##############################################################################
##############################################################################
###
### 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_1.12.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck’
* using R version 4.4.2 (2024-10-31)
* using platform: x86_64-apple-darwin20
* 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 12.7.6
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.12.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking 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 ... 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       51.817  2.036  58.303
corr_plot     50.901  1.913  54.660
FSmethod      50.564  1.821  53.831
pred_ensembel 24.962  0.446  23.765
calculateTC    4.605  0.439   5.211
enrichfindP    0.899  0.079  15.392
* 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 running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 3 NOTEs
See
  ‘/Users/biocbuild/bbs-3.20-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/4.4-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 4.4.2 (2024-10-31) -- "Pile of Leaves"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20

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 94.619586 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.293076 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.629497 
iter  10 value 94.837972
iter  20 value 92.382284
iter  30 value 92.358052
final  value 92.358027 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.291363 
final  value 94.052911 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.433915 
iter  10 value 94.015368
final  value 94.015114 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.873133 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 132.817248 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.164304 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.552930 
iter  10 value 91.793244
iter  20 value 85.048562
final  value 85.046865 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.976861 
iter  10 value 93.755673
iter  20 value 87.056633
iter  30 value 82.913431
iter  40 value 82.863089
iter  50 value 82.862404
iter  50 value 82.862404
iter  50 value 82.862404
final  value 82.862404 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.978976 
iter  10 value 93.735833
final  value 93.735800 
converged
Fitting Repeat 2 

# weights:  507
initial  value 120.240853 
iter  10 value 93.494554
iter  20 value 82.911315
iter  30 value 82.904446
final  value 82.904404 
converged
Fitting Repeat 3 

# weights:  507
initial  value 112.898323 
iter  10 value 93.925754
iter  20 value 88.317396
iter  30 value 86.837513
iter  40 value 85.665292
final  value 85.629610 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.288100 
iter  10 value 93.563109
final  value 93.501545 
converged
Fitting Repeat 5 

# weights:  507
initial  value 118.799655 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.667466 
iter  10 value 94.057325
iter  20 value 89.714425
iter  30 value 86.147819
iter  40 value 85.477202
iter  50 value 84.632884
final  value 84.575622 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.959652 
iter  10 value 94.058878
iter  20 value 93.469229
iter  30 value 86.077030
iter  40 value 85.339719
iter  50 value 84.508139
iter  60 value 84.103425
final  value 84.101247 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.732531 
iter  10 value 94.056816
iter  20 value 94.021037
iter  30 value 93.806757
iter  40 value 93.795732
iter  50 value 93.789275
iter  60 value 87.816386
iter  70 value 85.706508
iter  80 value 85.375574
iter  90 value 85.156628
iter 100 value 84.922601
final  value 84.922601 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 98.496318 
iter  10 value 93.995196
iter  20 value 84.569381
iter  30 value 83.147491
iter  40 value 82.962805
iter  50 value 82.201482
iter  60 value 81.952000
iter  70 value 81.859373
iter  80 value 81.680913
iter  90 value 81.564450
iter 100 value 81.502197
final  value 81.502197 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 102.726466 
iter  10 value 93.124203
iter  20 value 86.009427
iter  30 value 85.786903
iter  40 value 85.588672
iter  50 value 85.316177
iter  60 value 84.830196
iter  70 value 84.670418
iter  80 value 84.646024
iter  90 value 84.633715
final  value 84.630435 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.222616 
iter  10 value 96.154697
iter  20 value 94.059310
iter  30 value 93.314660
iter  40 value 86.871908
iter  50 value 83.477952
iter  60 value 82.864952
iter  70 value 82.484328
iter  80 value 81.865305
iter  90 value 81.721049
iter 100 value 81.599146
final  value 81.599146 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 114.062002 
iter  10 value 94.112711
iter  20 value 93.993579
iter  30 value 86.534633
iter  40 value 84.806748
iter  50 value 83.308592
iter  60 value 82.578214
iter  70 value 82.431647
iter  80 value 82.366234
iter  90 value 81.656008
iter 100 value 80.810072
final  value 80.810072 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 135.253794 
iter  10 value 94.104314
iter  20 value 90.757840
iter  30 value 88.999448
iter  40 value 86.589948
iter  50 value 84.713679
iter  60 value 83.513241
iter  70 value 83.074833
iter  80 value 82.506559
iter  90 value 80.731463
iter 100 value 80.590494
final  value 80.590494 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.324379 
iter  10 value 94.130146
iter  20 value 94.042240
iter  30 value 89.645334
iter  40 value 89.090827
iter  50 value 85.361833
iter  60 value 82.297771
iter  70 value 81.206817
iter  80 value 81.078024
iter  90 value 80.958449
iter 100 value 80.926746
final  value 80.926746 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.713848 
iter  10 value 94.211835
iter  20 value 90.277618
iter  30 value 89.925429
iter  40 value 88.924034
iter  50 value 86.749111
iter  60 value 85.915255
iter  70 value 84.123429
iter  80 value 82.321399
iter  90 value 80.701051
iter 100 value 80.576098
final  value 80.576098 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.221844 
iter  10 value 93.758528
iter  20 value 85.621336
iter  30 value 85.076966
iter  40 value 84.354491
iter  50 value 83.605834
iter  60 value 83.057541
iter  70 value 82.822754
iter  80 value 82.091937
iter  90 value 82.018315
iter 100 value 81.816360
final  value 81.816360 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.797124 
iter  10 value 94.410541
iter  20 value 92.713726
iter  30 value 87.576315
iter  40 value 84.271503
iter  50 value 82.367190
iter  60 value 81.837166
iter  70 value 81.051569
iter  80 value 80.567604
iter  90 value 80.385622
iter 100 value 80.145103
final  value 80.145103 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.905453 
iter  10 value 93.899826
iter  20 value 85.542634
iter  30 value 83.538449
iter  40 value 83.276847
iter  50 value 83.131428
iter  60 value 83.013849
iter  70 value 82.967091
iter  80 value 82.462364
iter  90 value 81.864965
iter 100 value 81.281307
final  value 81.281307 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.088828 
iter  10 value 95.768545
iter  20 value 90.112400
iter  30 value 84.976371
iter  40 value 84.511787
iter  50 value 83.638148
iter  60 value 81.629255
iter  70 value 80.937814
iter  80 value 80.655009
iter  90 value 80.460015
iter 100 value 80.285348
final  value 80.285348 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.671481 
iter  10 value 94.042146
iter  20 value 84.227904
iter  30 value 83.237351
iter  40 value 82.826328
iter  50 value 81.742630
iter  60 value 81.403539
iter  70 value 80.779702
iter  80 value 80.586033
iter  90 value 80.398603
iter 100 value 80.272149
final  value 80.272149 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.733459 
final  value 94.054498 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.300187 
final  value 94.054454 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.344963 
final  value 94.034522 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.127349 
final  value 94.054489 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.585380 
final  value 94.054586 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.019922 
iter  10 value 94.037732
iter  20 value 93.768270
iter  30 value 90.990111
iter  40 value 85.220326
iter  50 value 84.766130
iter  60 value 82.959481
iter  70 value 82.826096
iter  80 value 82.825619
final  value 82.825139 
converged
Fitting Repeat 2 

