##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings HPiP_1.18.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck’
* using R version 4.6.0 RC (2026-04-17 r89917)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
    GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
* running under: Ubuntu 24.04.4 LTS
* using session charset: UTF-8
* current time: 2026-05-02 05:15:54 UTC
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.18.0’
* 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
var_imp       35.773  0.593  36.406
corr_plot     34.536  0.469  35.110
FSmethod      34.341  0.493  34.911
pred_ensembel 13.050  0.298  12.008
enrichfindP    0.620  0.040  15.430
* 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-3.23-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.23-bioc/R/site-library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.18.0’
** 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 RC (2026-04-17 r89917) -- "Because it was There"
Copyright (C) 2026 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
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 96.612290 
iter  10 value 85.136949
iter  20 value 84.940479
final  value 84.940476 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.688018 
iter  10 value 84.822374
iter  20 value 84.551302
iter  30 value 84.541455
final  value 84.541454 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.783360 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.574151 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.686161 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.501277 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.387598 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 93.656357 
iter  10 value 88.520978
iter  20 value 88.340305
iter  30 value 88.278881
iter  40 value 88.269296
iter  50 value 88.268897
final  value 88.268889 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.538512 
final  value 93.841750 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.719191 
iter  10 value 92.828623
final  value 92.158508 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.492733 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 113.604333 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 112.177063 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 110.386288 
iter  10 value 89.507518
iter  20 value 86.013965
iter  30 value 86.005029
final  value 86.005013 
converged
Fitting Repeat 5 

