##############################################################################
##############################################################################
###
### 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_1.17.2.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2026-01-15 r89304)
* 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 ‘1.17.2’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking 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 ... ERROR
Running examples in ‘HPiP-Ex.R’ failed
The error most likely occurred in:

> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: enrichfindP
> ### Title: Functional Enrichment Analysis for Pathogen Interactors in the
> ###   High-Confidence Network.
> ### Aliases: enrichfindP
> 
> ### ** Examples
> 
> data('predicted_PPIs')
> #perform enrichment
> enrich.df <- enrichfindP(predicted_PPIs,
+ threshold = 0.05,
+ sources = c("GO", "KEGG"),
+ p.corrction.method = "bonferroni",
+ org = "hsapiens")
Error: Request to g:Profiler failed (HTTP 504). The service may be temporarily unavailable.
If the issue persists, please contact biit.support@ut.ee with a reproducible example.
Execution halted
Examples with CPU (user + system) or elapsed time > 5s
            user system elapsed
corr_plot 33.928  0.395  34.325
FSmethod  32.691  0.595  33.295
* 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: 1 ERROR, 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 ‘1.17.2’
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R Under development (unstable) (2026-01-15 r89304) -- "Unsuffered Consequences"
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
avNNet
Loading required package: ggplot2
Loading required package: lattice
Fitting Repeat 1 

# weights:  103
initial  value 106.756476 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.665535 
iter  10 value 92.130512
iter  20 value 86.647470
iter  30 value 86.604582
iter  40 value 86.524624
final  value 86.523608 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.218260 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.778545 
final  value 94.443243 
converged
Fitting Repeat 5 

# weights:  103
initial  value 118.756180 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.188607 
iter  10 value 94.443245
final  value 94.443243 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.753792 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.412166 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.134885 
iter  10 value 88.473765
iter  20 value 88.364347
iter  30 value 88.279609
final  value 88.278674 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.285636 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.295378 
iter  10 value 93.585332
iter  20 value 86.478504
iter  30 value 86.473720
iter  40 value 86.473175
final  value 86.473172 
converged
Fitting Repeat 2 

# weights:  507
initial  value 114.133355 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.345919 
iter  10 value 94.256436
final  value 94.255553 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.082871 
iter  10 value 94.472274
iter  10 value 94.472274
iter  10 value 94.472274
final  value 94.472274 
converged
Fitting Repeat 5 

# weights:  507
initial  value 119.349778 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.244662 
iter  10 value 94.486999
iter  20 value 94.261696
iter  30 value 93.145622
iter  40 value 87.638557
iter  50 value 86.514174
iter  60 value 85.582800
iter  70 value 83.848352
iter  80 value 83.822104
iter  90 value 83.686190
iter 100 value 83.611403
final  value 83.611403 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.149128 
iter  10 value 94.463117
iter  20 value 88.080138
iter  30 value 86.488556
iter  40 value 86.389328
iter  50 value 86.001523
iter  60 value 85.719907
iter  70 value 85.360835
iter  80 value 85.263724
iter  90 value 85.257244
iter 100 value 85.253513
final  value 85.253513 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 105.561282 
iter  10 value 94.489024
iter  20 value 88.320775
iter  30 value 87.780046
iter  40 value 87.582921
iter  50 value 87.082387
iter  60 value 86.979844
iter  70 value 86.246369
iter  80 value 85.458839
iter  90 value 85.275966
iter 100 value 85.253597
final  value 85.253597 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.936303 
iter  10 value 94.486519
iter  20 value 93.834090
iter  30 value 90.460514
iter  40 value 89.972548
iter  50 value 87.202842
iter  60 value 85.391660
iter  70 value 85.073522
iter  80 value 85.067818
final  value 85.067649 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.052298 
iter  10 value 89.919503
iter  20 value 87.902914
iter  30 value 86.550505
iter  40 value 86.010465
iter  50 value 85.981299
iter  60 value 85.412619
iter  70 value 84.934829
iter  80 value 84.929861
iter  90 value 84.822880
iter 100 value 84.774879
final  value 84.774879 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 113.178543 
iter  10 value 96.611536
iter  20 value 95.257909
iter  30 value 91.114800
iter  40 value 89.799405
iter  50 value 89.246199
iter  60 value 84.727647
iter  70 value 83.965267
iter  80 value 82.718489
iter  90 value 82.346648
iter 100 value 82.218194
final  value 82.218194 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.570667 
iter  10 value 94.410025
iter  20 value 90.262941
iter  30 value 89.154228
iter  40 value 88.518793
iter  50 value 87.472283
iter  60 value 86.008850
iter  70 value 84.860988
iter  80 value 83.721859
iter  90 value 83.715954
iter 100 value 83.668436
final  value 83.668436 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 116.744864 
iter  10 value 94.138083
iter  20 value 87.497227
iter  30 value 86.162599
iter  40 value 85.025357
iter  50 value 84.227595
iter  60 value 84.150345
iter  70 value 84.003027
iter  80 value 83.379250
iter  90 value 82.683890
iter 100 value 82.529773
final  value 82.529773 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.473616 
iter  10 value 93.966236
iter  20 value 92.524313
iter  30 value 91.849563
iter  40 value 91.586120
iter  50 value 89.529738
iter  60 value 86.717788
iter  70 value 85.171679
iter  80 value 85.040124
iter  90 value 84.993894
iter 100 value 84.958151
final  value 84.958151 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 118.118849 
iter  10 value 94.905577
iter  20 value 88.626627
iter  30 value 86.784214
iter  40 value 86.333558
iter  50 value 85.840751
iter  60 value 85.065523
iter  70 value 84.819515
iter  80 value 83.805355
iter  90 value 82.907456
iter 100 value 82.695233
final  value 82.695233 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 118.726692 
iter  10 value 94.411938
iter  20 value 88.071490
iter  30 value 84.349280
iter  40 value 83.366634
iter  50 value 83.017314
iter  60 value 82.681354
iter  70 value 82.385755
iter  80 value 82.155221
iter  90 value 82.124273
iter 100 value 82.113561
final  value 82.113561 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 115.624046 
iter  10 value 94.587995
iter  20 value 92.564537
iter  30 value 91.772038
iter  40 value 87.901791
iter  50 value 86.115076
iter  60 value 85.440894
iter  70 value 84.016593
iter  80 value 83.233826
iter  90 value 82.605930
iter 100 value 82.285041
final  value 82.285041 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.321568 
iter  10 value 94.167890
iter  20 value 88.580605
iter  30 value 86.201464
iter  40 value 84.296169
iter  50 value 83.530957
iter  60 value 82.708541
iter  70 value 82.580045
iter  80 value 82.373594
iter  90 value 82.336428
iter 100 value 82.330348
final  value 82.330348 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.532013 
iter  10 value 93.497377
iter  20 value 92.174422
iter  30 value 90.502948
iter  40 value 85.511821
iter  50 value 84.779726
iter  60 value 84.375809
iter  70 value 83.913628
iter  80 value 83.347749
iter  90 value 82.756312
iter 100 value 82.578836
final  value 82.578836 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 144.289988 
iter  10 value 97.054536
iter  20 value 94.489425
iter  30 value 91.812440
iter  40 value 88.920837
iter  50 value 87.799827
iter  60 value 87.496308
iter  70 value 87.147182
iter  80 value 85.477771
iter  90 value 84.612030
iter 100 value 83.079751
final  value 83.079751 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.923596 
final  value 94.486093 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.542846 
final  value 94.485803 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.520439 
final  value 94.444869 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.172542 
final  value 94.485804 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.948494 
iter  10 value 89.315474
iter  20 value 86.265810
iter  30 value 86.219528
iter  40 value 86.219097
iter  50 value 85.385968
final  value 85.385768 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.190443 
iter  10 value 94.471879
iter  20 value 94.330247
iter  30 value 93.210699
iter  40 value 92.473426
iter  50 value 92.470635
iter  60 value 92.012730
iter  70 value 91.774554
iter  80 value 91.687032
final  value 91.685815 
converged
Fitting Repeat 2 

