##############################################################################
##############################################################################
###
### 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_1.6.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.17-bioc-mac-arm64/meat/HPiP.Rcheck’
* using R version 4.3.1 (2023-06-16)
* using platform: aarch64-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 12.6.7
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.6.0’
* 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       42.582  0.969  63.304
corr_plot     40.789  1.029  61.326
FSmethod      39.735  0.996  58.749
pred_ensembel 15.196  0.275  20.017
enrichfindP    0.515  0.081  16.839
* 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-3.17-bioc-mac-arm64/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-arm64/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 4.3.1 (2023-06-16) -- "Beagle Scouts"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: aarch64-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 99.093011 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.043014 
iter  10 value 93.849227
iter  20 value 93.543689
final  value 93.514657 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.281845 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.519683 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.273292 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.548793 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.774829 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.978797 
iter  10 value 93.297653
final  value 93.102331 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.311935 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.211865 
final  value 94.484197 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.406244 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.604603 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.519269 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.499455 
iter  10 value 94.318609
final  value 94.305884 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.968723 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.145233 
iter  10 value 94.351536
iter  20 value 86.407142
iter  30 value 83.064890
iter  40 value 82.332755
iter  50 value 82.092483
iter  60 value 82.059682
final  value 82.059299 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.587546 
iter  10 value 94.163240
iter  20 value 89.422796
iter  30 value 83.597208
iter  40 value 82.051682
iter  50 value 82.016871
iter  60 value 81.910021
iter  70 value 81.632849
iter  80 value 81.512130
final  value 81.509585 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.592059 
iter  10 value 94.504609
iter  20 value 94.487219
iter  30 value 94.259353
iter  40 value 93.834082
iter  50 value 93.776061
iter  60 value 93.769689
iter  70 value 93.768896
iter  80 value 93.768383
final  value 93.767892 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.363444 
iter  10 value 94.438908
iter  20 value 91.645802
iter  30 value 90.884789
iter  40 value 90.056945
iter  50 value 90.022080
iter  60 value 89.770602
final  value 89.769459 
converged
Fitting Repeat 5 

# weights:  103
initial  value 112.187169 
iter  10 value 94.556282
iter  20 value 94.482744
iter  30 value 91.226755
iter  40 value 90.975508
iter  50 value 90.860460
iter  60 value 90.756500
final  value 90.756332 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.026531 
iter  10 value 94.659959
iter  20 value 92.861751
iter  30 value 86.084892
iter  40 value 82.037221
iter  50 value 80.432058
iter  60 value 80.130283
iter  70 value 79.854474
iter  80 value 79.406567
iter  90 value 78.520683
iter 100 value 78.041910
final  value 78.041910 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.649091 
iter  10 value 94.548945
iter  20 value 94.488604
iter  30 value 93.925023
iter  40 value 89.178234
iter  50 value 84.918749
iter  60 value 84.311216
iter  70 value 83.800395
iter  80 value 82.958100
iter  90 value 80.352916
iter 100 value 80.105104
final  value 80.105104 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.980360 
iter  10 value 94.772264
iter  20 value 87.227395
iter  30 value 84.485540
iter  40 value 82.429683
iter  50 value 81.014295
iter  60 value 79.862328
iter  70 value 78.939206
iter  80 value 78.751353
iter  90 value 78.658602
iter 100 value 78.646098
final  value 78.646098 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 132.797483 
iter  10 value 95.830014
iter  20 value 90.515405
iter  30 value 88.468790
iter  40 value 84.526879
iter  50 value 82.522863
iter  60 value 80.542395
iter  70 value 80.077430
iter  80 value 79.718104
iter  90 value 79.599408
iter 100 value 79.394732
final  value 79.394732 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.156873 
iter  10 value 94.486943
iter  20 value 94.290298
iter  30 value 93.274374
iter  40 value 87.568378
iter  50 value 82.826780
iter  60 value 82.088017
iter  70 value 81.370696
iter  80 value 81.312308
iter  90 value 81.225080
iter 100 value 81.179944
final  value 81.179944 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 119.624794 
iter  10 value 94.482544
iter  20 value 86.049428
iter  30 value 84.357552
iter  40 value 82.932373
iter  50 value 80.524838
iter  60 value 80.349030
iter  70 value 80.114790
iter  80 value 79.219440
iter  90 value 78.612935
iter 100 value 78.137727
final  value 78.137727 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 120.580281 
iter  10 value 96.371559
iter  20 value 92.706868
iter  30 value 85.004223
iter  40 value 80.119283
iter  50 value 79.793596
iter  60 value 79.306854
iter  70 value 78.179925
iter  80 value 77.875981
iter  90 value 77.561457
iter 100 value 77.526016
final  value 77.526016 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.467107 
iter  10 value 95.693536
iter  20 value 86.044667
iter  30 value 83.173994
iter  40 value 79.919600
iter  50 value 78.354857
iter  60 value 77.823892
iter  70 value 77.573249
iter  80 value 77.490163
iter  90 value 77.418228
iter 100 value 77.261431
final  value 77.261431 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 132.160381 
iter  10 value 95.058827
iter  20 value 91.300746
iter  30 value 90.527565
iter  40 value 88.739305
iter  50 value 84.221365
iter  60 value 83.564629
iter  70 value 79.508562
iter  80 value 79.200908
iter  90 value 78.817422
iter 100 value 78.132249
final  value 78.132249 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.923016 
iter  10 value 94.776067
iter  20 value 87.965783
iter  30 value 82.517364
iter  40 value 81.988011
iter  50 value 81.062889
iter  60 value 78.802040
iter  70 value 78.075676
iter  80 value 77.916994
iter  90 value 77.841915
iter 100 value 77.683453
final  value 77.683453 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.178247 
final  value 94.485877 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.342376 
iter  10 value 82.395387
iter  20 value 81.630554
iter  30 value 80.040000
iter  40 value 79.985883
final  value 79.985708 
converged
Fitting Repeat 3 

