##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.24-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.24-bioc/R/site-library --timings HPiP_1.19.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.24-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: 2026-05-04 04:42:51 UTC
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.19.0’
* 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
corr_plot     34.779  0.300  35.129
var_imp       34.075  0.471  34.574
FSmethod      33.855  0.567  34.486
pred_ensembel 13.024  0.096  11.862
enrichfindP    0.591  0.033   8.211
* 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-3.24-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.24-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.24-bioc/R/site-library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.19.0’
** 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 95.035797 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.207557 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.096513 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.367870 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.076179 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.785994 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.697636 
iter  10 value 94.326054
iter  10 value 94.326054
iter  10 value 94.326054
final  value 94.326054 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.881865 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  305
initial  value 108.932972 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.765641 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.006404 
iter  10 value 93.757213
final  value 93.747673 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.746951 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.600061 
iter  10 value 93.891063
iter  20 value 93.726256
final  value 93.726244 
converged
Fitting Repeat 4 

# weights:  507
initial  value 115.761581 
iter  10 value 94.431926
iter  20 value 94.427423
final  value 94.326094 
converged
Fitting Repeat 5 

# weights:  507
initial  value 112.721253 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.982834 
iter  10 value 94.423223
iter  20 value 94.256956
iter  30 value 94.139201
iter  40 value 93.974611
iter  50 value 92.309421
iter  60 value 89.318341
iter  70 value 86.952959
iter  80 value 85.155337
iter  90 value 84.679005
iter 100 value 84.248369
final  value 84.248369 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 102.820010 
iter  10 value 90.403351
iter  20 value 87.189989
iter  30 value 86.890926
iter  40 value 86.087861
iter  50 value 84.831167
iter  60 value 84.369137
iter  70 value 84.292438
iter  80 value 84.236486
final  value 84.234884 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.380436 
iter  10 value 94.400557
iter  20 value 92.584409
iter  30 value 90.943456
iter  40 value 85.846824
iter  50 value 84.808517
iter  60 value 83.995999
iter  70 value 83.335195
iter  80 value 83.285176
iter  90 value 83.266088
iter 100 value 83.246166
final  value 83.246166 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 103.446325 
iter  10 value 94.509305
iter  20 value 94.400206
iter  30 value 94.097142
iter  40 value 87.228299
iter  50 value 86.038520
iter  60 value 85.190746
iter  70 value 84.961206
final  value 84.956484 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.780089 
iter  10 value 94.468594
iter  20 value 93.127192
iter  30 value 92.430198
iter  40 value 92.412070
iter  50 value 92.303308
iter  60 value 92.242925
iter  70 value 92.116128
iter  80 value 87.629160
iter  90 value 83.558702
iter 100 value 82.558836
final  value 82.558836 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 104.479219 
iter  10 value 94.486284
iter  20 value 94.215024
iter  30 value 94.031434
iter  40 value 94.018137
iter  50 value 90.037267
iter  60 value 85.845653
iter  70 value 84.744292
iter  80 value 83.157676
iter  90 value 82.675070
iter 100 value 82.593285
final  value 82.593285 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 123.127344 
iter  10 value 94.619319
iter  20 value 94.489474
iter  30 value 88.411073
iter  40 value 86.762332
iter  50 value 85.079424
iter  60 value 84.861718
iter  70 value 84.778707
iter  80 value 84.029497
iter  90 value 83.653731
iter 100 value 83.621300
final  value 83.621300 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.097516 
iter  10 value 94.456731
iter  20 value 89.044307
iter  30 value 87.162073
iter  40 value 86.731489
iter  50 value 86.177545
iter  60 value 83.409168
iter  70 value 82.539068
iter  80 value 81.888883
iter  90 value 81.641280
iter 100 value 81.479213
final  value 81.479213 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 120.617560 
iter  10 value 94.300232
iter  20 value 88.762774
iter  30 value 87.648808
iter  40 value 86.067482
iter  50 value 83.499714
iter  60 value 82.037171
iter  70 value 81.523886
iter  80 value 81.325398
iter  90 value 81.246139
iter 100 value 81.217941
final  value 81.217941 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.569561 
iter  10 value 94.486412
iter  20 value 88.502461
iter  30 value 87.647429
iter  40 value 84.813623
iter  50 value 83.580443
iter  60 value 81.812204
iter  70 value 81.392098
iter  80 value 81.123575
iter  90 value 81.020362
iter 100 value 80.956334
final  value 80.956334 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.211325 
iter  10 value 94.992452
iter  20 value 93.292127
iter  30 value 87.998172
iter  40 value 86.490183
iter  50 value 86.209287
iter  60 value 85.956970
iter  70 value 82.609159
iter  80 value 81.601748
iter  90 value 81.332151
iter 100 value 80.880733
final  value 80.880733 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 114.670733 
iter  10 value 94.291798
iter  20 value 86.425190
iter  30 value 84.712489
iter  40 value 82.940811
iter  50 value 81.896963
iter  60 value 81.507382
iter  70 value 81.177935
iter  80 value 81.135155
iter  90 value 81.023697
iter 100 value 80.858051
final  value 80.858051 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.691868 
iter  10 value 94.608877
iter  20 value 92.849049
iter  30 value 86.880239
iter  40 value 85.799319
iter  50 value 84.769201
iter  60 value 83.158864
iter  70 value 81.602127
iter  80 value 81.266048
iter  90 value 80.830985
iter 100 value 80.566180
final  value 80.566180 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.216853 
iter  10 value 94.262249
iter  20 value 89.896104
iter  30 value 87.232593
iter  40 value 85.912961
iter  50 value 85.353158
iter  60 value 84.806254
iter  70 value 83.857071
iter  80 value 81.976778
iter  90 value 80.791239
iter 100 value 80.587548
final  value 80.587548 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 117.612130 
iter  10 value 94.657048
iter  20 value 94.252600
iter  30 value 90.267612
iter  40 value 89.726563
iter  50 value 88.091409
iter  60 value 85.743581
iter  70 value 83.344003
iter  80 value 82.358631
iter  90 value 81.889970
iter 100 value 81.716832
final  value 81.716832 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.966983 
final  value 94.485859 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.944624 
final  value 94.486020 
converged
Fitting Repeat 3 

