##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings HPiP_1.16.1.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.22-bioc/meat/HPiP.Rcheck’
* using R version 4.5.2 (2025-10-31)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
    GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
* running under: Ubuntu 24.04.3 LTS
* using session charset: UTF-8
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.16.1’
* 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 loading without being on the library search path ... 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     33.723  0.472  34.196
var_imp       32.839  0.631  33.472
FSmethod      32.666  0.433  33.101
pred_ensembel 12.705  0.098  11.521
enrichfindP    0.540  0.045  15.316
* 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 re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE

Status: 2 NOTEs
See
  ‘/home/biocbuild/bbs-3.22-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.22-bioc/R/site-library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.16.1’
** 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 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

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 96.833263 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.758084 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.527545 
iter  10 value 93.582419
final  value 93.582418 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.297623 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 110.237488 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.647443 
iter  10 value 92.555650
iter  20 value 91.691333
iter  30 value 91.632825
final  value 91.631953 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.163569 
iter  10 value 93.410332
final  value 93.410246 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.206441 
iter  10 value 93.582418
iter  10 value 93.582418
iter  10 value 93.582418
final  value 93.582418 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.905377 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.408048 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.624646 
iter  10 value 92.675378
iter  20 value 92.410492
iter  30 value 92.402248
final  value 92.402236 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.077718 
final  value 93.582418 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.200731 
final  value 93.582418 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.630958 
iter  10 value 86.875885
iter  20 value 82.087254
iter  30 value 81.046814
iter  40 value 80.986448
iter  50 value 80.986280
final  value 80.986275 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.932147 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.893710 
iter  10 value 91.487200
iter  20 value 83.553945
iter  30 value 82.252754
iter  40 value 81.858148
iter  50 value 81.524797
iter  60 value 81.442278
iter  70 value 81.436603
final  value 81.436543 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.006987 
iter  10 value 94.195060
iter  20 value 94.047040
iter  30 value 83.679367
iter  40 value 83.430408
iter  50 value 81.934798
iter  60 value 81.832011
iter  70 value 81.824407
final  value 81.824398 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.299177 
iter  10 value 94.054830
iter  20 value 87.644732
iter  30 value 83.375825
iter  40 value 81.972236
iter  50 value 81.850929
iter  60 value 81.825187
final  value 81.824398 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.917928 
iter  10 value 94.025809
iter  20 value 93.637138
iter  30 value 93.527745
iter  40 value 93.483728
iter  50 value 83.318120
iter  60 value 80.998011
iter  70 value 80.752816
iter  80 value 79.432141
iter  90 value 78.273179
iter 100 value 77.976307
final  value 77.976307 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 96.431080 
iter  10 value 93.977075
iter  20 value 92.776087
iter  30 value 90.485455
iter  40 value 90.401460
iter  50 value 86.047411
iter  60 value 82.741505
iter  70 value 79.515822
iter  80 value 79.433550
iter  90 value 78.728911
iter 100 value 78.300371
final  value 78.300371 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 113.599365 
iter  10 value 93.965803
iter  20 value 84.297425
iter  30 value 83.562627
iter  40 value 81.776251
iter  50 value 81.639452
iter  60 value 81.498941
iter  70 value 81.025232
iter  80 value 80.046236
iter  90 value 78.593094
iter 100 value 78.175521
final  value 78.175521 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.789472 
iter  10 value 94.645153
iter  20 value 93.981982
iter  30 value 93.648159
iter  40 value 86.251637
iter  50 value 83.716209
iter  60 value 82.112740
iter  70 value 80.104253
iter  80 value 79.627950
iter  90 value 79.288797
iter 100 value 77.843493
final  value 77.843493 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.089757 
iter  10 value 94.238407
iter  20 value 93.534374
iter  30 value 92.616154
iter  40 value 86.601522
iter  50 value 84.847566
iter  60 value 84.395009
iter  70 value 83.962583
iter  80 value 81.307735
iter  90 value 80.749775
iter 100 value 79.151085
final  value 79.151085 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.418648 
iter  10 value 94.516164
iter  20 value 93.424244
iter  30 value 88.509281
iter  40 value 87.901494
iter  50 value 86.777633
iter  60 value 81.540223
iter  70 value 79.090697
iter  80 value 78.729308
iter  90 value 78.437022
iter 100 value 78.345252
final  value 78.345252 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.342809 
iter  10 value 93.844117
iter  20 value 89.547805
iter  30 value 88.049697
iter  40 value 82.975509
iter  50 value 80.613064
iter  60 value 79.682091
iter  70 value 78.842094
iter  80 value 78.548771
iter  90 value 77.956077
iter 100 value 77.478579
final  value 77.478579 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.753658 
iter  10 value 93.619386
iter  20 value 93.060702
iter  30 value 92.892417
iter  40 value 91.398893
iter  50 value 89.516272
iter  60 value 85.885617
iter  70 value 85.050094
iter  80 value 84.132529
iter  90 value 80.309347
iter 100 value 78.343442
final  value 78.343442 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 119.061374 
iter  10 value 93.992847
iter  20 value 83.979269
iter  30 value 81.855124
iter  40 value 79.813396
iter  50 value 78.449324
iter  60 value 77.922454
iter  70 value 77.017259
iter  80 value 76.697803
iter  90 value 76.555220
iter 100 value 76.425101
