##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:HPiP.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings HPiP_1.8.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.18-bioc/meat/HPiP.Rcheck’
* using R version 4.3.3 (2024-02-29)
* using platform: x86_64-apple-darwin20 (64-bit)
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 12.2.0
* running under: macOS Monterey 12.7.1
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.8.0’
* 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 ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking R 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 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 ... OK
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
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       51.830  1.996  59.498
corr_plot     50.555  1.919  56.184
FSmethod      50.351  1.884  56.212
pred_ensembel 23.332  0.483  20.109
calculateTC    4.339  0.455   5.152
enrichfindP    0.875  0.098  15.652
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes in ‘inst/doc’ ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 1 NOTE
See
  ‘/Users/biocbuild/bbs-3.18-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.3-x86_64/Resources/library’
* installing *source* package ‘HPiP’ ...
** 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 4.3.3 (2024-02-29) -- "Angel Food Cake"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20 (64-bit)

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 97.195864 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.962736 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.983775 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.061711 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.771225 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 118.517467 
iter  10 value 94.144525
final  value 94.144481 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.603468 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.158138 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.784942 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 122.206982 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.184798 
iter  10 value 94.421972
final  value 94.117498 
converged
Fitting Repeat 2 

# weights:  507
initial  value 94.822183 
iter  10 value 93.199746
iter  20 value 93.011115
iter  30 value 92.999729
final  value 92.999564 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.723901 
iter  10 value 93.964832
iter  20 value 93.776162
iter  30 value 90.985495
iter  40 value 87.119533
iter  50 value 86.446514
iter  60 value 86.312405
iter  70 value 82.593729
final  value 82.593414 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.886394 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.983488 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.913850 
iter  10 value 94.488301
iter  20 value 93.953824
iter  30 value 93.926626
iter  40 value 93.920979
iter  50 value 92.489962
iter  60 value 89.323118
iter  70 value 88.988119
iter  80 value 88.979113
iter  90 value 88.968395
iter 100 value 84.661029
final  value 84.661029 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.059219 
iter  10 value 94.264608
iter  20 value 87.448692
iter  30 value 86.465003
iter  40 value 86.426242
iter  50 value 85.796259
iter  60 value 83.520348
iter  70 value 83.250093
final  value 83.246389 
converged
Fitting Repeat 3 

# weights:  103
initial  value 108.948403 
iter  10 value 94.528911
iter  20 value 94.488025
iter  30 value 94.272577
iter  40 value 91.824803
iter  50 value 91.662308
iter  60 value 89.011826
iter  70 value 84.249094
iter  80 value 82.954676
iter  90 value 81.926118
iter 100 value 81.841968
final  value 81.841968 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 109.007407 
iter  10 value 94.446018
iter  20 value 93.991722
iter  30 value 93.646207
iter  40 value 91.469078
iter  50 value 91.430940
iter  60 value 86.294189
iter  70 value 83.086856
iter  80 value 83.003569
iter  90 value 82.903814
final  value 82.902341 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.949072 
iter  10 value 92.082269
iter  20 value 86.046507
iter  30 value 85.396867
iter  40 value 84.122510
iter  50 value 83.764904
iter  60 value 83.583172
iter  70 value 83.366666
iter  80 value 83.326590
final  value 83.326567 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.078621 
iter  10 value 94.472489
iter  20 value 87.318553
iter  30 value 84.962708
iter  40 value 84.005965
iter  50 value 83.312781
iter  60 value 83.053525
iter  70 value 82.968150
iter  80 value 82.862140
iter  90 value 82.179333
iter 100 value 81.822133
final  value 81.822133 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.063052 
iter  10 value 94.083555
iter  20 value 88.040681
iter  30 value 85.853151
iter  40 value 84.163988
iter  50 value 83.461784
iter  60 value 83.271796
iter  70 value 83.082091
iter  80 value 83.022296
iter  90 value 83.017239
iter 100 value 82.969047
final  value 82.969047 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 113.463035 
iter  10 value 95.120200
iter  20 value 94.626286
iter  30 value 92.665808
iter  40 value 86.915856
iter  50 value 86.598424
iter  60 value 86.353835
iter  70 value 85.911212
iter  80 value 83.927847
iter  90 value 83.175659
iter 100 value 82.474444
final  value 82.474444 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.133402 
iter  10 value 85.507773
iter  20 value 83.512255
iter  30 value 82.777715
iter  40 value 81.670538
iter  50 value 81.229792
iter  60 value 80.846862
iter  70 value 80.634824
iter  80 value 80.551240
iter  90 value 80.546214
iter 100 value 80.543539
final  value 80.543539 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.569529 
iter  10 value 94.007050
iter  20 value 88.450515
iter  30 value 86.614911
iter  40 value 86.006746
iter  50 value 85.322656
iter  60 value 84.526570
iter  70 value 83.303561
iter  80 value 82.709036
iter  90 value 82.635368
iter 100 value 82.613139
final  value 82.613139 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 128.936859 
iter  10 value 94.403738
iter  20 value 89.471250
iter  30 value 84.475277
iter  40 value 83.850601
iter  50 value 83.537869
iter  60 value 83.120503
iter  70 value 82.812030
iter  80 value 82.434930
iter  90 value 81.670494
iter 100 value 81.434234
final  value 81.434234 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.794002 
iter  10 value 94.490817