# weights:  103
initial  value 114.027384 
final  value 94.485832 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.785931 
iter  10 value 94.485893
final  value 94.484220 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.001841 
final  value 94.485791 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.405736 
iter  10 value 94.330947
iter  20 value 92.881926
iter  30 value 84.688819
iter  40 value 84.171710
iter  50 value 84.158649
final  value 84.149959 
converged
Fitting Repeat 2 

# weights:  305
initial  value 112.014093 
iter  10 value 94.490753
iter  20 value 94.487807
iter  30 value 93.975852
iter  40 value 93.316427
iter  50 value 93.309823
iter  60 value 92.812643
iter  70 value 92.812459
final  value 92.812430 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.408223 
iter  10 value 94.488402
iter  20 value 93.949921
iter  30 value 87.323122
iter  40 value 87.313000
iter  50 value 87.295814
iter  60 value 87.285786
iter  70 value 87.261718
iter  80 value 87.140586
iter  90 value 87.139529
iter 100 value 86.483131
final  value 86.483131 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.367131 
iter  10 value 94.489627
iter  20 value 93.853726
iter  30 value 85.915580
iter  40 value 84.083298
iter  50 value 80.535578
iter  60 value 80.517348
iter  70 value 80.512327
iter  80 value 80.511408
iter  90 value 80.455812
iter 100 value 80.384930
final  value 80.384930 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.778015 
iter  10 value 94.489137
iter  20 value 94.484256
iter  30 value 86.478566
iter  40 value 86.456898
iter  40 value 86.456898
iter  40 value 86.456898
final  value 86.456898 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.876903 
iter  10 value 87.929498
iter  20 value 85.593949
iter  30 value 84.512466
iter  40 value 84.503905
iter  50 value 83.766462
iter  60 value 83.764734
iter  70 value 83.142973
iter  80 value 82.180736
iter  90 value 81.875225
iter 100 value 81.087313
final  value 81.087313 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 101.002553 
iter  10 value 94.451524
final  value 94.451179 
converged
Fitting Repeat 3 