final  value 76.425101 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.464425 
iter  10 value 94.129515
iter  20 value 93.617116
iter  30 value 93.011940
iter  40 value 88.619716
iter  50 value 86.050712
iter  60 value 85.242663
iter  70 value 84.130340
iter  80 value 79.935226
iter  90 value 78.003078
iter 100 value 77.222552
final  value 77.222552 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 115.839863 
iter  10 value 94.125493
iter  20 value 90.926145
iter  30 value 87.839401
iter  40 value 85.709892
iter  50 value 85.313501
iter  60 value 84.626327
iter  70 value 82.747980
iter  80 value 81.798354
iter  90 value 81.270298
iter 100 value 80.294125
final  value 80.294125 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.184430 
iter  10 value 95.769607
iter  20 value 93.706512
iter  30 value 92.543572
iter  40 value 87.365844
iter  50 value 81.166957
iter  60 value 80.639489
iter  70 value 79.003408
iter  80 value 78.685142
iter  90 value 78.363597
iter 100 value 78.284668
final  value 78.284668 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 110.592472 
final  value 94.054401 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.844331 
final  value 94.054562 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.479112 
final  value 94.054403 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.085354 
iter  10 value 93.412239
iter  20 value 93.406672
final  value 93.291889 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.843999 
final  value 94.054476 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.205623 
iter  10 value 93.494261
iter  20 value 93.469356
iter  30 value 93.465605
iter  40 value 92.909575
iter  50 value 83.340889
iter  60 value 80.652790
iter  70 value 80.591652
iter  80 value 80.556482
iter  90 value 80.554275
iter 100 value 80.546670
final  value 80.546670 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 95.949723 
iter  10 value 93.435423
iter  20 value 93.415416
iter  30 value 93.410781
iter  40 value 92.481597
iter  50 value 84.567844
iter  60 value 84.564650
iter  70 value 84.525225
iter  80 value 82.439510
iter  90 value 81.820642
iter 100 value 81.818793
final  value 81.818793 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 96.305628 
iter  10 value 94.056435
iter  20 value 93.639149
iter  30 value 93.464612
final  value 93.464606 
converged
Fitting Repeat 4 

# weights:  305
initial  value 122.756504 
iter  10 value 93.587415
iter  20 value 93.583341
final  value 93.582821 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.412675 
iter  10 value 92.571791
iter  20 value 92.253174
iter  30 value 92.251469
iter  40 value 91.068480
iter  50 value 89.377936
iter  60 value 89.259782
iter  70 value 89.149113
iter  80 value 89.148359
iter  90 value 89.147524
final  value 89.147405 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.347352 
iter  10 value 94.060923
iter  20 value 86.622271
iter  30 value 82.307557
iter  40 value 82.269662
iter  50 value 82.231026
iter  60 value 82.165968
iter  70 value 82.165174
iter  80 value 79.881467
iter  90 value 79.655157
iter 100 value 79.217953
final  value 79.217953 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 100.948276 
iter  10 value 84.913319
iter  20 value 84.176445
iter  30 value 84.173626
iter  40 value 83.145889
iter  50 value 82.900234
iter  60 value 82.897861
final  value 82.890831 
converged
Fitting Repeat 3 

# weights:  507
initial  value 112.870926 
iter  10 value 94.061004
iter  20 value 94.045242
iter  30 value 93.319485
iter  40 value 83.444136
iter  50 value 78.093301
iter  60 value 77.442572
iter  70 value 77.417893
iter  80 value 77.408221
iter  90 value 77.400678
iter 100 value 77.382739
final  value 77.382739 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 118.653444 
iter  10 value 93.591196
iter  20 value 93.560511
iter  30 value 93.162763
iter  40 value 90.076156
iter  50 value 85.426956
iter  60 value 83.419342
iter  70 value 83.295298
iter  80 value 83.295029
iter  90 value 83.293499
iter  90 value 83.293499
final  value 83.293446 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.396320 
iter  10 value 93.962667
iter  20 value 93.952803
iter  30 value 93.172623
iter  40 value 84.781790
iter  50 value 83.936822
iter  60 value 83.936368
iter  60 value 83.936368
iter  60 value 83.936367
final  value 83.936367 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.475260 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.777537 
iter  10 value 94.484255
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.538843 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.349090 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.238426 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.165682 
iter  10 value 94.291920
final  value 94.291893 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.920930 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.506908 
iter  10 value 91.458835
final  value 91.404237 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.911412 
iter  10 value 94.291892
iter  10 value 94.291892
iter  10 value 94.291892
final  value 94.291892 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.449549 
final  value 94.291892 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.538688 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.230770 
final  value 94.473119 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.560099 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 108.316949 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.835812 
final  value 94.322896 
converged
Fitting Repeat 1 

# weights:  103
initial  value 109.171714 
iter  10 value 94.492030
iter  20 value 94.439028
iter  30 value 93.424472
iter  40 value 91.826714
iter  50 value 90.515102
iter  60 value 90.396118
iter  70 value 89.250231
iter  80 value 83.128479
iter  90 value 81.660917
iter 100 value 81.153047
final  value 81.153047 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 98.448730 
iter  10 value 94.488490
iter  20 value 94.415243
iter  30 value 92.880249
iter  40 value 87.792919
iter  50 value 82.488182
iter  60 value 81.633925
iter  70 value 81.202916
iter  80 value 80.846328
iter  90 value 80.667390
final  value 80.667363 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.087383 
iter  10 value 94.486877
iter  20 value 94.486612
iter  30 value 86.646375
iter  40 value 84.878162
iter  50 value 84.541099
iter  60 value 84.322372
