##############################################################################
##############################################################################
###
### 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) (2026-03-05 r89546)
* 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 24.04.4 LTS
* using session charset: UTF-8
* current time: 2026-03-21 04:31:47 UTC
* 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 ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
var_imp       35.845  0.616  37.290
corr_plot     34.671  0.362  35.096
FSmethod      33.525  0.535  34.111
pred_ensembel 12.810  0.100  11.611
enrichfindP    0.591  0.046  20.016
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE

Status: 2 NOTEs
See
  ‘/home/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck/00check.log’
for details.

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


* installing to library ‘/home/biocbuild/bbs-3.23-bioc/R/site-library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.17.2’
** 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) (2026-03-05 r89546) -- "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 95.566981 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.698842 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.905231 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.047101 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.337849 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.228991 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.736759 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.148484 
final  value 94.032967 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.347933 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.230448 
iter  10 value 93.299161
iter  20 value 92.743502
final  value 92.743210 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.871019 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 94.968399 
iter  10 value 94.028500
final  value 94.028175 
converged
Fitting Repeat 3 

# weights:  507
initial  value 122.035665 
iter  10 value 93.923918
iter  10 value 93.923917
iter  10 value 93.923917
final  value 93.923917 
converged
Fitting Repeat 4 

# weights:  507
initial  value 109.097461 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 113.527417 
iter  10 value 94.051393
iter  20 value 94.050859
final  value 94.050855 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.022476 
iter  10 value 93.351463
iter  20 value 87.206656
iter  30 value 85.328916
iter  40 value 83.827157
iter  50 value 82.875938
iter  60 value 82.584196
iter  70 value 82.229636
iter  80 value 81.653116
iter  90 value 81.464737
final  value 81.464726 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.570650 
iter  10 value 94.055537
iter  20 value 84.722275
iter  30 value 84.080286
iter  40 value 82.555442
iter  50 value 82.461434
iter  60 value 82.357664
final  value 82.353627 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.748239 
iter  10 value 94.056674
iter  20 value 93.892218
iter  30 value 92.261701
iter  40 value 91.288052
iter  50 value 91.042708
iter  60 value 89.885941
iter  70 value 85.016469
iter  80 value 84.657132
iter  90 value 84.144469
iter 100 value 83.320434
final  value 83.320434 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.135265 
iter  10 value 89.153365
iter  20 value 86.153137
iter  30 value 83.511845
iter  40 value 82.980733
iter  50 value 82.535196
iter  60 value 82.455456
iter  70 value 82.371130
final  value 82.353627 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.712224 
iter  10 value 94.056659
iter  20 value 91.068959
iter  30 value 86.865677
iter  40 value 86.182088
iter  50 value 83.435796
iter  60 value 82.708792
iter  70 value 82.581954
iter  80 value 82.557764
iter  90 value 82.520221
iter 100 value 82.469915
final  value 82.469915 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 107.041526 
iter  10 value 94.478904
iter  20 value 93.857267
iter  30 value 88.870409
iter  40 value 85.160439
iter  50 value 84.855729
iter  60 value 82.887231
iter  70 value 82.284543
iter  80 value 82.126652
iter  90 value 81.949368
iter 100 value 81.737588
final  value 81.737588 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.781785 
iter  10 value 94.193666
iter  20 value 92.698858
iter  30 value 92.359989
iter  40 value 91.230697
iter  50 value 90.759548
iter  60 value 88.913518
iter  70 value 85.112938
iter  80 value 82.594004
iter  90 value 80.956511
iter 100 value 80.585277
final  value 80.585277 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.365579 
iter  10 value 86.850026
iter  20 value 86.037007
iter  30 value 83.228423
iter  40 value 81.820007
iter  50 value 81.018755
iter  60 value 80.534668
iter  70 value 80.224887
iter  80 value 80.120358
iter  90 value 80.046649
iter 100 value 80.030303
final  value 80.030303 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.868492 
iter  10 value 93.792680
iter  20 value 90.091997
iter  30 value 89.278062
iter  40 value 84.897284
iter  50 value 81.996932
iter  60 value 81.168244
iter  70 value 80.353950
iter  80 value 80.190484
iter  90 value 80.051165
iter 100 value 80.037520
final  value 80.037520 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.767778 
iter  10 value 94.036550
iter  20 value 87.665658
iter  30 value 85.053586
iter  40 value 83.433742
iter  50 value 82.969154
iter  60 value 81.514303
iter  70 value 80.847340
iter  80 value 80.306296
iter  90 value 80.155468
iter 100 value 80.115854
final  value 80.115854 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 118.546010 
iter  10 value 95.018365
iter  20 value 93.488527
iter  30 value 91.136009
iter  40 value 90.977961
iter  50 value 90.863369
iter  60 value 90.757115
iter  70 value 86.979888
iter  80 value 84.878029
iter  90 value 83.087727
iter 100 value 82.602107
final  value 82.602107 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 128.890369 
iter  10 value 94.128578
iter  20 value 93.269514
iter  30 value 83.637762
iter  40 value 82.660657
iter  50 value 82.065547
iter  60 value 81.355166
iter  70 value 80.892579
iter  80 value 80.491615
iter  90 value 80.284496
iter 100 value 80.216378
final  value 80.216378 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 117.285993 
iter  10 value 91.131769
iter  20 value 87.613666
iter  30 value 85.558360
iter  40 value 85.400065
iter  50 value 83.493039
iter  60 value 82.556960
iter  70 value 82.354178
iter  80 value 82.292779
iter  90 value 81.361528
iter 100 value 80.409833
final  value 80.409833 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.572304 
iter  10 value 94.209144
iter  20 value 93.411301
iter  30 value 89.482141
iter  40 value 89.060326
iter  50 value 87.433658
iter  60 value 84.839218
iter  70 value 83.800749
iter  80 value 83.705749
iter  90 value 83.211965
iter 100 value 82.167546
final  value 82.167546 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.698486 
iter  10 value 92.571851
iter  20 value 86.803794
iter  30 value 85.973394
iter  40 value 85.855267
iter  50 value 83.978059
iter  60 value 82.280332
iter  70 value 81.917747
iter  80 value 81.489943
iter  90 value 80.828514
iter 100 value 80.320718
final  value 80.320718 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.516527 
final  value 94.054545 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.202891 
final  value 94.054563 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.970066 
final  value 94.054676 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.560095 
final  value 94.054544 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.294700 
iter  10 value 94.054541
iter  20 value 94.042979
iter  30 value 93.951847
iter  40 value 82.346234
iter  50 value 82.334654
iter  60 value 82.334119
iter  70 value 82.312962
iter  80 value 82.305711
iter  90 value 82.012949
final  value 82.009831 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.479038 
iter  10 value 94.037828
iter  20 value 93.987299
iter  30 value 93.962445
iter  40 value 93.962327
iter  40 value 93.962327
iter  40 value 93.962327
final  value 93.962327 
converged
Fitting Repeat 2 