# weights:  305
initial  value 114.791138 
iter  10 value 94.489568
iter  20 value 94.423258
iter  30 value 92.568108
iter  40 value 85.935741
iter  50 value 83.836213
iter  60 value 83.668765
iter  70 value 83.393577
iter  80 value 83.387772
iter  90 value 83.387377
iter 100 value 83.162916
final  value 83.162916 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 98.210754 
iter  10 value 94.448109
iter  20 value 94.443908
final  value 94.443658 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.460479 
iter  10 value 94.489368
iter  20 value 94.412660
iter  30 value 91.296401
iter  40 value 85.402776
iter  50 value 82.829743
iter  60 value 82.552873
iter  70 value 82.550993
iter  80 value 82.512538
iter  90 value 82.511930
iter 100 value 82.511407
final  value 82.511407 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 97.450979 
iter  10 value 94.489045
iter  20 value 92.898098
iter  30 value 86.677622
iter  40 value 86.399525
iter  50 value 85.769034
iter  60 value 85.767415
final  value 85.767404 
converged
Fitting Repeat 1 

# weights:  507
initial  value 114.308007 
iter  10 value 94.494302
iter  20 value 94.266659
iter  30 value 91.997815
iter  40 value 91.959275
iter  50 value 91.838173
iter  60 value 91.513465
iter  70 value 91.085995
iter  80 value 91.076359
final  value 91.076356 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.088830 
iter  10 value 94.449667
iter  20 value 93.989794
iter  30 value 90.610620
iter  40 value 85.214045
iter  50 value 85.116557
iter  60 value 84.758954
final  value 84.750253 
converged
Fitting Repeat 3 

# weights:  507
initial  value 111.110977 
iter  10 value 94.451872
iter  20 value 94.445123
final  value 94.444617 
converged
Fitting Repeat 4 

# weights:  507
initial  value 125.898182 
iter  10 value 94.451334
iter  20 value 90.558256
iter  30 value 88.335131
iter  40 value 86.546426
iter  50 value 86.365763
final  value 86.364094 
converged
Fitting Repeat 5 

# weights:  507
initial  value 136.683655 
iter  10 value 94.491839
iter  20 value 93.499255
iter  30 value 91.999479
iter  40 value 91.632671
iter  50 value 88.653480
iter  60 value 88.415875
iter  70 value 88.083249
iter  80 value 87.882146
iter  90 value 87.844913
iter 100 value 86.831178
final  value 86.831178 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.606483 
iter  10 value 87.354155
final  value 87.283810 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.723468 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.195167 
final  value 94.484209 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.873317 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.018675 
iter  10 value 94.253033
iter  20 value 94.165766
final  value 94.165746 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.811053 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.892346 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.298016 
iter  10 value 94.470920
iter  20 value 94.443282
final  value 94.443183 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.406279 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 110.162269 
iter  10 value 94.439837
iter  20 value 94.165987
final  value 94.165747 
converged
Fitting Repeat 1 

# weights:  507
initial  value 112.434690 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.285833 
iter  10 value 94.500278
final  value 94.443137 
converged
Fitting Repeat 3 

# weights:  507
initial  value 114.587402 
iter  10 value 94.443142
final  value 94.443137 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.479458 
final  value 94.317413 
converged
Fitting Repeat 5 