iter  70 value 83.468757
iter  80 value 83.279532
iter  90 value 83.127351
iter 100 value 82.694542
final  value 82.694542 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 98.730432 
iter  10 value 93.865046
iter  20 value 90.516530
iter  30 value 88.914898
iter  40 value 85.180063
iter  50 value 83.310795
iter  60 value 82.873323
iter  70 value 82.830916
iter  80 value 82.699723
final  value 82.693747 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.826887 
iter  10 value 94.488455
iter  20 value 86.517317
iter  30 value 85.058888
iter  40 value 84.658996
iter  50 value 84.382794
iter  60 value 82.631854
iter  70 value 82.407116
iter  80 value 82.283455
iter  90 value 82.247317
final  value 82.243180 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.344279 
iter  10 value 94.844963
iter  20 value 92.398188
iter  30 value 90.377167
iter  40 value 88.554632
iter  50 value 83.153193
iter  60 value 82.848089
iter  70 value 81.564642
iter  80 value 81.159253
iter  90 value 80.873798
iter 100 value 80.828823
final  value 80.828823 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 118.945780 
iter  10 value 89.891707
iter  20 value 86.391242
iter  30 value 85.699204
iter  40 value 83.156050
iter  50 value 80.273203
iter  60 value 79.821739
iter  70 value 79.572500
iter  80 value 79.533318
iter  90 value 79.514306
iter 100 value 79.503382
final  value 79.503382 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 111.190195 
iter  10 value 94.126957
iter  20 value 85.361674
iter  30 value 84.163379
iter  40 value 82.822881
iter  50 value 80.416767
iter  60 value 79.880492
iter  70 value 79.483264
iter  80 value 79.393020
iter  90 value 79.380563
iter 100 value 79.372625
final  value 79.372625 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.371001 
iter  10 value 93.913418
iter  20 value 84.833847
iter  30 value 84.225103
iter  40 value 81.996982
iter  50 value 81.133746
iter  60 value 80.398878
iter  70 value 80.234044
iter  80 value 79.808777
iter  90 value 79.528306
iter 100 value 79.393687
final  value 79.393687 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.072156 
iter  10 value 94.477735
iter  20 value 91.853271
iter  30 value 90.393086
iter  40 value 86.090339
iter  50 value 83.898248
iter  60 value 82.321612
iter  70 value 81.394274
iter  80 value 81.035466
iter  90 value 80.939598
iter 100 value 80.591526
final  value 80.591526 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.848010 
iter  10 value 95.052751
iter  20 value 91.065203
iter  30 value 88.522720
iter  40 value 84.616498
iter  50 value 83.660290
iter  60 value 82.968902
iter  70 value 82.263358
iter  80 value 81.367068
iter  90 value 80.208143
iter 100 value 79.463472
final  value 79.463472 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.429936 
iter  10 value 94.901787
iter  20 value 89.736555
iter  30 value 86.640706
iter  40 value 85.706674
iter  50 value 84.572598
iter  60 value 83.530003
iter  70 value 81.733039
iter  80 value 80.145420
iter  90 value 79.534555
iter 100 value 79.129587
final  value 79.129587 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.091864 
iter  10 value 92.103468
iter  20 value 84.806384
iter  30 value 84.204662
iter  40 value 84.089506
iter  50 value 83.856976
iter  60 value 81.938607
iter  70 value 81.214623
iter  80 value 80.940262
iter  90 value 80.766251
iter 100 value 80.734247
final  value 80.734247 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.327316 
iter  10 value 94.540827
iter  20 value 87.971323
iter  30 value 84.328307
iter  40 value 83.961396
iter  50 value 83.835905
iter  60 value 83.552476
iter  70 value 82.022980
iter  80 value 81.468775
iter  90 value 81.369655
iter 100 value 81.347137
final  value 81.347137 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 112.075827 
iter  10 value 92.940991
iter  20 value 84.756715
iter  30 value 84.002474
iter  40 value 82.782258
iter  50 value 82.614917
iter  60 value 82.532001
iter  70 value 82.096468
iter  80 value 80.773709
iter  90 value 80.034270
iter 100 value 79.834067
final  value 79.834067 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.246784 
final  value 94.486125 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.209716 
final  value 94.485773 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.170471 
iter  10 value 94.485875
iter  20 value 94.420332
iter  30 value 90.796147
iter  40 value 90.789560
final  value 90.789524 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.558227 
final  value 94.485884 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.963228 
final  value 94.485773 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.826465 
iter  10 value 94.484735
iter  20 value 93.155715
iter  30 value 84.371168
final  value 84.371164 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.786459 
iter  10 value 94.487560
iter  20 value 94.467487
iter  30 value 86.186097
iter  40 value 82.169750
iter  50 value 82.167893
iter  60 value 80.528664
iter  70 value 79.781312
iter  80 value 79.489934
iter  90 value 79.250903
iter 100 value 78.650866
final  value 78.650866 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 107.463148 
iter  10 value 94.488703
iter  20 value 94.443772
iter  30 value 90.776405
iter  40 value 83.862452
iter  50 value 83.163218
iter  60 value 83.158782
iter  70 value 83.157153
iter  70 value 83.157153
final  value 83.157153 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.847062 
iter  10 value 94.490079
iter  20 value 94.489252
iter  30 value 94.432671
iter  40 value 91.880395
iter  50 value 91.873433
iter  60 value 91.872286
iter  70 value 89.502591
iter  80 value 83.775905
iter  90 value 82.729180
iter 100 value 82.727651
final  value 82.727651 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.427201 
iter  10 value 94.489321
iter  20 value 94.342856
iter  30 value 83.619439
iter  40 value 80.520986
iter  50 value 79.907966
iter  60 value 79.659208
iter  70 value 79.367585
iter  80 value 78.592633
iter  90 value 78.275033
iter 100 value 78.265706
final  value 78.265706 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 96.793372 
iter  10 value 94.300037
iter  20 value 93.783259
iter  30 value 84.051813
iter  40 value 82.719321
iter  50 value 82.690787
iter  60 value 82.689772
iter  70 value 80.045343
iter  80 value 79.185792
iter  90 value 78.327797
iter 100 value 78.310590