# weights:  507
initial  value 113.514460 
iter  10 value 92.945520
final  value 92.945355 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.352816 
iter  10 value 94.059588
iter  20 value 93.550889
iter  30 value 86.110374
iter  40 value 83.779183
iter  50 value 83.684953
iter  60 value 82.852442
iter  70 value 82.327429
final  value 82.299569 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.786859 
iter  10 value 93.792837
iter  20 value 92.490359
iter  30 value 92.227966
iter  40 value 91.411999
iter  50 value 87.599481
iter  60 value 86.999186
iter  70 value 85.042718
iter  80 value 81.285072
iter  90 value 81.144382
iter 100 value 81.092320
final  value 81.092320 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 105.673367 
iter  10 value 94.058898
iter  20 value 94.020166
iter  30 value 93.512602
iter  40 value 93.459395
iter  50 value 93.429296
iter  60 value 92.923453
iter  70 value 83.952473
iter  80 value 83.776176
iter  90 value 83.740691
iter 100 value 83.726342
final  value 83.726342 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.815541 
iter  10 value 94.056690
iter  20 value 93.489383
iter  30 value 89.393657
iter  40 value 88.046241
iter  50 value 81.912753
iter  60 value 81.006097
iter  70 value 80.175493
iter  80 value 80.085208
iter  90 value 80.069072
iter 100 value 80.056170
final  value 80.056170 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.261859 
iter  10 value 93.502458
iter  20 value 84.073894
iter  30 value 82.239236
iter  40 value 81.397257
iter  50 value 81.208905
iter  60 value 80.455942
iter  70 value 79.918315
final  value 79.908797 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.430166 
iter  10 value 94.119058
iter  20 value 90.893539
iter  30 value 82.380950
iter  40 value 81.061321
iter  50 value 79.857204
iter  60 value 79.317670
iter  70 value 78.828103
iter  80 value 78.704967
iter  90 value 78.654488
iter 100 value 78.648808
final  value 78.648808 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 125.765470 
iter  10 value 94.009136
iter  20 value 86.092124
iter  30 value 84.643106
iter  40 value 83.056243
iter  50 value 80.860478
iter  60 value 79.822990
iter  70 value 79.089745
iter  80 value 78.490461
iter  90 value 78.280373
iter 100 value 78.248498
final  value 78.248498 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 112.212174 
iter  10 value 93.850636
iter  20 value 87.205171
iter  30 value 85.204001
iter  40 value 84.185174
iter  50 value 82.501406
iter  60 value 81.769992
iter  70 value 81.222059
iter  80 value 80.181857
iter  90 value 79.839655
iter 100 value 79.593199
final  value 79.593199 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.509830 
iter  10 value 93.371102
iter  20 value 93.166748
iter  30 value 91.702622
iter  40 value 86.860961
iter  50 value 85.324640
iter  60 value 82.593216
iter  70 value 79.897583
iter  80 value 79.462643
iter  90 value 78.807763
iter 100 value 78.692707
final  value 78.692707 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 125.177919 
iter  10 value 92.815742
iter  20 value 92.417826
iter  30 value 86.457041
iter  40 value 82.441635
iter  50 value 80.947868
iter  60 value 79.326236
iter  70 value 78.923145
iter  80 value 78.811399
iter  90 value 78.711372
iter 100 value 78.679511
final  value 78.679511 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 115.789236 
iter  10 value 93.311283
iter  20 value 85.030218
iter  30 value 82.433162
iter  40 value 81.911468
iter  50 value 79.490935
iter  60 value 78.940075
iter  70 value 78.877185
iter  80 value 78.797329
iter  90 value 78.711971
iter 100 value 78.678104
final  value 78.678104 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 116.035382 
iter  10 value 87.294218
iter  20 value 81.472766
iter  30 value 80.073850
iter  40 value 79.897413
iter  50 value 79.501097
iter  60 value 79.063563
iter  70 value 79.008885
iter  80 value 78.975259
iter  90 value 78.885138
iter 100 value 78.810994
final  value 78.810994 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.653405 
iter  10 value 95.514845
iter  20 value 92.966776
iter  30 value 87.698088
iter  40 value 80.896126
iter  50 value 79.821175
iter  60 value 79.607418
iter  70 value 79.158112
iter  80 value 78.941275
iter  90 value 78.791426
iter 100 value 78.307705
final  value 78.307705 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 123.777529 
iter  10 value 94.155019
iter  20 value 92.130145
iter  30 value 83.524606
iter  40 value 82.087158
iter  50 value 81.360710
iter  60 value 80.538792
iter  70 value 79.266018
iter  80 value 78.990495
iter  90 value 78.935322
iter 100 value 78.813162
final  value 78.813162 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.270733 
iter  10 value 93.845195
iter  20 value 84.823146
iter  30 value 81.556640
iter  40 value 80.300325
iter  50 value 79.633216