# weights:  305
initial  value 108.049050 
iter  10 value 94.057808
iter  20 value 94.052922
final  value 94.052918 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.500853 
iter  10 value 94.057783
iter  20 value 94.053024
iter  30 value 93.802792
iter  40 value 85.822494
iter  50 value 85.810129
iter  60 value 85.625258
iter  70 value 85.440683
iter  80 value 85.364452
iter  90 value 85.359093
final  value 85.359074 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.487295 
iter  10 value 94.057744
iter  20 value 93.822338
iter  30 value 84.940978
iter  40 value 81.636407
iter  50 value 81.522726
iter  60 value 81.101265
iter  70 value 80.965778
iter  80 value 80.489494
iter  90 value 79.831632
iter 100 value 79.495999
final  value 79.495999 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 116.519100 
iter  10 value 94.057278
iter  20 value 94.040501
iter  30 value 94.037047
iter  40 value 94.035092
iter  50 value 94.033178
iter  60 value 91.047060
iter  70 value 85.324752
final  value 85.323830 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.114325 
iter  10 value 84.899768
iter  20 value 83.757954
iter  30 value 83.314064
iter  40 value 83.310534
iter  50 value 83.289605
iter  60 value 82.846530
iter  70 value 82.756952
iter  80 value 82.641556
iter  90 value 81.803888
iter 100 value 81.294893
final  value 81.294893 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 101.982064 
iter  10 value 94.036512
iter  20 value 94.003355
iter  30 value 92.893356
final  value 92.893349 
converged
Fitting Repeat 3 

# weights:  507
initial  value 120.949086 
iter  10 value 94.061627
final  value 94.053802 
converged
Fitting Repeat 4 

# weights:  507
initial  value 120.372010 
iter  10 value 92.892938
iter  20 value 87.298050
iter  30 value 84.795248
iter  40 value 83.979553
iter  50 value 83.300301
iter  60 value 83.233151
iter  70 value 83.229955
iter  80 value 83.062628
iter  90 value 82.576356
final  value 82.536371 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.274618 
iter  10 value 94.041456
iter  20 value 91.928352
iter  30 value 85.080173
iter  40 value 84.743869
iter  50 value 84.691674
final  value 84.691580 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.716130 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.042581 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.865124 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.684969 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 110.040957 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 115.549035 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.838221 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.223501 
iter  10 value 92.523916
final  value 92.523810 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.879869 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.445678 
final  value 93.900000 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.718859 
iter  10 value 93.915757
final  value 93.915748 
converged
Fitting Repeat 2 