# weights:  305
initial  value 109.908232 
iter  10 value 94.057728
iter  20 value 94.048040
iter  30 value 88.352136
iter  40 value 87.065584
iter  50 value 87.060845
iter  60 value 85.753726
final  value 85.644432 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.171330 
iter  10 value 94.057815
iter  20 value 92.466951
iter  30 value 85.598296
iter  40 value 85.502014
iter  50 value 85.501746
iter  50 value 85.501745
iter  50 value 85.501745
final  value 85.501745 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.572864 
iter  10 value 94.037344
iter  20 value 91.590405
iter  30 value 89.919441
iter  40 value 85.120076
iter  50 value 84.782734
iter  60 value 84.782221
final  value 84.782166 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.099494 
iter  10 value 94.057561
iter  20 value 94.032151
iter  30 value 86.346128
iter  40 value 83.510754
iter  50 value 82.816304
final  value 82.815190 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.280672 
iter  10 value 94.061803
iter  20 value 94.042814
iter  30 value 93.849834
iter  40 value 93.691937
final  value 93.691814 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.109906 
iter  10 value 93.827191
iter  20 value 93.819305
iter  30 value 93.782944
final  value 93.782903 
converged
Fitting Repeat 3 

# weights:  507
initial  value 120.796406 
iter  10 value 94.041201
iter  20 value 94.033025
iter  30 value 85.753962
iter  40 value 85.608208
final  value 85.608190 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.334474 
iter  10 value 94.041339
iter  20 value 94.032672
iter  30 value 87.884063
iter  40 value 87.579239
iter  50 value 86.734052
iter  60 value 86.298421
iter  70 value 86.295308
iter  70 value 86.295308
final  value 86.295308 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.470794 
iter  10 value 85.457834
iter  20 value 85.445845
iter  30 value 85.253310
iter  40 value 83.782110
iter  50 value 83.696682
iter  60 value 83.691674
iter  70 value 82.887009
iter  80 value 82.793642
iter  90 value 82.793162
iter 100 value 82.793049
final  value 82.793049 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.833279 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.303759 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.595902 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.415263 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.544778 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.393458 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.592344 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.874953 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.683072 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.763362 
iter  10 value 93.893191
final  value 93.888891 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.571960 
iter  10 value 93.336718
iter  20 value 91.107614
iter  30 value 91.082954
iter  40 value 89.608239
iter  50 value 89.475767
iter  50 value 89.475767
iter  50 value 89.475767
final  value 89.475767 
converged
Fitting Repeat 2 

# weights:  507
initial  value 117.788051 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 117.749249 
iter  10 value 91.147136
iter  20 value 91.050890
final  value 91.050726 
converged
Fitting Repeat 4 

# weights:  507
initial  value 121.380285 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.879197 
iter  10 value 94.476471
iter  10 value 94.476471
iter  10 value 94.476471
final  value 94.476471 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.369276 
iter  10 value 94.350796
iter  20 value 93.358826
iter  30 value 91.398935
iter  40 value 84.939994
iter  50 value 81.882170
iter  60 value 81.782547
iter  70 value 81.511152
iter  80 value 81.265162
iter  90 value 81.260573
final  value 81.260549 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.222614 
iter  10 value 94.301012
iter  20 value 85.453535
iter  30 value 84.300101
iter  40 value 83.947171
iter  50 value 81.975785
iter  60 value 81.298717
iter  70 value 81.262130
iter  80 value 81.260800
iter  90 value 81.260550
iter  90 value 81.260549
iter  90 value 81.260549
final  value 81.260549 
converged
Fitting Repeat 3 