iter  60 value 79.044016
iter  70 value 78.592238
iter  80 value 78.552937
iter  90 value 78.448650
iter 100 value 78.257132
final  value 78.257132 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.918830 
final  value 94.054639 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.416460 
final  value 94.055041 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.041092 
final  value 94.054707 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.463426 
iter  10 value 92.947725
iter  20 value 92.947054
iter  30 value 92.945927
iter  40 value 92.141295
iter  50 value 86.492891
iter  60 value 84.346876
iter  70 value 84.157156
final  value 84.156704 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.871764 
final  value 94.054435 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.270431 
iter  10 value 89.058260
iter  20 value 89.056047
iter  30 value 89.042481
iter  40 value 84.638843
iter  50 value 84.024253
iter  60 value 83.132837
final  value 83.132607 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.179110 
iter  10 value 94.057486
iter  20 value 94.052969
iter  30 value 93.963170
iter  40 value 83.286882
iter  50 value 83.184809
iter  60 value 83.181979
iter  70 value 80.710035
iter  80 value 77.998005
iter  90 value 77.769960
iter 100 value 77.628561
final  value 77.628561 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.225306 
iter  10 value 94.057938
iter  20 value 94.044336
iter  30 value 92.368686
iter  40 value 91.938575
iter  50 value 91.935259
iter  50 value 91.935258
final  value 91.935250 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.008778 
iter  10 value 94.057358
iter  20 value 94.038494
iter  30 value 91.994296
iter  40 value 91.990762
iter  50 value 88.620646
iter  60 value 82.603695
iter  70 value 82.369289
iter  80 value 82.368882
iter  90 value 81.876517
iter 100 value 81.580555
final  value 81.580555 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.704204 
iter  10 value 94.057266
iter  20 value 94.051114
iter  30 value 94.024025
iter  40 value 92.839118
iter  50 value 92.838490
iter  50 value 92.838490
iter  50 value 92.838489
final  value 92.838489 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.418907 
iter  10 value 92.954493
iter  20 value 92.953092
iter  30 value 84.727178
iter  40 value 83.237491
iter  50 value 83.201828
iter  60 value 83.201612
iter  70 value 83.001769
iter  80 value 82.721556
final  value 82.673000 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.015448 
iter  10 value 92.953934
iter  20 value 92.948021
iter  30 value 92.947496
iter  40 value 92.946684
iter  50 value 87.458788
iter  60 value 84.167033
iter  70 value 83.536563
iter  80 value 83.493397
iter  90 value 83.480103
iter 100 value 83.364236
final  value 83.364236 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.927070 
iter  10 value 92.180591
iter  20 value 92.173562
iter  30 value 91.822762
iter  40 value 87.447017
iter  50 value 82.316342
iter  60 value 80.793291
iter  70 value 78.444650
iter  80 value 77.880067
iter  90 value 77.385591
iter 100 value 77.325982
final  value 77.325982 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 99.301811 
iter  10 value 92.953813
iter  20 value 92.950526
iter  30 value 92.942286
iter  40 value 92.941529
iter  50 value 92.160629
iter  60 value 92.158351
iter  70 value 92.153698
final  value 92.153632 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.343923 
iter  10 value 92.948915
iter  20 value 92.947221
iter  30 value 91.845046
iter  40 value 86.572783
iter  50 value 84.751809
iter  60 value 79.968573
iter  70 value 78.421273
iter  80 value 77.428160
iter  90 value 77.051316
iter 100 value 76.896465
final  value 76.896465 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 105.761088 
iter  10 value 93.819019
iter  20 value 93.806016
final  value 93.805290 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.653212 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.278275 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.310269 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 108.417484 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.662324 
final  value 93.962733 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.140849 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.684714 
final  value 93.915746 
converged
Fitting Repeat 4 

# weights:  305
initial  value 111.845345 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.344237 
iter  10 value 92.800472
final  value 92.792105 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.116745 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.392633 
final  value 93.915746 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.092355 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.421732 
final  value 93.915746 
converged
Fitting Repeat 5 