final  value 78.310590 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 118.191086 
iter  10 value 94.495271
iter  20 value 94.433188
iter  30 value 88.772659
iter  40 value 85.931847
iter  50 value 84.709887
iter  60 value 83.201530
iter  70 value 82.986479
iter  80 value 82.893305
iter  90 value 82.892225
iter 100 value 82.870545
final  value 82.870545 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 116.204701 
iter  10 value 94.330501
iter  20 value 92.940745
iter  30 value 83.830213
iter  40 value 83.594280
final  value 83.594215 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.125080 
iter  10 value 94.492204
iter  20 value 94.216557
iter  30 value 87.926965
iter  40 value 83.340128
iter  50 value 83.221152
iter  60 value 82.163827
iter  70 value 82.133226
iter  80 value 82.132510
iter  90 value 82.130037
iter 100 value 81.943277
final  value 81.943277 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.761936 
iter  10 value 94.487743
iter  20 value 94.431443
iter  30 value 86.066751
iter  40 value 85.412211
iter  50 value 83.808390
iter  60 value 83.710701
iter  70 value 83.706741
iter  80 value 83.675496
iter  90 value 83.674199
iter 100 value 80.288792
final  value 80.288792 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.901332 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.939935 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.840054 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.723450 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.101353 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.315738 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.018629 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.870845 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.885214 
final  value 94.484210 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.985233 
final  value 93.772974 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.065983 
iter  10 value 93.619082
iter  20 value 90.793627
iter  30 value 90.788892
iter  40 value 90.788413
final  value 90.788412 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.003091 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.552587 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 107.354191 
iter  10 value 93.879452
iter  20 value 89.790613
iter  30 value 89.377253
iter  40 value 89.025470
iter  50 value 89.020668
final  value 89.020652 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.671734 
iter  10 value 93.806339
final  value 93.772973 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.643770 
iter  10 value 93.733687
iter  20 value 92.679976
iter  30 value 84.552421
iter  40 value 84.087766
iter  50 value 83.192742
iter  60 value 82.623476
iter  70 value 82.231633
iter  80 value 82.054390
iter  80 value 82.054390
iter  80 value 82.054390
final  value 82.054390 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.610616 
iter  10 value 94.444813
iter  20 value 93.638896
iter  30 value 92.907028
iter  40 value 86.545286
iter  50 value 85.469283
iter  60 value 84.032261
iter  70 value 83.912917
iter  80 value 82.886153
iter  90 value 82.194397
iter 100 value 82.054394
final  value 82.054394 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.365798 
iter  10 value 93.745049
iter  20 value 86.115514
iter  30 value 85.616953
iter  40 value 85.340685
iter  50 value 83.789333
iter  60 value 82.459218
iter  70 value 82.149727
iter  80 value 82.054393
final  value 82.054390 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.630277 
iter  10 value 94.486598
iter  20 value 94.394336
iter  30 value 93.981138
iter  40 value 93.977004
iter  50 value 93.701365
iter  60 value 93.040972
iter  70 value 86.252705
iter  80 value 85.846907
iter  90 value 84.746191
iter 100 value 84.541370
final  value 84.541370 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 116.773739 
iter  10 value 94.557149
iter  20 value 94.393993
iter  30 value 94.082288
iter  40 value 91.836437
iter  50 value 84.657085
iter  60 value 84.051584
iter  70 value 83.837388
iter  80 value 83.218882
iter  90 value 82.412392
iter 100 value 82.106017
final  value 82.106017 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 106.918032 
iter  10 value 93.665583
iter  20 value 86.332057
iter  30 value 83.463872
iter  40 value 83.095406
iter  50 value 82.882185
iter  60 value 82.496493
iter  70 value 82.351008
iter  80 value 81.938333
iter  90 value 81.856659
iter 100 value 81.761869
final  value 81.761869 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.246304 
iter  10 value 94.521307
iter  20 value 94.401108
iter  30 value 93.594132
iter  40 value 87.693486
iter  50 value 84.799499
iter  60 value 83.488986
iter  70 value 83.286165
iter  80 value 82.776009
iter  90 value 82.557338
iter 100 value 82.236814
final  value 82.236814 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.666619 
iter  10 value 93.828628
iter  20 value 87.307915
iter  30 value 82.907947
iter  40 value 82.138458
iter  50 value 81.445142
iter  60 value 81.157569
iter  70 value 80.986079
iter  80 value 80.777691
iter  90 value 80.694382
iter 100 value 80.541324
final  value 80.541324 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.183181 
iter  10 value 94.607718
iter  20 value 89.680372
iter  30 value 85.834495
iter  40 value 84.879300
iter  50 value 84.244357
iter  60 value 84.205445
iter  70 value 83.989623
iter  80 value 82.971881
iter  90 value 81.808504
iter 100 value 81.171928
final  value 81.171928 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.182696 
iter  10 value 94.450366
iter  20 value 92.460493
iter  30 value 84.788395
iter  40 value 83.908502
iter  50 value 81.858971
iter  60 value 81.286832
iter  70 value 81.160623
iter  80 value 81.126983
iter  90 value 81.098041
iter 100 value 81.084834
final  value 81.084834 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.231937 
iter  10 value 94.247553
iter  20 value 87.785995
iter  30 value 86.261523
iter  40 value 85.070836
iter  50 value 83.784207
iter  60 value 83.650209
iter  70 value 83.481745
iter  80 value 82.207611
iter  90 value 81.137434
iter 100 value 81.027258
final  value 81.027258 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 126.179629 
iter  10 value 93.310007
iter  20 value 88.719508
iter  30 value 86.733530
iter  40 value 84.522161
iter  50 value 83.680320
iter  60 value 82.689208
iter  70 value 82.307696
iter  80 value 82.198087
iter  90 value 81.656046
iter 100 value 81.417835