# weights:  507
initial  value 130.842977 
final  value 94.443243 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.997046 
iter  10 value 94.457012
iter  20 value 92.651726
iter  30 value 89.435020
iter  40 value 86.986086
iter  50 value 85.005426
iter  60 value 84.930424
iter  70 value 84.795992
iter  80 value 84.233707
iter  90 value 83.647380
iter 100 value 83.643415
final  value 83.643415 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.649070 
iter  10 value 93.627970
iter  20 value 93.459103
iter  30 value 89.812389
iter  40 value 87.348168
iter  50 value 86.896908
iter  60 value 85.339637
iter  70 value 84.605445
iter  80 value 84.101728
iter  90 value 83.705065
iter 100 value 83.643422
final  value 83.643422 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.564374 
iter  10 value 94.503415
iter  20 value 88.643875
iter  30 value 87.825731
iter  40 value 87.006854
iter  50 value 85.072758
iter  60 value 84.607730
iter  70 value 84.069426
iter  80 value 83.855250
iter  90 value 83.790227
final  value 83.790207 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.611968 
iter  10 value 94.486543
iter  20 value 94.240829
iter  30 value 88.939113
iter  40 value 87.950651
iter  50 value 87.333057
iter  60 value 86.805702
iter  70 value 86.199685
iter  80 value 85.660071
final  value 85.648011 
converged
Fitting Repeat 5 

# weights:  103
initial  value 120.932321 
iter  10 value 94.105394
iter  20 value 89.216930
iter  30 value 88.774729
iter  40 value 88.656461
iter  50 value 88.594467
iter  60 value 86.923654
iter  70 value 86.584675
final  value 86.584488 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.117967 
iter  10 value 94.484404
iter  20 value 89.465041
iter  30 value 88.649998
iter  40 value 87.994479
iter  50 value 86.028309
iter  60 value 85.639141
iter  70 value 85.114143
iter  80 value 84.420081
iter  90 value 83.850415
iter 100 value 83.741027
final  value 83.741027 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.171091 
iter  10 value 94.697628
iter  20 value 94.014633
iter  30 value 89.685438
iter  40 value 88.364993
iter  50 value 86.064470
iter  60 value 84.966958
iter  70 value 84.018731
iter  80 value 83.693993
iter  90 value 83.234142
iter 100 value 83.100378
final  value 83.100378 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.246307 
iter  10 value 94.498328
iter  20 value 90.353828
iter  30 value 87.961240
iter  40 value 86.883858
iter  50 value 85.031442
iter  60 value 84.019464
iter  70 value 83.539398
iter  80 value 83.466923
iter  90 value 83.412454
iter 100 value 83.081855
final  value 83.081855 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 120.368269 
iter  10 value 94.536770
iter  20 value 93.597986
iter  30 value 93.003138
iter  40 value 89.913037
iter  50 value 86.947660
iter  60 value 85.325441
iter  70 value 84.389992
iter  80 value 83.561048
iter  90 value 83.178687
iter 100 value 82.971877
final  value 82.971877 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.932317 
iter  10 value 94.506687
iter  20 value 90.155908
iter  30 value 88.565286
iter  40 value 87.422511
iter  50 value 87.016998
iter  60 value 84.732445
iter  70 value 83.487986
iter  80 value 83.428075
iter  90 value 83.208188
iter 100 value 82.831715
final  value 82.831715 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.963440 
iter  10 value 94.578780
iter  20 value 93.787132
iter  30 value 92.086832
iter  40 value 91.811405
iter  50 value 90.296929
iter  60 value 86.948090
iter  70 value 84.166800
iter  80 value 82.972550
iter  90 value 82.785966
iter 100 value 82.644054
final  value 82.644054 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.978057 
iter  10 value 94.164006
iter  20 value 87.176811
iter  30 value 86.716669
iter  40 value 86.607882
iter  50 value 86.460943
iter  60 value 86.310741
iter  70 value 86.240741
iter  80 value 85.851965
iter  90 value 84.896260
iter 100 value 83.688286
final  value 83.688286 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.658595 
iter  10 value 94.964586
iter  20 value 94.844452
iter  30 value 88.905059
iter  40 value 87.524816
iter  50 value 86.975297
iter  60 value 86.669374
iter  70 value 86.492215
iter  80 value 86.371762
iter  90 value 86.249162
iter 100 value 85.950923
final  value 85.950923 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 123.231082 
iter  10 value 94.554660
iter  20 value 94.491195
iter  30 value 93.515073
iter  40 value 89.811830
iter  50 value 87.560663
iter  60 value 85.423449
iter  70 value 83.661825
iter  80 value 82.976241
iter  90 value 82.717916
iter 100 value 82.693032
final  value 82.693032 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 120.605014 
iter  10 value 96.279160
iter  20 value 94.296155
iter  30 value 92.381723
iter  40 value 88.233778
iter  50 value 85.609138
iter  60 value 85.155900
iter  70 value 84.857849
iter  80 value 83.904211
iter  90 value 83.702131
iter 100 value 83.359038
final  value 83.359038 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.170637 
iter  10 value 94.485769
iter  20 value 94.482332
iter  30 value 91.722122
iter  40 value 90.326095
iter  50 value 90.325963
iter  60 value 90.325584
iter  70 value 90.325418
final  value 90.325388 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.039140 
final  value 94.485852 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.709975 
final  value 94.485783 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.333888 
iter  10 value 94.486089
iter  20 value 94.484228
final  value 94.484212 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.709290 
iter  10 value 94.485996
final  value 94.485059 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.013276 
iter  10 value 94.448466
iter  20 value 94.444820
iter  30 value 92.275473
iter  40 value 87.285683
iter  50 value 87.211879
iter  60 value 87.104686
final  value 87.104639 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.363569 
iter  10 value 94.489143
iter  20 value 94.466412
iter  30 value 89.599027
iter  40 value 88.752598
iter  50 value 88.715875
final  value 88.715790 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.127872 
iter  10 value 94.448198
iter  20 value 94.443435
iter  30 value 94.395624
iter  40 value 94.354465
final  value 94.354446 
converged
Fitting Repeat 4 