# weights:  507
initial  value 114.293495 
final  value 93.915746 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.696262 
iter  10 value 94.080102
iter  20 value 93.737965
iter  30 value 91.275830
iter  40 value 88.396420
iter  50 value 86.693107
iter  60 value 84.372519
iter  70 value 83.907999
iter  80 value 83.874027
iter  90 value 83.870848
final  value 83.869679 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.898065 
iter  10 value 93.613790
iter  20 value 90.525712
iter  30 value 90.189114
iter  40 value 87.644199
iter  50 value 85.608415
iter  60 value 85.399304
iter  70 value 85.025603
iter  80 value 84.156012
iter  90 value 83.373471
iter 100 value 83.306434
final  value 83.306434 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.985908 
iter  10 value 93.982525
iter  20 value 85.120095
iter  30 value 84.756140
iter  40 value 84.688476
iter  50 value 84.677828
iter  60 value 84.286350
iter  70 value 84.253242
final  value 84.253090 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.473784 
iter  10 value 94.035558
iter  20 value 93.785636
iter  30 value 92.738604
iter  40 value 91.909213
iter  50 value 90.934363
iter  60 value 90.516375
iter  70 value 90.441145
iter  80 value 90.044844
iter  90 value 89.467164
iter 100 value 89.466626
final  value 89.466626 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 102.223864 
iter  10 value 94.060054
iter  20 value 93.682451
iter  30 value 93.143881
iter  40 value 84.771513
iter  50 value 84.499670
iter  60 value 83.992072
iter  70 value 83.908887
iter  80 value 83.873081
iter  90 value 83.871453
final  value 83.865279 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.820091 
iter  10 value 94.066506
iter  20 value 93.389530
iter  30 value 93.089488
iter  40 value 85.214901
iter  50 value 84.555137
iter  60 value 84.445598
iter  70 value 84.196761
iter  80 value 83.835925
iter  90 value 82.803659
iter 100 value 82.551262
final  value 82.551262 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 119.811819 
iter  10 value 94.057132
iter  20 value 86.437847
iter  30 value 85.231198
iter  40 value 83.737573
iter  50 value 82.450211
iter  60 value 82.053602
iter  70 value 81.732019
iter  80 value 81.636774
iter  90 value 81.260687
iter 100 value 81.198531
final  value 81.198531 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.767163 
iter  10 value 93.943198
iter  20 value 90.737941
iter  30 value 88.141723
iter  40 value 84.648398
iter  50 value 83.637085
iter  60 value 82.760493
iter  70 value 81.920759
iter  80 value 81.243858
iter  90 value 81.129183
iter 100 value 80.812668
final  value 80.812668 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.761480 
iter  10 value 94.011335
iter  20 value 90.902657
iter  30 value 85.779375
iter  40 value 84.636715
iter  50 value 84.293242
iter  60 value 84.000603
iter  70 value 83.752187
iter  80 value 82.992447
iter  90 value 82.726202
iter 100 value 82.631084
final  value 82.631084 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.125001 
iter  10 value 94.554219
iter  20 value 94.079778
iter  30 value 92.382961
iter  40 value 84.688458
iter  50 value 84.073438
iter  60 value 83.351429
iter  70 value 82.903193
iter  80 value 82.369193
iter  90 value 81.670626
iter 100 value 81.578879
final  value 81.578879 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 111.400747 
iter  10 value 94.160225
iter  20 value 87.763854
iter  30 value 85.875461
iter  40 value 83.363231
iter  50 value 82.913783
iter  60 value 82.441018
iter  70 value 82.238575
iter  80 value 82.144189
iter  90 value 82.096873
iter 100 value 81.933153
final  value 81.933153 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.094732 
iter  10 value 91.027201
iter  20 value 85.572128
iter  30 value 84.320118
iter  40 value 83.058474
iter  50 value 82.051391
iter  60 value 81.509068
iter  70 value 81.470883
iter  80 value 81.438852
iter  90 value 81.428458
iter 100 value 81.416992
final  value 81.416992 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.148795 
iter  10 value 94.023717
iter  20 value 89.756111
iter  30 value 87.386297
iter  40 value 85.464974
iter  50 value 84.674506
iter  60 value 82.636594
iter  70 value 82.215710
iter  80 value 81.751159
iter  90 value 81.505897
iter 100 value 81.423770
final  value 81.423770 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.847844 
iter  10 value 92.208837
iter  20 value 84.871049
iter  30 value 84.370574
iter  40 value 83.067873
iter  50 value 82.139876
iter  60 value 81.778318
iter  70 value 81.362432
iter  80 value 80.867255
iter  90 value 80.763843
iter 100 value 80.705487
final  value 80.705487 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 116.960666 
iter  10 value 94.359183
iter  20 value 89.270792
iter  30 value 88.759406
iter  40 value 84.432786
iter  50 value 83.696486
iter  60 value 83.075746
iter  70 value 82.547086
iter  80 value 81.866157
iter  90 value 81.164332
iter 100 value 80.922569
final  value 80.922569 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.768291 
final  value 94.054532 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.502526 
iter  10 value 92.894630
iter  10 value 92.894629
iter  10 value 92.894629
final  value 92.894629 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.887372 
iter  10 value 92.281778
iter  20 value 92.249548
iter  30 value 91.214126
iter  40 value 91.209099
iter  50 value 91.206162
iter  60 value 91.206054
final  value 91.206004 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.801092 
final  value 94.054773 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.561832 
final  value 94.054738 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.288430 
iter  10 value 94.057290
iter  20 value 94.052926
final  value 94.052914 
converged
Fitting Repeat 2 

# weights:  305
initial  value 106.007435 
iter  10 value 94.056890
iter  20 value 93.916249
iter  30 value 93.679945
iter  40 value 90.602673
iter  50 value 85.011807
iter  60 value 84.933767
iter  70 value 84.927628
iter  80 value 84.921228
iter  90 value 84.920517
iter 100 value 84.648911
final  value 84.648911 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 97.282451 
iter  10 value 93.921019
iter  20 value 93.904444
iter  30 value 90.830846
final  value 90.669173 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.604446 
iter  10 value 94.057327
iter  20 value 93.906362
iter  30 value 92.893079
final  value 92.893076 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.716153 
iter  10 value 93.944970
iter  20 value 93.769328
iter  30 value 90.077086
iter  40 value 89.478922
iter  50 value 89.475794
iter  60 value 88.258417
iter  70 value 87.864064
final  value 87.832158 
converged
Fitting Repeat 1 

