converged
Fitting Repeat 2 

# weights:  507
initial  value 114.766375 
iter  10 value 94.261350
iter  20 value 94.255339
iter  30 value 94.185843
iter  40 value 94.183803
iter  50 value 94.163277
iter  60 value 91.220414
iter  70 value 90.737341
iter  80 value 85.427925
iter  90 value 85.319948
iter 100 value 84.412231
final  value 84.412231 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 100.333580 
iter  10 value 94.491772
iter  20 value 90.014932
iter  30 value 85.776962
iter  40 value 85.258282
iter  50 value 85.173970
iter  60 value 85.142713
iter  70 value 85.142262
iter  80 value 83.876071
iter  90 value 83.599850
iter 100 value 83.588840
final  value 83.588840 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 100.020523 
iter  10 value 94.492744
iter  20 value 94.358803
iter  30 value 88.582219
iter  40 value 88.565115
iter  50 value 87.563536
iter  60 value 86.311877
iter  70 value 84.638402
iter  80 value 83.594226
iter  90 value 82.182923
iter 100 value 81.826563
final  value 81.826563 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.264144 
iter  10 value 94.492084
iter  20 value 94.268746
iter  30 value 87.144227
iter  40 value 86.439149
iter  50 value 86.329083
iter  60 value 86.167069
iter  70 value 86.164284
iter  80 value 86.032780
iter  90 value 83.146694
iter 100 value 81.633441
final  value 81.633441 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.477637 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.608325 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.964685 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.341419 
final  value 94.003143 
converged
Fitting Repeat 5 

# weights:  103
initial  value 113.363818 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.175761 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 111.480178 
final  value 93.836066 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.323783 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.248789 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.426778 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.654407 
final  value 93.836066 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.116214 
final  value 93.371808 
converged
Fitting Repeat 3 

# weights:  507
initial  value 128.587747 
iter  10 value 93.834086
iter  20 value 93.478370
final  value 93.283335 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.207145 
final  value 93.836066 
converged
Fitting Repeat 5 