iter  20 value 94.116735
iter  30 value 87.187358
iter  40 value 85.523347
iter  50 value 85.011025
iter  60 value 81.909260
iter  70 value 81.553870
iter  80 value 81.181145
iter  90 value 81.044464
iter 100 value 80.978415
final  value 80.978415 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.831856 
iter  10 value 94.526252
iter  20 value 91.919502
iter  30 value 83.259932
iter  40 value 81.762898
iter  50 value 81.271671
iter  60 value 80.945263
iter  70 value 80.717341
iter  80 value 80.519412
iter  90 value 80.425102
iter 100 value 80.400677
final  value 80.400677 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.720812 
iter  10 value 95.870878
iter  20 value 85.540179
iter  30 value 84.940938
iter  40 value 84.831748
iter  50 value 84.523599
iter  60 value 82.670431
iter  70 value 82.350509
iter  80 value 81.525269
iter  90 value 80.865162
iter 100 value 80.673121
final  value 80.673121 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 119.914733 
iter  10 value 94.408020
iter  20 value 92.965300
iter  30 value 87.359712
iter  40 value 86.477269
iter  50 value 84.655209
iter  60 value 83.721508
iter  70 value 83.009143
iter  80 value 82.499883
iter  90 value 81.170251
iter 100 value 80.582061
final  value 80.582061 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.768875 
final  value 94.485989 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.927915 
final  value 94.485654 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.685393 
iter  10 value 94.461893
iter  20 value 94.455106
iter  30 value 91.135211
iter  40 value 83.976953
iter  50 value 82.565027
iter  60 value 82.526037
iter  70 value 82.525630
iter  80 value 82.525210
final  value 82.524813 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.963220 
final  value 94.485813 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.319190 
iter  10 value 93.302009
iter  20 value 93.301537
iter  30 value 88.596732
iter  40 value 82.110059
iter  50 value 81.989167
iter  60 value 81.988189
final  value 81.988182 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.481827 
iter  10 value 94.149328
iter  20 value 94.144845
iter  30 value 94.119238
iter  40 value 93.911583
iter  50 value 93.795332
iter  60 value 93.794490
iter  70 value 93.726806
final  value 93.723216 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.094281 
iter  10 value 94.471740
iter  20 value 94.467319
final  value 94.467280 
converged
Fitting Repeat 3 

# weights:  305
initial  value 114.831503 
iter  10 value 94.489213
iter  20 value 94.182179
iter  30 value 94.151919
iter  40 value 86.995514
iter  50 value 84.465639
iter  60 value 84.346642
iter  70 value 84.303683
final  value 84.303273 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.751663 
iter  10 value 88.114996
iter  20 value 82.506662
iter  30 value 82.355991
iter  40 value 82.284197
iter  50 value 82.276254
iter  60 value 82.274691
iter  70 value 82.272332
iter  70 value 82.272332
final  value 82.272332 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.280919 
iter  10 value 94.471868
iter  20 value 94.471115
iter  30 value 94.467000
iter  40 value 91.826717
iter  50 value 84.838218
iter  60 value 84.833746
iter  70 value 84.830664
iter  80 value 83.165485
iter  90 value 82.603945
iter 100 value 81.979361
final  value 81.979361 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 136.777841 
iter  10 value 94.475067
iter  20 value 94.416871
iter  30 value 85.286423
iter  40 value 84.120362
iter  50 value 83.938672
iter  60 value 83.671452
iter  70 value 83.666732
final  value 83.664750 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.950519 
iter  10 value 93.992523
iter  20 value 93.879412
iter  30 value 93.813542
iter  40 value 92.071760
iter  50 value 90.565606
iter  60 value 90.555100
iter  70 value 90.551880
iter  80 value 90.551401
iter  90 value 90.550258
iter 100 value 90.549981
final  value 90.549981 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.245418 
iter  10 value 94.492479
iter  20 value 94.482966
iter  30 value 94.196305
iter  40 value 85.511129
iter  50 value 84.800700
iter  60 value 84.798932
iter  70 value 84.795836
iter  80 value 83.377326
iter  90 value 81.745639
iter 100 value 81.707374
final  value 81.707374 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.557995 
iter  10 value 94.492547
iter  20 value 94.483873
iter  30 value 85.553048
iter  40 value 85.544988
iter  50 value 84.667466
iter  60 value 84.620225
final  value 84.610878 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.734931 
iter  10 value 92.238470
iter  20 value 92.235340
iter  30 value 92.228092
iter  40 value 92.223559
iter  50 value 91.970164
iter  60 value 91.967564
iter  60 value 91.967563
iter  60 value 91.967563
final  value 91.967563 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.762859 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.614796 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.361532 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.326411 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.981722 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.851261 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.992334 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.695869 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 109.791909 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.707982 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.416909 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 124.389183 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.286756 
iter  10 value 92.398876
iter  20 value 92.296314
final  value 92.296071 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.023357 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  507
initial  value 110.945678 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.347585 
iter  10 value 94.483749
iter  20 value 90.886995
iter  30 value 87.973248
iter  40 value 85.792919
iter  50 value 83.633247
iter  60 value 83.418972
iter  70 value 82.891736
iter  80 value 82.726782
iter  90 value 82.213609
iter 100 value 81.921526
final  value 81.921526 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.498890 
iter  10 value 94.487935
iter  20 value 94.327855
iter  30 value 88.209252
iter  40 value 85.256552
iter  50 value 84.955737
iter  60 value 82.583664
iter  70 value 82.277226
iter  80 value 82.273562