# weights:  507
initial  value 114.036886 
iter  10 value 93.682544
iter  20 value 93.489967
iter  30 value 93.076528
iter  40 value 93.057164
iter  50 value 88.979706
iter  60 value 86.452092
final  value 86.445879 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.880519 
iter  10 value 93.915746
iter  10 value 93.915746
iter  10 value 93.915746
final  value 93.915746 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.180945 
final  value 93.915746 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.045273 
iter  10 value 91.452238
iter  20 value 86.604541
iter  30 value 86.081684
iter  40 value 85.957463
iter  50 value 85.297386
iter  60 value 85.163054
final  value 85.162865 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.037335 
iter  10 value 94.086387
iter  20 value 87.489253
iter  30 value 85.119606
iter  40 value 83.695754
iter  50 value 83.517371
iter  60 value 82.890674
iter  70 value 82.686003
iter  80 value 82.684926
final  value 82.684773 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.995918 
iter  10 value 94.054865
iter  20 value 93.407293
iter  30 value 86.195231
iter  40 value 82.825952
iter  50 value 82.698422
iter  60 value 82.396431
iter  70 value 82.310623
iter  80 value 81.952958
final  value 81.946765 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.727351 
iter  10 value 92.786189
iter  20 value 92.448649
iter  30 value 92.290801
iter  40 value 86.926847
iter  50 value 85.154797
iter  60 value 83.448088
iter  70 value 81.450324
iter  80 value 81.175685
iter  90 value 79.509604
iter 100 value 79.397054
final  value 79.397054 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 101.388806 
iter  10 value 94.054594
iter  20 value 93.664969
iter  30 value 93.512220
iter  40 value 90.862982
iter  50 value 87.229739
iter  60 value 86.988213
iter  70 value 84.104394
iter  80 value 83.911410
iter  90 value 83.898005
iter 100 value 83.897842
final  value 83.897842 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 104.964891 
iter  10 value 93.894549
iter  20 value 93.349034
iter  30 value 88.606440
iter  40 value 87.606249
iter  50 value 87.158282
iter  60 value 84.473423
iter  70 value 84.133539
iter  80 value 83.997849
iter  90 value 83.570928
iter 100 value 79.751491
final  value 79.751491 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 104.817949 
iter  10 value 93.417865
iter  20 value 89.854431
iter  30 value 86.908206
iter  40 value 85.797884
iter  50 value 84.734118
iter  60 value 81.466950
iter  70 value 81.204651
iter  80 value 80.750439
iter  90 value 79.343311
iter 100 value 78.421060
final  value 78.421060 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 121.822492 
iter  10 value 94.561645
iter  20 value 93.648956
iter  30 value 90.219293
iter  40 value 88.563792
iter  50 value 88.250007
iter  60 value 85.646074
iter  70 value 83.693699
iter  80 value 80.746669
iter  90 value 79.729553
iter 100 value 78.575898
final  value 78.575898 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.090191 
iter  10 value 94.087182
iter  20 value 85.471660
iter  30 value 82.258233
iter  40 value 79.270033
iter  50 value 78.602116
iter  60 value 78.281308
iter  70 value 78.199346
iter  80 value 78.179228
iter  90 value 78.097516
iter 100 value 77.864453
final  value 77.864453 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 120.628406 
iter  10 value 94.142663
iter  20 value 89.054376
iter  30 value 84.505811
iter  40 value 83.782788
iter  50 value 81.829857
iter  60 value 80.827750
iter  70 value 80.221212
iter  80 value 79.807039
iter  90 value 79.038074
iter 100 value 78.534844
final  value 78.534844 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 122.506338 
iter  10 value 92.916647
iter  20 value 84.628772
iter  30 value 82.877591
iter  40 value 80.560314
iter  50 value 80.083969
iter  60 value 79.461404
iter  70 value 78.657442
iter  80 value 78.192646
iter  90 value 77.930723
iter 100 value 77.542445
final  value 77.542445 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.280131 
iter  10 value 94.297712
iter  20 value 88.911149
iter  30 value 84.795766
iter  40 value 83.178415
iter  50 value 80.378922
iter  60 value 80.239342
iter  70 value 79.808297
iter  80 value 79.427634
iter  90 value 78.779864
iter 100 value 78.600176
final  value 78.600176 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.352377 
iter  10 value 86.749425
iter  20 value 84.020266
iter  30 value 83.545989
iter  40 value 82.876797
iter  50 value 80.509098
iter  60 value 78.600541
iter  70 value 78.169767
iter  80 value 78.100358
iter  90 value 78.033215
iter 100 value 77.826463
final  value 77.826463 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.784577 
iter  10 value 94.392157
iter  20 value 93.891592
iter  30 value 89.220169
iter  40 value 84.254922
iter  50 value 83.614575
iter  60 value 83.462187
iter  70 value 82.474105
iter  80 value 81.173890
iter  90 value 80.412521
iter 100 value 79.184406
final  value 79.184406 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.446943 
iter  10 value 95.906361
iter  20 value 92.433264
iter  30 value 90.272669
iter  40 value 86.778828
iter  50 value 81.913794
iter  60 value 81.545327
iter  70 value 81.275106
iter  80 value 80.887304
iter  90 value 80.459196
iter 100 value 78.957903
final  value 78.957903 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.381677 
iter  10 value 96.094806
iter  20 value 93.919120
iter  30 value 85.720300
iter  40 value 83.800291
iter  50 value 83.192165
iter  60 value 82.882020
iter  70 value 82.638886
iter  80 value 82.464896
iter  90 value 80.696070
iter 100 value 79.277562
final  value 79.277562 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.107022 
final  value 94.054563 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.102781 
final  value 94.054527 
converged
Fitting Repeat 3 

# weights:  103
initial  value 112.496060 
iter  10 value 94.061200
iter  20 value 94.053354
final  value 94.052944 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.145432 
final  value 94.054528 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.722429 
final  value 94.054432 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.897930 
iter  10 value 94.058108
iter  20 value 94.053324
iter  30 value 88.214840
iter  40 value 85.110030
iter  50 value 84.372196
iter  60 value 84.092165
iter  70 value 83.619977
iter  80 value 83.594757
iter  90 value 83.289611
iter 100 value 83.242384
final  value 83.242384 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 95.690235 
iter  10 value 88.167125
iter  20 value 86.284949
iter  30 value 86.282520
iter  40 value 85.221627
iter  50 value 84.350756
iter  60 value 84.338238
iter  70 value 84.334429
iter  80 value 84.258256
iter  90 value 84.187016
iter 100 value 84.186979
final  value 84.186979 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 113.959920 
iter  10 value 94.057429
iter  20 value 94.051505
iter  30 value 93.899877
iter  40 value 89.240781
iter  50 value 87.705950
iter  60 value 87.675477
iter  70 value 87.647036
iter  80 value 87.458328
iter  90 value 87.392178
iter 100 value 87.205168
final  value 87.205168 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 97.915752 
iter  10 value 93.333426
iter  20 value 93.329597
iter  30 value 85.637034
iter  40 value 85.619240
iter  50 value 85.598530
iter  60 value 85.419386
iter  70 value 85.066206
iter  80 value 85.051011
iter  90 value 85.045250
iter 100 value 84.594629
final  value 84.594629 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.817749 
iter  10 value 94.057781
iter  20 value 94.008900
iter  30 value 92.024327
iter  40 value 87.187202
iter  50 value 86.531009
iter  60 value 85.048714
iter  70 value 85.034066
final  value 85.034052 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.804139 
iter  10 value 94.054723
iter  20 value 93.211632
iter  30 value 90.877627
iter  40 value 90.838405
iter  50 value 90.777895
iter  60 value 90.757945
final  value 90.757771 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.288938 
iter  10 value 93.923872
iter  20 value 89.941325
iter  30 value 85.613424
iter  40 value 85.609270
iter  50 value 85.598088
iter  60 value 85.250028
final  value 85.249967 
converged
Fitting Repeat 3 