# weights:  507
initial  value 116.934341 
iter  10 value 94.055083
final  value 94.054615 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.649884 
iter  10 value 94.025301
iter  20 value 93.827355
iter  30 value 86.854523
iter  40 value 86.304862
iter  50 value 85.022127
iter  60 value 84.307305
iter  70 value 84.064491
iter  80 value 84.054200
iter  90 value 84.005029
final  value 84.005026 
converged
Fitting Repeat 3 

# weights:  507
initial  value 108.994246 
iter  10 value 94.060737
iter  20 value 94.053955
iter  30 value 93.986771
iter  40 value 93.537393
iter  50 value 93.522080
iter  60 value 93.521103
iter  70 value 93.520762
iter  80 value 93.358924
iter  90 value 92.854699
iter 100 value 84.805471
final  value 84.805471 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.989125 
iter  10 value 93.987171
iter  20 value 89.946212
iter  30 value 84.144146
iter  40 value 82.041909
iter  50 value 81.907076
iter  60 value 81.904363
final  value 81.900841 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.669266 
iter  10 value 93.923986
iter  20 value 93.699239
iter  30 value 93.690586
iter  40 value 91.195984
iter  50 value 87.517722
iter  60 value 85.830318
iter  70 value 84.488834
iter  80 value 83.681829
iter  90 value 83.680920
iter 100 value 83.680825
final  value 83.680825 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.200989 
iter  10 value 94.491205
iter  20 value 94.476487
iter  30 value 86.076465
iter  40 value 85.951724
iter  40 value 85.951724
final  value 85.951717 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.202904 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.087005 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.581099 
final  value 94.484210 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.603617 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.598348 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.511815 
final  value 94.291892 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.177059 
final  value 94.291892 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.285794 
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 107.839506 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.163842 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 110.691582 
iter  10 value 93.348053
iter  20 value 92.725767
iter  30 value 92.557925
iter  40 value 92.209133
iter  50 value 92.199408
final  value 92.199398 
converged
Fitting Repeat 3 

# weights:  507
initial  value 123.581971 
iter  10 value 94.291892
iter  10 value 94.291892
iter  10 value 94.291892
final  value 94.291892 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.451599 
final  value 94.291892 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.573880 
iter  10 value 92.494016
iter  20 value 81.598969
iter  30 value 79.302251
iter  40 value 79.105836
iter  50 value 79.083742
iter  60 value 79.083175
final  value 79.083164 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.572557 
iter  10 value 84.570791
iter  20 value 83.590709
iter  30 value 82.950301
iter  40 value 82.922829
final  value 82.922809 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.742578 
iter  10 value 94.822237
iter  20 value 94.485889
iter  30 value 89.352131
iter  40 value 85.384659
iter  50 value 82.183891
iter  60 value 82.094107
iter  70 value 81.571299
iter  80 value 80.742802
iter  90 value 80.066950
iter 100 value 80.004053
final  value 80.004053 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.759133 
iter  10 value 93.982857
iter  20 value 87.523731
iter  30 value 84.545892
iter  40 value 84.005347
iter  50 value 83.436204
iter  60 value 83.179708
iter  70 value 83.021340
iter  80 value 82.951889
iter  90 value 82.922809
iter  90 value 82.922809
iter  90 value 82.922809
final  value 82.922809 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.169501 
iter  10 value 94.488737
iter  20 value 94.290752
iter  30 value 92.575418
iter  40 value 91.996498
iter  50 value 84.763965
iter  60 value 84.263092
iter  70 value 83.747319
iter  80 value 83.538960
iter  90 value 83.332062
iter 100 value 83.280660
final  value 83.280660 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 105.636412 
iter  10 value 94.490537
iter  20 value 94.274963
iter  30 value 89.484033
iter  40 value 85.845061
iter  50 value 85.153183
iter  60 value 84.768453
iter  70 value 81.362038
iter  80 value 80.792983
iter  90 value 80.251121
iter 100 value 80.241908
final  value 80.241908 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 103.405112 
iter  10 value 94.558421
iter  20 value 93.587860
iter  30 value 85.755995
iter  40 value 84.697444
iter  50 value 84.266013
iter  60 value 83.999655
iter  70 value 83.614637
iter  80 value 83.330106
iter  90 value 82.251433
iter 100 value 81.343336
final  value 81.343336 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.073512 
iter  10 value 94.221164
iter  20 value 89.384499
iter  30 value 88.135660
iter  40 value 87.798017
iter  50 value 85.492124
iter  60 value 85.030172
iter  70 value 83.565594
iter  80 value 83.386406
iter  90 value 83.055767
iter 100 value 82.726118
final  value 82.726118 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 128.066380 
iter  10 value 94.871074
iter  20 value 85.744943
iter  30 value 84.411918
iter  40 value 83.928845
iter  50 value 83.279958
iter  60 value 81.136344
iter  70 value 80.739681
iter  80 value 79.526773
iter  90 value 78.989392
iter 100 value 78.878695
final  value 78.878695 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.290038 
iter  10 value 94.546135
iter  20 value 94.289679
iter  30 value 94.162964
iter  40 value 85.388255
iter  50 value 80.779786
iter  60 value 80.263423
iter  70 value 79.522900
iter  80 value 79.321020
iter  90 value 79.181664
iter 100 value 79.107745
final  value 79.107745 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.419476 
iter  10 value 89.216877
iter  20 value 84.919913
iter  30 value 81.150255
iter  40 value 80.451269
iter  50 value 79.713737
iter  60 value 79.132745
iter  70 value 79.109868
iter  80 value 78.936628
iter  90 value 78.774362
iter 100 value 78.637893
final  value 78.637893 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 119.083993 
iter  10 value 94.358783
iter  20 value 85.538198
iter  30 value 83.702421
iter  40 value 80.909190
iter  50 value 79.379367
iter  60 value 79.149552
iter  70 value 79.039961
iter  80 value 78.980416
iter  90 value 78.884489
iter 100 value 78.620052
final  value 78.620052 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.973755 
iter  10 value 94.616559
iter  20 value 85.606422
iter  30 value 84.170019
iter  40 value 81.399895
iter  50 value 80.420114
iter  60 value 79.997516
iter  70 value 78.783659
iter  80 value 78.577603
iter  90 value 78.518187
iter 100 value 78.466875
final  value 78.466875 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.558934 
iter  10 value 94.607462
iter  20 value 87.166985
iter  30 value 85.502526
iter  40 value 81.643274
iter  50 value 80.479989
iter  60 value 80.247941
iter  70 value 80.053787
iter  80 value 79.897884
iter  90 value 79.447259
iter 100 value 78.968932
final  value 78.968932 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 119.756265 
iter  10 value 94.672879
iter  20 value 93.304815
iter  30 value 88.517865
iter  40 value 87.517288
iter  50 value 83.628887
iter  60 value 83.410629
iter  70 value 82.920912
iter  80 value 81.316509
iter  90 value 79.824218
iter 100 value 79.442807
final  value 79.442807 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 122.201702 
iter  10 value 94.638724
iter  20 value 94.474892
iter  30 value 93.336354
iter  40 value 84.323898
iter  50 value 81.902090
iter  60 value 81.247749
iter  70 value 79.439838
iter  80 value 78.999290
iter  90 value 78.538957
iter 100 value 78.459317
final  value 78.459317 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.672640 
iter  10 value 94.293577
iter  20 value 94.292998
iter  30 value 91.819962
iter  40 value 88.712937
iter  50 value 88.711867
iter  60 value 88.710408
final  value 88.710339 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.648058 
iter  10 value 94.342914
iter  20 value 94.293712
iter  30 value 94.292283
final  value 94.292083 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.384769 
final  value 94.485850 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.052939 
final  value 94.485892 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.907635 
iter  10 value 94.471896
final  value 94.443443 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.657642 
iter  10 value 94.488516
iter  20 value 93.792312
iter  30 value 85.014545
iter  40 value 84.587157
final  value 84.587130 
converged
Fitting Repeat 2 