# weights:  103
initial  value 110.969182 
final  value 94.485959 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.515163 
final  value 94.485631 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.919979 
final  value 94.485808 
converged
Fitting Repeat 1 

# weights:  305
initial  value 115.823220 
iter  10 value 93.788265
iter  20 value 93.786859
final  value 93.786140 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.510716 
iter  10 value 94.310853
iter  20 value 94.026525
final  value 93.851911 
converged
Fitting Repeat 3 

# weights:  305
initial  value 113.577314 
iter  10 value 94.488608
iter  20 value 94.376908
iter  30 value 84.171911
iter  40 value 83.268024
iter  50 value 83.159222
iter  60 value 83.132131
final  value 83.131975 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.960148 
iter  10 value 94.447827
iter  20 value 94.443922
iter  30 value 89.897689
iter  40 value 80.433700
iter  50 value 80.386857
iter  60 value 80.380782
iter  70 value 80.365929
iter  80 value 80.346026
final  value 80.345973 
converged
Fitting Repeat 5 

# weights:  305
initial  value 121.490635 
iter  10 value 94.489039
iter  20 value 94.397839
final  value 93.922732 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.393767 
iter  10 value 87.262737
iter  20 value 85.921737
iter  30 value 85.870313
iter  40 value 85.868257
iter  50 value 85.838275
iter  60 value 85.672427
iter  70 value 85.666161
iter  80 value 85.656952
iter  90 value 81.706674
iter 100 value 81.434492
final  value 81.434492 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.046925 
iter  10 value 93.736730
iter  20 value 93.701682
iter  30 value 93.678007
iter  40 value 93.660282
iter  50 value 93.659456
iter  60 value 93.658521
iter  70 value 92.816555
iter  80 value 92.815012
iter  90 value 92.814728
iter 100 value 92.742421
final  value 92.742421 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 101.589494 
iter  10 value 94.451393
iter  20 value 93.876228
iter  30 value 93.853125
iter  40 value 93.754554
iter  50 value 93.754238
iter  60 value 93.753388
iter  70 value 93.387371
iter  80 value 83.801495
iter  90 value 83.699087
iter 100 value 83.697820
final  value 83.697820 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 99.465687 
iter  10 value 94.491745
iter  20 value 94.423329
final  value 93.784074 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.640928 
iter  10 value 94.491921
iter  20 value 93.740251
iter  30 value 81.957267
iter  40 value 81.933093
iter  50 value 81.916963
iter  60 value 81.659367
iter  70 value 81.654478
final  value 81.652489 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.736974 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.150730 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.864662 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 116.983286 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.087004 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.058944 
iter  10 value 92.845505
iter  20 value 92.521354
final  value 92.521274 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.718008 
iter  10 value 92.945357
final  value 92.945355 
converged
Fitting Repeat 3 

# weights:  305
initial  value 123.730549 
iter  10 value 92.951436
iter  20 value 92.945356
iter  20 value 92.945355
iter  20 value 92.945355
final  value 92.945355 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.510873 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.266924 
iter  10 value 92.945356
iter  10 value 92.945356
iter  10 value 92.945356
final  value 92.945356 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.998000 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.624044 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.589059 
iter  10 value 92.988213
final  value 92.945355 
converged
Fitting Repeat 4 