# weights:  507
initial  value 122.862806 
iter  10 value 93.923619
iter  20 value 93.672473
iter  30 value 88.884481
iter  40 value 86.897690
iter  50 value 86.850926
iter  60 value 86.850677
iter  70 value 86.850154
iter  80 value 86.849901
final  value 86.849882 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.324140 
iter  10 value 93.784422
iter  20 value 93.189683
iter  30 value 84.722555
iter  40 value 84.117758
iter  50 value 83.735344
iter  60 value 81.509552
iter  70 value 81.383157
iter  80 value 81.138797
iter  90 value 80.908988
iter 100 value 80.908150
final  value 80.908150 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 128.496135 
iter  10 value 93.923698
iter  20 value 93.669579
iter  30 value 92.641189
iter  40 value 87.425811
iter  50 value 85.435672
iter  60 value 85.423990
iter  70 value 85.419748
iter  80 value 85.202742
iter  90 value 80.705243
iter 100 value 80.398797
final  value 80.398797 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.523797 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.370389 
iter  10 value 92.269816
final  value 92.269063 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.923243 
final  value 94.114232 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.206040 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.685271 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.984255 
iter  10 value 94.215091
iter  20 value 94.214011
final  value 94.214007 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.125486 
final  value 94.275363 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.565140 
iter  10 value 93.119697
iter  20 value 82.358170
iter  30 value 82.152103
iter  40 value 82.145311
iter  40 value 82.145311
final  value 82.145311 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.084789 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.518898 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 120.685704 
iter  10 value 94.278927
final  value 94.275362 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.473789 
iter  10 value 92.129311
iter  20 value 91.849815
final  value 91.849812 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.947282 
final  value 94.275362 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.894813 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.244414 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.137484 
iter  10 value 94.487581
iter  20 value 94.209401
iter  30 value 91.045345
iter  40 value 90.413764
iter  50 value 84.413435
iter  60 value 83.990069
iter  70 value 83.931728
iter  80 value 81.220202
iter  90 value 80.804280
iter 100 value 80.782450
final  value 80.782450 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.972390 
iter  10 value 94.476429
iter  20 value 94.274206
iter  30 value 93.656082
iter  40 value 89.887397
iter  50 value 86.254998
iter  60 value 85.070796
iter  70 value 81.779115
iter  80 value 81.675364
iter  90 value 81.595541
iter 100 value 81.585048
final  value 81.585048 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.414018 
iter  10 value 94.509164
iter  20 value 89.128324
iter  30 value 85.811865
iter  40 value 83.040331
iter  50 value 82.559614
iter  60 value 81.786487
iter  70 value 81.585575
final  value 81.584782 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.357031 
iter  10 value 94.648808
iter  20 value 93.583682
iter  30 value 88.931061
iter  40 value 86.598967
iter  50 value 83.819904
iter  60 value 83.538576
iter  70 value 83.471689
final  value 83.471126 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.245826 
iter  10 value 88.525920
iter  20 value 83.830170
iter  30 value 83.250139
iter  40 value 82.620094
iter  50 value 82.013377
iter  60 value 81.958448
iter  60 value 81.958448
iter  60 value 81.958448
final  value 81.958448 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.269261 
iter  10 value 94.463783
iter  20 value 84.265400
iter  30 value 83.560954
iter  40 value 82.449776
iter  50 value 80.798198
iter  60 value 79.866724
iter  70 value 79.557362
iter  80 value 79.384868
iter  90 value 79.233312
iter 100 value 78.979788
final  value 78.979788 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.703221 
iter  10 value 92.742798
iter  20 value 90.546555
iter  30 value 84.062059
iter  40 value 82.540731
iter  50 value 82.435910
iter  60 value 82.341201
iter  70 value 81.816463
iter  80 value 81.698221
iter  90 value 81.220506
iter 100 value 80.804555
final  value 80.804555 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.037903 
iter  10 value 94.458321
iter  20 value 94.239521
iter  30 value 94.189746
iter  40 value 93.984924
iter  50 value 84.055482
iter  60 value 82.467388
iter  70 value 82.108036
iter  80 value 81.862501
iter  90 value 81.761369
iter 100 value 81.739521
final  value 81.739521 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.178283 
iter  10 value 94.454531
iter  20 value 94.215380
iter  30 value 83.595825
iter  40 value 82.706112
iter  50 value 81.997557
iter  60 value 81.844009
iter  70 value 81.815856
iter  80 value 81.720485
iter  90 value 81.484261
iter 100 value 80.454306
final  value 80.454306 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.618407 
iter  10 value 94.313742
iter  20 value 91.535305
iter  30 value 86.455531
iter  40 value 85.232107
iter  50 value 82.777287
iter  60 value 82.502096
iter  70 value 82.238301
iter  80 value 82.233172
iter  90 value 82.216305
iter 100 value 82.080986
final  value 82.080986 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 140.129532 
iter  10 value 94.350106
iter  20 value 87.275279
iter  30 value 84.525139
iter  40 value 82.954857
iter  50 value 81.991964
iter  60 value 81.556197
iter  70 value 80.292281
iter  80 value 79.287511
iter  90 value 79.118340
iter 100 value 78.995645
final  value 78.995645 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.358661 
iter  10 value 93.908999
iter  20 value 87.337342
iter  30 value 85.186666
iter  40 value 83.815239
iter  50 value 82.993679
iter  60 value 81.037543
iter  70 value 80.836700
iter  80 value 80.210211
iter  90 value 79.891406
iter 100 value 79.202319
final  value 79.202319 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.390301 
iter  10 value 93.811405
iter  20 value 91.643497
iter  30 value 89.165644
iter  40 value 87.765513
iter  50 value 86.803692
iter  60 value 82.883150
iter  70 value 80.521942
iter  80 value 79.867937
iter  90 value 79.721166
iter 100 value 79.562290
final  value 79.562290 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.348304 
iter  10 value 98.892284
iter  20 value 94.422763
iter  30 value 94.271815
iter  40 value 93.822306
iter  50 value 83.497653
iter  60 value 83.102077
iter  70 value 82.465408
iter  80 value 81.401538
iter  90 value 80.650756
iter 100 value 79.505109
final  value 79.505109 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.311267 
iter  10 value 94.867074
iter  20 value 86.351857
iter  30 value 81.812335
iter  40 value 80.425074
iter  50 value 79.935379
iter  60 value 79.607541
iter  70 value 79.344722
iter  80 value 79.105686
iter  90 value 79.041576
iter 100 value 79.002282
final  value 79.002282 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.681403 
iter  10 value 94.491186
final  value 94.489046 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.058366 
iter  10 value 94.485860
iter  20 value 94.484294
iter  30 value 85.766724
iter  40 value 83.901751
iter  50 value 83.279987
iter  60 value 81.910409
iter  70 value 81.659740
iter  80 value 81.649589
final  value 81.585002 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.750207 
final  value 94.485707 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.541200 
final  value 94.485631 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.202187 
final  value 94.485933 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.792091 
iter  10 value 94.093938
iter  20 value 94.091007
iter  30 value 85.980985
iter  40 value 81.534951
iter  50 value 81.018863
iter  60 value 81.017227
final  value 81.017222 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.029520 
iter  10 value 94.488700
iter  20 value 94.484263
final  value 94.484214 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.435463 
iter  10 value 94.484648
iter  20 value 94.363609
iter  30 value 94.214616
final  value 94.214329 
converged
Fitting Repeat 4 