# weights:  507
initial  value 110.095065 
iter  10 value 94.333925
iter  20 value 93.984187
iter  30 value 84.893361
iter  40 value 83.750030
iter  50 value 83.740930
iter  50 value 83.740930
final  value 83.740930 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.537106 
iter  10 value 94.449069
iter  20 value 94.192794
iter  30 value 87.259883
iter  40 value 86.267973
iter  50 value 86.261488
iter  60 value 86.237713
iter  70 value 86.164785
iter  80 value 85.697796
iter  90 value 85.495448
final  value 85.494928 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.269990 
iter  10 value 93.528980
iter  20 value 93.522339
iter  30 value 92.645796
iter  40 value 92.643454
iter  50 value 92.638322
iter  60 value 92.623409
iter  70 value 91.612758
iter  80 value 85.918899
iter  90 value 84.282335
iter 100 value 82.761794
final  value 82.761794 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.476050 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.805287 
iter  10 value 94.032984
final  value 94.032967 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.271498 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.111145 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.545249 
iter  10 value 93.452828
iter  20 value 88.740691
iter  30 value 86.728551
iter  40 value 86.121507
iter  50 value 86.098023
final  value 86.097907 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.400905 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.950645 
iter  10 value 94.052876
final  value 94.052465 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.763877 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 114.100284 
final  value 94.032967 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.958551 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.155616 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 120.818462 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.403238 
final  value 94.032967 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.773550 
iter  10 value 94.011188
iter  20 value 93.975647
final  value 93.971431 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.398171 
final  value 94.011561 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.879671 
iter  10 value 94.065880
iter  20 value 93.847042
iter  30 value 89.504920
iter  40 value 87.768151
iter  50 value 86.488738
iter  60 value 85.600982
iter  70 value 85.569394
iter  80 value 85.567681
final  value 85.567660 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.095355 
iter  10 value 94.047621
iter  20 value 93.788438
iter  30 value 87.999658
iter  40 value 86.664497
iter  50 value 85.963804
iter  60 value 85.667245
iter  70 value 85.569789
iter  80 value 85.568225
final  value 85.567660 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.386199 
iter  10 value 94.036101
iter  20 value 90.466276
iter  30 value 86.893033
iter  40 value 86.763312
iter  50 value 86.614101
iter  60 value 86.100044
iter  70 value 85.782140
final  value 85.773810 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.447377 
iter  10 value 93.954859
iter  20 value 93.613834
iter  30 value 89.677766
iter  40 value 88.910239
iter  50 value 86.933050
iter  60 value 86.735055
iter  70 value 86.542990
iter  80 value 86.454488
iter  90 value 85.861251
iter 100 value 85.688582
final  value 85.688582 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 98.561639 
iter  10 value 94.056701
iter  20 value 94.028184
iter  30 value 92.775227
iter  40 value 92.132101
iter  50 value 89.002521
iter  60 value 87.237193
iter  70 value 86.309472
iter  80 value 86.100640
iter  90 value 86.099040
final  value 86.099032 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.465055 
iter  10 value 93.692970
iter  20 value 89.351253
iter  30 value 87.152469
iter  40 value 86.304533
iter  50 value 86.010224
iter  60 value 85.527639
iter  70 value 84.654840
iter  80 value 83.846309
iter  90 value 83.659067
iter 100 value 83.482683
final  value 83.482683 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.008618 
iter  10 value 94.077295
iter  20 value 88.843682
iter  30 value 88.139820
iter  40 value 86.798396
iter  50 value 85.613754
iter  60 value 84.544482
iter  70 value 83.986503
iter  80 value 83.662361
iter  90 value 82.880911
iter 100 value 82.681137
final  value 82.681137 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 113.907814 
iter  10 value 94.009573
iter  20 value 88.409933
iter  30 value 86.899356
iter  40 value 86.151718
iter  50 value 85.487396
iter  60 value 83.196208
iter  70 value 82.682254
iter  80 value 82.564948
iter  90 value 82.353561
iter 100 value 82.209799
final  value 82.209799 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.271640 
iter  10 value 93.987652
iter  20 value 92.497732
iter  30 value 92.118886
iter  40 value 92.007009
iter  50 value 88.367834
iter  60 value 83.712082
iter  70 value 83.225171
iter  80 value 83.047099
iter  90 value 82.952094
iter 100 value 82.898451
final  value 82.898451 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.109007 
iter  10 value 93.994978
iter  20 value 90.483866
iter  30 value 89.685860
iter  40 value 85.676574
iter  50 value 85.285704
iter  60 value 85.118051
iter  70 value 83.797698
iter  80 value 82.911896
iter  90 value 82.603027
iter 100 value 82.291026
final  value 82.291026 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 145.859965 
iter  10 value 94.070679
iter  20 value 88.470223
iter  30 value 87.623286
iter  40 value 86.528753
iter  50 value 85.743727
iter  60 value 84.932027
iter  70 value 84.598061
iter  80 value 83.448265
iter  90 value 82.955498
iter 100 value 82.744706
final  value 82.744706 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.198217 
iter  10 value 94.034963
iter  20 value 93.944361
iter  30 value 88.382675
iter  40 value 84.399542
iter  50 value 83.270823
iter  60 value 82.827467
iter  70 value 82.760090
iter  80 value 82.458427
iter  90 value 82.250381
iter 100 value 82.136179
final  value 82.136179 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.802430 
iter  10 value 94.287537
iter  20 value 93.945843
iter  30 value 88.461534
iter  40 value 88.045091
iter  50 value 86.642739
iter  60 value 84.791582
iter  70 value 83.273229
iter  80 value 83.035011
iter  90 value 82.676395
iter 100 value 82.340844
final  value 82.340844 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.074438 
iter  10 value 93.531501
iter  20 value 87.532552
iter  30 value 85.509684
iter  40 value 84.694326
iter  50 value 83.382971
iter  60 value 82.827838
iter  70 value 82.128128
iter  80 value 82.030968
iter  90 value 81.985680
iter 100 value 81.974412
final  value 81.974412 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.059399 
iter  10 value 94.290016
iter  20 value 92.950597
iter  30 value 89.504586
iter  40 value 86.302763
iter  50 value 85.036199
iter  60 value 83.153486
iter  70 value 82.584428
iter  80 value 82.419120
iter  90 value 82.276880
iter 100 value 82.038479
final  value 82.038479 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 110.580757 
iter  10 value 93.124298
iter  20 value 92.070582
iter  30 value 86.642099
iter  40 value 86.640402
iter  50 value 86.596365
iter  60 value 86.186865
iter  70 value 86.169442
iter  80 value 86.168786
iter  90 value 86.168173
final  value 86.167643 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.520192 
iter  10 value 94.054958
iter  20 value 94.052953
final  value 94.052951 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.049441 
final  value 94.034656 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.209800 
iter  10 value 93.651113
final  value 93.641900 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.564777 
final  value 94.054488 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.237252 
iter  10 value 94.038019
iter  20 value 94.024134
iter  30 value 94.018088
iter  40 value 94.004323
iter  50 value 93.991952
iter  60 value 93.991744
iter  70 value 93.990882
iter  80 value 93.986876
iter  90 value 93.986391
iter 100 value 93.985839
final  value 93.985839 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.861163 
iter  10 value 94.079758
iter  20 value 86.700337
iter  30 value 86.495375
iter  40 value 86.477954
iter  50 value 86.176824
iter  60 value 86.166259
iter  70 value 86.165421
iter  80 value 86.165334
final  value 86.165307 
converged
Fitting Repeat 3 

# weights:  305
initial  value 108.397722 
iter  10 value 94.057793
iter  20 value 94.053048
iter  30 value 87.413902
iter  40 value 86.425894
iter  50 value 86.421735
iter  60 value 86.334827
iter  70 value 86.328227
iter  80 value 86.270212
final  value 86.252488 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.305431 
iter  10 value 93.973553
iter  20 value 93.904992
iter  30 value 93.900311
iter  40 value 89.788945
iter  50 value 88.214542
final  value 88.212917 
converged
Fitting Repeat 5 

# weights:  305
initial  value 112.276570 
iter  10 value 94.038489
iter  20 value 94.034456
final  value 94.034181 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.322880 
iter  10 value 94.060963
iter  20 value 94.017087
iter  30 value 91.565641
iter  40 value 88.297603
iter  50 value 88.211632
iter  60 value 88.198319
iter  70 value 88.149187
iter  80 value 87.535230
iter  90 value 86.339852
iter 100 value 84.272701
final  value 84.272701 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 101.802733 
iter  10 value 94.045223
iter  20 value 94.040441
iter  30 value 93.980376
iter  40 value 92.274918
iter  50 value 91.932449
final  value 91.932400 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.884121 
iter  10 value 94.061277
iter  20 value 94.044820
iter  30 value 89.909837
iter  40 value 85.859548
iter  50 value 85.843719
final  value 85.843236 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.429896 
iter  10 value 94.050412
iter  20 value 94.023579
iter  30 value 94.017021
iter  30 value 94.017020
iter  30 value 94.017020
final  value 94.017020 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.232867 
iter  10 value 94.041014
iter  20 value 93.770056
iter  30 value 92.209946
iter  40 value 91.620649
final  value 91.620556 
converged
Fitting Repeat 1 