# weights:  507
initial  value 109.508172 
iter  10 value 92.597284
iter  20 value 90.459032
final  value 90.447059 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.708895 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.025595 
iter  10 value 94.248824
iter  20 value 94.054855
iter  30 value 89.228372
iter  40 value 84.722391
iter  50 value 83.723910
iter  60 value 83.257107
iter  70 value 82.995662
iter  80 value 82.882156
iter  90 value 82.402160
iter 100 value 82.351426
final  value 82.351426 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.633101 
iter  10 value 93.948844
iter  20 value 84.227480
iter  30 value 83.999225
iter  40 value 83.303790
iter  50 value 83.096772
iter  60 value 82.909320
iter  70 value 82.884124
iter  80 value 82.830464
iter  90 value 82.353549
iter 100 value 82.339027
final  value 82.339027 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.782540 
iter  10 value 94.062404
iter  20 value 94.038791
iter  30 value 92.952450
iter  40 value 88.470311
iter  50 value 85.407709
iter  60 value 84.086426
iter  70 value 83.619552
iter  80 value 83.273194
iter  90 value 81.779853
iter 100 value 80.846500
final  value 80.846500 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 100.303164 
iter  10 value 93.999541
iter  20 value 92.943036
iter  30 value 92.832819
iter  40 value 92.823166
iter  50 value 92.821034
iter  60 value 92.821012
iter  70 value 92.820227
iter  70 value 92.820227
final  value 92.820227 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.452489 
iter  10 value 94.070679
iter  20 value 94.057325
iter  30 value 87.547066
iter  40 value 84.777415
iter  50 value 83.422855
iter  60 value 83.074903
iter  70 value 82.919954
iter  80 value 82.881614
iter  80 value 82.881614
final  value 82.881614 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.966280 
iter  10 value 93.295180
iter  20 value 83.778973
iter  30 value 83.433980
iter  40 value 82.846152
iter  50 value 81.183057
iter  60 value 79.496086
iter  70 value 78.965505
iter  80 value 78.419657
iter  90 value 78.181941
iter 100 value 78.020777
final  value 78.020777 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.769232 
iter  10 value 86.550420
iter  20 value 83.295511
iter  30 value 83.193757
iter  40 value 82.032273
iter  50 value 81.144984
iter  60 value 80.199388
iter  70 value 79.586029
iter  80 value 79.460251
iter  90 value 79.437341
iter 100 value 79.384864
final  value 79.384864 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 112.042545 
iter  10 value 94.310812
iter  20 value 92.812947
iter  30 value 84.659016
iter  40 value 83.218127
iter  50 value 82.047797
iter  60 value 81.116417
iter  70 value 80.762738
iter  80 value 80.669113
iter  90 value 80.666867
iter 100 value 80.666579
final  value 80.666579 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 121.430890 
iter  10 value 94.393820
iter  20 value 92.954476
iter  30 value 85.894147
iter  40 value 84.289777
iter  50 value 82.609047
iter  60 value 80.572757
iter  70 value 79.371824
iter  80 value 78.969507
iter  90 value 78.506604
iter 100 value 78.180413
final  value 78.180413 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 125.618105 
iter  10 value 94.739568
iter  20 value 89.529938
iter  30 value 83.690696
iter  40 value 82.566624
iter  50 value 82.468169
iter  60 value 82.264029
iter  70 value 81.258212
iter  80 value 79.750025
iter  90 value 79.434740
iter 100 value 79.224106
final  value 79.224106 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.375341 
iter  10 value 93.340799
iter  20 value 88.008146
iter  30 value 84.368616
iter  40 value 83.250203
iter  50 value 81.954885
iter  60 value 81.559485
iter  70 value 81.101971
iter  80 value 80.800222
iter  90 value 80.632464
iter 100 value 80.501012
final  value 80.501012 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.778994 
iter  10 value 93.694287
iter  20 value 92.954119
iter  30 value 92.893461
iter  40 value 92.747052
iter  50 value 87.562382
iter  60 value 81.138166
iter  70 value 79.939088
iter  80 value 79.503765
iter  90 value 78.532861
iter 100 value 78.142726
final  value 78.142726 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 101.760680 
iter  10 value 94.221832
iter  20 value 84.717014
iter  30 value 83.542360
iter  40 value 82.113230
iter  50 value 81.940567
iter  60 value 81.249145
iter  70 value 80.389331
iter  80 value 80.074827
iter  90 value 79.982495
iter 100 value 79.965593
final  value 79.965593 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.216253 
iter  10 value 94.179058
iter  20 value 93.703883
iter  30 value 92.805961
iter  40 value 92.620491
iter  50 value 89.910036
iter  60 value 85.804468
iter  70 value 84.349392
iter  80 value 81.525941
iter  90 value 80.907920
iter 100 value 80.360737
final  value 80.360737 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 117.563642 
iter  10 value 96.563254
iter  20 value 93.069265
iter  30 value 84.943091
iter  40 value 81.978866
iter  50 value 80.849771
iter  60 value 80.474655
iter  70 value 79.360232
iter  80 value 78.771243
iter  90 value 78.519722
iter 100 value 78.224830
final  value 78.224830 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.404880 
iter  10 value 94.054399
iter  20 value 94.032997
iter  30 value 93.041901
iter  40 value 92.522604
final  value 92.522602 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.636203 
iter  10 value 92.947426
iter  20 value 92.946548
iter  30 value 92.943115
iter  40 value 92.523615
iter  50 value 89.136357
iter  60 value 86.078477
iter  70 value 85.669243
iter  80 value 84.097304
iter  90 value 79.866786
iter 100 value 77.696920
final  value 77.696920 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 102.290742 
iter  10 value 93.728016
iter  20 value 93.723521
iter  30 value 93.157603
iter  40 value 92.541728
iter  50 value 92.521911
iter  60 value 92.521826
final  value 92.521824 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.654178 
final  value 94.054571 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.200349 
final  value 94.054668 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.788596 
iter  10 value 94.057645
iter  20 value 93.859134
iter  30 value 93.809072
iter  40 value 93.516717
iter  50 value 90.011951
iter  60 value 90.010613
iter  70 value 87.375603
iter  80 value 86.265129
iter  90 value 85.988142
final  value 85.980466 
converged
Fitting Repeat 2 