# weights:  305
initial  value 110.123219 
iter  10 value 94.488936
iter  20 value 94.484230
iter  30 value 94.416291
iter  40 value 92.649045
iter  50 value 92.039528
iter  60 value 82.151934
iter  70 value 82.149671
iter  80 value 80.407913
iter  90 value 79.772776
iter 100 value 78.649527
final  value 78.649527 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.510602 
iter  10 value 94.489044
iter  20 value 91.508394
iter  30 value 88.601859
iter  40 value 85.355610
iter  50 value 85.295461
iter  60 value 85.281341
iter  70 value 84.567126
iter  80 value 84.499567
iter  90 value 84.498433
iter 100 value 81.349866
final  value 81.349866 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 99.858377 
iter  10 value 93.549217
iter  20 value 92.794908
iter  30 value 90.383727
iter  40 value 88.365452
iter  50 value 85.752259
iter  60 value 85.740032
iter  70 value 85.733497
iter  80 value 85.651309
iter  90 value 85.192634
iter 100 value 81.643904
final  value 81.643904 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 119.294554 
iter  10 value 94.283546
iter  20 value 94.217480
iter  30 value 94.211142
iter  40 value 94.158724
final  value 94.158142 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.297265 
iter  10 value 85.543313
iter  20 value 84.761875
iter  30 value 84.706239
iter  40 value 83.804087
iter  50 value 83.425073
iter  60 value 81.583563
iter  70 value 80.562448
iter  80 value 80.560662
iter  90 value 80.560354
final  value 80.558836 
converged
Fitting Repeat 4 

# weights:  507
initial  value 113.517650 
iter  10 value 94.492814
iter  20 value 94.463378
iter  30 value 93.806137
iter  40 value 93.230644
iter  50 value 91.860940
final  value 91.860653 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.858895 
iter  10 value 94.492166
iter  20 value 94.415395
iter  30 value 82.782295
iter  40 value 82.408670
iter  50 value 82.363683
iter  60 value 82.326119
iter  70 value 82.100938
iter  80 value 81.525227
iter  90 value 79.459357
iter 100 value 78.936700
final  value 78.936700 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.824594 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.814739 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 117.967378 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.743522 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.158018 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.908755 
iter  10 value 94.293350
iter  20 value 94.287654
final  value 94.287627 
converged
Fitting Repeat 2 

# weights:  305
initial  value 112.427702 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 114.930566 
iter  10 value 92.922006
iter  20 value 92.590363
iter  30 value 92.590173
final  value 92.590167 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.958718 
iter  10 value 94.305882
iter  10 value 94.305882
iter  10 value 94.305882
final  value 94.305882 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.753792 
final  value 94.443243 
converged
Fitting Repeat 1 

# weights:  507
initial  value 113.287960 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.485780 
final  value 94.443243 
converged
Fitting Repeat 3 

# weights:  507
initial  value 147.130621 
iter  10 value 94.306007
final  value 94.305882 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.986377 
final  value 94.354286 
converged
Fitting Repeat 5 