# weights:  103
initial  value 94.812603 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.438785 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.211182 
iter  10 value 93.196488
iter  20 value 91.960829
final  value 91.960589 
converged
Fitting Repeat 4 

# weights:  103
initial  value 110.103515 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 118.833308 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.272362 
iter  10 value 94.046740
final  value 94.046703 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.505003 
final  value 94.467391 
converged
Fitting Repeat 3 

# weights:  305
initial  value 111.341134 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.433778 
final  value 94.428839 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.492301 
final  value 94.022968 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.098584 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.714381 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 116.275184 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.030355 
final  value 94.423529 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.696523 
iter  10 value 94.046835
iter  20 value 85.743477
iter  30 value 83.824089
iter  40 value 83.011552
final  value 83.011502 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.733101 
iter  10 value 94.493769
iter  20 value 92.730430
iter  30 value 91.849851
iter  40 value 88.208414
iter  50 value 85.249298
iter  60 value 84.741430
iter  70 value 83.751566
iter  80 value 83.492747
final  value 83.491154 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.820467 
iter  10 value 94.269602
iter  20 value 88.626388
iter  30 value 86.732995
iter  40 value 85.238379
iter  50 value 83.022183
iter  60 value 82.035470
iter  70 value 81.705388
iter  80 value 81.465981
iter  90 value 81.408942
final  value 81.408935 
converged
Fitting Repeat 3 

# weights:  103
initial  value 109.823022 
iter  10 value 94.492548
iter  20 value 89.755641
iter  30 value 85.716471
iter  40 value 84.351599
iter  50 value 83.977164
iter  60 value 83.772366
iter  70 value 83.505936
iter  80 value 83.491154
iter  80 value 83.491154
iter  80 value 83.491154
final  value 83.491154 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.789183 
iter  10 value 93.662389
iter  20 value 87.722099
iter  30 value 83.897059
iter  40 value 83.698123
iter  50 value 83.549073
iter  60 value 83.492630
final  value 83.491154 
converged
Fitting Repeat 5 

# weights:  103
initial  value 108.193223 
iter  10 value 99.849862
iter  20 value 94.469937
iter  30 value 87.363638
iter  40 value 85.173776
iter  50 value 84.518754
iter  60 value 83.733412
iter  70 value 83.494185
iter  80 value 83.491154
iter  80 value 83.491154
iter  80 value 83.491154
final  value 83.491154 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.785068 
iter  10 value 94.568724
iter  20 value 94.176211
iter  30 value 87.536864
iter  40 value 84.366819
iter  50 value 83.531977
iter  60 value 83.461693
iter  70 value 83.458754
iter  80 value 83.422586
iter  90 value 83.228557
iter 100 value 83.194653
final  value 83.194653 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.511708 
iter  10 value 94.495247
iter  20 value 94.269260
iter  30 value 92.457359
iter  40 value 86.736092
iter  50 value 84.646502
iter  60 value 84.159090
iter  70 value 82.835590
iter  80 value 82.428231
iter  90 value 82.027358
iter 100 value 81.869117
final  value 81.869117 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 124.300420 
iter  10 value 95.022368
iter  20 value 88.715714
iter  30 value 85.539722
iter  40 value 84.936217
iter  50 value 84.414046
iter  60 value 83.911358
iter  70 value 82.118773
iter  80 value 81.113645
iter  90 value 80.496674
iter 100 value 80.098702
final  value 80.098702 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 127.054074 
iter  10 value 95.846375
iter  20 value 87.375912
iter  30 value 84.910457
iter  40 value 83.360808
iter  50 value 82.164477
iter  60 value 81.075512
iter  70 value 80.936759
iter  80 value 80.450351
iter  90 value 80.318080
iter 100 value 80.291445
final  value 80.291445 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.222078 
iter  10 value 94.481128
iter  20 value 87.186510
iter  30 value 84.391082
iter  40 value 83.540061
iter  50 value 83.371235
iter  60 value 82.524984
iter  70 value 80.966830
iter  80 value 80.603308
iter  90 value 80.176647
iter 100 value 79.960791
final  value 79.960791 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.894253 
iter  10 value 93.804688
iter  20 value 86.458787
iter  30 value 83.616232
iter  40 value 81.443920
iter  50 value 80.848265
iter  60 value 80.318254
iter  70 value 80.236919
iter  80 value 80.157105
iter  90 value 80.116332
iter 100 value 80.059541
final  value 80.059541 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 114.615160 
iter  10 value 94.729790
iter  20 value 93.814766
iter  30 value 91.799768
iter  40 value 83.605313
iter  50 value 83.277890
iter  60 value 83.052208
iter  70 value 82.650338
iter  80 value 82.154206
iter  90 value 81.960710
iter 100 value 81.704600
final  value 81.704600 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 125.085972 
iter  10 value 98.804306
iter  20 value 91.986635
iter  30 value 87.132691
iter  40 value 84.441359
iter  50 value 82.571280
iter  60 value 82.202185
iter  70 value 82.050293
iter  80 value 81.923183
iter  90 value 81.596494
iter 100 value 80.887128
final  value 80.887128 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 115.866536 
iter  10 value 94.865604
iter  20 value 90.043112
iter  30 value 87.909797
iter  40 value 87.588261
iter  50 value 85.836334
iter  60 value 82.800530
iter  70 value 81.768552
iter  80 value 81.007893
iter  90 value 80.901535
iter 100 value 80.644953
final  value 80.644953 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 122.416923 
iter  10 value 96.727970
iter  20 value 88.610266
iter  30 value 85.522268
iter  40 value 83.154676
iter  50 value 81.705984
iter  60 value 81.307308
iter  70 value 80.633009
iter  80 value 80.245569
iter  90 value 80.147020
iter 100 value 80.110714
final  value 80.110714 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.308628 
iter  10 value 94.485720
iter  20 value 94.484261
iter  30 value 94.271983
iter  40 value 89.636930
iter  50 value 89.374463
iter  60 value 89.196540
iter  70 value 87.674361
iter  80 value 86.530204
iter  90 value 86.503272
iter 100 value 86.403831
final  value 86.403831 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.333062 
final  value 94.469105 
converged
Fitting Repeat 3 