# weights:  305
initial  value 109.693627 
iter  10 value 94.488459
iter  20 value 94.458130
iter  30 value 92.752876
iter  40 value 85.852573
iter  50 value 85.846639
iter  60 value 85.792212
iter  70 value 85.395315
iter  80 value 83.496144
iter  90 value 82.358457
iter 100 value 82.298324
final  value 82.298324 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 95.390962 
iter  10 value 94.481453
iter  20 value 90.884849
iter  30 value 87.293413
iter  40 value 87.289309
iter  50 value 87.068058
iter  60 value 86.641021
iter  70 value 83.380058
iter  80 value 82.870882
iter  90 value 81.772238
iter 100 value 81.432575
final  value 81.432575 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 98.427212 
iter  10 value 94.393605
iter  20 value 94.107334
iter  30 value 94.105273
iter  40 value 94.091202
iter  50 value 94.067365
iter  60 value 94.066791
final  value 94.066702 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.405976 
iter  10 value 94.492047
iter  20 value 94.484230
iter  30 value 94.135681
iter  40 value 92.462029
iter  50 value 92.295160
iter  60 value 91.835209
iter  70 value 91.803430
iter  80 value 87.282431
iter  90 value 86.484807
iter 100 value 83.775473
final  value 83.775473 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.151368 
iter  10 value 94.451175
iter  20 value 93.826004
iter  30 value 86.424521
iter  40 value 85.508694
final  value 85.492554 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.550164 
iter  10 value 94.492039
iter  20 value 94.448693
iter  30 value 94.285238
iter  40 value 93.882962
iter  50 value 90.192617
final  value 90.125396 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.561397 
iter  10 value 94.491946
iter  20 value 94.484211
iter  30 value 88.148628
iter  40 value 86.629784
iter  50 value 85.088404
iter  60 value 84.633745
iter  70 value 83.911454
iter  80 value 83.496337
iter  90 value 83.491645
iter 100 value 83.043040
final  value 83.043040 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.552581 
iter  10 value 94.404670
final  value 94.275362 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.998865 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.077698 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.555787 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.430204 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.345287 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.718626 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.519951 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.874936 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 109.339911 
iter  10 value 94.168918
iter  20 value 90.830838
iter  30 value 85.322818
iter  40 value 84.885620
iter  50 value 84.846659
iter  60 value 84.004663
iter  70 value 83.949984
final  value 83.949775 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.462392 
iter  10 value 93.530551
iter  20 value 93.498974
final  value 93.498965 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.218503 
final  value 94.305883 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.822696 
final  value 94.275363 
converged
Fitting Repeat 4 

# weights:  507
initial  value 111.571272 
iter  10 value 86.862668
iter  20 value 86.377637
iter  30 value 85.683890
final  value 85.647280 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.310275 
final  value 94.448052 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.523748 
iter  10 value 94.514648
iter  20 value 92.105839
iter  30 value 82.929395
iter  40 value 82.105684
iter  50 value 81.516094
iter  60 value 81.402949
iter  70 value 80.434499
iter  80 value 79.955888
iter  80 value 79.955888
final  value 79.955888 
converged
Fitting Repeat 2 

# weights:  103
initial  value 109.972077 
iter  10 value 94.364306
iter  20 value 85.830234
iter  30 value 82.190826
iter  40 value 81.801282
iter  50 value 80.584645
iter  60 value 79.884039
iter  70 value 79.796619
iter  80 value 79.754871
final  value 79.754866 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.999710 
iter  10 value 94.168565
iter  20 value 89.708600
iter  30 value 85.744636
iter  40 value 82.775637
iter  50 value 80.859505
iter  60 value 80.311386
iter  70 value 79.997518
iter  80 value 79.840762
iter  90 value 79.764091
final  value 79.754867 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.992006 
iter  10 value 94.488498
iter  20 value 94.127193
iter  30 value 85.840558
iter  40 value 83.885264
iter  50 value 83.462107
iter  60 value 83.264597
iter  70 value 83.246294
final  value 83.246273 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.466136 
iter  10 value 94.469776
iter  20 value 90.980968
iter  30 value 85.935807
iter  40 value 84.551024
iter  50 value 81.929017
iter  60 value 80.304821
iter  70 value 79.882936
iter  80 value 79.858071
final  value 79.857690 
converged
Fitting Repeat 1 

# weights:  305
initial  value 125.913504 
iter  10 value 94.968695
iter  20 value 85.636485
iter  30 value 83.982623
iter  40 value 82.554627
iter  50 value 81.542838
iter  60 value 81.062489
iter  70 value 80.717824
iter  80 value 80.507056
iter  90 value 80.310075
iter 100 value 80.143428
final  value 80.143428 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.030763 
iter  10 value 94.473064
iter  20 value 94.253077
iter  30 value 92.952477
iter  40 value 88.612082
iter  50 value 85.627124
iter  60 value 84.879951
iter  70 value 84.652731
iter  80 value 79.769670
iter  90 value 79.412755
iter 100 value 79.104724
final  value 79.104724 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.017042 
iter  10 value 94.460547
iter  20 value 87.417030
iter  30 value 84.785278
iter  40 value 82.945480
iter  50 value 82.455291
iter  60 value 80.476874
iter  70 value 79.930442
iter  80 value 79.498965
iter  90 value 79.324876
iter 100 value 79.232121
final  value 79.232121 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.462490 
iter  10 value 91.942300
iter  20 value 85.571322
iter  30 value 84.195389
iter  40 value 83.451114
iter  50 value 82.040824
iter  60 value 81.178202
iter  70 value 80.644741
iter  80 value 80.020790
iter  90 value 79.867291
iter 100 value 79.587560
final  value 79.587560 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 118.211607 
iter  10 value 93.944990
iter  20 value 83.718992
iter  30 value 83.612136
iter  40 value 83.099595
iter  50 value 82.636702
iter  60 value 82.539112
iter  70 value 80.283575
iter  80 value 78.891545
iter  90 value 78.506952
iter 100 value 78.439113
final  value 78.439113 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.373654 
iter  10 value 95.612003
iter  20 value 92.231312
iter  30 value 88.004273
iter  40 value 87.800491
iter  50 value 84.334470
iter  60 value 82.744754
iter  70 value 82.513079
iter  80 value 82.265224
iter  90 value 81.534294
iter 100 value 79.779953
final  value 79.779953 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.521509 
iter  10 value 94.460224
iter  20 value 93.098729
iter  30 value 91.346374
iter  40 value 83.186746
iter  50 value 81.906854
iter  60 value 81.366861
iter  70 value 81.045862
iter  80 value 80.964794
iter  90 value 80.502835
iter 100 value 79.236519
final  value 79.236519 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.936593 
iter  10 value 94.235533
iter  20 value 86.622350
iter  30 value 84.780286
iter  40 value 83.883607
iter  50 value 83.558222
iter  60 value 83.183536
iter  70 value 80.883241
iter  80 value 80.398310
iter  90 value 80.031029
iter 100 value 79.680163
final  value 79.680163 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.353506 
iter  10 value 94.641088
iter  20 value 85.320571
iter  30 value 84.560106
iter  40 value 83.282913
iter  50 value 82.838352
iter  60 value 80.597013
iter  70 value 79.969580
iter  80 value 79.371569
iter  90 value 78.654811
iter 100 value 78.081296
final  value 78.081296 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.118216 
iter  10 value 94.695285
iter  20 value 94.411007
iter  30 value 89.032002
iter  40 value 84.626631
iter  50 value 82.250130
iter  60 value 81.463272
iter  70 value 81.026610
iter  80 value 80.057984
iter  90 value 79.467202
iter 100 value 79.244977
final  value 79.244977 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.730358 
final  value 94.485707 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.178828 
final  value 94.485707 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.168754 
iter  10 value 94.485723
iter  20 value 93.394536
iter  30 value 86.735574
iter  40 value 85.273577
iter  50 value 84.433253
iter  60 value 84.424189
final  value 84.420578 
converged
Fitting Repeat 4 