# weights:  305
initial  value 110.578932 
iter  10 value 94.297375
iter  20 value 94.292724
final  value 94.291974 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.171558 
iter  10 value 94.490971
iter  20 value 94.371013
iter  30 value 86.263437
iter  40 value 84.123400
iter  50 value 83.427351
iter  50 value 83.427350
final  value 83.427350 
converged
Fitting Repeat 4 

# weights:  305
initial  value 121.374307 
iter  10 value 91.839942
iter  20 value 91.212925
iter  30 value 91.156720
iter  40 value 91.081828
iter  50 value 91.079627
final  value 91.078825 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.049546 
iter  10 value 94.488898
iter  20 value 94.314227
iter  30 value 89.489143
final  value 89.373294 
converged
Fitting Repeat 1 

# weights:  507
initial  value 110.383199 
iter  10 value 94.301250
iter  20 value 94.282561
iter  30 value 85.968236
iter  40 value 85.250480
iter  50 value 85.131914
iter  60 value 85.125334
iter  70 value 85.125019
final  value 85.125018 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.086610 
iter  10 value 93.027285
iter  20 value 93.008774
iter  30 value 93.007233
final  value 93.007111 
converged
Fitting Repeat 3 

# weights:  507
initial  value 124.486899 
iter  10 value 94.320396
iter  20 value 94.316683
iter  30 value 94.300469
iter  40 value 87.651002
iter  50 value 86.645355
iter  60 value 86.610030
iter  70 value 86.554109
final  value 86.553509 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.716672 
iter  10 value 94.299803
iter  20 value 94.294683
iter  30 value 94.294347
iter  40 value 94.272168
iter  50 value 94.095505
iter  60 value 94.092023
iter  70 value 90.982441
final  value 86.591645 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.887019 
iter  10 value 84.922286
iter  20 value 84.890436
iter  30 value 84.883625
iter  40 value 83.650440
iter  50 value 80.196211
iter  60 value 80.163764
iter  70 value 80.127637
iter  80 value 80.123531
iter  90 value 80.106460
iter 100 value 79.987428
final  value 79.987428 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.620642 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.993952 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.568164 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.175450 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.105691 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.185945 
final  value 94.443244 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.253164 
iter  10 value 94.443244
iter  10 value 94.443243
iter  10 value 94.443243
final  value 94.443243 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.070570 
iter  10 value 94.444102
iter  20 value 94.443247
final  value 94.443244 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.168137 
iter  10 value 94.484235
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.169789 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.714305 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.500501 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.611257 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 119.847750 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.491044 
final  value 94.057142 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.238804 
iter  10 value 94.486440
iter  20 value 94.261036
iter  30 value 89.432543
iter  40 value 87.150150
iter  50 value 86.753078
iter  60 value 86.751358
final  value 86.751353 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.374831 
iter  10 value 94.504684
iter  20 value 94.435092
iter  30 value 93.404341
iter  40 value 93.326320
iter  50 value 93.279035
iter  60 value 89.396947
iter  70 value 87.790190
iter  80 value 87.096914
iter  90 value 87.031666
iter 100 value 86.563380
final  value 86.563380 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.436859 
iter  10 value 94.484451
iter  20 value 94.002808
iter  30 value 93.663114
iter  40 value 87.884471
iter  50 value 87.237969
iter  60 value 87.153328
iter  70 value 86.956169
iter  80 value 86.752244
final  value 86.751353 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.132275 
iter  10 value 94.491285
iter  20 value 94.488796
iter  30 value 94.481322
iter  40 value 92.515859
iter  50 value 88.226524
iter  60 value 86.802426
iter  70 value 86.583241
iter  80 value 86.281863
final  value 86.281639 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.667607 
iter  10 value 94.488488
iter  20 value 94.469118
iter  30 value 92.392380
iter  40 value 87.827780
iter  50 value 86.377495
iter  60 value 85.518120
iter  70 value 85.055532
iter  80 value 83.843583
iter  90 value 83.710564
iter 100 value 83.663363
final  value 83.663363 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 124.076151 
iter  10 value 94.362992
iter  20 value 88.783986
iter  30 value 85.200210
iter  40 value 84.866759
iter  50 value 83.985637
iter  60 value 83.181644
iter  70 value 82.846764
iter  80 value 82.770986
iter  90 value 82.757196
iter 100 value 82.660618
final  value 82.660618 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.511638 
iter  10 value 88.889908
iter  20 value 85.748763
iter  30 value 85.376616
iter  40 value 85.032656
iter  50 value 84.975170
iter  60 value 84.942045
iter  70 value 84.502166
iter  80 value 83.863935
iter  90 value 83.632463
iter 100 value 83.338167
final  value 83.338167 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 110.727117 
iter  10 value 94.476422
iter  20 value 86.386635
iter  30 value 84.503569
iter  40 value 84.017376
iter  50 value 83.976893
iter  60 value 83.929400
iter  70 value 83.760312
iter  80 value 83.720387
iter  90 value 83.650188
iter 100 value 83.631304
final  value 83.631304 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.667834 
iter  10 value 94.394127
iter  20 value 90.576968
iter  30 value 87.299062
iter  40 value 86.223466
iter  50 value 85.034755
iter  60 value 84.249559
iter  70 value 83.549676
iter  80 value 83.397757
iter  90 value 83.392465
iter 100 value 83.391436
final  value 83.391436 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 117.212347 
iter  10 value 94.480695
iter  20 value 93.419692
iter  30 value 85.842935
iter  40 value 85.639569
iter  50 value 85.594139
iter  60 value 85.540529
iter  70 value 84.211247
iter  80 value 82.813124
iter  90 value 81.949904
iter 100 value 81.366963
final  value 81.366963 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.777313 
iter  10 value 96.543024
iter  20 value 91.409519
iter  30 value 89.262456
iter  40 value 87.129298
iter  50 value 86.477650
iter  60 value 83.962620
iter  70 value 83.285238
iter  80 value 82.978162
iter  90 value 82.887035
iter 100 value 82.821225
final  value 82.821225 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.510016 
iter  10 value 94.596579
iter  20 value 87.894313
iter  30 value 86.236204
iter  40 value 84.282524
iter  50 value 83.903651
iter  60 value 83.552441
iter  70 value 82.645586
iter  80 value 82.018086
iter  90 value 81.840108
iter 100 value 81.773629
final  value 81.773629 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.691911 
iter  10 value 94.269005
iter  20 value 89.649203
iter  30 value 87.518297
iter  40 value 86.313454
iter  50 value 86.125595
iter  60 value 85.457182
iter  70 value 85.093468
iter  80 value 84.906841
iter  90 value 84.584558
iter 100 value 84.016692
final  value 84.016692 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 122.299574 
iter  10 value 97.828160
iter  20 value 92.312713
iter  30 value 88.580656
iter  40 value 86.730649
iter  50 value 85.110814
iter  60 value 83.513493
iter  70 value 82.621611
iter  80 value 82.446539
iter  90 value 82.266425
iter 100 value 81.891396
final  value 81.891396 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.650526 
iter  10 value 94.413944
iter  20 value 87.778584
iter  30 value 86.838191
iter  40 value 84.999240
iter  50 value 83.574626
iter  60 value 82.691190
iter  70 value 82.164382
iter  80 value 81.969176
iter  90 value 81.575058
iter 100 value 81.289854
final  value 81.289854 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.727990 
iter  10 value 94.214442
iter  10 value 94.214441
iter  10 value 94.214441
final  value 94.214441 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.002187 
iter  10 value 94.486229
final  value 94.484269 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.314172 
final  value 94.485586 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.146449 
final  value 94.485950 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.522017 
iter  10 value 94.485743
iter  20 value 94.484216
iter  30 value 85.165644
iter  40 value 85.094000
iter  50 value 85.011191
final  value 85.009884 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.773160 
iter  10 value 94.489247
iter  20 value 94.474921
iter  30 value 94.213257
iter  40 value 94.212916
final  value 94.212899 
converged
Fitting Repeat 2 

# weights:  305
initial  value 109.271569 
iter  10 value 94.453912
iter  20 value 85.783063
iter  30 value 85.044293
final  value 85.010517 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.342539 
iter  10 value 93.907650
iter  20 value 93.857922
iter  30 value 93.853308
iter  40 value 93.852063
iter  50 value 93.851956
final  value 93.851913 
converged
Fitting Repeat 4 