# weights:  305
initial  value 112.881769 
iter  10 value 94.058093
iter  20 value 93.639586
iter  30 value 88.266801
iter  40 value 86.929284
iter  50 value 86.515066
iter  60 value 86.514461
iter  70 value 85.528309
iter  80 value 85.527256
iter  90 value 85.527110
final  value 85.526943 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.446382 
iter  10 value 93.701772
iter  20 value 93.697531
iter  30 value 93.285155
iter  40 value 87.368260
iter  50 value 86.008091
iter  60 value 81.560888
iter  70 value 81.549378
final  value 81.549020 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.531323 
iter  10 value 94.056165
iter  20 value 93.473364
final  value 92.946331 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.746307 
iter  10 value 94.054183
iter  20 value 92.971193
final  value 92.945964 
converged
Fitting Repeat 1 

# weights:  507
initial  value 119.761142 
iter  10 value 94.060718
iter  20 value 94.054373
iter  30 value 93.150844
final  value 92.946188 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.815336 
iter  10 value 93.637327
iter  20 value 91.635836
iter  30 value 89.131402
iter  40 value 89.027321
iter  50 value 89.025742
iter  60 value 87.200569
iter  70 value 87.197167
iter  80 value 87.197073
iter  90 value 87.196819
iter 100 value 85.983596
final  value 85.983596 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 121.278805 
iter  10 value 94.055549
iter  20 value 93.907655
iter  30 value 92.947856
final  value 92.947854 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.406232 
iter  10 value 92.529943
iter  20 value 92.528885
iter  30 value 92.524415
iter  40 value 92.524002
iter  50 value 92.522521
iter  60 value 92.182531
iter  70 value 88.599569
iter  80 value 81.504270
iter  90 value 80.315205
iter 100 value 78.842787
final  value 78.842787 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 94.745203 
iter  10 value 94.060569
iter  20 value 93.320936
iter  30 value 92.524792
iter  40 value 92.524073
iter  50 value 92.523725
iter  60 value 92.523396
iter  70 value 92.493257
iter  80 value 83.673549
iter  90 value 83.532622
iter 100 value 83.532165
final  value 83.532165 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.492494 
final  value 94.326054 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.923005 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 118.201687 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 109.327916 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.989992 
iter  10 value 93.246207
iter  20 value 92.395996
iter  30 value 92.389199
final  value 92.389186 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.790359 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.901183 
iter  10 value 92.037797
final  value 91.740981 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.426541 
iter  10 value 94.466823
iter  10 value 94.466823
iter  10 value 94.466823
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.778681 
iter  10 value 92.634720
iter  20 value 92.608991
final  value 92.608648 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.512682 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.023999 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  507
initial  value 121.783074 
iter  10 value 94.484211
iter  10 value 94.484211
iter  10 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 123.803193 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.704090 
iter  10 value 92.574411
final  value 92.570161 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.461700 
iter  10 value 92.922007
final  value 92.921209 
converged
Fitting Repeat 1 