final  value 81.417835 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.162183 
iter  10 value 93.686655
iter  20 value 89.439555
iter  30 value 85.998635
iter  40 value 84.743945
iter  50 value 82.984125
iter  60 value 81.865596
iter  70 value 81.675559
iter  80 value 81.429633
iter  90 value 81.088128
iter 100 value 80.952558
final  value 80.952558 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 124.730965 
iter  10 value 94.186466
iter  20 value 90.490640
iter  30 value 88.747866
iter  40 value 86.476498
iter  50 value 85.801842
iter  60 value 84.602060
iter  70 value 83.285256
iter  80 value 83.006856
iter  90 value 82.041251
iter 100 value 81.401804
final  value 81.401804 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.743729 
iter  10 value 94.321636
iter  20 value 90.661037
iter  30 value 87.217977
iter  40 value 84.745191
iter  50 value 82.915657
iter  60 value 81.490020
iter  70 value 81.371605
iter  80 value 81.132706
iter  90 value 80.812041
iter 100 value 80.716827
final  value 80.716827 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.384368 
iter  10 value 93.825751
final  value 93.774851 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.099726 
final  value 93.638729 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.587710 
final  value 94.485904 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.071423 
final  value 94.485648 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.259171 
final  value 94.486126 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.255409 
iter  10 value 94.489121
iter  20 value 94.484932
iter  30 value 93.774114
final  value 93.774093 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.092242 
iter  10 value 94.489396
iter  20 value 94.484637
iter  30 value 93.670640
iter  40 value 93.491327
iter  50 value 85.787731
iter  60 value 83.103693
iter  70 value 82.713318
iter  80 value 81.852443
iter  90 value 81.270760
iter 100 value 81.219718
final  value 81.219718 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 97.170513 
iter  10 value 93.398150
iter  20 value 93.390054
iter  30 value 93.388143
iter  40 value 93.387771
iter  50 value 93.382582
iter  60 value 86.102385
iter  70 value 85.905353
iter  80 value 85.902139
iter  90 value 85.902055
iter  90 value 85.902055
final  value 85.902055 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.790966 
iter  10 value 94.328143
iter  20 value 92.584520
iter  30 value 85.490332
iter  40 value 85.490008
iter  50 value 85.463950
iter  60 value 85.462646
iter  70 value 85.462203
final  value 85.462136 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.421563 
iter  10 value 94.489987
iter  20 value 94.449574
iter  30 value 91.030260
iter  40 value 85.679245
iter  50 value 85.638503
iter  60 value 85.601688
iter  70 value 85.597089
iter  80 value 85.581731
iter  90 value 85.577673
iter 100 value 85.577111
final  value 85.577111 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 100.661910 
iter  10 value 93.575569
iter  20 value 93.509252
iter  30 value 93.374271
final  value 93.374264 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.267958 
iter  10 value 93.575974
iter  20 value 90.838508
iter  30 value 85.448920
iter  40 value 85.431699
iter  50 value 82.677492
iter  60 value 82.133554
iter  70 value 80.706719
iter  80 value 80.653671
iter  90 value 80.588538
iter 100 value 80.584775
final  value 80.584775 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 94.594535 
iter  10 value 91.330986
iter  20 value 91.328256
iter  30 value 90.740520
iter  40 value 89.036159
iter  50 value 87.830536
iter  60 value 87.829958
iter  70 value 87.828411
iter  80 value 86.468774
iter  90 value 85.376017
final  value 85.375922 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.827085 
iter  10 value 93.783348
iter  20 value 93.781711
iter  30 value 92.394401
iter  40 value 87.225521
iter  50 value 87.170133
iter  60 value 86.500094
iter  70 value 84.017077
iter  80 value 83.579540
iter  90 value 83.185245
iter 100 value 83.053131
final  value 83.053131 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.697883 
iter  10 value 94.492911
iter  20 value 94.138674
iter  30 value 93.774361
final  value 93.774266 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.132960 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.988715 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.515679 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 109.627977 
iter  10 value 93.941612
final  value 93.809648 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.751875 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.083817 
iter  10 value 94.354396
iter  10 value 94.354396
iter  10 value 94.354396
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  305
initial  value 116.792613 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.009339 
final  value 94.354395 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.456536 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.028944 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.648145 
iter  10 value 90.707086
iter  20 value 88.328738
iter  30 value 88.250806
iter  40 value 87.114158
final  value 87.113878 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.158148 
iter  10 value 94.243406
iter  20 value 85.171456
iter  30 value 84.479679
iter  40 value 84.128286
iter  50 value 84.119834
final  value 84.119780 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.012699 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 110.949998 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.753030 
final  value 94.353550 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.907574 
iter  10 value 94.453264
iter  20 value 94.173305
iter  30 value 94.148377
iter  40 value 93.925881
iter  50 value 87.619465
iter  60 value 84.166228
iter  70 value 83.825780
iter  80 value 83.613686
iter  90 value 82.768049
iter 100 value 81.971542
final  value 81.971542 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 100.976396 
iter  10 value 94.492894
iter  20 value 91.389331
iter  30 value 86.211990
iter  40 value 85.422080
iter  50 value 85.216052
iter  60 value 85.184318
iter  70 value 85.182870
iter  80 value 84.200931
iter  90 value 83.858884
iter 100 value 83.782463
final  value 83.782463 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.009965 
iter  10 value 94.411711
iter  20 value 93.998343
iter  30 value 90.150682
iter  40 value 84.714002