# weights:  507
initial  value 120.739837 
iter  10 value 91.019219
iter  20 value 82.698946
iter  30 value 79.945052
iter  40 value 79.944336
final  value 79.944242 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.098632 
iter  10 value 94.128972
iter  20 value 84.403505
iter  30 value 82.746566
iter  40 value 82.019781
iter  50 value 82.004082
iter  60 value 81.251062
iter  70 value 80.593441
iter  80 value 80.472495
iter  90 value 80.309730
iter 100 value 80.149463
final  value 80.149463 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 102.403443 
iter  10 value 94.488290
iter  20 value 93.707919
iter  30 value 88.623238
iter  40 value 86.182032
iter  50 value 85.512179
iter  50 value 85.512178
final  value 85.512178 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.316041 
iter  10 value 93.303040
iter  20 value 88.049843
iter  30 value 87.114610
iter  40 value 86.215584
iter  50 value 86.070093
final  value 86.070091 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.037496 
iter  10 value 94.488598
iter  20 value 88.947951
iter  30 value 84.556078
iter  40 value 84.286936
iter  50 value 83.847313
iter  60 value 83.122578
iter  70 value 83.027339
final  value 83.027327 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.295264 
iter  10 value 94.402848
iter  20 value 90.355512
iter  30 value 83.154882
iter  40 value 82.734201
iter  50 value 81.069924
iter  60 value 80.656896
iter  70 value 80.499591
iter  80 value 80.303447
final  value 80.300755 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.685093 
iter  10 value 94.748492
iter  20 value 87.034515
iter  30 value 83.867200
iter  40 value 83.457093
iter  50 value 82.819180
iter  60 value 82.329506
iter  70 value 81.945791
iter  80 value 81.786597
iter  90 value 81.281890
iter 100 value 81.189194
final  value 81.189194 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 111.936071 
iter  10 value 94.469441
iter  20 value 87.956910
iter  30 value 87.415042
iter  40 value 85.193283
iter  50 value 83.765372
iter  60 value 83.085737
iter  70 value 82.964768
iter  80 value 82.881214
iter  90 value 82.446081
iter 100 value 80.985515
final  value 80.985515 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 113.797149 
iter  10 value 94.404943
iter  20 value 92.193840
iter  30 value 91.352287
iter  40 value 85.846943
iter  50 value 83.679236
iter  60 value 83.344706
iter  70 value 81.906213
iter  80 value 80.974637
iter  90 value 80.684687
iter 100 value 80.267813
final  value 80.267813 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.541639 
iter  10 value 94.495741
iter  20 value 89.582139
iter  30 value 86.744835
iter  40 value 84.858493
iter  50 value 83.634755
iter  60 value 83.603921
iter  70 value 83.366049
iter  80 value 80.854698
iter  90 value 80.163865
iter 100 value 80.026132
final  value 80.026132 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.044309 
iter  10 value 95.436148
iter  20 value 91.610817
iter  30 value 89.438813
iter  40 value 85.118594
iter  50 value 84.514599
iter  60 value 83.990320
iter  70 value 83.963759
iter  80 value 83.888639
iter  90 value 83.654610
iter 100 value 83.581844
final  value 83.581844 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.984784 
iter  10 value 94.662814
iter  20 value 90.982179
iter  30 value 86.476580
iter  40 value 85.987993
iter  50 value 84.205727
iter  60 value 82.902981
iter  70 value 82.541468
iter  80 value 82.469357
iter  90 value 81.353078
iter 100 value 79.911839
final  value 79.911839 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 118.457530 
iter  10 value 94.464864
iter  20 value 90.343003
iter  30 value 84.372652
iter  40 value 83.502252
iter  50 value 82.985020
iter  60 value 81.900217
iter  70 value 80.634456
iter  80 value 80.354100
iter  90 value 79.931636
iter 100 value 79.671050
final  value 79.671050 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.964709 
iter  10 value 94.438443
iter  20 value 89.719594
iter  30 value 86.784103
iter  40 value 84.969923
iter  50 value 83.155530
iter  60 value 81.013298
iter  70 value 80.532021
iter  80 value 80.249880
iter  90 value 79.572609
iter 100 value 78.681643
final  value 78.681643 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 117.192256 
iter  10 value 94.794768
iter  20 value 92.666846
iter  30 value 91.213716
iter  40 value 85.146788
iter  50 value 83.154831
iter  60 value 82.066275
iter  70 value 80.619389
iter  80 value 80.311038
iter  90 value 79.631575
iter 100 value 79.142588
final  value 79.142588 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 120.859209 
iter  10 value 94.666088
iter  20 value 92.883261
iter  30 value 86.947599
iter  40 value 84.895931
iter  50 value 82.627245
iter  60 value 81.264252
iter  70 value 80.082452
iter  80 value 79.180571
iter  90 value 78.291555
iter 100 value 78.079045
final  value 78.079045 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.435030 
final  value 94.485740 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.868911 
iter  10 value 94.486511
final  value 94.484909 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.682270 
final  value 94.486010 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.247358 
iter  10 value 94.445009
iter  20 value 94.443664
final  value 94.443458 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.927212 
final  value 94.485836 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.518114 
iter  10 value 94.487776
iter  20 value 92.825540
iter  30 value 85.059628
iter  40 value 84.357835
iter  50 value 83.917343
iter  60 value 81.228733
iter  70 value 81.088400
iter  80 value 81.031811
iter  90 value 81.030013
final  value 81.029828 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.769632 
iter  10 value 94.448573
iter  20 value 94.184215
iter  30 value 86.533199
iter  40 value 86.524292
iter  50 value 86.183125
iter  60 value 84.771687
iter  70 value 80.022315
iter  80 value 78.437891
iter  90 value 78.047016
iter 100 value 77.502829
final  value 77.502829 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 95.025386 
iter  10 value 94.404677
iter  20 value 90.612354
iter  30 value 90.094663
iter  40 value 89.601858
final  value 89.601776 
converged
Fitting Repeat 4 

# weights:  305
initial  value 113.912376 
iter  10 value 94.406736
iter  20 value 94.404697
iter  30 value 94.400497
iter  40 value 93.808857
iter  50 value 88.610139
iter  60 value 82.740526
iter  70 value 82.740190
iter  80 value 81.648853
iter  90 value 81.364722
iter 100 value 80.967305
final  value 80.967305 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 94.736052 
iter  10 value 94.359263
iter  20 value 94.326786
iter  30 value 94.306346
final  value 94.306298 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.650314 
iter  10 value 94.408237
iter  20 value 88.148075
iter  30 value 85.595583
iter  40 value 82.460524
iter  50 value 81.824693
iter  60 value 81.823320
iter  70 value 81.812447
iter  80 value 81.810884
iter  90 value 81.809524
iter 100 value 81.806690
final  value 81.806690 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 101.706945 
iter  10 value 94.492659
iter  20 value 94.393632
iter  30 value 94.330926
iter  40 value 94.214444
iter  50 value 85.752042
iter  60 value 85.707534
iter  70 value 82.803395
iter  80 value 80.794176
iter  90 value 80.747013
iter 100 value 80.746472
final  value 80.746472 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.405923 
iter  10 value 94.493191
iter  20 value 94.466089
iter  30 value 92.792700
final  value 92.628785 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.392755 
iter  10 value 94.451334
iter  20 value 94.448462
final  value 94.447894 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.363967 
iter  10 value 94.451525
iter  20 value 91.381404
iter  30 value 86.049988
iter  40 value 85.997318
iter  50 value 85.994676
iter  60 value 85.950582
iter  70 value 84.583186
iter  80 value 80.685800
iter  90 value 79.772266
final  value 79.748230 
converged
Fitting Repeat 1 