# weights:  103
initial  value 120.600944 
iter  10 value 94.329198
iter  20 value 89.137454
iter  30 value 85.002571
iter  40 value 81.880899
iter  50 value 81.343014
iter  60 value 81.276189
iter  70 value 81.260972
final  value 81.260549 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.335613 
iter  10 value 94.263902
iter  20 value 85.691687
iter  30 value 81.835306
iter  40 value 81.747012
iter  50 value 81.303966
iter  60 value 81.260666
final  value 81.260549 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.494134 
iter  10 value 94.488598
iter  20 value 94.462409
iter  30 value 94.164603
iter  40 value 90.553811
iter  50 value 81.627145
iter  60 value 79.717770
iter  70 value 79.356307
iter  80 value 78.906416
iter  90 value 78.776358
iter 100 value 78.707360
final  value 78.707360 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 102.429307 
iter  10 value 94.815444
iter  20 value 93.871984
iter  30 value 92.850777
iter  40 value 92.748792
iter  50 value 88.271685
iter  60 value 84.958360
iter  70 value 83.228154
iter  80 value 79.765315
iter  90 value 79.237546
iter 100 value 78.510456
final  value 78.510456 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 114.021303 
iter  10 value 94.565245
iter  20 value 91.899099
iter  30 value 89.425236
iter  40 value 84.710315
iter  50 value 81.327138
iter  60 value 79.582197
iter  70 value 78.773748
iter  80 value 78.274765
iter  90 value 77.918098
iter 100 value 77.830602
final  value 77.830602 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.602731 
iter  10 value 94.258902
iter  20 value 86.900327
iter  30 value 85.144980
iter  40 value 82.515958
iter  50 value 81.567949
iter  60 value 81.062693
iter  70 value 80.371362
iter  80 value 79.029439
iter  90 value 78.062752
iter 100 value 77.640764
final  value 77.640764 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.238221 
iter  10 value 94.492113
iter  20 value 91.639723
iter  30 value 84.535754
iter  40 value 81.542906
iter  50 value 81.473400
iter  60 value 80.836553
iter  70 value 78.942003
iter  80 value 78.181151
iter  90 value 77.403649
iter 100 value 77.025829
final  value 77.025829 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 112.208135 
iter  10 value 94.689745
iter  20 value 86.970127
iter  30 value 84.731056
iter  40 value 84.487315
iter  50 value 81.374532
iter  60 value 80.256913
iter  70 value 79.726891
iter  80 value 79.410399
iter  90 value 78.739243
iter 100 value 78.404426
final  value 78.404426 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 123.625735 
iter  10 value 96.258429
iter  20 value 95.278080
iter  30 value 92.160524
iter  40 value 91.432265
iter  50 value 81.676129
iter  60 value 80.219181
iter  70 value 78.832402
iter  80 value 78.513790
iter  90 value 77.541824
iter 100 value 77.390310
final  value 77.390310 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.693370 
iter  10 value 94.241512
iter  20 value 94.024906
iter  30 value 92.227931
iter  40 value 81.875998
iter  50 value 79.773283
iter  60 value 78.894799
iter  70 value 78.440269
iter  80 value 77.998549
iter  90 value 77.612590
iter 100 value 77.257079
final  value 77.257079 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.863868 
iter  10 value 94.568160
iter  20 value 93.185173
iter  30 value 83.928272
iter  40 value 83.611715
iter  50 value 81.579007
iter  60 value 79.350711
iter  70 value 79.027220
iter  80 value 78.884545
iter  90 value 78.805310
iter 100 value 78.235531
final  value 78.235531 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.901197 
iter  10 value 94.350586
iter  20 value 91.486665
iter  30 value 86.101262
iter  40 value 85.109655
iter  50 value 82.754788
iter  60 value 81.891430
iter  70 value 80.793644
iter  80 value 79.061699
iter  90 value 78.557361
iter 100 value 77.884142
final  value 77.884142 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.818847 
iter  10 value 94.235961
iter  20 value 87.611759
iter  30 value 83.465308
iter  40 value 82.861034
iter  50 value 81.758265
iter  60 value 81.148221
iter  70 value 80.728145
iter  80 value 79.201326
iter  90 value 77.890346
iter 100 value 77.067725
final  value 77.067725 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.850314 
final  value 94.485808 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.795127 
final  value 94.485777 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.567518 
final  value 94.485481 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.252324 
final  value 94.486223 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.182289 
final  value 94.485860 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.791451 
iter  10 value 93.927256
iter  20 value 93.926609
iter  30 value 93.920325
iter  40 value 91.948414
iter  50 value 91.734260
final  value 91.733926 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.822465 
iter  10 value 94.489135
iter  20 value 94.484240
final  value 94.484208 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.643485 
iter  10 value 94.489069
iter  20 value 94.445049
iter  30 value 85.613403
iter  40 value 80.961514
iter  50 value 78.177703
iter  60 value 76.837957
iter  70 value 76.694165
iter  80 value 76.693196
iter  90 value 76.693026
final  value 76.692563 
converged
Fitting Repeat 4 

# weights:  305
initial  value 114.269045 
iter  10 value 94.280152
iter  20 value 93.474893
iter  30 value 80.597635
iter  40 value 80.148481
iter  50 value 80.140282
iter  60 value 80.139267
iter  70 value 79.858515
iter  80 value 79.825539
iter  90 value 79.825023
final  value 79.824974 
converged
Fitting Repeat 5 