# weights:  103
initial  value 108.341615 
iter  10 value 94.485984
iter  20 value 94.484260
iter  30 value 94.472205
iter  40 value 94.467410
iter  40 value 94.467409
iter  40 value 94.467409
final  value 94.467409 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.988621 
final  value 94.485828 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.272775 
iter  10 value 94.468969
iter  20 value 94.467575
iter  20 value 94.467575
iter  20 value 94.467575
final  value 94.467575 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.040885 
iter  10 value 94.489124
iter  20 value 94.484564
iter  30 value 87.063965
iter  40 value 86.960290
iter  50 value 86.876360
iter  60 value 86.526895
iter  70 value 83.735794
iter  80 value 83.731019
iter  90 value 83.730632
iter 100 value 82.932582
final  value 82.932582 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.832906 
iter  10 value 93.760784
iter  20 value 93.757667
iter  30 value 91.908156
iter  40 value 91.178191
iter  50 value 91.126030
iter  60 value 90.878695
iter  70 value 90.850982
final  value 90.850952 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.300127 
iter  10 value 94.352760
iter  20 value 94.343584
iter  30 value 94.341061
iter  40 value 94.338217
iter  50 value 94.335742
iter  60 value 87.146104
iter  70 value 85.129366
iter  80 value 82.723752
iter  90 value 82.722856
iter 100 value 81.791793
final  value 81.791793 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 97.985082 
iter  10 value 94.489089
iter  20 value 94.482906
iter  30 value 94.429364
iter  40 value 94.404577
iter  50 value 88.251743
iter  60 value 88.214585
iter  70 value 86.617807
iter  80 value 86.545180
final  value 86.545179 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.980664 
iter  10 value 94.488550
iter  20 value 94.451152
iter  30 value 94.345857
iter  40 value 93.898965
iter  50 value 85.298409
iter  60 value 84.481822
iter  70 value 84.458756
iter  80 value 84.345799
iter  90 value 84.197443
iter 100 value 83.477390
final  value 83.477390 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 95.345291 
iter  10 value 94.474777
iter  20 value 94.467625
iter  30 value 90.989550
iter  40 value 87.653513
iter  50 value 84.425611
iter  60 value 83.870621
iter  70 value 81.300719
iter  80 value 80.228247
iter  90 value 79.962977
iter 100 value 79.952675
final  value 79.952675 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.674428 
iter  10 value 94.479789
iter  20 value 94.337314
iter  30 value 92.641778
iter  40 value 84.413382
iter  50 value 83.436615
iter  60 value 82.955249
iter  70 value 82.372727
iter  80 value 82.062934
final  value 82.062928 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.619879 
iter  10 value 94.436784
iter  20 value 94.215738
iter  30 value 87.233106
iter  40 value 86.529014
iter  50 value 84.378092
iter  60 value 82.433296
iter  70 value 81.619250
iter  80 value 81.614795
iter  90 value 81.600255
iter 100 value 81.599583
final  value 81.599583 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.721030 
iter  10 value 94.215277
iter  20 value 84.639638
iter  30 value 83.801325
iter  40 value 83.725146
iter  50 value 83.722176
iter  50 value 83.722175
final  value 83.722175 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.172154 
iter  10 value 90.299886
iter  20 value 86.971131
iter  30 value 86.964425
iter  40 value 86.947621
iter  50 value 86.914154
iter  60 value 86.855171
iter  70 value 86.808184
iter  80 value 85.813435
final  value 85.812838 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.292018 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 110.896482 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.187555 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.984444 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.802746 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.751801 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.607603 
iter  10 value 94.296310
iter  10 value 94.296309
iter  10 value 94.296309
final  value 94.296309 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.407515 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.894145 
iter  10 value 94.063075
iter  20 value 93.935391
final  value 93.935239 
converged
Fitting Repeat 5 

# weights:  305
initial  value 116.953689 
iter  10 value 94.159629
final  value 94.159612 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.324721 
iter  10 value 93.002676
iter  20 value 92.974736
final  value 92.974681 
converged
Fitting Repeat 2 

# weights:  507
initial  value 94.779275 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.976256 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.613126 
iter  10 value 94.328277
final  value 94.309525 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.957566 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.930557 
iter  10 value 94.396631
iter  20 value 89.176029
iter  30 value 88.695456
iter  40 value 85.389391
iter  50 value 85.085931
iter  60 value 84.802928
iter  70 value 84.751059
iter  80 value 84.731048
final  value 84.730815 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.316117 
iter  10 value 94.523762
iter  20 value 92.603734
iter  30 value 88.302546
iter  40 value 87.578265
iter  50 value 85.006124
iter  60 value 84.804037
iter  70 value 84.735264
iter  80 value 84.409816
iter  90 value 84.300091
iter 100 value 84.296585
final  value 84.296585 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.674264 
iter  10 value 94.492333
iter  20 value 94.211210
iter  30 value 90.329903
iter  40 value 82.512154
iter  50 value 81.725083
iter  60 value 81.394233
iter  70 value 81.062033
iter  80 value 80.927085
final  value 80.924052 
converged
Fitting Repeat 4 