final  value 82.270225 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.877837 
iter  10 value 94.486694
iter  20 value 93.519291
iter  30 value 85.926570
iter  40 value 85.111616
iter  50 value 84.936357
iter  60 value 82.633699
iter  70 value 82.545493
iter  80 value 82.405419
iter  90 value 82.017474
iter 100 value 81.933344
final  value 81.933344 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 100.750859 
iter  10 value 94.486478
iter  20 value 89.402975
iter  30 value 85.029916
iter  40 value 84.780490
iter  50 value 84.663497
iter  60 value 84.595689
final  value 84.595337 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.669914 
iter  10 value 93.614051
iter  20 value 85.443333
iter  30 value 84.855308
iter  40 value 84.724597
iter  50 value 84.675279
iter  60 value 84.605605
iter  70 value 84.594647
final  value 84.593355 
converged
Fitting Repeat 1 

# weights:  305
initial  value 122.824968 
iter  10 value 97.423582
iter  20 value 94.521946
iter  30 value 94.514475
iter  40 value 87.263650
iter  50 value 86.813847
iter  60 value 85.963083
iter  70 value 85.413412
iter  80 value 84.015555
iter  90 value 83.802609
iter 100 value 83.734670
final  value 83.734670 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.008449 
iter  10 value 94.265259
iter  20 value 88.793131
iter  30 value 88.296845
iter  40 value 86.409062
iter  50 value 85.506934
iter  60 value 84.484622
iter  70 value 83.746164
iter  80 value 81.610135
iter  90 value 80.727028
iter 100 value 80.433797
final  value 80.433797 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.225021 
iter  10 value 94.589344
iter  20 value 90.735091
iter  30 value 86.717746
iter  40 value 85.723441
iter  50 value 83.952100
iter  60 value 83.471011
iter  70 value 82.957014
iter  80 value 82.076986
iter  90 value 80.944334
iter 100 value 80.408491
final  value 80.408491 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 111.439949 
iter  10 value 92.469770
iter  20 value 85.933094
iter  30 value 84.920917
iter  40 value 84.058404
iter  50 value 83.605265
iter  60 value 83.385213
iter  70 value 82.716625
iter  80 value 81.461551
iter  90 value 80.640083
iter 100 value 80.153844
final  value 80.153844 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.066309 
iter  10 value 94.571556
iter  20 value 87.759014
iter  30 value 87.556765
iter  40 value 85.276716
iter  50 value 85.087358
iter  60 value 83.344946
iter  70 value 82.829457
iter  80 value 82.355845
iter  90 value 82.006249
iter 100 value 81.627152
final  value 81.627152 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 113.985060 
iter  10 value 96.342415
iter  20 value 94.585941
iter  30 value 93.002417
iter  40 value 92.674434
iter  50 value 91.817844
iter  60 value 89.965867
iter  70 value 87.110679
iter  80 value 86.369875
iter  90 value 84.031688
iter 100 value 83.148730
final  value 83.148730 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.557748 
iter  10 value 94.594835
iter  20 value 94.354923
iter  30 value 92.830617
iter  40 value 89.442802
iter  50 value 85.552700
iter  60 value 83.052304
iter  70 value 81.839436
iter  80 value 81.308262
iter  90 value 81.013678
iter 100 value 80.920827
final  value 80.920827 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.037100 
iter  10 value 95.374865
iter  20 value 88.204239
iter  30 value 86.225912
iter  40 value 85.718976
iter  50 value 85.290040
iter  60 value 84.151405
iter  70 value 83.755998
iter  80 value 83.714893
iter  90 value 83.462908
iter 100 value 82.383301
final  value 82.383301 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.075617 
iter  10 value 95.160840
iter  20 value 94.411208
iter  30 value 86.922234
iter  40 value 85.511614
iter  50 value 84.980469
iter  60 value 84.731765
iter  70 value 83.376174
iter  80 value 82.047730
iter  90 value 80.990720
iter 100 value 80.489677
final  value 80.489677 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.187414 
iter  10 value 94.494802
iter  20 value 92.588795
iter  30 value 84.764272
iter  40 value 84.664253
iter  50 value 84.501022
iter  60 value 84.405109
iter  70 value 83.539966
iter  80 value 81.953540
iter  90 value 80.750469
iter 100 value 80.580919
final  value 80.580919 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.180544 
final  value 94.485930 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.807808 
final  value 94.486043 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.862102 
final  value 94.485925 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.757969 
iter  10 value 94.495246
iter  20 value 92.025643
iter  30 value 87.289909
iter  40 value 87.289732
iter  50 value 85.327880
iter  60 value 85.211053
iter  70 value 85.209943
final  value 85.209689 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.586901 
iter  10 value 92.855984
iter  20 value 92.854852
iter  30 value 92.853705
iter  40 value 91.978841
iter  50 value 91.913491
iter  60 value 91.911245
iter  70 value 91.910609
final  value 91.910559 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.772226 
iter  10 value 94.488217
iter  20 value 94.471458
iter  30 value 88.755386
final  value 88.729376 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.154007 
iter  10 value 92.756327
iter  20 value 92.753265
iter  30 value 91.035542
iter  40 value 88.768810
final  value 88.768805 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.269997 
iter  10 value 94.488764
iter  20 value 94.378952
iter  30 value 86.966462
iter  40 value 85.907984
final  value 85.907786 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.123989 
iter  10 value 92.304282
iter  20 value 92.227014
iter  30 value 92.187621
iter  40 value 92.147005
iter  50 value 91.961406
iter  60 value 90.580917
iter  70 value 90.469154
iter  80 value 90.419895
iter  90 value 90.416451
iter 100 value 90.416394
final  value 90.416394 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.385931 
iter  10 value 92.790995
iter  20 value 92.784372
iter  30 value 85.532924
iter  40 value 85.273768
iter  50 value 85.202920
final  value 85.201867 
converged
Fitting Repeat 1 

# weights:  507
initial  value 116.120386 
iter  10 value 94.493458
iter  20 value 94.485304
iter  30 value 93.950037
iter  40 value 87.652365
iter  50 value 83.497503
iter  60 value 83.432417
iter  70 value 83.262438
iter  80 value 82.986939
iter  90 value 82.315044
iter 100 value 78.840812