# weights:  305
initial  value 118.235883 
iter  10 value 94.489392
iter  20 value 94.386467
iter  30 value 93.235483
iter  40 value 93.211378
final  value 93.211259 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.271158 
iter  10 value 93.616397
iter  20 value 93.614383
iter  30 value 93.545521
iter  40 value 93.535662
iter  50 value 93.534924
iter  60 value 93.533648
iter  70 value 92.604568
iter  80 value 90.760239
iter  90 value 84.238739
iter 100 value 80.184013
final  value 80.184013 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 100.558634 
iter  10 value 94.491404
iter  20 value 94.279047
iter  30 value 92.445407
iter  40 value 92.345095
iter  50 value 92.344780
iter  60 value 90.527843
iter  70 value 89.003971
iter  80 value 86.660057
iter  90 value 81.726872
iter 100 value 77.571311
final  value 77.571311 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 96.401290 
iter  10 value 94.105003
iter  20 value 94.060275
iter  30 value 93.500927
iter  40 value 84.661212
iter  50 value 79.142063
iter  60 value 76.015074
iter  70 value 75.954241
iter  80 value 75.945191
iter  90 value 75.662786
iter 100 value 75.550288
final  value 75.550288 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.867853 
iter  10 value 93.788612
iter  20 value 93.786634
iter  30 value 93.785026
iter  40 value 93.765721
iter  50 value 93.721758
iter  60 value 92.027810
iter  70 value 91.989920
final  value 91.989844 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.655137 
iter  10 value 91.495906
iter  20 value 90.029522
iter  30 value 89.394796
iter  40 value 88.623302
iter  50 value 88.619104
final  value 88.613944 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.366748 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.344078 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.515391 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.289217 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 109.287149 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.878449 
iter  10 value 92.936829
iter  20 value 92.933350
final  value 92.933334 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.994112 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.083315 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.063563 
iter  10 value 93.673014
final  value 93.672974 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.562890 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.902086 
iter  10 value 94.046531
iter  20 value 94.044448
final  value 94.044445 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.988840 
iter  10 value 92.134908
iter  20 value 92.134734
final  value 92.134731 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.226059 
iter  10 value 91.646136
final  value 91.644444 
converged
Fitting Repeat 4 

# weights:  507
initial  value 108.403749 
iter  10 value 90.981663
iter  20 value 83.397877
iter  30 value 82.029609
final  value 81.846670 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.040452 
final  value 93.868966 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.187329 
iter  10 value 94.070065
iter  20 value 94.053225
iter  30 value 93.158442
iter  40 value 85.141348
iter  50 value 84.242086
iter  60 value 83.893925
iter  70 value 83.341181
iter  80 value 82.839583
iter  90 value 81.427943
final  value 81.359669 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.164118 
iter  10 value 94.185111
iter  20 value 94.056182
iter  30 value 93.236238
iter  40 value 93.159277
iter  50 value 93.143624
iter  60 value 93.143400
iter  70 value 93.124738
iter  80 value 93.124322
iter  90 value 89.096806
iter 100 value 86.778239
final  value 86.778239 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 105.287274 
iter  10 value 93.989627
iter  20 value 91.441881
iter  30 value 88.812224
iter  40 value 86.318630
iter  50 value 85.805099
iter  60 value 85.160529
iter  70 value 84.200564
iter  80 value 83.017685
iter  90 value 82.372446
iter 100 value 81.626222
final  value 81.626222 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 98.218314 
iter  10 value 94.050839
iter  20 value 87.229271
iter  30 value 86.690465
iter  40 value 83.558334
iter  50 value 83.053174
iter  60 value 81.805089
iter  70 value 81.187525
iter  80 value 81.180298
final  value 81.180100 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.719106 
iter  10 value 94.058610
iter  20 value 93.959272
iter  30 value 93.804002
iter  40 value 93.799192
iter  50 value 86.361938
iter  60 value 85.876107
iter  70 value 85.498985
iter  80 value 84.153443
iter  90 value 83.725979
iter 100 value 83.238355
final  value 83.238355 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 101.671001 
iter  10 value 93.763071
iter  20 value 88.549497
iter  30 value 87.545351
iter  40 value 84.142731
iter  50 value 81.700216
iter  60 value 80.760956
iter  70 value 80.573287
iter  80 value 80.392835
iter  90 value 80.292743
iter 100 value 80.227893
final  value 80.227893 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.727089 
iter  10 value 94.036591
iter  20 value 93.842212
iter  30 value 92.439381
iter  40 value 86.430333
iter  50 value 85.862672
iter  60 value 83.432330
iter  70 value 81.915382
iter  80 value 81.093379
iter  90 value 80.640638
iter 100 value 80.414874
final  value 80.414874 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.970014 
iter  10 value 94.076230
iter  20 value 88.254382
iter  30 value 86.896628
iter  40 value 85.639550
iter  50 value 84.427053
iter  60 value 81.342025
iter  70 value 80.991945
iter  80 value 80.673037
iter  90 value 80.590591
iter 100 value 80.435341
final  value 80.435341 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.893046 
iter  10 value 88.384168
iter  20 value 84.891544
iter  30 value 84.429727
iter  40 value 83.236049
iter  50 value 82.364951
iter  60 value 81.993814
iter  70 value 81.225965
iter  80 value 80.341502