# weights:  103
initial  value 112.384057 
iter  10 value 85.957832
iter  20 value 85.956642
iter  30 value 85.956036
iter  40 value 84.765305
iter  50 value 84.764217
final  value 84.764197 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.445006 
iter  10 value 94.216026
iter  20 value 94.215495
iter  30 value 91.597835
final  value 83.956543 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.845604 
iter  10 value 88.212705
iter  20 value 87.773837
iter  30 value 87.768126
iter  40 value 85.460612
iter  50 value 83.669158
iter  60 value 82.973409
iter  70 value 82.948591
iter  70 value 82.948591
iter  70 value 82.948590
final  value 82.948590 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.192602 
iter  10 value 94.486470
iter  20 value 94.476341
iter  30 value 94.141837
iter  40 value 91.629973
iter  50 value 91.446408
iter  60 value 91.342945
iter  70 value 91.323560
iter  80 value 81.795293
iter  90 value 81.739127
final  value 81.739032 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.338470 
iter  10 value 94.489076
iter  20 value 94.326484
iter  30 value 91.444528
iter  40 value 91.440704
iter  50 value 91.329349
iter  60 value 91.265516
iter  70 value 91.264611
iter  80 value 91.192523
final  value 91.192290 
converged
Fitting Repeat 4 

# weights:  305
initial  value 115.485371 
iter  10 value 94.489627
iter  20 value 94.484605
iter  30 value 92.627875
iter  40 value 90.627429
iter  50 value 90.560226
final  value 90.560223 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.272374 
iter  10 value 94.489202
iter  20 value 94.484214
iter  20 value 94.484213
final  value 94.484213 
converged
Fitting Repeat 1 

# weights:  507
initial  value 128.667023 
iter  10 value 94.283641
iter  20 value 94.276117
final  value 94.275837 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.866500 
iter  10 value 94.491719
iter  20 value 92.472474
iter  30 value 83.101976
iter  40 value 82.632901
iter  50 value 82.631241
iter  60 value 82.564371
final  value 82.564121 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.357554 
iter  10 value 94.283584
iter  20 value 94.033803
iter  30 value 87.677631
iter  40 value 84.580299
iter  50 value 84.347705
iter  60 value 84.192314
final  value 84.149483 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.679632 
iter  10 value 94.284269
iter  20 value 94.277363
iter  30 value 92.632156
iter  40 value 90.509003
iter  50 value 90.446470
iter  60 value 90.445407
iter  70 value 89.814825
iter  80 value 80.000894
iter  90 value 79.903048
final  value 79.902974 
converged
Fitting Repeat 5 

# weights:  507
initial  value 118.244412 
iter  10 value 93.789893
iter  20 value 92.020420
iter  30 value 91.981956
iter  40 value 90.414884
iter  50 value 90.364896
iter  60 value 90.361566
iter  70 value 85.495026
iter  80 value 81.004990
iter  90 value 80.430379
iter 100 value 80.427979
final  value 80.427979 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.082278 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.983776 
iter  10 value 90.853981
iter  20 value 89.942788
final  value 89.940914 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.445572 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.338706 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.249027 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.440504 
iter  10 value 93.915736
final  value 93.410245 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.188046 
final  value 93.810010 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.494647 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.800448 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.417673 
final  value 94.050000 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.018428 
iter  10 value 85.409953
iter  20 value 82.669558
iter  30 value 82.666269
final  value 82.666086 
converged
Fitting Repeat 2 

# weights:  507
initial  value 117.483742 
final  value 93.915746 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.034785 
iter  10 value 91.458539
iter  20 value 91.387446
iter  20 value 91.387446
iter  20 value 91.387446
final  value 91.387446 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.244042 
final  value 93.915747 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.649140 
iter  10 value 92.377252
final  value 92.377055 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.608197 
iter  10 value 94.062053
iter  20 value 93.914552
iter  30 value 93.473698
iter  40 value 93.464753
iter  50 value 93.461267
iter  60 value 93.460695
iter  70 value 93.070457
iter  80 value 87.522922
iter  90 value 86.241839
iter 100 value 86.095772
final  value 86.095772 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 98.520671 
iter  10 value 93.337477
iter  20 value 85.855128
iter  30 value 83.941334
iter  40 value 83.577827
iter  50 value 83.120854
final  value 83.120452 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.917031 
iter  10 value 93.998516
iter  20 value 90.167952
iter  30 value 85.870242
iter  40 value 85.738346
iter  50 value 85.627248
iter  60 value 83.410814
iter  70 value 83.096066
iter  80 value 83.014138
iter  90 value 83.012414
final  value 83.012366 
converged
Fitting Repeat 4 