# weights:  103
initial  value 106.027921 
iter  10 value 94.043030
iter  20 value 84.765424
iter  30 value 81.747074
iter  40 value 80.059334
iter  50 value 79.845797
iter  60 value 79.189583
iter  70 value 78.687268
iter  80 value 78.633340
final  value 78.633339 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.363283 
iter  10 value 94.450702
iter  20 value 84.557088
iter  30 value 82.677038
iter  40 value 81.774932
iter  50 value 81.701210
iter  60 value 79.159019
iter  70 value 78.652887
iter  80 value 78.590311
iter  90 value 78.451275
final  value 78.446458 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.309600 
iter  10 value 94.495091
iter  20 value 86.500065
iter  30 value 84.129257
iter  40 value 83.755848
iter  50 value 81.454719
iter  60 value 81.136626
iter  70 value 81.083262
final  value 81.078190 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.595913 
iter  10 value 94.486559
iter  20 value 90.365366
iter  30 value 86.149998
iter  40 value 84.335601
iter  50 value 84.158559
iter  60 value 83.828878
iter  70 value 80.777617
iter  80 value 80.041199
iter  90 value 79.021912
iter 100 value 78.790059
final  value 78.790059 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.608015 
iter  10 value 94.224667
iter  20 value 86.273152
iter  30 value 83.201875
iter  40 value 80.416853
iter  50 value 79.459329
iter  60 value 79.371517
iter  70 value 79.311395
iter  80 value 79.172943
iter  90 value 79.011534
iter 100 value 78.805014
final  value 78.805014 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 107.375946 
iter  10 value 94.509733
iter  20 value 94.403085
iter  30 value 84.731851
iter  40 value 84.160467
iter  50 value 82.555969
iter  60 value 80.574208
iter  70 value 78.646527
iter  80 value 77.587842
iter  90 value 77.397614
iter 100 value 77.210017
final  value 77.210017 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.628236 
iter  10 value 94.325924
iter  20 value 93.878768
iter  30 value 86.737926
iter  40 value 84.906443
iter  50 value 82.677387
iter  60 value 81.808068
iter  70 value 81.512180
iter  80 value 80.142146
iter  90 value 78.377329
iter 100 value 77.874408
final  value 77.874408 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 126.528101 
iter  10 value 94.505863
iter  20 value 91.770269
iter  30 value 85.125691
iter  40 value 83.357959
iter  50 value 82.991500
iter  60 value 80.132296
iter  70 value 78.708105
iter  80 value 78.345462
iter  90 value 78.233634
iter 100 value 77.601820
final  value 77.601820 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 111.199388 
iter  10 value 97.603459
iter  20 value 95.538566
iter  30 value 87.369266
iter  40 value 83.259408
iter  50 value 79.380454
iter  60 value 78.838666
iter  70 value 78.412441
iter  80 value 77.988078
iter  90 value 77.575542
iter 100 value 77.422538
final  value 77.422538 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 117.953034 
iter  10 value 94.724477
iter  20 value 92.640455
iter  30 value 85.789685
iter  40 value 84.466578
iter  50 value 82.403760
iter  60 value 81.739710
iter  70 value 81.463356
iter  80 value 80.523033
iter  90 value 80.088495
iter 100 value 79.713452
final  value 79.713452 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.235872 
iter  10 value 94.500790
iter  20 value 93.952982
iter  30 value 82.445759
iter  40 value 82.183892
iter  50 value 81.541406
iter  60 value 80.168688
iter  70 value 79.061475
iter  80 value 78.199605
iter  90 value 78.042219
iter 100 value 77.826341
final  value 77.826341 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 121.268887 
iter  10 value 92.728352
iter  20 value 88.391404
iter  30 value 82.108874
iter  40 value 80.785624
iter  50 value 80.679340
iter  60 value 80.333087
iter  70 value 80.256294
iter  80 value 80.190100
iter  90 value 79.914443
iter 100 value 79.440868
final  value 79.440868 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 115.782781 
iter  10 value 94.669375
iter  20 value 89.137814
iter  30 value 85.531453
iter  40 value 80.775892
iter  50 value 79.416424
iter  60 value 78.812748
iter  70 value 77.690653
iter  80 value 77.548549
iter  90 value 77.304939
iter 100 value 77.201051
final  value 77.201051 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.404450 
iter  10 value 94.625888
iter  20 value 86.150458
iter  30 value 85.057945
iter  40 value 83.951504
iter  50 value 82.498484
iter  60 value 81.289635
iter  70 value 81.151268
iter  80 value 81.009599
iter  90 value 79.636487
iter 100 value 78.303670
final  value 78.303670 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.829686 
iter  10 value 94.483814
iter  20 value 83.526624
iter  30 value 82.157826
iter  40 value 81.958706
iter  50 value 80.492758
iter  60 value 79.381887
iter  70 value 79.004839
iter  80 value 78.454142
iter  90 value 77.960999
iter 100 value 77.827884
final  value 77.827884 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.344671 
final  value 94.485762 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.911214 
final  value 94.486116 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.349168 
final  value 94.485648 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.806476 
final  value 94.485702 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.830934 
final  value 94.486083 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.869133 
iter  10 value 94.488600
iter  20 value 94.320170
iter  30 value 87.938396
iter  40 value 87.877477
iter  50 value 87.708603
iter  60 value 87.691509
iter  70 value 83.978801
iter  80 value 81.445477
iter  90 value 80.352005
iter 100 value 79.961928
final  value 79.961928 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.919410 
iter  10 value 94.489210
iter  20 value 86.034939
iter  30 value 83.800670
iter  40 value 83.799143
final  value 83.798398 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.316624 
iter  10 value 94.489259
iter  20 value 94.471805
iter  30 value 92.365224
iter  40 value 88.917409
iter  50 value 87.933369
iter  60 value 82.957677
iter  70 value 82.170281
iter  80 value 79.498462
iter  90 value 77.989685
iter 100 value 77.857461
final  value 77.857461 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.342011 
iter  10 value 94.485550
iter  20 value 93.505510
iter  30 value 91.167042
final  value 91.166956 
converged
Fitting Repeat 5 

# weights:  305
initial  value 110.910273 
iter  10 value 94.471625
iter  20 value 94.467335
iter  30 value 94.271544
iter  40 value 83.789629
iter  50 value 83.787061
iter  60 value 83.784871
iter  70 value 81.013884
iter  80 value 81.013680
iter  80 value 81.013680
final  value 81.013680 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.334332 
iter  10 value 94.475774
iter  20 value 94.060883
iter  30 value 93.910176
iter  40 value 91.178906
iter  50 value 91.166577
final  value 91.166550 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.109041 
iter  10 value 94.334068
iter  20 value 94.326513
iter  30 value 84.903239
iter  40 value 83.458883
iter  50 value 80.092112
final  value 79.996814 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.267370 
iter  10 value 93.578818
iter  20 value 93.495325
iter  30 value 91.169268
iter  40 value 91.161184
iter  50 value 91.159691
iter  60 value 91.158886
final  value 91.158879 
converged
Fitting Repeat 4 

# weights:  507
initial  value 112.375012 
iter  10 value 94.333971
iter  20 value 94.188556
iter  30 value 93.880371
final  value 93.880081 
converged
Fitting Repeat 5 