iter  50 value 84.387562
iter  60 value 83.609063
iter  70 value 82.915550
iter  80 value 82.236225
iter  90 value 82.196036
iter 100 value 82.159943
final  value 82.159943 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 104.328747 
iter  10 value 94.486831
iter  20 value 94.260404
iter  30 value 94.051410
iter  40 value 93.850927
iter  50 value 88.722076
iter  60 value 85.054669
iter  70 value 84.657548
iter  80 value 84.315459
iter  90 value 83.154164
iter 100 value 82.236708
final  value 82.236708 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 108.361943 
iter  10 value 94.256458
iter  20 value 92.228726
iter  30 value 91.721657
iter  40 value 91.661366
iter  50 value 91.660740
final  value 91.660737 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.885049 
iter  10 value 94.488302
iter  20 value 94.471456
iter  30 value 87.714445
iter  40 value 86.194262
iter  50 value 85.283249
iter  60 value 84.086930
iter  70 value 83.855520
iter  80 value 82.281201
iter  90 value 81.521380
iter 100 value 81.122974
final  value 81.122974 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.244376 
iter  10 value 93.997067
iter  20 value 93.818626
iter  30 value 90.269949
iter  40 value 89.148233
iter  50 value 86.124659
iter  60 value 84.880020
iter  70 value 83.146502
iter  80 value 81.758916
iter  90 value 81.021090
iter 100 value 80.893260
final  value 80.893260 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.297189 
iter  10 value 94.452320
iter  20 value 92.669528
iter  30 value 85.512910
iter  40 value 82.239432
iter  50 value 81.964783
iter  60 value 81.820222
iter  70 value 81.459843
iter  80 value 81.078244
iter  90 value 80.717000
iter 100 value 80.573196
final  value 80.573196 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 121.173469 
iter  10 value 95.897040
iter  20 value 94.429090
iter  30 value 93.350534
iter  40 value 87.130847
iter  50 value 86.382046
iter  60 value 85.939224
iter  70 value 85.342422
iter  80 value 83.791235
iter  90 value 83.144531
iter 100 value 81.879839
final  value 81.879839 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.829299 
iter  10 value 93.749580
iter  20 value 84.993538
iter  30 value 84.341286
iter  40 value 83.815230
iter  50 value 82.818502
iter  60 value 82.128623
iter  70 value 81.940374
iter  80 value 81.832468
iter  90 value 81.781580
iter 100 value 81.603028
final  value 81.603028 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.251591 
iter  10 value 94.476884
iter  20 value 88.213981
iter  30 value 86.096256
iter  40 value 85.979023
iter  50 value 85.628497
iter  60 value 84.564686
iter  70 value 82.553773
iter  80 value 81.442600
iter  90 value 81.291018
iter 100 value 81.137834
final  value 81.137834 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.953661 
iter  10 value 94.753704
iter  20 value 93.424763
iter  30 value 85.632947
iter  40 value 82.827387
iter  50 value 82.421450
iter  60 value 81.900132
iter  70 value 81.562830
iter  80 value 80.883423
iter  90 value 80.743940
iter 100 value 80.440677
final  value 80.440677 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 125.354827 
iter  10 value 97.949104
iter  20 value 94.165230
iter  30 value 93.750412
iter  40 value 88.544372
iter  50 value 84.769694
iter  60 value 83.609337
iter  70 value 83.102615
iter  80 value 82.475857
iter  90 value 82.351437
iter 100 value 82.172017
final  value 82.172017 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.916948 
iter  10 value 94.488939
iter  20 value 92.579924
iter  30 value 91.715256
iter  40 value 87.378105
iter  50 value 85.124892
iter  60 value 83.292623
iter  70 value 82.972306
iter  80 value 82.480978
iter  90 value 81.720271
iter 100 value 80.928682
final  value 80.928682 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 125.770396 
iter  10 value 94.689201
iter  20 value 91.525170
iter  30 value 86.502993
iter  40 value 83.463074
iter  50 value 81.897295
iter  60 value 81.037860
iter  70 value 80.902522
iter  80 value 80.791872
iter  90 value 80.758062
iter 100 value 80.685924
final  value 80.685924 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.568450 
iter  10 value 93.212232
iter  20 value 93.076292
iter  30 value 93.043034
iter  40 value 88.495800
iter  50 value 88.251423
iter  60 value 86.040859
iter  70 value 85.529663
iter  80 value 85.490369
iter  90 value 85.490186
iter 100 value 85.489054
final  value 85.489054 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 102.822795 
iter  10 value 94.356348
iter  20 value 94.354507
iter  30 value 94.282419
iter  40 value 85.513580
iter  50 value 85.511985
iter  60 value 85.510861
iter  70 value 85.510401
iter  80 value 84.658393
iter  90 value 84.123983
iter 100 value 84.121090
final  value 84.121090 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 109.689149 
iter  10 value 94.485693
iter  20 value 94.484290
final  value 94.484218 
converged
Fitting Repeat 4 

# weights:  103
initial  value 115.618325 
iter  10 value 94.485998
final  value 94.484246 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.155327 
iter  10 value 94.485635
iter  10 value 94.485634
iter  10 value 94.485633
final  value 94.485633 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.624958 
iter  10 value 94.489196
iter  20 value 94.357962
final  value 93.810152 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.537303 
iter  10 value 94.485331
iter  20 value 94.478040
iter  30 value 93.938679
iter  40 value 93.753479
final  value 93.753315 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.435352 
iter  10 value 94.488907
iter  20 value 94.484288
iter  30 value 93.439958
iter  40 value 91.934665
iter  50 value 91.922143
iter  60 value 88.447747
iter  70 value 84.700587
iter  80 value 84.150707
iter  90 value 83.559156
iter 100 value 82.695054
final  value 82.695054 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 97.129588 
iter  10 value 94.489150
iter  20 value 92.855751
iter  30 value 90.580085
iter  40 value 90.556554
final  value 90.556540 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.328496 
iter  10 value 92.120613
iter  20 value 86.670015
iter  30 value 86.634095
iter  40 value 86.595950
iter  50 value 83.758935
iter  60 value 82.851823
iter  70 value 81.132257
iter  80 value 80.231132
iter  90 value 80.170115
iter 100 value 80.150610
final  value 80.150610 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 96.914734 