# weights:  103
initial  value 119.433418 
iter  10 value 94.226024
iter  20 value 94.045666
iter  30 value 93.578454
iter  40 value 93.480438
iter  50 value 93.469224
iter  60 value 92.928588
iter  70 value 87.733476
iter  80 value 86.456327
iter  90 value 85.445861
iter 100 value 83.867471
final  value 83.867471 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.561699 
iter  10 value 94.034388
iter  20 value 89.076671
iter  30 value 86.483390
iter  40 value 85.947892
iter  50 value 85.721355
iter  60 value 85.509467
iter  70 value 84.294654
iter  80 value 83.053049
iter  90 value 83.017709
final  value 83.012366 
converged
Fitting Repeat 1 

# weights:  305
initial  value 121.365001 
iter  10 value 94.024963
iter  20 value 86.283839
iter  30 value 85.842400
iter  40 value 84.821518
iter  50 value 81.911146
iter  60 value 80.719822
iter  70 value 80.578113
iter  80 value 80.462232
iter  90 value 80.395309
iter 100 value 80.367514
final  value 80.367514 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.655956 
iter  10 value 94.074997
iter  20 value 93.379792
iter  30 value 83.869127
iter  40 value 83.557648
iter  50 value 82.101077
iter  60 value 81.199538
iter  70 value 80.854673
iter  80 value 80.500989
iter  90 value 80.471327
iter 100 value 80.460694
final  value 80.460694 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.453698 
iter  10 value 93.912366
iter  20 value 90.361299
iter  30 value 89.405516
iter  40 value 87.820709
iter  50 value 84.047137
iter  60 value 83.803414
iter  70 value 83.521842
iter  80 value 81.875702
iter  90 value 80.818623
iter 100 value 80.713067
final  value 80.713067 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.666169 
iter  10 value 94.055086
iter  20 value 93.726599
iter  30 value 93.514748
iter  40 value 93.037850
iter  50 value 89.821937
iter  60 value 84.122239
iter  70 value 82.160995
iter  80 value 82.087252
iter  90 value 81.921236
iter 100 value 81.313994
final  value 81.313994 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.123337 
iter  10 value 94.069843
iter  20 value 93.715486
iter  30 value 90.559404
iter  40 value 86.887450
iter  50 value 83.989358
iter  60 value 82.328339
iter  70 value 81.753263
iter  80 value 81.368931
iter  90 value 81.011389
iter 100 value 80.847050
final  value 80.847050 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 126.797836 
iter  10 value 93.199113
iter  20 value 92.130392
iter  30 value 88.275945
iter  40 value 83.322455
iter  50 value 81.912135
iter  60 value 81.239511
iter  70 value 80.941398
iter  80 value 80.808774
iter  90 value 80.531007
iter 100 value 80.429911
final  value 80.429911 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 110.741912 
iter  10 value 94.723140
iter  20 value 87.223901
iter  30 value 83.563393
iter  40 value 82.773654
iter  50 value 82.256008
iter  60 value 81.878594
iter  70 value 81.817892
iter  80 value 81.778255
iter  90 value 81.178829
iter 100 value 80.934738
final  value 80.934738 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.580908 
iter  10 value 94.020817
iter  20 value 92.609598
iter  30 value 88.337271
iter  40 value 86.331071
iter  50 value 83.002131
iter  60 value 82.559966
iter  70 value 82.363093
iter  80 value 82.092836
iter  90 value 81.205324
iter 100 value 81.082311
final  value 81.082311 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.847012 
iter  10 value 94.279588
iter  20 value 93.434755
iter  30 value 87.861053
iter  40 value 84.516337
iter  50 value 83.781973
iter  60 value 82.362347
iter  70 value 81.812915
iter  80 value 81.649754
iter  90 value 81.572830
iter 100 value 80.929021
final  value 80.929021 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.718191 
iter  10 value 93.739197
iter  20 value 84.644197
iter  30 value 84.269372
iter  40 value 82.527557
iter  50 value 81.850452
iter  60 value 81.806316
iter  70 value 81.543782
iter  80 value 80.875047
iter  90 value 80.515973
iter 100 value 80.388478
final  value 80.388478 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.596666 
final  value 93.811854 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.140445 
final  value 94.054317 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.322504 
final  value 94.054658 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.484983 
iter  10 value 93.917807
iter  20 value 93.711765
final  value 93.697344 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.352498 
final  value 93.917448 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.988429 
iter  10 value 94.058166
iter  20 value 94.052945
iter  20 value 94.052945
iter  20 value 94.052945
final  value 94.052945 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.492619 
iter  10 value 94.052763
iter  20 value 92.109941
iter  30 value 83.568675
iter  40 value 83.558653
iter  50 value 82.266001
iter  60 value 81.587857
iter  70 value 81.473909
iter  80 value 81.468435
final  value 81.468413 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.307098 
iter  10 value 93.920349
iter  20 value 93.775386
iter  30 value 84.371273
iter  40 value 83.579892
iter  50 value 83.571799
iter  60 value 83.571725
iter  70 value 83.498177
iter  80 value 83.468036
final  value 83.468033 
converged
Fitting Repeat 4 