# weights:  305
initial  value 116.476129 
iter  10 value 94.448507
iter  20 value 94.446995
final  value 94.446170 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.946431 
iter  10 value 94.485089
iter  20 value 94.475111
iter  30 value 89.319222
iter  40 value 88.660054
iter  50 value 87.140417
iter  60 value 86.962432
iter  70 value 85.608244
iter  80 value 85.606921
iter  90 value 85.588625
iter 100 value 85.465505
final  value 85.465505 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 113.705578 
iter  10 value 94.212117
iter  20 value 94.204549
iter  30 value 94.203865
iter  40 value 94.203816
iter  40 value 94.203816
iter  40 value 94.203816
final  value 94.203816 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.824124 
iter  10 value 92.520205
iter  20 value 91.404118
iter  30 value 91.364629
iter  40 value 91.363018
iter  50 value 86.594615
iter  60 value 85.921111
iter  70 value 85.629505
iter  80 value 85.605913
iter  90 value 85.604243
final  value 85.604233 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.853735 
iter  10 value 94.498397
iter  20 value 94.267796
iter  30 value 88.655315
iter  40 value 84.525925
iter  50 value 84.484823
iter  60 value 84.319587
iter  70 value 83.610171
iter  80 value 83.464326
iter  90 value 83.462700
iter 100 value 83.435073
final  value 83.435073 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 98.327542 
iter  10 value 94.490541
iter  20 value 94.045669
iter  30 value 88.116071
iter  40 value 88.068593
iter  50 value 84.487971
iter  60 value 84.151573
final  value 83.655671 
converged
Fitting Repeat 5 

# weights:  507
initial  value 109.949783 
iter  10 value 94.455019
iter  20 value 94.356193
iter  30 value 84.075015
iter  40 value 83.844327
final  value 83.843835 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.854106 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.201571 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.336705 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 112.289812 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.961216 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.960590 
final  value 94.484210 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.883760 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.440380 
iter  10 value 87.687622
iter  20 value 82.438861
iter  30 value 82.259611
iter  40 value 80.928862
final  value 80.841615 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.302308 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.074050 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.970858 
iter  10 value 94.354545
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.386649 
final  value 94.322897 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.232975 
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.119283 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 112.967438 
iter  10 value 94.405566
final  value 94.322898 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.116968 
iter  10 value 93.884905
iter  20 value 92.903607
iter  30 value 87.010290
iter  40 value 85.735010
iter  50 value 84.381454
iter  60 value 82.176201
iter  70 value 81.219583
iter  80 value 80.062525
iter  90 value 80.018621
iter  90 value 80.018621
iter  90 value 80.018621
final  value 80.018621 
converged
Fitting Repeat 2 

# weights:  103
initial  value 109.761710 
iter  10 value 94.463418
iter  20 value 85.798024
iter  30 value 84.665996
iter  40 value 84.623309
iter  50 value 83.856844
iter  60 value 82.931259
iter  70 value 82.854918
iter  80 value 82.847069
final  value 82.847066 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.814493 
iter  10 value 94.461621
iter  20 value 88.653721
iter  30 value 85.043783
iter  40 value 84.574884
iter  50 value 84.046568
iter  60 value 83.343195
iter  70 value 83.301214
final  value 83.301075 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.863199 
iter  10 value 93.848298
iter  20 value 92.061286
iter  30 value 84.784976
iter  40 value 84.205336
iter  50 value 83.476142
iter  60 value 83.349456
iter  70 value 82.292906
final  value 82.287707 
converged
Fitting Repeat 5 