# weights:  103
initial  value 112.854990 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.648926 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.748875 
iter  10 value 94.052582
final  value 94.052434 
converged
Fitting Repeat 4 

# weights:  103
initial  value 109.889696 
final  value 94.275363 
converged
Fitting Repeat 5 

# weights:  103
initial  value 111.435756 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.460126 
final  value 94.275362 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.724888 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.707738 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.094159 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.706699 
iter  10 value 94.402440
iter  10 value 94.402439
iter  10 value 94.402439
final  value 94.402439 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.119298 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.074227 
iter  10 value 92.080683
iter  20 value 91.519398
iter  30 value 91.330552
iter  40 value 91.329353
final  value 91.329329 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.136277 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.418339 
final  value 94.244048 
converged
Fitting Repeat 5 

# weights:  507
initial  value 109.630877 
iter  10 value 93.531077
iter  20 value 92.900234
iter  30 value 92.792758
iter  40 value 91.280434
final  value 91.215847 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.405834 
iter  10 value 93.740132
iter  20 value 88.098800
iter  30 value 87.617546
iter  40 value 87.171616
iter  50 value 87.070205
iter  60 value 85.409350
iter  70 value 84.386552
iter  80 value 84.159256
iter  90 value 84.004382
iter 100 value 83.910081
final  value 83.910081 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 98.390932 
iter  10 value 94.470293
iter  20 value 92.686003
iter  30 value 87.664632
iter  40 value 86.290966
iter  50 value 85.570900
iter  60 value 84.546934
iter  70 value 84.286299
iter  80 value 84.060817
iter  90 value 83.928546
iter 100 value 83.881834
final  value 83.881834 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 103.617518 
iter  10 value 94.488530
iter  20 value 94.247481
iter  30 value 90.098510
iter  40 value 88.016742
iter  50 value 87.464338
iter  60 value 86.764634
iter  70 value 85.299367
iter  80 value 84.330394
iter  90 value 84.141587
iter 100 value 83.935226
final  value 83.935226 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.438511 
iter  10 value 93.980114
iter  20 value 92.344518
iter  30 value 91.733914
iter  40 value 87.423202
iter  50 value 86.803307
iter  60 value 84.471032
iter  70 value 83.946820
iter  80 value 83.845680
iter  90 value 83.831014
iter 100 value 83.805702
final  value 83.805702 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 100.520159 
iter  10 value 94.482220
iter  20 value 94.221864
iter  30 value 93.575245
iter  40 value 88.836949
iter  50 value 85.384337
iter  60 value 84.894308
iter  70 value 84.522078
iter  80 value 84.129703
iter  90 value 83.804320
iter 100 value 83.740471
final  value 83.740471 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 102.389723 
iter  10 value 94.490834
iter  20 value 94.393677
iter  30 value 94.120563
iter  40 value 92.264100
iter  50 value 87.933680
iter  60 value 86.770875
iter  70 value 85.679598
iter  80 value 85.270879
iter  90 value 85.050603
iter 100 value 84.489619
final  value 84.489619 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 114.492090 
iter  10 value 94.591276
iter  20 value 87.852201
iter  30 value 87.092788
iter  40 value 85.725703
iter  50 value 85.064371
iter  60 value 84.774844
iter  70 value 83.979193
iter  80 value 83.757712
iter  90 value 83.532267
iter 100 value 83.063508
final  value 83.063508 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.393692 
iter  10 value 94.514230
iter  20 value 94.257844
iter  30 value 93.973825
iter  40 value 90.414068
iter  50 value 86.688565
iter  60 value 85.705579
iter  70 value 84.803154
iter  80 value 84.314995
iter  90 value 83.698097
iter 100 value 83.374037
final  value 83.374037 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 115.841868 
iter  10 value 93.181026
iter  20 value 87.497121
iter  30 value 87.039557
iter  40 value 84.549478
iter  50 value 84.296257
iter  60 value 84.109409
iter  70 value 83.956993
iter  80 value 83.108522
iter  90 value 82.836586
iter 100 value 82.486811
final  value 82.486811 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 112.758341 
iter  10 value 94.160595
iter  20 value 87.846193
iter  30 value 87.578727
iter  40 value 85.538863
iter  50 value 84.307847
iter  60 value 83.416913
iter  70 value 82.885614
iter  80 value 82.682141
iter  90 value 82.641968
iter 100 value 82.621310
final  value 82.621310 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 117.856687 
iter  10 value 94.160624
iter  20 value 88.088125
iter  30 value 85.605402
iter  40 value 84.896540
iter  50 value 84.128941
iter  60 value 83.630150
iter  70 value 83.420947
iter  80 value 83.065767
iter  90 value 82.999720
iter 100 value 82.840572
final  value 82.840572 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.620311 
iter  10 value 94.066429
iter  20 value 88.031392
iter  30 value 87.453259
iter  40 value 84.915702
iter  50 value 84.379595
iter  60 value 84.258036
iter  70 value 84.096043
iter  80 value 83.978022
iter  90 value 83.796584
iter 100 value 83.538099
final  value 83.538099 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.581378 
iter  10 value 94.175593
iter  20 value 89.944117
iter  30 value 86.770526
iter  40 value 85.429106
iter  50 value 85.098674
iter  60 value 84.812686
iter  70 value 83.506181
iter  80 value 82.981843
iter  90 value 82.494846
iter 100 value 82.399079
final  value 82.399079 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 117.584485 
iter  10 value 96.783805
iter  20 value 94.339113
iter  30 value 86.914650
iter  40 value 85.723330
iter  50 value 85.465470
iter  60 value 83.944730
iter  70 value 83.031404
iter  80 value 82.949788
iter  90 value 82.729220
iter 100 value 82.679995
final  value 82.679995 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 115.247819 
iter  10 value 94.791007
iter  20 value 94.261721
iter  30 value 91.729012
iter  40 value 90.505989
iter  50 value 88.782911
iter  60 value 87.475659
iter  70 value 84.318766
iter  80 value 83.874208
iter  90 value 82.982128
iter 100 value 82.893122
final  value 82.893122 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.719912 
final  value 94.462156 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.508161 
final  value 94.485937 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.812107 
iter  10 value 94.092981
iter  20 value 94.090021
iter  30 value 94.089020
iter  40 value 93.770619
iter  50 value 89.562528
iter  60 value 86.430796
iter  70 value 86.065333
iter  80 value 85.578838
iter  90 value 85.025861
iter 100 value 84.761753
final  value 84.761753 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 98.951861 
final  value 94.485875 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.306439 
final  value 94.485786 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.924875 
iter  10 value 94.489256
iter  20 value 94.484256
final  value 94.484210 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.861007 
iter  10 value 91.822670
iter  20 value 91.109687
iter  30 value 91.107951
final  value 91.105515 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.551189 
iter  10 value 94.277810
iter  20 value 94.056810
iter  30 value 94.053092
iter  40 value 90.026834
iter  50 value 88.079733
final  value 88.079086 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.678826 
iter  10 value 92.027406
iter  20 value 91.097293
iter  30 value 91.093296
iter  40 value 90.954131
iter  50 value 89.820676
iter  60 value 84.483729
iter  70 value 84.141359
iter  80 value 83.069615
iter  90 value 82.415272
iter 100 value 81.230812
final  value 81.230812 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 117.636428 
iter  10 value 94.518626
iter  20 value 94.252467
iter  30 value 94.078466
iter  40 value 94.022746
iter  50 value 94.007206
iter  60 value 93.954772
iter  70 value 93.952725
iter  70 value 93.952725
final  value 93.952725 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.863749 
iter  10 value 94.061627
iter  20 value 94.021529
iter  30 value 94.014420
iter  40 value 93.960613
iter  50 value 93.823013
iter  60 value 90.417671
iter  70 value 89.722430
iter  80 value 89.714710
iter  90 value 89.711081
iter 100 value 89.710761
final  value 89.710761 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 100.511621 
iter  10 value 94.469600
iter  20 value 93.279917
iter  30 value 86.744140
iter  40 value 86.640568
iter  50 value 86.618456
iter  60 value 86.608888
iter  70 value 86.426792
iter  80 value 85.756620
iter  90 value 85.729040
iter 100 value 85.492686
final  value 85.492686 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.604624 
iter  10 value 92.880416
iter  20 value 86.869449
iter  30 value 86.849849
iter  40 value 86.720793
final  value 86.719257 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.313594 
iter  10 value 94.283655
iter  20 value 94.277838
iter  30 value 91.949155
iter  40 value 90.730768
iter  50 value 90.670206
iter  60 value 87.766410
iter  70 value 84.455100
iter  80 value 84.411825
iter  90 value 84.410920
iter 100 value 84.405481
final  value 84.405481 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.631550 
iter  10 value 94.347168
iter  20 value 93.930268
iter  30 value 86.853608
iter  40 value 85.016874
iter  50 value 84.934369
iter  60 value 84.930625
final  value 84.930256 
converged
Fitting Repeat 1 