# weights:  103
initial  value 109.139012 
iter  10 value 94.690869
iter  20 value 94.483961
iter  30 value 85.505585
iter  40 value 84.826292
iter  50 value 84.527231
iter  60 value 84.352894
iter  70 value 84.342052
iter  80 value 84.297047
final  value 84.296557 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.671723 
iter  10 value 94.486433
iter  20 value 89.591481
iter  30 value 85.074182
iter  40 value 84.838879
iter  50 value 84.799407
iter  60 value 84.775904
iter  70 value 84.740633
final  value 84.730815 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.161768 
iter  10 value 94.571084
iter  20 value 93.185207
iter  30 value 92.818751
iter  40 value 91.319467
iter  50 value 84.967001
iter  60 value 84.754029
iter  70 value 84.475280
iter  80 value 83.336932
iter  90 value 82.811558
iter 100 value 82.540927
final  value 82.540927 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.640574 
iter  10 value 94.485481
iter  20 value 94.293851
iter  30 value 88.806602
iter  40 value 85.458179
iter  50 value 82.906923
iter  60 value 81.408781
iter  70 value 80.917884
iter  80 value 80.348869
iter  90 value 79.961758
iter 100 value 79.705951
final  value 79.705951 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.233318 
iter  10 value 94.631136
iter  20 value 93.991599
iter  30 value 87.897976
iter  40 value 87.847749
iter  50 value 86.407719
iter  60 value 81.812352
iter  70 value 81.155472
iter  80 value 80.669574
iter  90 value 80.317669
iter 100 value 79.933037
final  value 79.933037 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.310221 
iter  10 value 94.914109
iter  20 value 94.447331
iter  30 value 93.574438
iter  40 value 88.375290
iter  50 value 88.100243
iter  60 value 87.956979
iter  70 value 87.828611
iter  80 value 84.120978
iter  90 value 82.642874
iter 100 value 80.704409
final  value 80.704409 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.955280 
iter  10 value 94.336162
iter  20 value 88.480542
iter  30 value 88.067128
iter  40 value 85.953620
iter  50 value 85.785037
iter  60 value 85.722909
iter  70 value 85.435414
iter  80 value 82.454045
iter  90 value 80.803862
iter 100 value 80.562325
final  value 80.562325 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 124.222176 
iter  10 value 95.863869
iter  20 value 92.607023
iter  30 value 92.166653
iter  40 value 92.106964
iter  50 value 90.061623
iter  60 value 87.427272
iter  70 value 83.717980
iter  80 value 81.888297
iter  90 value 80.508998
iter 100 value 80.128297
final  value 80.128297 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 129.537710 
iter  10 value 94.101853
iter  20 value 87.125237
iter  30 value 82.908789
iter  40 value 82.383920
iter  50 value 81.422233
iter  60 value 80.398068
iter  70 value 79.466335
iter  80 value 79.241614
iter  90 value 79.224179
iter 100 value 79.164710
final  value 79.164710 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.005665 
iter  10 value 96.537733
iter  20 value 93.596898
iter  30 value 89.068220
iter  40 value 88.277317
iter  50 value 87.802223
iter  60 value 86.404980
iter  70 value 83.516475
iter  80 value 81.654079
iter  90 value 81.269324
iter 100 value 80.989116
final  value 80.989116 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 114.116209 
iter  10 value 94.617389
iter  20 value 88.379447
iter  30 value 84.862043
iter  40 value 83.259432
iter  50 value 82.727372
iter  60 value 81.862676
iter  70 value 81.005949
iter  80 value 80.562134
iter  90 value 80.171840
iter 100 value 79.952408
final  value 79.952408 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 139.344747 
iter  10 value 94.549800
iter  20 value 93.613336
iter  30 value 88.856002
iter  40 value 88.690595
iter  50 value 88.259014
iter  60 value 86.732591
iter  70 value 84.692809
iter  80 value 81.801777
iter  90 value 80.461174
iter 100 value 80.270301
final  value 80.270301 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 111.371677 
final  value 94.485980 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.237518 
final  value 94.485772 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.700522 
final  value 94.486019 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.342411 
final  value 94.485922 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.671413 
final  value 94.485960 
converged
Fitting Repeat 1 

# weights:  305
initial  value 119.566582 
iter  10 value 94.488930
iter  20 value 94.484456
final  value 94.484441 
converged
Fitting Repeat 2 

# weights:  305
initial  value 111.751194 
iter  10 value 93.815215
iter  20 value 93.649176
iter  30 value 93.645577
iter  40 value 93.629233
final  value 93.629217 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.226221 
iter  10 value 94.488619
iter  20 value 94.390518
iter  30 value 89.413243
final  value 89.413236 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.371319 
iter  10 value 94.149467
iter  20 value 94.117253
iter  30 value 91.255766
iter  40 value 91.183765
iter  50 value 88.269340
iter  60 value 88.260617
iter  60 value 88.260617
final  value 88.260617 
converged
Fitting Repeat 5 