iter  10 value 94.120523
iter  20 value 94.109167
iter  30 value 94.107309
iter  40 value 91.844557
iter  50 value 91.055337
iter  60 value 91.052605
iter  70 value 91.050739
iter  80 value 91.025052
iter  90 value 90.777089
iter 100 value 90.631243
final  value 90.631243 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 98.039712 
iter  10 value 94.487516
iter  20 value 94.384110
iter  30 value 87.803382
iter  40 value 85.299350
iter  50 value 85.255264
final  value 85.255260 
converged
Fitting Repeat 3 

# weights:  507
initial  value 93.644348 
iter  10 value 86.751588
iter  20 value 85.139130
iter  30 value 84.512513
iter  40 value 84.503753
iter  50 value 84.497661
iter  60 value 84.387564
iter  70 value 84.149019
iter  80 value 83.776609
iter  90 value 81.739477
iter 100 value 81.157690
final  value 81.157690 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 97.646277 
iter  10 value 94.361595
iter  20 value 94.245084
iter  30 value 93.816847
iter  40 value 93.810006
final  value 93.809813 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.883515 
iter  10 value 94.368167
iter  20 value 93.919445
iter  30 value 93.305006
iter  40 value 91.542304
iter  50 value 91.094915
iter  60 value 91.037800
final  value 91.037787 
converged
Fitting Repeat 1 

# weights:  103
initial  value 106.805443 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.040763 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.264169 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 117.934119 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 110.771616 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.056652 
iter  10 value 93.974677
iter  20 value 93.972878
iter  20 value 93.972877
iter  20 value 93.972877
final  value 93.972877 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.768458 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.102637 
iter  10 value 94.032978
final  value 94.032967 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.488644 
final  value 94.017143 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.543279 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 114.251394 
final  value 93.884577 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.200377 
final  value 94.032967 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.126699 
iter  10 value 94.012545
iter  20 value 94.009989
final  value 94.009972 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.676044 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 120.125361 
iter  10 value 94.075899
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.551733 
iter  10 value 94.051056
iter  20 value 93.899368
iter  30 value 86.854739
iter  40 value 83.489054
iter  50 value 83.262650
iter  60 value 82.973011
iter  70 value 82.729672
iter  80 value 82.718118
final  value 82.718067 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.721951 
iter  10 value 94.055327
iter  20 value 93.914027
iter  30 value 93.682160
iter  40 value 87.947658
iter  50 value 87.510213
iter  60 value 87.145738
iter  70 value 85.351458
iter  80 value 83.285925
iter  90 value 82.758613
iter 100 value 82.719068
final  value 82.719068 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 107.263717 
iter  10 value 94.013450
iter  20 value 91.120163
iter  30 value 86.413906
iter  40 value 84.056433
iter  50 value 83.474620
iter  60 value 83.373332
iter  70 value 83.306390
iter  80 value 83.228368
iter  90 value 82.867513
iter 100 value 82.722753
final  value 82.722753 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.351417 
iter  10 value 94.057665
iter  20 value 93.223608
iter  30 value 92.275803
iter  40 value 91.551947
iter  50 value 90.216759
iter  60 value 85.303624
iter  70 value 82.211158
iter  80 value 81.756427
iter  90 value 81.750204
iter 100 value 81.749941
final  value 81.749941 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 98.472214 
iter  10 value 94.040223
iter  20 value 90.643274
iter  30 value 87.112032
iter  40 value 86.665639
iter  50 value 84.067817
iter  60 value 82.326802
iter  70 value 82.259051
iter  80 value 82.257117
iter  90 value 82.256765
iter  90 value 82.256765
iter  90 value 82.256765
final  value 82.256765 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.730241 
iter  10 value 93.998891
iter  20 value 87.732763
iter  30 value 86.435690
iter  40 value 86.125673
iter  50 value 83.289270
iter  60 value 82.720702
iter  70 value 82.469826
iter  80 value 82.079954
iter  90 value 82.064146
iter 100 value 82.010471
final  value 82.010471 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.127583 
iter  10 value 94.016897
iter  20 value 88.546578
iter  30 value 88.026993
iter  40 value 86.260302
iter  50 value 83.855953
iter  60 value 82.972751
iter  70 value 82.518734
iter  80 value 82.032385
iter  90 value 81.843798
iter 100 value 81.787773
final  value 81.787773 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 129.914416 
iter  10 value 94.066651
iter  20 value 93.868036
iter  30 value 90.879617
iter  40 value 85.730198
iter  50 value 83.469484
iter  60 value 82.300236
iter  70 value 82.271260
iter  80 value 82.226625
iter  90 value 82.192445
iter 100 value 81.974840
final  value 81.974840 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.232617 
iter  10 value 93.522769
iter  20 value 84.395430
iter  30 value 83.152926
iter  40 value 82.591294
iter  50 value 82.391373
iter  60 value 81.923840
iter  70 value 81.055681
iter  80 value 80.881057
iter  90 value 80.829395
iter 100 value 80.773537
final  value 80.773537 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.259021 
iter  10 value 93.980715
iter  20 value 93.824025
iter  30 value 93.022165
iter  40 value 90.347733
iter  50 value 84.302411
iter  60 value 83.850150
iter  70 value 83.643847
iter  80 value 83.019992
iter  90 value 82.917685
iter 100 value 82.629550
final  value 82.629550 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.245528 
iter  10 value 93.644613
iter  20 value 84.984573
iter  30 value 84.490874
iter  40 value 83.748548
iter  50 value 83.109536
iter  60 value 81.354617
iter  70 value 81.086026
iter  80 value 80.872208
iter  90 value 80.821622
iter 100 value 80.694856
final  value 80.694856 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 122.003777 
iter  10 value 94.290393
iter  20 value 92.086427
iter  30 value 88.629118
iter  40 value 87.720402
iter  50 value 86.515077
iter  60 value 85.554077