iter  90 value 79.969674
iter 100 value 79.783397
final  value 79.783397 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.255720 
iter  10 value 94.019916
iter  20 value 90.022806
iter  30 value 89.133855
iter  40 value 88.741729
iter  50 value 87.806425
iter  60 value 84.381199
iter  70 value 82.492904
iter  80 value 80.574891
iter  90 value 79.935156
iter 100 value 79.886075
final  value 79.886075 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 111.649044 
iter  10 value 95.067920
iter  20 value 93.734103
iter  30 value 87.699695
iter  40 value 83.734654
iter  50 value 83.122367
iter  60 value 81.888353
iter  70 value 81.519515
iter  80 value 80.874286
iter  90 value 80.578217
iter 100 value 80.221837
final  value 80.221837 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.499464 
iter  10 value 94.000906
iter  20 value 91.420305
iter  30 value 87.005616
iter  40 value 84.061251
iter  50 value 81.576093
iter  60 value 80.720299
iter  70 value 80.539073
iter  80 value 80.330622
iter  90 value 80.296313
iter 100 value 80.164853
final  value 80.164853 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 151.863121 
iter  10 value 105.221824
iter  20 value 101.858959
iter  30 value 95.270934
iter  40 value 93.795913
iter  50 value 86.659416
iter  60 value 84.542592
iter  70 value 82.876588
iter  80 value 81.778606
iter  90 value 81.254356
iter 100 value 81.061226
final  value 81.061226 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.525824 
iter  10 value 94.133383
iter  20 value 92.220284
iter  30 value 88.708759
iter  40 value 84.730024
iter  50 value 83.364718
iter  60 value 83.300247
iter  70 value 82.819666
iter  80 value 82.478534
iter  90 value 81.979239
iter 100 value 81.901400
final  value 81.901400 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 120.357554 
iter  10 value 95.061287
iter  20 value 87.484496
iter  30 value 85.029686
iter  40 value 83.796825
iter  50 value 83.435258
iter  60 value 82.740794
iter  70 value 82.482661
iter  80 value 82.433828
iter  90 value 82.222352
iter 100 value 81.033820
final  value 81.033820 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.304975 
iter  10 value 94.072179
iter  20 value 94.065618
iter  30 value 91.825982
iter  40 value 85.389727
iter  50 value 82.833280
iter  60 value 82.518982
iter  70 value 82.478956
iter  80 value 82.474155
iter  90 value 82.389919
iter 100 value 82.275436
final  value 82.275436 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.548432 
iter  10 value 93.675171
iter  20 value 93.674675
iter  30 value 93.673239
iter  40 value 93.276913
iter  50 value 85.627182
iter  60 value 84.116756
iter  70 value 83.770691
iter  80 value 83.769874
final  value 83.769823 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.070990 
final  value 94.054565 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.168518 
final  value 94.054579 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.563977 
final  value 94.054397 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.712703 
iter  10 value 93.663131
iter  20 value 93.206463
iter  30 value 87.057893
iter  40 value 84.250665
final  value 84.238453 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.082991 
iter  10 value 93.746808
iter  20 value 93.584013
iter  30 value 93.170203
iter  40 value 92.936848
iter  50 value 92.935280
iter  60 value 92.534676
iter  70 value 92.510610
iter  80 value 92.509772
iter  90 value 92.509623
iter 100 value 91.888678
final  value 91.888678 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 98.106164 
iter  10 value 93.677447
iter  20 value 93.100538
iter  30 value 92.894419
iter  40 value 89.545978
iter  50 value 85.785474
iter  60 value 83.144572
iter  70 value 83.127989
iter  80 value 83.091601
iter  90 value 82.464986
iter 100 value 82.449775
final  value 82.449775 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.026298 
iter  10 value 93.678675
iter  20 value 93.675050
iter  30 value 93.506597
iter  40 value 92.955339
iter  50 value 92.925613
iter  60 value 90.880682
iter  70 value 90.875978
iter  80 value 90.510331
iter  90 value 90.298260
iter 100 value 90.263701
final  value 90.263701 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 117.834711 
iter  10 value 94.084662
iter  20 value 94.068116
iter  30 value 92.959398
iter  40 value 92.943222
iter  50 value 92.458678
iter  60 value 86.147992
iter  70 value 84.233127
iter  80 value 84.182426
iter  90 value 84.182149
iter 100 value 84.179775
final  value 84.179775 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.518268 
iter  10 value 93.681584
iter  20 value 93.675268
iter  30 value 93.476846
iter  40 value 92.934460
iter  50 value 92.933986
iter  60 value 92.579077
iter  70 value 91.304676
final  value 91.304670 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.655009 
iter  10 value 94.040753
iter  20 value 94.040146
iter  30 value 94.035878
iter  40 value 91.820952
iter  50 value 91.592080
iter  60 value 91.196129
iter  70 value 91.080198
iter  80 value 91.074800
iter  90 value 90.034340
iter 100 value 85.066690
final  value 85.066690 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 135.388449 
iter  10 value 94.060473
iter  20 value 93.899409
final  value 92.934687 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.341674 
iter  10 value 94.057313
iter  20 value 93.881420
iter  30 value 85.821706
iter  40 value 84.876084
iter  50 value 84.747815
iter  60 value 84.675565
iter  70 value 83.331310
iter  80 value 79.731966
iter  90 value 78.875338
iter 100 value 78.808628
final  value 78.808628 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 102.332175 
iter  10 value 94.057855
iter  20 value 93.979473
iter  30 value 93.629906
iter  40 value 93.464689
iter  50 value 85.843292
iter  60 value 83.045862
iter  70 value 82.215519
iter  80 value 81.488864
final  value 81.306386 
converged
Fitting Repeat 1 