# weights:  507
initial  value 116.400148 
final  value 93.969040 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.177490 
iter  10 value 94.120742
iter  20 value 94.056019
iter  30 value 93.909882
iter  40 value 93.890421
iter  50 value 93.889541
iter  60 value 92.289597
iter  70 value 86.735487
iter  80 value 86.280416
iter  90 value 86.254046
iter 100 value 86.247965
final  value 86.247965 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 98.105518 
iter  10 value 93.534919
iter  20 value 91.348891
iter  30 value 88.272203
iter  40 value 87.387209
iter  50 value 85.580856
iter  60 value 85.518256
iter  70 value 85.287140
iter  80 value 84.800266
iter  90 value 84.635049
iter 100 value 84.432641
final  value 84.432641 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.229767 
iter  10 value 94.060261
iter  20 value 93.478688
iter  30 value 88.219761
iter  40 value 86.349372
iter  50 value 85.805312
iter  60 value 85.680297
iter  70 value 85.578336
iter  80 value 85.527101
iter  90 value 85.479590
iter 100 value 84.967598
final  value 84.967598 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 98.870205 
iter  10 value 94.056179
iter  20 value 93.281239
iter  30 value 87.946226
iter  40 value 86.561770
iter  50 value 86.315603
iter  60 value 86.160123
iter  70 value 85.908046
iter  80 value 85.855791
iter  90 value 85.174834
iter 100 value 85.058203
final  value 85.058203 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 101.338543 
iter  10 value 93.153421
iter  20 value 87.923897
iter  30 value 87.749644
iter  40 value 87.604992
iter  50 value 87.125906
iter  60 value 85.942142
iter  70 value 85.139366
iter  80 value 84.818711
iter  90 value 84.586630
iter 100 value 84.435131
final  value 84.435131 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 98.254377 
iter  10 value 88.170368
iter  20 value 86.709482
iter  30 value 86.302722
iter  40 value 85.486695
iter  50 value 84.201984
iter  60 value 83.612464
iter  70 value 83.447577
iter  80 value 83.392869
iter  90 value 83.299970
iter 100 value 83.245719
final  value 83.245719 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.877074 
iter  10 value 94.756598
iter  20 value 93.839405
iter  30 value 93.169807
iter  40 value 89.775895
iter  50 value 86.861412
iter  60 value 85.143022
iter  70 value 84.577187
iter  80 value 83.970496
iter  90 value 83.897455
iter 100 value 83.589878
final  value 83.589878 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.552065 
iter  10 value 93.424092
iter  20 value 87.122490
iter  30 value 86.762149
iter  40 value 86.414428
iter  50 value 85.387937
iter  60 value 85.105333
iter  70 value 85.048302
iter  80 value 84.793913
iter  90 value 84.472047
iter 100 value 83.833525
final  value 83.833525 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.316058 
iter  10 value 94.195994
iter  20 value 94.000064
iter  30 value 88.777067
iter  40 value 88.222834
iter  50 value 86.206738
iter  60 value 85.050959
iter  70 value 84.127140
iter  80 value 83.925157
iter  90 value 83.473215
iter 100 value 83.453411
final  value 83.453411 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.786342 
iter  10 value 94.207554
iter  20 value 94.084854
iter  30 value 93.996792
iter  40 value 93.604266
iter  50 value 90.490969
iter  60 value 90.047326
iter  70 value 88.394263
iter  80 value 87.417826
iter  90 value 85.807946
iter 100 value 84.896657
final  value 84.896657 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.122708 
iter  10 value 93.631764
iter  20 value 92.306720
iter  30 value 87.960333
iter  40 value 87.729031
iter  50 value 87.295725
iter  60 value 86.239547
iter  70 value 85.629205
iter  80 value 85.203335
iter  90 value 84.694204
iter 100 value 84.415933
final  value 84.415933 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 154.295790 
iter  10 value 94.236826
iter  20 value 93.901576
iter  30 value 89.742757
iter  40 value 87.322159
iter  50 value 86.028769
iter  60 value 85.580794
iter  70 value 84.679091
iter  80 value 83.791536
iter  90 value 83.415315
iter 100 value 83.317261
final  value 83.317261 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.213018 
iter  10 value 94.615276
iter  20 value 92.712889
iter  30 value 86.727152
iter  40 value 86.075803
iter  50 value 85.014172
iter  60 value 84.536244
iter  70 value 84.367787
iter  80 value 84.234560
iter  90 value 83.946419
iter 100 value 83.674304
final  value 83.674304 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.702356 
iter  10 value 97.918758
iter  20 value 92.321540
iter  30 value 88.177175
iter  40 value 87.085456
iter  50 value 85.475874
iter  60 value 85.325281
iter  70 value 84.927561
iter  80 value 84.891230
iter  90 value 84.479940
iter 100 value 84.195888
final  value 84.195888 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 136.356015 
iter  10 value 94.065611
iter  20 value 92.613612
iter  30 value 92.235954
iter  40 value 90.144452
iter  50 value 88.766962
iter  60 value 87.394357
iter  70 value 85.156966
iter  80 value 84.326154
iter  90 value 83.902914
iter 100 value 83.707987
final  value 83.707987 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.209490 
iter  10 value 93.838035
iter  20 value 93.836871
iter  30 value 93.836264
final  value 93.836255 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.783817 
final  value 94.054527 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.104299 
final  value 94.054631 
converged
Fitting Repeat 4 