iter  70 value 85.459193
iter  80 value 85.095358
iter  90 value 83.347837
iter 100 value 82.362452
final  value 82.362452 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 131.483182 
iter  10 value 94.067856
iter  20 value 88.005447
iter  30 value 86.850638
iter  40 value 86.050039
iter  50 value 85.163244
iter  60 value 84.495485
iter  70 value 82.751303
iter  80 value 81.958310
iter  90 value 81.751979
iter 100 value 81.556894
final  value 81.556894 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 140.887463 
iter  10 value 93.343945
iter  20 value 86.285223
iter  30 value 83.537749
iter  40 value 82.672484
iter  50 value 81.532188
iter  60 value 81.008448
iter  70 value 80.758700
iter  80 value 80.642762
iter  90 value 80.621102
iter 100 value 80.535955
final  value 80.535955 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 102.567070 
iter  10 value 94.166776
iter  20 value 86.931683
iter  30 value 86.280337
iter  40 value 84.432649
iter  50 value 82.695462
iter  60 value 80.872660
iter  70 value 80.671262
iter  80 value 80.546289
iter  90 value 80.417445
iter 100 value 80.322056
final  value 80.322056 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.161347 
iter  10 value 94.054632
iter  20 value 94.052955
final  value 94.052915 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.870982 
final  value 94.054671 
converged
Fitting Repeat 3 

# weights:  103
initial  value 109.156277 
final  value 94.054589 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.723194 
final  value 94.054515 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.112610 
final  value 94.054803 
converged
Fitting Repeat 1 

# weights:  305
initial  value 122.563858 
iter  10 value 94.037348
iter  20 value 94.033974
iter  30 value 90.051044
iter  40 value 86.522519
iter  50 value 85.735281
iter  60 value 85.730755
iter  70 value 84.517198
iter  80 value 84.279673
iter  90 value 84.030685
iter  90 value 84.030684
iter  90 value 84.030684
final  value 84.030684 
converged
Fitting Repeat 2 

# weights:  305
initial  value 109.454990 
iter  10 value 94.057594
iter  20 value 94.034943
iter  30 value 93.716405
iter  40 value 84.320619
iter  50 value 83.305327
iter  60 value 83.302713
iter  70 value 83.300327
iter  80 value 83.242068
iter  90 value 82.893692
iter 100 value 82.871075
final  value 82.871075 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 98.565235 
iter  10 value 94.057302
iter  20 value 92.885596
iter  30 value 86.324257
iter  40 value 86.185791
iter  50 value 86.178131
iter  60 value 86.176102
iter  70 value 84.577943
iter  80 value 82.988437
iter  90 value 82.868859
final  value 82.868461 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.157094 
iter  10 value 94.056015
iter  20 value 93.855764
iter  30 value 87.665602
iter  40 value 86.969673
iter  50 value 86.958453
final  value 86.957808 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.048816 
iter  10 value 94.037617
iter  20 value 94.033307
iter  30 value 93.600433
iter  40 value 91.932617
iter  50 value 91.816559
final  value 91.785546 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.424751 
iter  10 value 94.041468
iter  20 value 94.039887
iter  30 value 94.033821
final  value 94.033805 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.357520 
iter  10 value 94.061384
iter  20 value 93.376573
iter  30 value 91.974072
iter  40 value 88.918864
iter  50 value 88.721852
iter  60 value 88.418776
iter  70 value 87.504243
iter  80 value 87.475706
final  value 87.475638 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.782811 
iter  10 value 94.061483
iter  20 value 94.053343
iter  30 value 91.041485
iter  40 value 86.201821
iter  50 value 86.057723
iter  60 value 86.047208
iter  70 value 85.868063
iter  80 value 85.845800
iter  90 value 85.333335
iter 100 value 84.217231
final  value 84.217231 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.416143 
iter  10 value 94.060415
iter  20 value 93.833965
iter  30 value 87.994953
iter  40 value 85.169992
iter  50 value 85.144667
iter  60 value 85.128371
iter  70 value 85.127176
iter  80 value 85.127066
iter  90 value 85.122559
iter 100 value 85.118324
final  value 85.118324 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 100.106136 
iter  10 value 93.917586
iter  20 value 93.892663
iter  30 value 93.836132
iter  40 value 88.753117
iter  50 value 88.000929
iter  60 value 85.072325
iter  70 value 83.458421
iter  80 value 83.433278
iter  90 value 83.430679
iter 100 value 83.324990
final  value 83.324990 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 125.139474 
iter  10 value 117.977190
iter  20 value 113.961475
iter  30 value 107.269474
iter  40 value 105.056835
iter  50 value 102.902456
iter  60 value 102.459582
iter  70 value 101.551217
iter  80 value 101.451243
iter  90 value 101.247587
iter 100 value 101.079994
final  value 101.079994 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 133.953141 
iter  10 value 115.930239
iter  20 value 108.749293
iter  30 value 106.174993
iter  40 value 105.446613
iter  50 value 103.518473
iter  60 value 102.816025
iter  70 value 102.104921
iter  80 value 101.045458
iter  90 value 100.963369
iter 100 value 100.866925
final  value 100.866925 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 126.282432 
iter  10 value 117.890937
iter  20 value 117.692787
iter  30 value 110.979638
iter  40 value 109.661439
iter  50 value 105.890307
iter  60 value 103.898138
iter  70 value 102.756183
iter  80 value 102.431687
iter  90 value 101.981914
iter 100 value 101.483429
final  value 101.483429 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 125.187693 
iter  10 value 118.352370
iter  20 value 116.346184
iter  30 value 110.397312
iter  40 value 105.118591
iter  50 value 104.693063
iter  60 value 104.239954
iter  70 value 103.069748
iter  80 value 101.483732
iter  90 value 100.802266
iter 100 value 100.787054
final  value 100.787054 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 131.825635 
iter  10 value 117.896193
iter  20 value 117.803545
iter  30 value 117.442184
iter  40 value 112.858163
iter  50 value 106.596007
iter  60 value 105.586535
iter  70 value 103.510165
iter  80 value 102.746508
iter  90 value 102.475280
iter 100 value 102.206418
final  value 102.206418 
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 -- Tue Feb 24 00:31:01 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 
 40.320   0.777  95.349