# weights:  103
initial  value 111.768996 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.652127 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.204398 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.824511 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 111.810940 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.597194 
iter  10 value 93.681191
iter  20 value 88.930016
iter  30 value 86.251108
iter  40 value 85.787170
iter  50 value 85.783567
final  value 85.783533 
converged
Fitting Repeat 2 

# weights:  305
initial  value 114.246138 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 112.984669 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 120.003426 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.758105 
final  value 94.466821 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.891747 
iter  10 value 92.976875
iter  20 value 92.750894
iter  30 value 92.603577
final  value 92.602314 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.536199 
iter  10 value 94.484143
final  value 94.484137 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.852197 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.241449 
final  value 94.484210 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.723374 
iter  10 value 92.907001
iter  20 value 92.874557
iter  20 value 92.874557
final  value 92.874557 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.479671 
iter  10 value 94.490097
iter  20 value 94.416898
iter  30 value 87.289645
iter  40 value 86.806221
iter  50 value 85.875214
iter  60 value 85.125733
iter  70 value 85.014459
iter  80 value 84.890826
iter  90 value 84.797678
iter 100 value 84.791672
final  value 84.791672 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.620049 
iter  10 value 94.486405
iter  20 value 87.341525
iter  30 value 86.605584
iter  40 value 86.201753
iter  50 value 85.936132
iter  60 value 85.803521
iter  70 value 85.728295
final  value 85.728279 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.398263 
iter  10 value 94.488749
iter  20 value 94.486627
iter  30 value 92.345505
iter  40 value 88.971248
iter  50 value 86.750168
iter  60 value 84.441986
iter  70 value 84.145485
iter  80 value 83.849030
iter  90 value 83.259135
iter 100 value 82.848606
final  value 82.848606 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.799885 
iter  10 value 93.580157
iter  20 value 92.257785
iter  30 value 87.000618
iter  40 value 86.760750
iter  50 value 85.730641
iter  60 value 85.455437
iter  70 value 85.440327
iter  80 value 85.186565
iter  90 value 84.911741
iter 100 value 84.849032
final  value 84.849032 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.846596 
iter  10 value 94.520811
iter  20 value 94.482928
iter  30 value 91.296641
iter  40 value 90.712938
iter  50 value 90.469359
iter  60 value 90.239604
iter  70 value 90.184329
iter  80 value 90.168265
final  value 90.167284 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.935809 
iter  10 value 93.062075
iter  20 value 86.446849
iter  30 value 85.641978
iter  40 value 85.104964
iter  50 value 83.312475
iter  60 value 83.050140
iter  70 value 82.841320
iter  80 value 82.740265
iter  90 value 82.720858
iter 100 value 82.701526
final  value 82.701526 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.585227 
iter  10 value 94.537409
iter  20 value 91.004036
iter  30 value 90.104249
iter  40 value 87.786458
iter  50 value 84.855295
iter  60 value 83.166547
iter  70 value 82.899032
iter  80 value 82.315256
iter  90 value 82.163237
iter 100 value 82.027405
final  value 82.027405 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.864424 
iter  10 value 94.500940
iter  20 value 90.268814
iter  30 value 89.679191
iter  40 value 89.532090
iter  50 value 85.225273
iter  60 value 84.874230
iter  70 value 84.425745
iter  80 value 82.853102
iter  90 value 81.747891
iter 100 value 81.564331
final  value 81.564331 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.232057 
iter  10 value 94.298655
iter  20 value 91.168852
iter  30 value 88.082743
iter  40 value 85.278532
iter  50 value 84.217944
iter  60 value 84.092352
iter  70 value 83.979474
iter  80 value 83.955227
iter  90 value 83.802314
iter 100 value 83.466847
final  value 83.466847 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.652978 
iter  10 value 94.528646
iter  20 value 87.445547
iter  30 value 86.060758
iter  40 value 85.760299
iter  50 value 85.219559
iter  60 value 84.908439
iter  70 value 82.869975
iter  80 value 82.686851
iter  90 value 82.117580
iter 100 value 81.717457
final  value 81.717457 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.225128 
iter  10 value 94.630916
iter  20 value 89.260535
iter  30 value 86.557797
iter  40 value 86.112943
iter  50 value 85.892347
iter  60 value 85.434966
iter  70 value 84.759716
iter  80 value 83.529725
iter  90 value 82.301784
iter 100 value 82.026507
final  value 82.026507 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 110.447350 
iter  10 value 94.590813
iter  20 value 92.680133
iter  30 value 88.993414
iter  40 value 86.038973
iter  50 value 85.305001
iter  60 value 84.987719
iter  70 value 84.055155
iter  80 value 83.133279
iter  90 value 82.897767
iter 100 value 82.729028
final  value 82.729028 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 117.837854 
iter  10 value 95.009670
iter  20 value 94.131763
iter  30 value 86.962364
iter  40 value 86.063014
iter  50 value 85.307285
iter  60 value 85.191341
iter  70 value 85.116118
iter  80 value 84.876653
iter  90 value 82.993765
iter 100 value 82.087362
final  value 82.087362 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 117.754690 
iter  10 value 95.225305
iter  20 value 91.835489
iter  30 value 90.376288
iter  40 value 86.686415
iter  50 value 83.405067
iter  60 value 83.151039
iter  70 value 83.024447
iter  80 value 82.471118
iter  90 value 81.956412
iter 100 value 81.800266
final  value 81.800266 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 115.636892 
iter  10 value 94.649398
iter  20 value 94.117357
iter  30 value 90.968893
iter  40 value 90.565642
iter  50 value 89.390014
iter  60 value 87.663156
iter  70 value 87.277492
iter  80 value 85.030875
iter  90 value 84.538035
iter 100 value 84.440836
final  value 84.440836 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.890126 
final  value 94.485753 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.203436 
final  value 94.485766 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.721729 
final  value 94.486041 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.616945 
final  value 94.468521 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.860889 
final  value 94.485882 
converged
Fitting Repeat 1 

# weights:  305
initial  value 114.811982 
iter  10 value 94.489014
iter  20 value 94.473107
iter  30 value 90.513351
iter  40 value 89.970054
iter  50 value 89.888620
iter  60 value 89.887016
final  value 89.887008 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.099395 
iter  10 value 94.489247
iter  20 value 94.433415
iter  30 value 89.696767
iter  40 value 89.647168
iter  50 value 89.457122
iter  60 value 89.163891
iter  70 value 89.159906
iter  80 value 88.124927
iter  90 value 84.915291
iter 100 value 82.340016
final  value 82.340016 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.432098 
iter  10 value 94.489485
iter  20 value 94.309264
iter  30 value 88.678133
iter  40 value 86.181085
iter  50 value 86.167775
final  value 86.167706 
converged
Fitting Repeat 4 