final  value 78.840812 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 100.353732 
iter  10 value 94.491944
iter  20 value 94.479323
iter  30 value 91.739849
iter  40 value 87.954276
iter  50 value 84.183124
iter  60 value 81.307719
iter  70 value 81.191163
iter  80 value 81.130811
iter  90 value 81.129417
iter  90 value 81.129417
final  value 81.129417 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.396609 
iter  10 value 94.492156
iter  20 value 94.469967
iter  30 value 89.294396
iter  40 value 86.725951
iter  50 value 86.309919
iter  60 value 86.308364
iter  70 value 85.254700
iter  80 value 83.577433
iter  90 value 83.444648
iter 100 value 83.444227
final  value 83.444227 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 101.624594 
iter  10 value 87.740722
iter  20 value 87.659441
iter  30 value 85.691176
iter  40 value 85.681150
iter  50 value 85.680536
iter  60 value 83.848281
iter  70 value 82.448590
iter  80 value 82.103300
iter  90 value 82.103060
iter 100 value 82.102874
final  value 82.102874 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 100.396144 
iter  10 value 94.493370
iter  20 value 94.484134
iter  30 value 91.294881
iter  40 value 82.756696
iter  50 value 79.718222
iter  60 value 79.307366
iter  70 value 79.219715
iter  80 value 79.218863
final  value 79.218738 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.809648 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.847212 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.513310 
iter  10 value 90.093274
iter  20 value 87.446983
iter  30 value 87.275560
iter  40 value 86.875857
iter  50 value 84.616961
final  value 84.609495 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.444782 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.352484 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.292760 
iter  10 value 86.633346
iter  20 value 84.505225
iter  30 value 82.028206
iter  40 value 81.940059
iter  50 value 81.938785
final  value 81.938342 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.932687 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.846559 
iter  10 value 88.022264
final  value 87.553922 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.510618 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 124.394664 
iter  10 value 94.052910
iter  10 value 94.052910
iter  10 value 94.052910
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 110.749883 
iter  10 value 89.699796
iter  20 value 87.391838
iter  30 value 87.388699
final  value 87.388692 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.381501 
final  value 92.945355 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.041486 
iter  10 value 94.053056
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 111.101954 
iter  10 value 92.945376
final  value 92.945355 
converged
Fitting Repeat 5 

# weights:  507
initial  value 119.132810 
final  value 92.945356 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.066593 
iter  10 value 93.361500
iter  20 value 92.552892
iter  30 value 91.108920
iter  40 value 86.624933
iter  50 value 86.363458
iter  60 value 84.014396
iter  70 value 83.498498
final  value 83.495838 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.087437 
iter  10 value 94.051774
iter  20 value 93.237769
iter  30 value 93.230833
iter  40 value 92.809100
iter  50 value 91.619151
iter  60 value 87.775330
iter  70 value 86.867875
iter  80 value 84.139674
iter  90 value 84.050913
iter 100 value 84.011814
final  value 84.011814 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 99.424605 
iter  10 value 94.043131
iter  20 value 93.626101
iter  30 value 93.439455
iter  40 value 93.005239
iter  50 value 92.705764
iter  60 value 89.201854
iter  70 value 87.043807
iter  80 value 86.252679
iter  90 value 82.214600
iter 100 value 81.569560
final  value 81.569560 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 104.728450 
iter  10 value 94.057079
iter  20 value 93.629120
iter  30 value 93.286943
iter  40 value 93.232121
iter  50 value 92.749171
iter  60 value 91.158058
iter  70 value 87.651533
iter  80 value 82.751503
iter  90 value 82.516824
iter 100 value 82.300946
final  value 82.300946 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.689613 
iter  10 value 94.056602
iter  20 value 93.399531
iter  30 value 93.002991
iter  40 value 92.840887
iter  50 value 92.788697
iter  60 value 92.100137
iter  70 value 82.746298
iter  80 value 81.954885
iter  90 value 81.807979
iter 100 value 81.490646
final  value 81.490646 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 102.088154 
iter  10 value 94.073359
iter  20 value 88.924860
iter  30 value 86.456847
iter  40 value 84.296024
iter  50 value 82.219433
iter  60 value 80.421586
iter  70 value 80.298420
iter  80 value 79.994917
iter  90 value 79.476873
iter 100 value 79.116535
final  value 79.116535 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.895096 
iter  10 value 94.103923
iter  20 value 85.699428
iter  30 value 83.949410
iter  40 value 82.927983
iter  50 value 82.200822
iter  60 value 82.120722
iter  70 value 82.102640
iter  80 value 82.086133
iter  90 value 82.058489
iter 100 value 81.662189
final  value 81.662189 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.785692 
iter  10 value 94.130814
iter  20 value 93.281149
iter  30 value 92.524399
iter  40 value 85.954886
iter  50 value 83.365619
iter  60 value 81.496153
iter  70 value 80.430026
iter  80 value 79.362306
iter  90 value 79.151677
iter 100 value 79.123933
final  value 79.123933 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 112.381669 
iter  10 value 94.246417
iter  20 value 90.142067
iter  30 value 83.104621
iter  40 value 82.726820
iter  50 value 82.208997
iter  60 value 80.276889
iter  70 value 79.472762
iter  80 value 79.155901
iter  90 value 79.081031
iter 100 value 79.058352
final  value 79.058352 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.879640 
iter  10 value 93.783753
iter  20 value 87.709711
iter  30 value 85.665602
iter  40 value 84.053339
iter  50 value 82.632993
iter  60 value 81.815126
iter  70 value 80.415989
iter  80 value 79.559011
iter  90 value 79.122922
iter 100 value 78.993560
final  value 78.993560 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.463343 
iter  10 value 94.943792
iter  20 value 93.365133
iter  30 value 88.918817
iter  40 value 86.909235
iter  50 value 85.257918
iter  60 value 81.914818
iter  70 value 79.270353