# weights:  305
initial  value 109.199659 
iter  10 value 94.057750
iter  20 value 94.040200
iter  30 value 93.215537
iter  40 value 93.054039
final  value 93.053882 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.649051 
iter  10 value 93.934084
iter  20 value 93.920221
iter  30 value 93.918315
iter  40 value 93.554433
iter  50 value 91.482620
iter  60 value 91.480428
iter  70 value 82.012987
final  value 81.864774 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.837654 
iter  10 value 83.729936
iter  20 value 82.204753
iter  30 value 81.570431
iter  40 value 81.016770
final  value 81.010967 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.425658 
iter  10 value 93.923722
iter  20 value 93.916409
final  value 93.916074 
converged
Fitting Repeat 3 

# weights:  507
initial  value 128.341301 
iter  10 value 87.497084
iter  20 value 82.614888
iter  30 value 82.609705
iter  40 value 82.392655
iter  50 value 81.972148
iter  60 value 81.638841
iter  70 value 81.597969
iter  80 value 81.597890
iter  90 value 81.597281
iter 100 value 81.001467
final  value 81.001467 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 127.170441 
iter  10 value 93.924369
iter  20 value 92.828735
iter  30 value 87.852632
iter  40 value 87.802915
final  value 87.802024 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.728864 
iter  10 value 94.060373
iter  20 value 93.975320
iter  30 value 84.578479
iter  40 value 83.145411
iter  50 value 81.477001
iter  60 value 81.097702
final  value 81.097625 
converged
Fitting Repeat 1 

# weights:  103
initial  value 106.506674 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.462270 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.947950 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.563782 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.295352 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 116.937857 
iter  10 value 93.989631
final  value 93.987879 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.133298 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.271875 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.767113 
iter  10 value 82.475902
iter  20 value 81.339644
final  value 81.339643 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.019357 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.632308 
final  value 92.792106 
converged
Fitting Repeat 2 

# weights:  507
initial  value 118.176134 
iter  10 value 91.764746
iter  20 value 83.776646
iter  30 value 83.581042
iter  40 value 83.339621
iter  50 value 82.682574
final  value 82.654975 
converged
Fitting Repeat 3 

# weights:  507
initial  value 128.642370 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.050445 
iter  10 value 90.423614
final  value 90.420366 
converged
Fitting Repeat 5 

# weights:  507
initial  value 119.373087 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.199877 
iter  10 value 94.054571
iter  20 value 93.477215
iter  30 value 92.826511
iter  40 value 86.881345
iter  50 value 85.313593
iter  60 value 85.059719
iter  70 value 81.626426
iter  80 value 81.574841
iter  90 value 81.569267
iter 100 value 81.568488
final  value 81.568488 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 109.752797 
iter  10 value 94.054856
iter  20 value 84.331304
iter  30 value 82.228127
iter  40 value 81.000324
iter  50 value 79.595909
iter  60 value 79.218472
iter  70 value 78.811993
iter  80 value 78.673534
iter  90 value 78.457572
iter 100 value 78.431459
final  value 78.431459 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 108.032423 
iter  10 value 93.879101
iter  20 value 85.760736
iter  30 value 80.035503
iter  40 value 79.781605
iter  50 value 79.611710
iter  60 value 79.057253
iter  70 value 78.433655
final  value 78.431458 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.411749 
iter  10 value 93.690442
iter  20 value 92.026234
iter  30 value 85.633764
iter  40 value 79.809032
iter  50 value 79.588593
iter  60 value 78.967591
iter  70 value 78.649704
iter  80 value 78.524381
iter  90 value 78.274311
iter 100 value 78.232082
final  value 78.232082 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.036688 
iter  10 value 94.067944
iter  20 value 90.999848
iter  30 value 88.936678
iter  40 value 88.876280
iter  50 value 80.521795
iter  60 value 79.798027
iter  70 value 79.551286
iter  80 value 78.805732
iter  90 value 78.392478
iter 100 value 78.364112
final  value 78.364112 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 122.517217 
iter  10 value 93.126462
iter  20 value 90.360153
iter  30 value 82.383073
iter  40 value 79.814472
iter  50 value 78.222958
iter  60 value 77.500522
iter  70 value 77.367812
iter  80 value 77.336424
iter  90 value 77.187971
iter 100 value 77.049905
final  value 77.049905 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.098289 
iter  10 value 94.270150
iter  20 value 92.735957
iter  30 value 85.755676
iter  40 value 85.028687
iter  50 value 83.747494
iter  60 value 79.890770
iter  70 value 79.453043
iter  80 value 79.200786
iter  90 value 78.593853
iter 100 value 78.000227
final  value 78.000227 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 140.438333 
iter  10 value 91.217955
iter  20 value 84.442089
iter  30 value 82.665902
iter  40 value 81.699352
iter  50 value 80.842351
iter  60 value 79.734004
iter  70 value 79.182594
iter  80 value 79.036319
iter  90 value 78.928523
iter 100 value 78.797750
final  value 78.797750 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.509481 
iter  10 value 94.020602
iter  20 value 92.626002
iter  30 value 90.677843
iter  40 value 89.927457
iter  50 value 86.912551
iter  60 value 80.093982
iter  70 value 79.616291
iter  80 value 78.897794
iter  90 value 78.726196
iter 100 value 78.431689
final  value 78.431689 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 115.288424 
iter  10 value 94.086127
iter  20 value 82.945122
iter  30 value 82.668193
iter  40 value 81.992262
iter  50 value 81.334788
iter  60 value 81.042191
iter  70 value 80.993365
iter  80 value 80.930403
iter  90 value 79.794266
iter 100 value 78.234798
final  value 78.234798 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.203595 
iter  10 value 93.965948
iter  20 value 83.896848
iter  30 value 80.225605
iter  40 value 79.651756
iter  50 value 78.991248
iter  60 value 78.543347
iter  70 value 78.304957
iter  80 value 77.285321
iter  90 value 77.069915
iter 100 value 76.700378
final  value 76.700378 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.018283 
iter  10 value 94.186360
iter  20 value 91.752123
iter  30 value 88.532792
iter  40 value 85.678319
iter  50 value 82.456444
iter  60 value 80.078338
iter  70 value 78.388366
iter  80 value 77.895488
iter  90 value 77.577821
iter 100 value 76.971304
final  value 76.971304 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.904198 
iter  10 value 94.015033
iter  20 value 93.583483
iter  30 value 91.899353
iter  40 value 82.731350
iter  50 value 81.087657
iter  60 value 80.601941
iter  70 value 79.206561
iter  80 value 78.184184
iter  90 value 77.160750
iter 100 value 76.413053
final  value 76.413053 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 131.930001 
iter  10 value 93.944349
iter  20 value 89.722856
iter  30 value 86.697947
iter  40 value 84.428185
iter  50 value 80.944037
iter  60 value 79.222790
iter  70 value 77.983518
iter  80 value 76.963381
iter  90 value 76.547783
iter 100 value 76.390395
final  value 76.390395 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.257743 
iter  10 value 96.391933
iter  20 value 88.287319
iter  30 value 82.783752
iter  40 value 82.471059
iter  50 value 82.329027
iter  60 value 81.857938
iter  70 value 80.998732
iter  80 value 79.328672
iter  90 value 78.548790
iter 100 value 78.138801
final  value 78.138801 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.238354 
iter  10 value 91.685042
iter  20 value 90.455075
iter  30 value 90.451465
iter  40 value 90.451396
final  value 90.451344 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.219266 
final  value 94.054740 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.401899 
iter  10 value 93.655532
iter  20 value 93.653505
iter  30 value 93.587620
iter  40 value 82.416621
final  value 82.334061 
converged
Fitting Repeat 4 