# weights:  103
initial  value 109.784540 
final  value 94.054712 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.356745 
final  value 94.054316 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.008621 
iter  10 value 94.057957
iter  20 value 94.053078
iter  30 value 92.154331
iter  40 value 88.933328
iter  50 value 87.640608
iter  60 value 87.585770
iter  70 value 87.574481
iter  80 value 87.554763
iter  90 value 85.675922
iter 100 value 85.570074
final  value 85.570074 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.473106 
iter  10 value 94.057573
iter  20 value 94.052927
final  value 94.052921 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.558709 
iter  10 value 94.057727
iter  20 value 92.928055
iter  30 value 87.414976
iter  40 value 87.410960
final  value 87.410898 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.406801 
iter  10 value 93.973920
iter  20 value 93.879166
iter  30 value 93.834399
final  value 93.834382 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.794968 
iter  10 value 94.057904
iter  20 value 93.223579
iter  30 value 89.033153
iter  40 value 86.481381
iter  50 value 85.493433
iter  60 value 85.432470
iter  70 value 85.408242
iter  80 value 85.407811
iter  90 value 85.406539
iter 100 value 85.248152
final  value 85.248152 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.039897 
iter  10 value 93.667471
iter  20 value 92.708936
iter  30 value 92.680753
iter  40 value 91.917821
iter  50 value 91.904223
iter  60 value 87.054284
iter  70 value 84.673205
iter  80 value 84.672901
iter  90 value 84.660456
iter 100 value 84.404943
final  value 84.404943 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 95.048348 
iter  10 value 93.844099
iter  20 value 93.835957
iter  30 value 93.474433
iter  40 value 93.463145
iter  50 value 93.461992
iter  60 value 93.429608
iter  70 value 93.428348
iter  80 value 93.427868
final  value 93.427842 
converged
Fitting Repeat 3 

# weights:  507
initial  value 124.563668 
iter  10 value 93.845482
iter  20 value 93.650808
iter  30 value 87.650013
iter  40 value 86.751933
iter  50 value 83.689361
iter  60 value 83.219466
iter  70 value 82.390318
iter  80 value 82.284922
iter  90 value 82.064786
iter 100 value 81.804309
final  value 81.804309 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 94.764424 
iter  10 value 93.844387
iter  20 value 93.836545
iter  30 value 93.836176
iter  40 value 93.700367
iter  50 value 87.478529
iter  60 value 87.214702
iter  70 value 83.925712
iter  80 value 82.968262
iter  90 value 82.558223
iter 100 value 82.535278
final  value 82.535278 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 99.647726 
iter  10 value 93.211628
iter  20 value 93.195569
iter  30 value 90.846435
iter  40 value 87.475069
final  value 87.474415 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.710757 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.748778 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.345465 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.785022 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.714642 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.469060 
final  value 94.275362 
converged
Fitting Repeat 2 

# weights:  305
initial  value 111.070706 
iter  10 value 94.365463
iter  10 value 94.365462
iter  10 value 94.365462
final  value 94.365462 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.984313 
iter  10 value 94.442936
final  value 94.442934 
converged
Fitting Repeat 4 