iter  80 value 78.932069
iter  90 value 78.820406
iter 100 value 78.732455
final  value 78.732455 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 123.606992 
iter  10 value 94.019297
iter  20 value 85.999408
iter  30 value 84.621865
iter  40 value 83.154532
iter  50 value 82.870861
iter  60 value 82.805585
iter  70 value 82.291040
iter  80 value 81.552171
iter  90 value 81.107106
iter 100 value 80.428428
final  value 80.428428 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 115.332079 
iter  10 value 93.200709
iter  20 value 86.806674
iter  30 value 84.754419
iter  40 value 82.750281
iter  50 value 81.543204
iter  60 value 81.156645
iter  70 value 80.727824
iter  80 value 80.486912
iter  90 value 80.374838
iter 100 value 80.216772
final  value 80.216772 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.518945 
iter  10 value 92.987112
iter  20 value 92.763395
iter  30 value 88.688851
iter  40 value 86.747694
iter  50 value 81.686907
iter  60 value 80.268538
iter  70 value 79.325260
iter  80 value 79.059001
iter  90 value 78.720990
iter 100 value 78.635708
final  value 78.635708 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.624787 
iter  10 value 93.223477
iter  20 value 88.745234
iter  30 value 84.226110
iter  40 value 83.402471
iter  50 value 81.323691
iter  60 value 80.148906
iter  70 value 79.861500
iter  80 value 79.698622
iter  90 value 79.617235
iter 100 value 79.356832
final  value 79.356832 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 105.676438 
final  value 94.054519 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.443732 
final  value 94.054626 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.118761 
iter  10 value 94.057706
iter  20 value 94.055500
final  value 94.052913 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.340518 
final  value 94.054525 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.061341 
final  value 94.054626 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.295787 
iter  10 value 92.951301
iter  20 value 92.949299
iter  30 value 91.101869
iter  40 value 84.936004
iter  50 value 83.335775
iter  60 value 81.831956
final  value 81.817713 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.294497 
iter  10 value 94.056772
iter  20 value 93.978763
iter  30 value 92.312918
iter  40 value 92.143578
final  value 92.143518 
converged
Fitting Repeat 3 

# weights:  305
initial  value 120.159623 
iter  10 value 94.057948
iter  20 value 94.022146
iter  30 value 89.294647
iter  40 value 81.182505
iter  50 value 81.058746
iter  60 value 81.029839
iter  70 value 80.664072
iter  80 value 79.937267
iter  90 value 79.542570
iter 100 value 78.311223
final  value 78.311223 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.485029 
iter  10 value 94.057265
iter  20 value 93.353091
iter  30 value 84.240759
iter  40 value 83.983039
iter  50 value 83.713717
final  value 83.713625 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.403743 
iter  10 value 92.950645
iter  20 value 92.948006
iter  30 value 90.743205
iter  40 value 84.308290
iter  50 value 83.274115
final  value 83.274111 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.729674 
iter  10 value 94.056339
iter  20 value 93.793778
final  value 92.564759 
converged
Fitting Repeat 2 

# weights:  507
initial  value 90.849823 
iter  10 value 86.521398
iter  20 value 85.510811
iter  30 value 85.506859
iter  40 value 85.505066
iter  50 value 83.344751
iter  60 value 82.654766
iter  70 value 82.472005
iter  80 value 82.471121
iter  90 value 82.229997
iter 100 value 81.961195
final  value 81.961195 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.217106 
iter  10 value 94.057414
iter  20 value 94.056959
iter  30 value 93.977992
iter  40 value 93.681868
iter  50 value 93.673733
iter  60 value 92.559138
iter  70 value 92.551838
iter  80 value 92.516086
iter  90 value 92.515941
iter 100 value 92.495104
final  value 92.495104 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 98.404028 
iter  10 value 92.953992
iter  20 value 92.952182
iter  30 value 91.896237
iter  40 value 91.631509
iter  50 value 91.629789
iter  60 value 91.629684
iter  70 value 91.629508
iter  80 value 91.432680
iter  90 value 89.632930
iter 100 value 87.315529
final  value 87.315529 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.918699 
iter  10 value 92.953765
iter  20 value 92.950292
iter  30 value 92.504979
iter  40 value 89.993265
iter  50 value 84.809917
iter  60 value 79.536890
iter  70 value 78.697379
iter  80 value 78.668140
iter  90 value 78.603183
iter 100 value 78.270184
final  value 78.270184 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.186394 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.222492 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.154979 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.170980 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.082932 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.256725 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 110.139541 
final  value 94.008696 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.101930 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.197615 
iter  10 value 93.824616
final  value 93.785768 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.735474 
iter  10 value 93.860357
final  value 93.860355 
converged
Fitting Repeat 1 

# weights:  507
initial  value 114.733817 
iter  10 value 86.781147
iter  20 value 85.996611
final  value 85.531862 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.019197 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 112.445909 
final  value 94.008696 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.897095 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.161715 
final  value 94.008696 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.958379 
iter  10 value 93.874027
iter  20 value 87.098081
iter  30 value 86.590342
iter  40 value 85.769802
iter  50 value 85.479538
iter  60 value 84.992701
iter  70 value 84.958339
iter  80 value 84.955379
iter  90 value 84.954536
iter  90 value 84.954535
iter  90 value 84.954535
final  value 84.954535 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.393325 
iter  10 value 93.913235
iter  20 value 88.080300
iter  30 value 87.622075
iter  40 value 87.115553
iter  50 value 86.237868
iter  60 value 85.284132
iter  70 value 84.861470
iter  80 value 84.848156
iter  90 value 84.824821