# weights:  103
initial  value 108.384344 
final  value 94.054622 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.810024 
iter  10 value 94.054479
iter  20 value 94.048546
iter  30 value 93.410381
iter  40 value 88.558846
iter  50 value 88.133967
iter  60 value 83.142687
iter  70 value 83.142046
iter  70 value 83.142046
iter  70 value 83.142046
final  value 83.142046 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.333011 
iter  10 value 92.640553
iter  20 value 92.528857
iter  30 value 92.528312
iter  40 value 91.717454
iter  50 value 91.213744
iter  60 value 89.984790
iter  70 value 89.580172
iter  80 value 89.579366
iter  90 value 89.579153
final  value 89.579148 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.415588 
iter  10 value 93.920507
iter  20 value 93.437207
iter  30 value 93.412082
iter  40 value 93.410817
final  value 93.410812 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.904357 
iter  10 value 94.074205
iter  20 value 82.604583
iter  30 value 81.847070
iter  40 value 81.843525
iter  50 value 81.840930
iter  60 value 81.809580
iter  70 value 81.804113
iter  80 value 81.800308
iter  90 value 81.735997
iter 100 value 78.870011
final  value 78.870011 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 95.621811 
iter  10 value 94.057597
iter  20 value 93.592627
iter  30 value 93.448379
iter  40 value 84.591003
iter  50 value 84.468379
iter  60 value 84.362438
iter  70 value 81.876228
final  value 81.873453 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.730131 
iter  10 value 94.055970
iter  20 value 94.020509
iter  30 value 83.685510
iter  40 value 83.086811
iter  50 value 81.913029
iter  60 value 81.866670
iter  70 value 81.864159
iter  80 value 81.847289
iter  90 value 81.836188
iter 100 value 81.836062
final  value 81.836062 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 95.492409 
iter  10 value 92.579723
iter  20 value 92.579112
iter  30 value 92.034383
iter  40 value 91.908405
iter  50 value 91.905303
iter  60 value 91.324406
iter  70 value 82.102407
iter  80 value 81.637427
iter  90 value 80.055872
iter 100 value 79.660686
final  value 79.660686 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 121.035578 
iter  10 value 94.060537
iter  20 value 93.581782
iter  30 value 92.960290
iter  40 value 91.420707
iter  50 value 90.613274
iter  60 value 89.344710
iter  70 value 89.342970
final  value 89.342653 
converged
Fitting Repeat 3 

# weights:  507
initial  value 118.577105 
iter  10 value 94.061051
iter  20 value 93.991553
iter  30 value 93.418357
iter  40 value 93.399015
final  value 93.397800 
converged
Fitting Repeat 4 

# weights:  507
initial  value 113.413344 
iter  10 value 93.867541
iter  20 value 93.580978
iter  30 value 93.579779
iter  40 value 90.929410
iter  50 value 89.899956
iter  60 value 89.757972
iter  70 value 89.705403
iter  80 value 86.132348
iter  90 value 78.171874
iter 100 value 77.902473
final  value 77.902473 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 95.046031 
iter  10 value 94.025445
iter  20 value 85.124582
iter  30 value 84.997679
iter  40 value 84.381166
final  value 84.224374 
converged
Fitting Repeat 1 

# weights:  305
initial  value 119.477504 
iter  10 value 117.895082
iter  20 value 117.890399
iter  30 value 117.058110
iter  40 value 104.774954
iter  50 value 104.296334
iter  60 value 104.293271
final  value 104.292156 
converged
Fitting Repeat 2 

# weights:  305
initial  value 121.287971 
iter  10 value 117.898241
iter  20 value 117.893213
final  value 117.893207 
converged
Fitting Repeat 3 

# weights:  305
initial  value 128.762099 
iter  10 value 117.895343
iter  20 value 113.252079
iter  30 value 108.326632
iter  40 value 108.324121
iter  50 value 108.177609
final  value 108.175361 
converged
Fitting Repeat 4 

# weights:  305
initial  value 127.812292 
iter  10 value 117.763955
iter  20 value 117.710724
iter  30 value 109.136748
iter  40 value 108.962782
iter  50 value 108.954257
iter  60 value 108.951523
iter  60 value 108.951523
final  value 108.951523 
converged
Fitting Repeat 5 

# weights:  305
initial  value 128.081149 
iter  10 value 117.895928
iter  20 value 117.891110
final  value 117.891045 
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 -- Fri Feb 27 01:00:10 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 
 39.621   1.277 501.294