# weights:  305
initial  value 110.922006 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 113.004928 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.661487 
iter  10 value 93.946399
final  value 93.920042 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.722356 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 113.638667 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 111.245255 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.025732 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.458669 
iter  10 value 94.327788
iter  20 value 88.114932
iter  30 value 87.137984
iter  40 value 84.739658
iter  50 value 84.536579
iter  60 value 84.424727
iter  70 value 84.410079
final  value 84.409375 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.374684 
iter  10 value 94.505168
iter  20 value 86.542843
iter  30 value 84.203492
iter  40 value 83.668013
iter  50 value 83.274079
iter  60 value 82.815209
iter  70 value 82.305698
iter  80 value 82.222014
iter  90 value 82.088469
final  value 82.088227 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.125857 
iter  10 value 93.598900
iter  20 value 86.415985
iter  30 value 85.839715
iter  40 value 85.317978
iter  50 value 85.057731
iter  60 value 84.744103
final  value 84.740626 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.968731 
iter  10 value 94.490608
iter  20 value 94.488689
iter  30 value 87.798927
iter  40 value 85.880022
iter  50 value 85.476270
iter  60 value 85.085452
iter  70 value 84.755797
final  value 84.751834 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.260534 
iter  10 value 94.407952
iter  20 value 91.666371
iter  30 value 85.033871
iter  40 value 84.617971
iter  50 value 84.435572
iter  60 value 84.243314
iter  70 value 83.977026
iter  80 value 83.929257
iter  90 value 83.861889
final  value 83.860904 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.847499 
iter  10 value 94.503378
iter  20 value 92.641059
iter  30 value 89.240108
iter  40 value 83.730877
iter  50 value 82.671067
iter  60 value 81.761322
iter  70 value 81.306384
iter  80 value 81.087788
iter  90 value 81.074600
iter 100 value 81.070695
final  value 81.070695 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.505600 
iter  10 value 94.486372
iter  20 value 90.059704
iter  30 value 85.997047
iter  40 value 85.466463
iter  50 value 85.196972
iter  60 value 84.429923
iter  70 value 83.133386
iter  80 value 82.619918
iter  90 value 82.091102
iter 100 value 81.708988
final  value 81.708988 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 117.022436 
iter  10 value 93.699702
iter  20 value 87.761950
iter  30 value 85.159992
iter  40 value 83.840417
iter  50 value 82.219378
iter  60 value 81.900187
iter  70 value 81.751478
iter  80 value 81.542177
iter  90 value 81.468581
iter 100 value 81.219394
final  value 81.219394 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.738448 
iter  10 value 94.460495
iter  20 value 93.588791
iter  30 value 89.504496
iter  40 value 87.879080
iter  50 value 85.641970
iter  60 value 84.492102
iter  70 value 83.952193
iter  80 value 83.827170
iter  90 value 82.636432
iter 100 value 81.321406
final  value 81.321406 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.371927 
iter  10 value 94.480991
iter  20 value 87.155915
iter  30 value 85.183937
iter  40 value 83.579940
iter  50 value 82.231657
iter  60 value 81.102139
iter  70 value 80.924360
iter  80 value 80.702612
iter  90 value 80.608533
iter 100 value 80.595724
final  value 80.595724 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.782609 
iter  10 value 94.523208
iter  20 value 88.834028
iter  30 value 87.679073
iter  40 value 87.093877
iter  50 value 85.854582
iter  60 value 82.966548
iter  70 value 82.186161
iter  80 value 82.060856
iter  90 value 82.006873
iter 100 value 81.986993
final  value 81.986993 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.647061 
iter  10 value 95.844916
iter  20 value 88.437924
iter  30 value 85.859093
iter  40 value 84.559919
iter  50 value 83.165309
iter  60 value 82.619272
iter  70 value 82.244878
iter  80 value 81.911399
iter  90 value 81.155860
iter 100 value 80.698820
final  value 80.698820 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 99.447751 
iter  10 value 94.034524
iter  20 value 89.388753
iter  30 value 84.203143
iter  40 value 82.946828
iter  50 value 82.411655
iter  60 value 82.155284
iter  70 value 81.950557
iter  80 value 81.640063
iter  90 value 81.406568
iter 100 value 81.370244
final  value 81.370244 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.657247 
iter  10 value 94.428519
iter  20 value 90.458806
iter  30 value 89.769042
iter  40 value 88.019837
iter  50 value 85.390313
iter  60 value 82.153091
iter  70 value 81.502993
iter  80 value 81.386168
iter  90 value 81.163437
iter 100 value 81.081494
final  value 81.081494 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 114.075302 
iter  10 value 91.236670
iter  20 value 85.487276
iter  30 value 84.528163
iter  40 value 83.504248
iter  50 value 82.000880
iter  60 value 81.787199
iter  70 value 81.474497
iter  80 value 80.966322
iter  90 value 80.742984
iter 100 value 80.641425
final  value 80.641425 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.669369 
final  value 94.486087 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.069727 
final  value 94.486261 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.352737 
iter  10 value 94.486003
iter  20 value 94.482989
iter  30 value 92.086840
iter  40 value 90.093471
iter  50 value 85.761255
iter  60 value 85.732417
iter  70 value 85.714635
iter  80 value 85.711724
iter  90 value 85.707460
iter 100 value 85.539799
final  value 85.539799 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 107.163885 
final  value 94.485640 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.688558 
final  value 94.485924 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.839469 
iter  10 value 94.489130
iter  20 value 94.484329
iter  30 value 90.348254
iter  40 value 89.146239
iter  50 value 88.871824
iter  60 value 88.056825
iter  60 value 88.056825
iter  60 value 88.056825
final  value 88.056825 
converged
Fitting Repeat 2 