# weights:  507
initial  value 109.544778 
iter  10 value 92.616948
iter  20 value 92.610805
iter  30 value 92.233650
iter  40 value 84.561849
iter  50 value 81.628594
iter  60 value 79.264523
iter  70 value 78.199316
iter  80 value 76.561065
iter  90 value 76.245005
iter 100 value 76.086090
final  value 76.086090 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.868445 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.895761 
final  value 93.903984 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.735739 
final  value 94.008696 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.101965 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.445385 
final  value 94.052911 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.875485 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.316852 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.445710 
iter  10 value 94.032972
final  value 94.032967 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.797379 
iter  10 value 93.628702
iter  20 value 93.277632
iter  30 value 93.277172
final  value 93.277164 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.005468 
iter  10 value 91.837911
iter  20 value 86.346492
iter  30 value 85.079192
iter  40 value 83.167883
iter  50 value 83.122943
iter  60 value 83.070115
final  value 83.067455 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.173615 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 113.882300 
iter  10 value 93.986764
iter  10 value 93.986764
iter  10 value 93.986764
final  value 93.986764 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.660687 
final  value 93.723634 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.377641 
final  value 94.032967 
converged
Fitting Repeat 5 

# weights:  507
initial  value 113.722384 
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.218149 
iter  10 value 94.036005
iter  20 value 87.784746
iter  30 value 85.560812
iter  40 value 85.021679
iter  50 value 84.064111
iter  60 value 83.488665
iter  70 value 83.398020
iter  80 value 83.326556
final  value 83.323541 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.820919 
iter  10 value 94.056501
iter  20 value 94.019008
iter  30 value 92.174276
iter  40 value 88.658081
iter  50 value 85.564036
iter  60 value 84.600722
iter  70 value 83.389426
iter  80 value 82.875338
iter  90 value 82.672757
iter 100 value 82.500461
final  value 82.500461 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 100.208291 
iter  10 value 94.057993
iter  20 value 88.432026
iter  30 value 86.687595
iter  40 value 85.846307
iter  50 value 85.567463
iter  60 value 85.387623
iter  70 value 84.570125
iter  80 value 83.437757
iter  90 value 83.037719
iter 100 value 83.032931
final  value 83.032931 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.811435 
iter  10 value 94.042629
iter  20 value 93.062627
iter  30 value 92.649199
iter  40 value 92.577596
iter  50 value 92.533718
iter  60 value 92.482540
final  value 92.481188 
converged
Fitting Repeat 5 

# weights:  103
initial  value 107.199545 
iter  10 value 94.042871
iter  20 value 91.672879
iter  30 value 87.121264
iter  40 value 86.158218
iter  50 value 84.358555
iter  60 value 83.579004
iter  70 value 83.172948
iter  80 value 82.886608
iter  90 value 82.667185
final  value 82.667114 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.862593 
iter  10 value 94.050849
iter  20 value 92.413919
iter  30 value 84.975086
iter  40 value 83.686800
iter  50 value 83.320678
iter  60 value 83.205481
iter  70 value 83.053602
iter  80 value 82.836461
iter  90 value 82.109595
iter 100 value 81.666507
final  value 81.666507 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 111.823303 
iter  10 value 94.121021
iter  20 value 90.646823
iter  30 value 87.253040
iter  40 value 86.811691
iter  50 value 86.615068
iter  60 value 86.364572
iter  70 value 85.767955
iter  80 value 84.042467
iter  90 value 83.060072
iter 100 value 82.491093
final  value 82.491093 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 111.596629 
iter  10 value 94.084227
iter  20 value 87.039884
iter  30 value 85.304612
iter  40 value 84.983930
iter  50 value 83.517453
iter  60 value 82.908157
iter  70 value 82.204391
iter  80 value 81.835634
iter  90 value 81.748772
iter 100 value 81.705816
final  value 81.705816 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.318426 
iter  10 value 94.059069
iter  20 value 91.283278
iter  30 value 89.629861
iter  40 value 87.151978
iter  50 value 82.140935
iter  60 value 81.311781
iter  70 value 80.550416
iter  80 value 80.088826
iter  90 value 80.014739
iter 100 value 79.974179
final  value 79.974179 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 97.208089 
iter  10 value 87.591146
iter  20 value 86.185892
iter  30 value 84.373048
iter  40 value 82.981783
iter  50 value 82.605682
iter  60 value 82.500387
iter  70 value 82.233252
iter  80 value 82.042063
iter  90 value 81.327165
iter 100 value 80.609096
final  value 80.609096 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.423026 
iter  10 value 94.117248
iter  20 value 88.352075
iter  30 value 85.642819
iter  40 value 84.962713
iter  50 value 82.749076
iter  60 value 82.328551
iter  70 value 81.726583
iter  80 value 81.240900
iter  90 value 81.007718
iter 100 value 80.840611
final  value 80.840611 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 110.205790 
iter  10 value 92.583901
iter  20 value 87.423458
iter  30 value 86.447537
iter  40 value 86.273698
iter  50 value 83.469386
iter  60 value 81.752986
iter  70 value 80.746826
iter  80 value 80.526102
iter  90 value 80.467864
iter 100 value 80.432520
final  value 80.432520 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.723397 
iter  10 value 94.559938
iter  20 value 86.509404
iter  30 value 84.817581
iter  40 value 84.160749
iter  50 value 83.578810
iter  60 value 83.325234
iter  70 value 82.977867
iter  80 value 82.075745
iter  90 value 81.977374
iter 100 value 81.723592
final  value 81.723592 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.261387 
iter  10 value 93.907648
iter  20 value 91.469172
iter  30 value 86.750985
iter  40 value 85.287740
iter  50 value 82.112976
iter  60 value 80.916077
iter  70 value 80.696051
iter  80 value 80.325829
iter  90 value 80.166856
iter 100 value 79.952731
final  value 79.952731 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.598347 
iter  10 value 93.986063
iter  20 value 85.734943
iter  30 value 84.834427
iter  40 value 84.359167
iter  50 value 83.530007
iter  60 value 80.922053
iter  70 value 80.540603
iter  80 value 80.411181
iter  90 value 80.332095
iter 100 value 80.316540
final  value 80.316540 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.057672 
iter  10 value 94.003832
iter  20 value 93.964042
iter  30 value 93.963881
iter  40 value 93.913085
iter  50 value 93.912843
final  value 93.912765 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.339436 
final  value 94.054552 
converged
Fitting Repeat 3 