iter 100 value 84.660583
final  value 84.660583 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 100.279415 
iter  10 value 94.057048
iter  20 value 94.048863
iter  30 value 93.308056
iter  40 value 92.897340
iter  50 value 92.313823
iter  60 value 89.321794
iter  70 value 88.170460
iter  80 value 86.180554
iter  90 value 85.752782
iter 100 value 85.574466
final  value 85.574466 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 101.566360 
iter  10 value 94.056627
iter  20 value 94.002614
iter  30 value 88.441779
iter  40 value 88.150581
iter  50 value 87.741343
iter  60 value 86.820599
iter  70 value 85.315791
iter  80 value 84.610030
iter  90 value 84.569868
iter 100 value 84.565613
final  value 84.565613 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 101.098001 
iter  10 value 94.264961
iter  20 value 94.064554
iter  30 value 94.012096
iter  40 value 93.704653
iter  50 value 93.684848
iter  60 value 89.450003
iter  70 value 84.044216
iter  80 value 83.543810
iter  90 value 83.442181
iter 100 value 82.854372
final  value 82.854372 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 101.997527 
iter  10 value 92.197097
iter  20 value 88.678942
iter  30 value 85.996577
iter  40 value 85.452583
iter  50 value 83.626368
iter  60 value 83.447422
iter  70 value 82.927938
iter  80 value 82.439453
iter  90 value 82.403224
iter 100 value 82.290938
final  value 82.290938 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 119.698083 
iter  10 value 93.776575
iter  20 value 86.283822
iter  30 value 82.695688
iter  40 value 81.584533
iter  50 value 81.151426
iter  60 value 80.919043
iter  70 value 80.624895
iter  80 value 80.592763
iter  90 value 80.590744
iter 100 value 80.572744
final  value 80.572744 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.961508 
iter  10 value 94.727680
iter  20 value 93.881753
iter  30 value 89.267793
iter  40 value 86.381520
iter  50 value 85.519855
iter  60 value 85.244305
iter  70 value 83.775629
iter  80 value 81.887147
iter  90 value 80.733943
iter 100 value 80.469186
final  value 80.469186 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.944637 
iter  10 value 94.393948
iter  20 value 93.724090
iter  30 value 93.654816
iter  40 value 87.976775
iter  50 value 86.023769
iter  60 value 85.199809
iter  70 value 84.702344
iter  80 value 84.683997
iter  90 value 84.646689
iter 100 value 84.614876
final  value 84.614876 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.754202 
iter  10 value 93.989815
iter  20 value 93.691108
iter  30 value 93.455723
iter  40 value 92.674711
iter  50 value 87.760542
iter  60 value 87.094720
iter  70 value 86.335491
iter  80 value 85.655839
iter  90 value 83.823785
iter 100 value 82.756888
final  value 82.756888 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 111.971877 
iter  10 value 94.249711
iter  20 value 88.552741
iter  30 value 85.307944
iter  40 value 84.378606
iter  50 value 82.837828
iter  60 value 81.680267
iter  70 value 80.452825
iter  80 value 80.190750
iter  90 value 80.111935
iter 100 value 80.077710
final  value 80.077710 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 125.827248 
iter  10 value 94.036888
iter  20 value 93.536556
iter  30 value 88.766259
iter  40 value 85.615441
iter  50 value 83.731016
iter  60 value 82.265117
iter  70 value 81.631996
iter  80 value 80.800388
iter  90 value 80.409188
iter 100 value 80.190431
final  value 80.190431 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.278665 
iter  10 value 94.357172
iter  20 value 92.988081
iter  30 value 89.235048
iter  40 value 85.340678
iter  50 value 84.252188
iter  60 value 83.897784
iter  70 value 83.094371
iter  80 value 81.988843
iter  90 value 81.577141
iter 100 value 81.315970
final  value 81.315970 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.986297 
iter  10 value 94.003966
iter  20 value 87.115458
iter  30 value 86.495692
iter  40 value 86.307050
iter  50 value 84.866352
iter  60 value 83.806051
iter  70 value 82.520630
iter  80 value 81.228099
iter  90 value 80.678494
iter 100 value 80.459090
final  value 80.459090 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.493816 
iter  10 value 94.085713
iter  20 value 93.219825
iter  30 value 90.071772
iter  40 value 85.295741
iter  50 value 84.790343
iter  60 value 83.760089
iter  70 value 83.542914
iter  80 value 82.466787
iter  90 value 82.058945
iter 100 value 81.518667
final  value 81.518667 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.231236 
final  value 94.054514 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.188687 
final  value 94.054539 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.843409 
final  value 94.010295 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.172059 
iter  10 value 94.054675
iter  20 value 93.952246
iter  30 value 85.584991
iter  40 value 85.541526
iter  50 value 85.526381
iter  60 value 85.184181
iter  70 value 85.169708
iter  80 value 85.160755
final  value 85.160111 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.627407 
final  value 94.054614 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.260094 
iter  10 value 94.057364
iter  20 value 93.930798
iter  30 value 88.306939
iter  40 value 88.210415
iter  50 value 88.209639
iter  60 value 86.902329
iter  70 value 82.363633
iter  80 value 81.488282
iter  90 value 81.486922
final  value 81.486714 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.536545 
iter  10 value 94.053867
iter  20 value 89.381384
iter  30 value 83.705942
iter  40 value 82.680946
iter  50 value 82.671235
iter  60 value 81.917479
iter  70 value 81.456847
iter  80 value 81.411022
iter  90 value 81.409394
iter 100 value 81.377415
final  value 81.377415 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 119.903967 
iter  10 value 94.024178
iter  20 value 93.877185
iter  30 value 87.683887
iter  40 value 86.061123
iter  50 value 85.895380
iter  60 value 85.888627
iter  70 value 85.875519
iter  80 value 85.874661
iter  90 value 85.722404
iter 100 value 85.658388
final  value 85.658388 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 119.688605 
iter  10 value 94.057732
iter  20 value 93.926280
iter  30 value 88.684726
iter  40 value 86.352153
iter  50 value 85.397210
iter  60 value 85.388490
final  value 85.388457 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.374168 
iter  10 value 94.057791
iter  20 value 94.052915
iter  30 value 93.657701