# weights:  305
initial  value 132.744199 
iter  10 value 94.472343
iter  20 value 94.429497
iter  30 value 94.425310
iter  40 value 94.424349
final  value 94.424233 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.999930 
iter  10 value 94.489165
iter  20 value 93.460865
iter  30 value 86.344342
iter  40 value 86.342429
iter  50 value 86.175377
iter  60 value 86.130379
iter  70 value 86.129761
iter  80 value 86.129311
final  value 86.129098 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.160000 
iter  10 value 94.086642
iter  20 value 88.490830
iter  30 value 85.197770
iter  40 value 84.590215
iter  50 value 83.142605
iter  60 value 82.386678
iter  70 value 82.234309
iter  80 value 81.892850
iter  90 value 81.852392
iter 100 value 81.184801
final  value 81.184801 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.442181 
iter  10 value 94.474735
iter  20 value 94.419757
iter  30 value 91.208154
iter  40 value 91.183872
iter  50 value 90.416240
iter  60 value 87.367545
iter  70 value 82.467670
iter  80 value 81.673767
iter  90 value 81.642889
iter 100 value 81.532630
final  value 81.532630 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 117.232182 
iter  10 value 92.421575
iter  20 value 90.465627
iter  30 value 90.427073
iter  40 value 90.426527
iter  50 value 90.425662
iter  60 value 90.066969
iter  70 value 90.041244
iter  80 value 90.035666
iter  90 value 89.613344
iter 100 value 87.698349
final  value 87.698349 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 99.934916 
iter  10 value 90.309691
iter  20 value 85.556681
iter  30 value 85.555722
iter  40 value 85.455703
iter  50 value 85.453326
iter  60 value 85.433406
iter  70 value 84.912593
iter  80 value 84.479568
iter  90 value 84.478839
iter 100 value 84.478738
final  value 84.478738 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 101.495860 
iter  10 value 94.474420
iter  20 value 94.341529
iter  30 value 91.997566
iter  40 value 87.761425
iter  50 value 87.510698
iter  60 value 87.498552
iter  70 value 87.420137
iter  80 value 87.413626
final  value 87.413588 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.631673 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.142130 
iter  10 value 87.269539
iter  20 value 84.997069
final  value 84.996944 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.679592 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.562847 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.395142 
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.667844 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.726122 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 108.046582 
final  value 94.484209 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.491660 
iter  10 value 83.376923
iter  20 value 83.337442
iter  30 value 83.336236
final  value 83.336235 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.226787 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.196375 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.838322 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.096161 
final  value 94.354394 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.898155 
iter  10 value 93.988095
iter  10 value 93.988095
iter  10 value 93.988095
final  value 93.988095 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.803904 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.017354 
iter  10 value 94.079637
iter  20 value 93.323936
iter  30 value 85.383405
iter  40 value 84.617076
iter  50 value 82.100965
iter  60 value 81.648444
iter  70 value 81.371727
final  value 81.352866 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.819864 
iter  10 value 94.511364
iter  20 value 94.211392
iter  30 value 86.428525
iter  40 value 84.713164
iter  50 value 84.147426
iter  60 value 83.993414
iter  70 value 83.796901
iter  80 value 83.785030
final  value 83.784385 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.124971 
iter  10 value 94.496045
iter  20 value 86.606663
iter  30 value 84.638016
iter  40 value 84.349648
iter  50 value 84.287699
iter  60 value 84.255325
iter  70 value 83.801888
final  value 83.790039 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.778227 
iter  10 value 89.792603
iter  20 value 85.764009
iter  30 value 85.145778
iter  40 value 84.340503
iter  50 value 83.818409
iter  60 value 83.784392
final  value 83.784385 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.641490 
iter  10 value 94.353754
iter  20 value 93.987660
iter  30 value 93.980010
iter  40 value 93.978289
iter  50 value 93.978065
iter  60 value 93.977835
iter  70 value 93.977593
iter  80 value 93.976996
iter  80 value 93.976995
iter  90 value 92.714959
iter 100 value 84.548370
final  value 84.548370 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 100.922309 
iter  10 value 94.011335
iter  20 value 87.497987
iter  30 value 87.240848
iter  40 value 86.222982
iter  50 value 83.632905
iter  60 value 81.926471
iter  70 value 80.936116
iter  80 value 80.821906
iter  90 value 80.803184
iter 100 value 80.569765
final  value 80.569765 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.052581 
iter  10 value 94.491966
iter  20 value 94.025180
iter  30 value 93.975426
iter  40 value 93.196571
iter  50 value 89.918713
iter  60 value 86.911793
iter  70 value 81.981834
iter  80 value 80.615072
iter  90 value 79.926431
iter 100 value 79.388974
final  value 79.388974 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 115.869179 
iter  10 value 94.498376
iter  20 value 94.336373
iter  30 value 86.853593
iter  40 value 84.436512
iter  50 value 84.191114
iter  60 value 83.821403
iter  70 value 83.625269
iter  80 value 83.567382
iter  90 value 83.545519
iter 100 value 83.356345
final  value 83.356345 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.625150 
iter  10 value 94.562040
iter  20 value 94.320152
iter  30 value 90.754001
iter  40 value 84.760733
iter  50 value 84.218576
iter  60 value 82.709634
iter  70 value 81.375015
iter  80 value 80.153307
iter  90 value 79.895724
iter 100 value 79.661827
final  value 79.661827 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.799322 
iter  10 value 94.455864
iter  20 value 92.988049
iter  30 value 91.364528
iter  40 value 87.936027
iter  50 value 84.366273
iter  60 value 84.076280
iter  70 value 82.264084
iter  80 value 81.736058
iter  90 value 81.486975
iter 100 value 81.341199
final  value 81.341199 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.102494 
iter  10 value 96.891515
iter  20 value 94.225709
iter  30 value 93.647011
iter  40 value 87.539035
iter  50 value 86.627869
iter  60 value 83.324332
iter  70 value 82.818789
iter  80 value 82.407558
iter  90 value 80.595644
iter 100 value 79.705846
final  value 79.705846 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 116.004952 
iter  10 value 94.990364
iter  20 value 92.084379
iter  30 value 85.911126
iter  40 value 82.815181
iter  50 value 81.546476
iter  60 value 79.680108
iter  70 value 79.150616
iter  80 value 79.078142
iter  90 value 79.010612
iter 100 value 78.910566
final  value 78.910566 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 116.911057 
iter  10 value 92.992036
iter  20 value 87.793697
iter  30 value 85.472836
iter  40 value 83.457909
iter  50 value 81.066240
iter  60 value 80.600734
iter  70 value 79.857196
iter  80 value 79.552315
iter  90 value 79.494186
iter 100 value 79.348978
final  value 79.348978 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 127.706220 
iter  10 value 95.537783
iter  20 value 93.852904
iter  30 value 87.433770
iter  40 value 84.627713
iter  50 value 80.845764
iter  60 value 80.088966
iter  70 value 79.973457
iter  80 value 79.929977
iter  90 value 79.688467
iter 100 value 79.370228
final  value 79.370228 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.256760 
iter  10 value 94.830714
iter  20 value 91.065955
iter  30 value 85.693433
iter  40 value 85.410001
iter  50 value 84.289295
iter  60 value 82.650634
iter  70 value 80.915049
iter  80 value 80.547415
iter  90 value 80.290571
iter 100 value 79.678605
final  value 79.678605 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.294443 
final  value 94.485779 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.872164 
final  value 94.486167 
converged
Fitting Repeat 3 