# weights:  103
initial  value 117.605055 
final  value 94.054565 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.853974 
final  value 93.993062 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.242100 
final  value 94.054463 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.414443 
iter  10 value 94.058262
iter  20 value 94.047128
iter  30 value 93.842625
iter  40 value 90.890294
iter  50 value 90.829747
iter  60 value 90.817402
final  value 90.816242 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.575856 
iter  10 value 94.038385
iter  20 value 94.035728
iter  30 value 94.033955
final  value 94.033953 
converged
Fitting Repeat 3 

# weights:  305
initial  value 111.774543 
iter  10 value 94.038155
iter  20 value 88.729987
iter  30 value 87.022456
iter  40 value 84.605304
iter  50 value 84.596406
final  value 84.596400 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.253867 
iter  10 value 94.038143
iter  20 value 94.033092
iter  30 value 93.593875
iter  40 value 93.204255
final  value 93.204016 
converged
Fitting Repeat 5 

# weights:  305
initial  value 119.380344 
iter  10 value 94.058175
iter  20 value 94.053208
iter  30 value 86.473543
iter  40 value 86.394532
iter  50 value 86.393292
iter  60 value 86.341071
final  value 86.341068 
converged
Fitting Repeat 1 

# weights:  507
initial  value 110.101429 
iter  10 value 94.042536
iter  20 value 94.034073
iter  30 value 86.136436
iter  40 value 85.536304
final  value 85.535513 
converged
Fitting Repeat 2 

# weights:  507
initial  value 94.489513 
iter  10 value 88.126940
iter  20 value 85.544042
iter  30 value 85.160215
iter  40 value 85.123075
iter  50 value 84.661093
iter  60 value 84.173631
iter  70 value 84.098394
iter  80 value 84.097719
iter  90 value 84.094821
iter 100 value 84.069964
final  value 84.069964 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 115.645518 
iter  10 value 93.908103
iter  20 value 91.111445
iter  30 value 87.693698
iter  40 value 85.255534
iter  50 value 84.785225
iter  60 value 84.719088
iter  70 value 84.708052
iter  80 value 84.704065
final  value 84.704042 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.934209 
iter  10 value 94.060674
iter  20 value 94.004201
iter  30 value 92.395973
iter  40 value 89.416262
iter  50 value 85.117033
iter  60 value 84.491417
iter  70 value 83.697504
iter  80 value 82.987153
iter  90 value 82.892873
iter 100 value 79.649981
final  value 79.649981 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 118.330325 
iter  10 value 89.131988
iter  20 value 85.680298
iter  30 value 85.508900
iter  40 value 85.502146
iter  50 value 85.495431
iter  60 value 85.139209
final  value 85.136657 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.461413 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.596406 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.185103 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.052593 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.754445 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.831041 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.693682 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 110.894830 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.578709 
iter  10 value 92.000909
iter  20 value 91.893361
iter  30 value 91.893280
iter  30 value 91.893279
iter  30 value 91.893279
final  value 91.893279 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.000039 
iter  10 value 94.312038
iter  10 value 94.312038
iter  10 value 94.312038
final  value 94.312038 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.847490 
iter  10 value 92.015970
iter  20 value 89.427882
iter  30 value 88.455378
iter  40 value 88.443663
final  value 88.443641 
converged
Fitting Repeat 2 

# weights:  507
initial  value 94.857420 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  507
initial  value 110.554711 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  507
initial  value 112.469103 
iter  10 value 94.147256
final  value 94.145584 
converged
Fitting Repeat 5 