# weights:  305
initial  value 114.228637 
iter  10 value 93.949808
iter  20 value 93.912317
iter  30 value 93.911216
iter  40 value 93.910225
iter  50 value 93.889416
iter  60 value 93.815538
iter  70 value 93.717652
iter  80 value 93.711627
iter  90 value 93.537858
iter 100 value 93.520332
final  value 93.520332 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.299145 
iter  10 value 94.492964
iter  20 value 94.482954
iter  30 value 87.697849
iter  40 value 87.165433
final  value 87.153306 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.125064 
iter  10 value 94.152799
iter  20 value 94.146424
iter  30 value 94.091174
iter  40 value 94.089563
final  value 94.089007 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.656042 
iter  10 value 94.362456
iter  20 value 93.942427
iter  30 value 87.665757
iter  40 value 87.366002
iter  50 value 84.883962
iter  60 value 82.701513
iter  70 value 82.700242
iter  80 value 82.175933
iter  90 value 81.525828
iter 100 value 81.525431
final  value 81.525431 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.956173 
iter  10 value 94.362690
iter  20 value 94.356800
iter  30 value 94.227887
iter  40 value 94.135165
iter  50 value 94.134255
iter  60 value 94.132803
iter  70 value 93.748417
iter  80 value 89.033548
iter  90 value 82.955761
iter 100 value 79.896887
final  value 79.896887 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 95.752259 
iter  10 value 94.486948
iter  20 value 85.935691
iter  30 value 85.166963
iter  40 value 83.915800
iter  50 value 83.906750
iter  60 value 83.373236
iter  70 value 81.682267
iter  80 value 81.486761
final  value 81.484872 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.899742 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.910570 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 108.088956 
iter  10 value 92.295812
iter  20 value 92.281095
final  value 92.281082 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.323489 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 107.789336 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.289577 
final  value 92.649123 
converged
Fitting Repeat 2 

# weights:  305
initial  value 106.527691 
iter  10 value 92.334642
iter  20 value 92.281128
final  value 92.281082 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.547661 
iter  10 value 92.289041
iter  20 value 92.281088
final  value 92.281082 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.532853 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.230639 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 111.349856 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.914883 
iter  10 value 92.657913
iter  20 value 92.649131
final  value 92.649123 
converged
Fitting Repeat 3 

# weights:  507
initial  value 112.775768 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 108.274196 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.754872 
iter  10 value 94.028036
final  value 94.027933 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.965016 
iter  10 value 94.056672
iter  20 value 93.134599
iter  30 value 89.382893
iter  40 value 84.911157
iter  50 value 83.059955
iter  60 value 81.726547
iter  70 value 81.557956
iter  80 value 81.390025
iter  90 value 81.320431
final  value 81.319140 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.333200 
iter  10 value 94.056392
iter  20 value 84.094920
iter  30 value 82.341320
iter  40 value 81.810648
iter  50 value 81.690239
final  value 81.688123 
converged
Fitting Repeat 3 