# weights:  103
initial  value 109.012797 
final  value 94.485750 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.418002 
final  value 94.485648 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.593859 
final  value 94.486053 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.210564 
iter  10 value 91.471265
iter  20 value 91.469182
iter  30 value 91.462254
iter  40 value 90.910106
iter  50 value 90.883904
iter  60 value 90.883445
iter  70 value 90.883094
iter  80 value 90.882531
iter  80 value 90.882530
iter  80 value 90.882530
final  value 90.882530 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.085279 
iter  10 value 94.488677
iter  20 value 94.484342
final  value 94.484213 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.962876 
iter  10 value 94.488733
iter  20 value 94.484262
iter  30 value 93.315004
final  value 93.301011 
converged
Fitting Repeat 4 

# weights:  305
initial  value 112.970501 
iter  10 value 93.993271
iter  20 value 93.989793
iter  30 value 93.268526
iter  40 value 86.469898
iter  50 value 84.918678
iter  60 value 84.742883
iter  70 value 84.741987
iter  80 value 84.737362
iter  90 value 84.736895
final  value 84.736806 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.521780 
iter  10 value 94.358917
final  value 94.356534 
converged
Fitting Repeat 1 

# weights:  507
initial  value 119.413457 
iter  10 value 94.492851
iter  20 value 94.443147
iter  30 value 93.996789
iter  40 value 91.493281
iter  50 value 83.281820
iter  60 value 81.726809
iter  70 value 81.147741
iter  80 value 80.246177
iter  90 value 80.241887
iter 100 value 80.215717
final  value 80.215717 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 99.421605 
iter  10 value 94.363718
iter  20 value 94.355606
iter  30 value 93.064215
iter  40 value 86.676278
iter  50 value 85.347161
iter  60 value 85.318950
iter  70 value 82.841113
iter  80 value 81.942177
iter  90 value 80.741480
iter 100 value 80.735041
final  value 80.735041 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 95.521124 
iter  10 value 94.362622
iter  20 value 94.104328
iter  30 value 86.273463
final  value 86.273363 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.245974 
iter  10 value 94.492350
iter  20 value 94.310525
final  value 93.931758 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.501085 
iter  10 value 94.489992
iter  20 value 93.399148
iter  30 value 89.960276
iter  40 value 87.447520
iter  50 value 84.300260
iter  60 value 82.668982
iter  70 value 82.660561
iter  80 value 82.659113
iter  80 value 82.659112
iter  80 value 82.659112
final  value 82.659112 
converged
Fitting Repeat 1 

# weights:  103
initial  value 126.296842 
iter  10 value 117.935179
iter  20 value 113.196238
iter  30 value 110.570271
iter  40 value 108.853164
iter  50 value 108.108863
iter  60 value 106.932960
iter  70 value 106.296276
iter  80 value 106.084020
iter  90 value 105.800889
iter 100 value 105.315809
final  value 105.315809 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 130.913362 
iter  10 value 117.903887
iter  20 value 117.700361
iter  30 value 117.657662
iter  40 value 117.590056
iter  50 value 117.521587
iter  60 value 117.518733
iter  70 value 117.513542
iter  80 value 116.007827
iter  90 value 107.685124
iter 100 value 106.190986
final  value 106.190986 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 123.694323 
iter  10 value 117.887195
iter  20 value 117.798208
iter  30 value 113.319421
iter  40 value 107.754223
iter  50 value 106.084292
iter  60 value 105.994247
iter  70 value 105.584750
iter  80 value 105.263632
final  value 105.258333 
converged
Fitting Repeat 4 

# weights:  103
initial  value 132.303052 
iter  10 value 118.013089
iter  20 value 117.329454
iter  30 value 115.374043
iter  40 value 115.224186
iter  50 value 113.766313
iter  60 value 106.700262
iter  70 value 104.459443
iter  80 value 104.437705
iter  90 value 104.417896
iter 100 value 104.130049
final  value 104.130049 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 120.267537 
iter  10 value 117.879557
iter  20 value 109.677121
iter  30 value 105.581575
iter  40 value 103.759585
iter  50 value 103.128970
iter  60 value 103.091812
iter  70 value 103.007291
iter  80 value 102.568024
final  value 102.565868 
converged
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Tue Jan 14 04:48:55 2025 
*********************************************** 
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 
 75.374   2.293 137.743