# weights:  507
initial  value 178.179844 
iter  10 value 117.936975
iter  20 value 113.550495
iter  30 value 109.761989
iter  40 value 107.530293
iter  50 value 103.521129
iter  60 value 102.728135
iter  70 value 102.182772
iter  80 value 101.805559
iter  90 value 101.498027
iter 100 value 100.925884
final  value 100.925884 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 182.603389 
iter  10 value 118.566731
iter  20 value 117.623382
iter  30 value 111.441098
iter  40 value 106.835963
iter  50 value 105.332265
iter  60 value 104.364900
iter  70 value 102.439433
iter  80 value 102.083640
iter  90 value 101.845648
iter 100 value 101.104514
final  value 101.104514 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 133.457116 
iter  10 value 118.051680
iter  20 value 110.768611
iter  30 value 108.833921
iter  40 value 107.149280
iter  50 value 103.839656
iter  60 value 103.295990
iter  70 value 101.752720
iter  80 value 101.230289
iter  90 value 100.977544
iter 100 value 100.834630
final  value 100.834630 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 169.721675 
iter  10 value 116.520807
iter  20 value 114.251784
iter  30 value 110.738370
iter  40 value 106.290781
iter  50 value 106.050503
iter  60 value 105.918996
iter  70 value 105.741496
iter  80 value 105.372444
iter  90 value 105.161400
iter 100 value 104.553884
final  value 104.553884 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 153.594282 
iter  10 value 118.470981
iter  20 value 108.400755
iter  30 value 107.128141
iter  40 value 105.542715
iter  50 value 102.990814
iter  60 value 102.024337
iter  70 value 101.465468
iter  80 value 101.366920
iter  90 value 101.114592
iter 100 value 100.980178
final  value 100.980178 
stopped after 100 iterations
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Sat Mar 21 00:37:37 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 
 41.181   1.251 113.213