# weights:  103
initial  value 115.398937 
iter  10 value 94.491855
iter  20 value 94.057395
iter  30 value 91.590767
iter  40 value 90.521564
iter  50 value 87.384839
iter  60 value 83.635089
iter  70 value 83.095615
iter  80 value 82.813963
iter  90 value 82.657266
final  value 82.657045 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.965799 
iter  10 value 94.581683
iter  20 value 94.490117
iter  30 value 88.132252
iter  40 value 81.786967
iter  50 value 79.708875
iter  60 value 79.266828
iter  70 value 78.937220
iter  80 value 78.821786
iter  90 value 78.731306
iter 100 value 78.717800
final  value 78.717800 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.872313 
iter  10 value 94.341494
iter  20 value 85.445674
iter  30 value 84.407375
iter  40 value 83.128048
iter  50 value 83.063649
iter  60 value 82.978308
iter  70 value 82.613955
iter  80 value 81.125525
iter  90 value 80.029049
iter 100 value 79.847210
final  value 79.847210 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 116.256683 
iter  10 value 95.009559
iter  20 value 90.293367
iter  30 value 89.437963
iter  40 value 85.959781
iter  50 value 84.397170
iter  60 value 83.667310
iter  70 value 83.440125
iter  80 value 82.744739
iter  90 value 81.673917
iter 100 value 80.201019
final  value 80.201019 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 111.132073 
iter  10 value 94.409303
iter  20 value 92.594351
iter  30 value 91.532865
iter  40 value 87.140752
iter  50 value 83.000596
iter  60 value 82.420581
iter  70 value 82.238883
iter  80 value 82.165662
iter  90 value 80.988000
iter 100 value 80.939278
final  value 80.939278 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.695233 
iter  10 value 94.019683
iter  20 value 85.860909
iter  30 value 84.839282
iter  40 value 83.324060
iter  50 value 83.073672
iter  60 value 83.048702
iter  70 value 82.549416
iter  80 value 81.283511
iter  90 value 79.246986
iter 100 value 78.788201
final  value 78.788201 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.034835 
iter  10 value 95.367636
iter  20 value 89.535630
iter  30 value 85.766015
iter  40 value 82.415501
iter  50 value 81.828277
iter  60 value 81.507614
iter  70 value 80.908073
iter  80 value 79.883161
iter  90 value 79.706333
iter 100 value 79.360025
final  value 79.360025 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.393102 
iter  10 value 96.910167
iter  20 value 92.702123
iter  30 value 83.920795
iter  40 value 82.968332
iter  50 value 81.627920
iter  60 value 80.522810
iter  70 value 79.351023
iter  80 value 78.520647
iter  90 value 78.394143
iter 100 value 78.327799
final  value 78.327799 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 120.083106 
iter  10 value 94.473218
iter  20 value 86.726871
iter  30 value 81.706318
iter  40 value 80.253054
iter  50 value 79.045547
iter  60 value 78.855392
iter  70 value 78.284318
iter  80 value 78.194598
iter  90 value 78.041209
iter 100 value 78.002166
final  value 78.002166 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.268514 
iter  10 value 94.514473
iter  20 value 83.929710
iter  30 value 81.810555
iter  40 value 81.186281
iter  50 value 80.855173
iter  60 value 80.050940
iter  70 value 79.161551
iter  80 value 78.951560
iter  90 value 78.919350
iter 100 value 78.619155
final  value 78.619155 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.883494 
iter  10 value 96.525842
iter  20 value 87.810758
iter  30 value 87.109832
iter  40 value 84.292689
iter  50 value 83.966507
iter  60 value 83.676326
iter  70 value 83.412211
iter  80 value 83.125631
iter  90 value 82.657463
iter 100 value 81.592515
final  value 81.592515 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.709465 
final  value 94.355792 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.440916 
final  value 94.485818 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.281301 
iter  10 value 94.486063
iter  20 value 94.485789
iter  20 value 94.485789
iter  20 value 94.485789
final  value 94.485789 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.393834 
final  value 94.486192 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.023017 
final  value 94.485989 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.574598 
iter  10 value 94.486239
final  value 94.484433 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.593776 
iter  10 value 94.489074
iter  20 value 93.150046
iter  30 value 91.726779
iter  40 value 91.581079
iter  50 value 91.531092
final  value 91.529576 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.175103 
iter  10 value 94.489301
iter  20 value 94.370649
final  value 94.354465 
converged
Fitting Repeat 4 

# weights:  305
initial  value 125.063108 
iter  10 value 94.358833
iter  20 value 93.734169
iter  30 value 87.366596
iter  40 value 83.524454
iter  50 value 83.443723
iter  60 value 83.441179
final  value 83.441017 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.007650 
iter  10 value 94.488428
iter  20 value 94.484313
iter  30 value 84.735800
iter  40 value 81.569613
final  value 80.551648 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.540498 
iter  10 value 92.820644
iter  20 value 85.821340
iter  30 value 82.929507
iter  40 value 81.531696
iter  50 value 81.379958
iter  60 value 81.332091
final  value 81.331179 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.332196 
iter  10 value 94.489614
iter  20 value 92.343100
iter  30 value 84.229029
iter  40 value 84.195891
iter  50 value 84.191076
iter  60 value 82.360668
iter  70 value 78.967357
iter  80 value 78.945646
iter  90 value 78.944708
iter 100 value 78.893638
final  value 78.893638 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 101.314485 
iter  10 value 94.158740
iter  20 value 92.413663
iter  30 value 91.388449
iter  40 value 82.443171
iter  50 value 81.665451
iter  60 value 81.516503
iter  70 value 81.430915
iter  80 value 81.366587
iter  90 value 81.365589
iter 100 value 81.362549
final  value 81.362549 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.433990 
iter  10 value 87.386311
iter  20 value 87.221759
iter  30 value 86.555516
final  value 86.553129 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.151979 
iter  10 value 94.490861
iter  20 value 93.828622
iter  30 value 86.748818
iter  40 value 83.998811
iter  50 value 83.830686
iter  60 value 83.250955
iter  70 value 82.071213
iter  80 value 81.589923
iter  90 value 81.446939
final  value 81.441104 
converged
Fitting Repeat 1 

# weights:  507
initial  value 124.166899 
iter  10 value 112.622190
iter  20 value 110.337973
iter  30 value 106.498927
iter  40 value 105.831518
iter  50 value 105.829723
iter  60 value 105.797530
iter  70 value 105.784046
iter  80 value 105.783309
final  value 105.783264 
converged
Fitting Repeat 2 

# weights:  507
initial  value 120.551287 
iter  10 value 117.766185
final  value 117.764253 
converged
Fitting Repeat 3 

# weights:  507
initial  value 120.350482 
iter  10 value 117.738824
iter  20 value 117.732320
iter  30 value 107.058340
iter  40 value 106.974370
iter  50 value 104.629655
iter  60 value 101.669838
iter  70 value 101.220283
iter  80 value 101.212012
iter  90 value 101.121540
iter 100 value 100.999645
final  value 100.999645 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 123.221058 
iter  10 value 117.852575
iter  20 value 117.766895
iter  30 value 117.758892
iter  40 value 116.445043
iter  50 value 106.088595
iter  60 value 105.514230
iter  70 value 105.510258
final  value 105.508083 
converged
Fitting Repeat 5 

# weights:  507
initial  value 152.085273 
iter  10 value 117.898662
iter  20 value 117.891013
iter  30 value 106.912560
final  value 106.903183 
converged
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Sat May  2 01:21:33 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 
 40.605   1.162 107.312