# weights:  103
initial  value 112.859225 
iter  10 value 100.518923
iter  20 value 94.059192
iter  30 value 88.421291
iter  40 value 85.247390
iter  50 value 84.729271
iter  60 value 84.172578
iter  70 value 84.006293
iter  80 value 83.920585
iter  90 value 81.458523
iter 100 value 80.694251
final  value 80.694251 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 101.448126 
iter  10 value 94.042214
iter  20 value 87.669082
iter  30 value 82.672232
iter  40 value 81.849919
iter  50 value 81.006280
iter  60 value 80.350045
iter  70 value 80.057024
iter  80 value 79.845188
iter  90 value 79.792107
iter 100 value 79.115867
final  value 79.115867 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 113.173695 
iter  10 value 93.980119
iter  20 value 90.883004
iter  30 value 83.940405
iter  40 value 83.579871
iter  50 value 81.914736
iter  60 value 81.698265
final  value 81.689404 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.657160 
iter  10 value 87.507677
iter  20 value 83.641592
iter  30 value 82.386249
iter  40 value 81.946636
iter  50 value 79.772205
iter  60 value 79.067241
iter  70 value 78.907031
iter  80 value 78.746620
iter  90 value 78.681377
iter 100 value 78.591069
final  value 78.591069 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.014686 
iter  10 value 94.225726
iter  20 value 93.291716
iter  30 value 83.177970
iter  40 value 82.078901
iter  50 value 81.678355
iter  60 value 81.408978
iter  70 value 81.321475
iter  80 value 80.960763
iter  90 value 80.247541
iter 100 value 80.213633
final  value 80.213633 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 107.890834 
iter  10 value 94.104296
iter  20 value 92.581986
iter  30 value 85.540822
iter  40 value 82.731844
iter  50 value 80.743847
iter  60 value 80.004091
iter  70 value 79.440560
iter  80 value 78.819347
iter  90 value 78.510635
iter 100 value 78.209687
final  value 78.209687 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.593603 
iter  10 value 92.908156
iter  20 value 91.959668
iter  30 value 89.713993
iter  40 value 85.521778
iter  50 value 84.737179
iter  60 value 81.793398
iter  70 value 81.122634
iter  80 value 80.899639
iter  90 value 80.562290
iter 100 value 80.252540
final  value 80.252540 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.689412 
iter  10 value 94.051395
iter  20 value 92.949701
iter  30 value 92.770043
iter  40 value 84.665270
iter  50 value 83.120484
iter  60 value 82.361476
iter  70 value 80.882222
iter  80 value 78.848114
iter  90 value 77.351969
iter 100 value 77.150999
final  value 77.150999 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 114.304655 
iter  10 value 93.277408
iter  20 value 91.651424
iter  30 value 88.063666
iter  40 value 82.924958
iter  50 value 80.112561
iter  60 value 78.181141
iter  70 value 77.010876
iter  80 value 76.670597
iter  90 value 76.452696
iter 100 value 76.273314
final  value 76.273314 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 128.370199 
iter  10 value 86.350284
iter  20 value 83.880678
iter  30 value 83.504327
iter  40 value 83.230322
iter  50 value 82.651541
iter  60 value 80.572298
iter  70 value 79.655786
iter  80 value 79.418590
iter  90 value 79.230670
iter 100 value 79.052029
final  value 79.052029 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 115.926242 
iter  10 value 93.047723
iter  20 value 91.210787
iter  30 value 82.158563
iter  40 value 80.038762
iter  50 value 79.175832
iter  60 value 78.407437
iter  70 value 77.858724
iter  80 value 77.334742
iter  90 value 76.726210
iter 100 value 76.352521
final  value 76.352521 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.518946 
iter  10 value 94.556993
iter  20 value 93.596868
iter  30 value 92.648046
iter  40 value 89.348588
iter  50 value 85.964396
iter  60 value 85.309634
iter  70 value 80.802256
iter  80 value 80.423050
iter  90 value 80.033740
iter 100 value 79.401681
final  value 79.401681 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 122.455131 
iter  10 value 93.810595
iter  20 value 92.940469
iter  30 value 86.131008
iter  40 value 85.807505
iter  50 value 81.447919
iter  60 value 79.196573
iter  70 value 77.651320
iter  80 value 77.011744
iter  90 value 76.904424
iter 100 value 76.794028
final  value 76.794028 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.587524 
final  value 94.054301 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.851141 
final  value 94.054876 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.063437 
final  value 94.054633 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.558286 
iter  10 value 94.054323
iter  20 value 93.319229
iter  30 value 92.290349
final  value 92.290345 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.143152 
final  value 94.054636 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.329912 
iter  10 value 94.057654
iter  20 value 94.035842
iter  30 value 83.298915
iter  40 value 83.144667
iter  50 value 83.144537
iter  60 value 82.545612
iter  70 value 82.326647
final  value 82.324823 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.563717 
iter  10 value 94.057793
iter  20 value 93.643841
iter  30 value 86.036196
iter  40 value 82.451037
iter  50 value 82.331038
iter  60 value 81.525303
iter  70 value 81.248151
iter  80 value 81.248032
iter  90 value 81.247357
final  value 81.247189 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.418519 
iter  10 value 92.898363
iter  20 value 91.885583
iter  30 value 91.778484
iter  40 value 87.734710
iter  50 value 83.977362
final  value 83.977355 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.693642 
iter  10 value 94.054227
iter  20 value 92.796204
iter  30 value 91.904808
final  value 91.860530 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.302131 
iter  10 value 94.057635
iter  20 value 83.067113
iter  30 value 82.326814
iter  40 value 82.326601
iter  50 value 82.325393
iter  60 value 82.325267
final  value 82.324971 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.333088 
iter  10 value 92.305416
iter  20 value 92.294661
iter  30 value 92.164983
iter  40 value 88.988282
iter  50 value 83.160797
iter  60 value 82.126531
iter  70 value 82.093897
iter  80 value 81.637446
iter  90 value 81.465689
iter 100 value 81.463618
final  value 81.463618 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 114.891271 
iter  10 value 92.319263
iter  20 value 90.109008
iter  30 value 83.935496
iter  40 value 83.843025
iter  50 value 83.834358
iter  60 value 83.569352
iter  70 value 83.409878
iter  80 value 82.701210
iter  90 value 82.556546
iter 100 value 82.555516
final  value 82.555516 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.052306 
iter  10 value 92.982223
iter  20 value 92.944169
iter  30 value 92.861152
iter  40 value 91.206874
iter  50 value 82.046713
iter  60 value 81.560174
iter  70 value 81.556719
iter  80 value 81.362759
iter  90 value 78.381624
iter 100 value 77.619246
final  value 77.619246 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 93.914625 
iter  10 value 85.367399
iter  20 value 85.155972
iter  30 value 85.134546
iter  40 value 82.444919
iter  50 value 79.573299
iter  60 value 79.455586
iter  70 value 79.340764
iter  80 value 79.267863
iter  90 value 79.264509
iter 100 value 79.263445
final  value 79.263445 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.378048 
iter  10 value 92.296595
iter  20 value 92.292592
iter  30 value 92.285286
iter  40 value 89.626425
iter  50 value 80.133923
iter  60 value 78.153535
iter  70 value 76.186581
iter  80 value 75.098761
iter  90 value 74.609166
iter 100 value 74.415925
final  value 74.415925 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 142.363010 
iter  10 value 117.768339
iter  20 value 117.765704
iter  30 value 117.760219
iter  40 value 117.534694
iter  50 value 117.502915
iter  60 value 117.502369
iter  70 value 117.500359
iter  80 value 117.499705
iter  90 value 117.499543
final  value 117.499527 
converged
Fitting Repeat 2 

# weights:  507
initial  value 131.196938 
iter  10 value 111.027507
iter  20 value 106.715486
iter  30 value 105.148630
iter  40 value 105.071739
iter  50 value 105.060519
iter  60 value 104.827540
iter  70 value 104.810494
iter  80 value 104.791453
iter  90 value 104.783432
iter 100 value 104.738154
final  value 104.738154 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 120.633652 
iter  10 value 117.738528
iter  20 value 115.851760
iter  30 value 108.455134
iter  40 value 104.381154
iter  50 value 104.315071
iter  60 value 103.730643
iter  70 value 103.383340
iter  80 value 103.382808
iter  90 value 103.382069
final  value 103.382014 
converged
Fitting Repeat 4 

# weights:  507
initial  value 144.404812 
iter  10 value 117.783780
iter  20 value 117.773707
iter  30 value 108.407188
iter  40 value 103.852130
iter  50 value 103.595879
iter  60 value 103.493166
iter  70 value 103.203737
iter  80 value 103.173442
iter  90 value 103.080367
iter 100 value 103.027925
final  value 103.027925 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 118.900690 
iter  10 value 117.874266
iter  20 value 117.866677
iter  30 value 117.623066
iter  40 value 116.449800
iter  50 value 112.668715
iter  60 value 112.539300
iter  70 value 112.221500
final  value 112.079633 
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 -- Mon May  4 00:48:08 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 
 40.913   1.007  91.876