final  value 93.657606 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.055189 
iter  10 value 93.610815
iter  20 value 93.107519
iter  30 value 92.922345
iter  40 value 88.784986
iter  50 value 84.626766
iter  60 value 84.301087
iter  70 value 84.129639
iter  80 value 84.123386
iter  90 value 84.122096
iter 100 value 84.120215
final  value 84.120215 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 95.391124 
iter  10 value 94.017066
iter  20 value 93.752143
iter  30 value 86.178372
iter  40 value 86.038556
iter  50 value 86.037775
iter  60 value 85.538905
iter  70 value 85.535400
iter  80 value 85.408304
iter  90 value 85.319906
final  value 85.319710 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.065154 
iter  10 value 93.920286
iter  20 value 93.860292
iter  30 value 93.668027
iter  40 value 92.279485
iter  50 value 87.217309
iter  60 value 85.437518
iter  70 value 84.873559
iter  80 value 84.863907
iter  90 value 84.862007
iter 100 value 83.703244
final  value 83.703244 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 101.057722 
iter  10 value 94.016979
iter  20 value 94.009062
final  value 94.008964 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.831121 
iter  10 value 94.016675
iter  20 value 93.685604
iter  30 value 84.098097
iter  40 value 81.846300
iter  50 value 81.341828
iter  60 value 81.248779
iter  70 value 80.721789
iter  80 value 80.197587
iter  90 value 79.573968
iter 100 value 79.471025
final  value 79.471025 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.965379 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.608948 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.800422 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.426440 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.683810 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.554784 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 109.483668 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.928703 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.881847 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.025006 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.255059 
final  value 94.309797 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.763799 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.921000 
iter  10 value 92.616232
iter  20 value 91.859599
final  value 91.825813 
converged
Fitting Repeat 4 

# weights:  507
initial  value 116.306830 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.968774 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.794575 
iter  10 value 94.393220
iter  20 value 91.383622
iter  30 value 91.261289
iter  40 value 89.264214
iter  50 value 84.598577
iter  60 value 84.157867
iter  70 value 83.533745
iter  80 value 82.923576
iter  90 value 82.558945
iter 100 value 82.554931
final  value 82.554931 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.777289 
iter  10 value 94.682989
iter  20 value 94.483270
iter  30 value 92.339884
iter  40 value 90.973349
iter  50 value 88.838997
iter  60 value 87.865963
iter  70 value 86.211287
iter  80 value 83.271030
iter  90 value 82.509092
iter 100 value 82.092287
final  value 82.092287 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.649860 
iter  10 value 94.519366
iter  20 value 92.010974
iter  30 value 89.638654
iter  40 value 89.418326
iter  50 value 85.139126
iter  60 value 84.815589
iter  70 value 84.345368
iter  80 value 83.308661
iter  90 value 83.300705
iter 100 value 82.643472
final  value 82.643472 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 106.506297 
iter  10 value 94.487973
iter  20 value 85.997200
iter  30 value 84.003699
iter  40 value 83.741668
iter  50 value 83.443571
iter  60 value 83.198717
iter  70 value 82.653587
iter  80 value 82.085459
iter  90 value 81.173894
iter 100 value 80.886721
final  value 80.886721 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.498011 
iter  10 value 94.671105
iter  20 value 94.488539
iter  30 value 94.389855
iter  40 value 90.306616
iter  50 value 83.890099
iter  60 value 83.329462
iter  70 value 82.991706
iter  80 value 82.567265
iter  90 value 81.514939
iter 100 value 81.193965
final  value 81.193965 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 111.607563 
iter  10 value 94.617166
iter  20 value 94.190471
iter  30 value 91.457351
iter  40 value 87.370726
iter  50 value 86.555017
iter  60 value 83.897573
iter  70 value 82.819913
iter  80 value 81.928448
iter  90 value 81.631658
iter 100 value 81.138681
final  value 81.138681 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.730561 
iter  10 value 94.511720
iter  20 value 93.784855
iter  30 value 88.102763
iter  40 value 84.041231
iter  50 value 82.458736
iter  60 value 82.098278
iter  70 value 81.836294
iter  80 value 81.386647
iter  90 value 80.378486
iter 100 value 79.819794
final  value 79.819794 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.402981 
iter  10 value 94.478790
iter  20 value 87.994124
iter  30 value 84.866987
iter  40 value 83.263189
iter  50 value 81.303931
iter  60 value 80.792968
iter  70 value 80.009319
iter  80 value 79.656261
iter  90 value 79.416585
iter 100 value 79.260746
final  value 79.260746 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.679528 
iter  10 value 94.117679
iter  20 value 86.828295
iter  30 value 85.416068
iter  40 value 84.316742
iter  50 value 82.991085
iter  60 value 82.325427
iter  70 value 81.544275
iter  80 value 81.094192
iter  90 value 80.972066
iter 100 value 80.960979
final  value 80.960979 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 110.268351 
iter  10 value 94.355814
iter  20 value 87.330370
iter  30 value 84.751098
iter  40 value 84.004660
iter  50 value 81.716990
iter  60 value 80.235647
iter  70 value 79.774737
iter  80 value 79.694147
iter  90 value 79.560243
iter 100 value 79.276964
final  value 79.276964 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 121.188249 
iter  10 value 94.426956
iter  20 value 87.976879
iter  30 value 85.641081
iter  40 value 82.863576
iter  50 value 81.381177
iter  60 value 79.861507
iter  70 value 79.326535
iter  80 value 79.111807
iter  90 value 78.988984
iter 100 value 78.912825
final  value 78.912825 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 119.058898 
iter  10 value 95.200084
iter  20 value 86.414899
iter  30 value 84.503598
iter  40 value 82.456794
iter  50 value 80.959057
iter  60 value 80.103591