# weights:  305
initial  value 113.422375 
iter  10 value 94.448406
iter  20 value 94.440031
iter  30 value 89.928512
iter  40 value 84.133698
iter  50 value 84.115266
iter  60 value 83.943375
iter  70 value 83.929337
iter  80 value 83.929049
iter  90 value 83.927823
final  value 83.927710 
converged
Fitting Repeat 3 

# weights:  305
initial  value 111.736619 
iter  10 value 94.489100
iter  20 value 94.484485
iter  30 value 94.320285
iter  40 value 89.440083
iter  50 value 84.334596
iter  60 value 83.890315
final  value 83.890255 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.716227 
iter  10 value 94.488881
iter  20 value 94.483887
iter  30 value 90.378508
iter  40 value 89.637501
iter  50 value 89.162129
iter  60 value 89.115460
iter  70 value 89.115129
final  value 89.114985 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.563867 
iter  10 value 94.489118
iter  20 value 94.484273
iter  30 value 91.441502
iter  40 value 85.223131
iter  50 value 85.164932
final  value 85.164828 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.126814 
iter  10 value 94.492489
iter  20 value 94.436859
iter  30 value 86.795318
iter  40 value 84.793555
iter  50 value 84.424186
iter  60 value 84.423588
final  value 84.423583 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.712986 
iter  10 value 94.492891
iter  20 value 93.113656
iter  30 value 84.257676
iter  40 value 83.057270
iter  50 value 82.592920
iter  60 value 82.429682
iter  70 value 82.263171
iter  80 value 82.021045
final  value 82.021044 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.869486 
iter  10 value 94.492229
final  value 94.486906 
converged
Fitting Repeat 4 

# weights:  507
initial  value 116.115755 
iter  10 value 93.443276
iter  20 value 87.315920
iter  30 value 86.667919
iter  40 value 85.423253
iter  50 value 85.414185
iter  60 value 84.144799
iter  70 value 83.862361
iter  80 value 83.842480
iter  90 value 83.830324
iter 100 value 83.826115
final  value 83.826115 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 102.233956 
iter  10 value 94.236298
iter  20 value 94.230934
iter  30 value 86.810422
iter  40 value 84.068608
iter  50 value 83.870246
iter  60 value 83.553574
iter  70 value 83.273789
final  value 83.271923 
converged
Fitting Repeat 1 

# weights:  507
initial  value 134.654595 
iter  10 value 116.789344
iter  20 value 110.585471
iter  30 value 108.029894
iter  40 value 105.829778
iter  50 value 105.535548
iter  60 value 105.342921
iter  70 value 102.994635
iter  80 value 101.625406
iter  90 value 101.473829
iter 100 value 101.421998
final  value 101.421998 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 128.289381 
iter  10 value 114.854518
iter  20 value 112.987174
iter  30 value 110.365410
iter  40 value 104.245573
iter  50 value 103.095479
iter  60 value 102.417773
iter  70 value 101.548500
iter  80 value 101.294309
iter  90 value 100.905000
iter 100 value 100.805554
final  value 100.805554 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 149.805368 
iter  10 value 117.629466
iter  20 value 115.894166
iter  30 value 108.849816
iter  40 value 105.215968
iter  50 value 103.923370
iter  60 value 102.714397
iter  70 value 101.727458
iter  80 value 101.469531
iter  90 value 101.406536
iter 100 value 101.212037
final  value 101.212037 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 132.454163 
iter  10 value 121.804719
iter  20 value 113.108372
iter  30 value 108.457949
iter  40 value 106.783855
iter  50 value 106.003898
iter  60 value 103.963567
iter  70 value 103.417440
iter  80 value 103.296593
iter  90 value 102.640632
iter 100 value 102.341520
final  value 102.341520 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 131.088410 
iter  10 value 109.795592
iter  20 value 106.431934
iter  30 value 105.877796
iter  40 value 103.996119
iter  50 value 102.188582
iter  60 value 101.568294
iter  70 value 101.392701
iter  80 value 101.174310
iter  90 value 100.678370
iter 100 value 100.545867
final  value 100.545867 
stopped after 100 iterations
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 -- Fri Apr 10 20:40:41 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 
 21.708   0.808  85.236