iter  70 value 79.338769
iter  80 value 79.048307
iter  90 value 78.946207
iter 100 value 78.921931
final  value 78.921931 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.368281 
iter  10 value 94.489984
iter  20 value 94.336209
iter  30 value 84.511968
iter  40 value 82.415345
iter  50 value 80.556481
iter  60 value 80.318254
iter  70 value 79.629685
iter  80 value 79.501657
iter  90 value 79.349108
iter 100 value 79.245173
final  value 79.245173 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 125.766771 
iter  10 value 95.803545
iter  20 value 86.994505
iter  30 value 85.634957
iter  40 value 82.324177
iter  50 value 81.040076
iter  60 value 80.531619
iter  70 value 80.293890
iter  80 value 80.182577
iter  90 value 79.995550
iter 100 value 79.858542
final  value 79.858542 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 127.527437 
iter  10 value 93.811204
iter  20 value 86.116286
iter  30 value 83.805045
iter  40 value 83.039007
iter  50 value 82.094908
iter  60 value 81.661172
iter  70 value 81.044739
iter  80 value 80.535442
iter  90 value 80.231030
iter 100 value 79.921030
final  value 79.921030 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.240103 
final  value 94.485772 
converged
Fitting Repeat 2 

# weights:  103
initial  value 115.736108 
final  value 94.485829 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.619420 
final  value 94.485749 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.391107 
final  value 94.485866 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.750491 
final  value 94.485853 
converged
Fitting Repeat 1 

# weights:  305
initial  value 128.209025 
iter  10 value 94.489093
iter  20 value 94.484818
iter  30 value 92.153313
iter  40 value 91.924232
iter  50 value 91.865866
iter  60 value 91.865140
final  value 91.865134 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.171354 
iter  10 value 94.433994
iter  20 value 94.431689
iter  30 value 94.428829
final  value 94.426618 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.239954 
iter  10 value 89.339624
iter  20 value 81.181218
iter  30 value 81.054051
iter  40 value 81.053580
iter  50 value 80.960718
iter  60 value 80.870927
iter  70 value 80.850501
iter  80 value 80.850390
iter  90 value 80.849051
iter 100 value 80.847013
final  value 80.847013 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.066955 
iter  10 value 94.489830
iter  20 value 93.738523
iter  30 value 84.431798
iter  40 value 84.399388
iter  50 value 84.398363
iter  60 value 83.396000
iter  70 value 83.120690
iter  80 value 82.405304
iter  90 value 81.622880
iter 100 value 81.085106
final  value 81.085106 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 95.464262 
iter  10 value 94.471597
iter  20 value 94.077710
iter  30 value 85.527317
iter  40 value 81.063258
iter  50 value 81.060569
iter  60 value 81.052619
iter  70 value 81.019346
iter  80 value 81.018468
iter  90 value 81.017561
iter 100 value 80.845402
final  value 80.845402 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 113.368678 
iter  10 value 94.436814
iter  20 value 94.429277
iter  30 value 84.817110
iter  40 value 82.519405
iter  50 value 82.195345
iter  60 value 81.534986
iter  70 value 78.395810
iter  80 value 78.168615
iter  90 value 78.095933
iter 100 value 78.092836
final  value 78.092836 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.270132 
iter  10 value 94.483465
iter  20 value 94.451350
iter  30 value 94.329018
iter  40 value 94.315346
iter  50 value 91.123107
iter  60 value 91.114972
final  value 91.114140 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.399168 
iter  10 value 94.486432
iter  20 value 85.447739
iter  30 value 84.198303
iter  40 value 84.194230
iter  50 value 84.193992
iter  60 value 84.193910
iter  70 value 84.193753
iter  80 value 83.643409
iter  90 value 80.663289
iter 100 value 79.019600
final  value 79.019600 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 97.468642 
iter  10 value 94.343074
iter  20 value 93.907862
iter  30 value 93.903070
iter  40 value 93.832679
iter  50 value 89.929842
final  value 89.682601 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.975099 
iter  10 value 92.160827
iter  20 value 91.110782
iter  30 value 91.106585
iter  40 value 91.104221
iter  50 value 91.101459
iter  60 value 90.728580
iter  70 value 90.675979
iter  80 value 90.658048
iter  90 value 90.579602
iter 100 value 90.466561
final  value 90.466561 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 127.847025 
iter  10 value 118.091374
iter  20 value 117.697296
iter  30 value 109.283254
iter  40 value 104.891696
iter  50 value 103.563212
iter  60 value 103.001296
iter  70 value 102.743700
iter  80 value 102.605599
iter  90 value 102.041565
iter 100 value 101.663928
final  value 101.663928 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 140.488254 
iter  10 value 117.861463
iter  20 value 106.729052
iter  30 value 105.906109
iter  40 value 105.604448
iter  50 value 105.372208
iter  60 value 104.584226
iter  70 value 102.893854
iter  80 value 102.242981
iter  90 value 101.462877
iter 100 value 101.285708
final  value 101.285708 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 147.865938 
iter  10 value 117.925069
iter  20 value 108.849425
iter  30 value 105.401242
iter  40 value 104.725859
iter  50 value 103.143790
iter  60 value 101.849999
iter  70 value 101.482460
iter  80 value 101.185323
iter  90 value 100.837854
iter 100 value 100.707760
final  value 100.707760 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 130.570828 
iter  10 value 118.412201
iter  20 value 117.653256
iter  30 value 114.602895
iter  40 value 109.454815
iter  50 value 107.864515
iter  60 value 107.213245
iter  70 value 106.698229
iter  80 value 104.765126
iter  90 value 103.472572
iter 100 value 102.815060
final  value 102.815060 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 128.945900 
iter  10 value 118.018309
iter  20 value 113.043938
iter  30 value 108.651527
iter  40 value 107.137439
iter  50 value 105.805314
iter  60 value 105.207870
iter  70 value 104.923207
iter  80 value 104.230648
iter  90 value 102.624869
iter 100 value 102.084144
final  value 102.084144 
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 -- Thu Mar 28 04:11:17 2024 
*********************************************** 
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 
 71.380   2.193  78.643