# weights:  507
initial  value 120.824103 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.879303 
iter  10 value 94.259539
iter  20 value 92.760721
iter  30 value 88.187640
iter  40 value 87.965896
iter  50 value 87.570957
iter  60 value 86.301384
iter  70 value 85.888457
iter  80 value 85.811125
final  value 85.809966 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.260790 
iter  10 value 94.488258
iter  20 value 93.726549
iter  30 value 89.357484
iter  40 value 88.876190
iter  50 value 88.593574
iter  60 value 88.587327
final  value 88.586097 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.646456 
iter  10 value 94.476752
iter  20 value 93.813760
iter  30 value 89.347276
iter  40 value 88.935106
iter  50 value 88.807187
iter  60 value 88.601630
final  value 88.586097 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.271146 
iter  10 value 94.487486
iter  20 value 94.217798
iter  30 value 94.128356
iter  40 value 94.044078
iter  50 value 91.772033
iter  60 value 90.173786
iter  70 value 89.536991
iter  80 value 88.754124
iter  90 value 88.586968
final  value 88.586097 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.516912 
iter  10 value 91.445983
iter  20 value 89.232782
iter  30 value 89.150946
iter  40 value 88.705037
iter  50 value 88.547652
final  value 88.541845 
converged
Fitting Repeat 1 

# weights:  305
initial  value 119.052654 
iter  10 value 94.260476
iter  20 value 90.586662
iter  30 value 88.938550
iter  40 value 87.053589
iter  50 value 86.430663
iter  60 value 86.220323
iter  70 value 86.062300
iter  80 value 85.925326
iter  90 value 85.756621
iter 100 value 85.621511
final  value 85.621511 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.200872 
iter  10 value 94.352778
iter  20 value 88.259727
iter  30 value 87.381786
iter  40 value 86.529899
iter  50 value 85.323434
iter  60 value 84.826549
iter  70 value 84.770971
iter  80 value 84.764980
iter  90 value 84.756608
iter 100 value 84.742766
final  value 84.742766 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.672303 
iter  10 value 94.597171
iter  20 value 94.204372
iter  30 value 90.933757
iter  40 value 88.139786
iter  50 value 86.518450
iter  60 value 86.111639
iter  70 value 86.053084
iter  80 value 85.978610
iter  90 value 85.832008
iter 100 value 85.755847
final  value 85.755847 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 114.745573 
iter  10 value 93.803622
iter  20 value 93.133039
iter  30 value 89.507595
iter  40 value 89.015274
iter  50 value 88.760331
iter  60 value 88.309297
iter  70 value 85.950433
iter  80 value 85.708366
iter  90 value 85.211503
iter 100 value 85.091924
final  value 85.091924 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 120.969045 
iter  10 value 94.635753
iter  20 value 94.397230
iter  30 value 89.763732
iter  40 value 87.801554
iter  50 value 87.083251
iter  60 value 86.019352
iter  70 value 85.817343
iter  80 value 85.636768
iter  90 value 85.286486
iter 100 value 85.057626
final  value 85.057626 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.155602 
iter  10 value 94.805165
iter  20 value 94.184519
iter  30 value 89.883099
iter  40 value 89.337954
iter  50 value 88.676082
iter  60 value 85.882437
iter  70 value 85.135933
iter  80 value 84.967992
iter  90 value 84.820396
iter 100 value 84.634657
final  value 84.634657 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.529530 
iter  10 value 95.325706
iter  20 value 94.785308
iter  30 value 92.642567
iter  40 value 90.795603
iter  50 value 89.234706
iter  60 value 87.044432
iter  70 value 86.153767
iter  80 value 85.633888
iter  90 value 84.959943
iter 100 value 84.547505
final  value 84.547505 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.557987 
iter  10 value 95.172431
iter  20 value 94.363624
iter  30 value 91.532377
iter  40 value 89.742213
iter  50 value 89.023639
iter  60 value 86.742925
iter  70 value 85.173008
iter  80 value 85.003031
iter  90 value 84.849256
iter 100 value 84.536694
final  value 84.536694 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.877244 
iter  10 value 97.223675
iter  20 value 91.189425
iter  30 value 88.552062
iter  40 value 86.023642
iter  50 value 85.813737
iter  60 value 85.429010
iter  70 value 85.222517
iter  80 value 84.917383
iter  90 value 84.887708
iter 100 value 84.878081
final  value 84.878081 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 118.894769 
iter  10 value 94.499125
iter  20 value 94.441305
iter  30 value 90.032023
iter  40 value 89.066983
iter  50 value 88.194381
iter  60 value 87.487275
iter  70 value 86.505609
iter  80 value 86.453479
iter  90 value 86.421066
iter 100 value 86.348631
final  value 86.348631 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.031325 
final  value 94.485923 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.693679 
iter  10 value 94.486013
iter  20 value 94.484225
iter  30 value 94.157646
final  value 94.112854 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.721175 
final  value 94.485956 
converged
Fitting Repeat 4 

# weights:  103
initial  value 108.593678 
final  value 94.485844 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.274795 
final  value 94.485771 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.403733 
iter  10 value 94.488829
iter  20 value 94.477917
iter  30 value 93.888294
iter  40 value 89.047714
iter  50 value 88.272498
iter  60 value 86.391108
iter  70 value 86.306753
iter  80 value 86.305447
iter  90 value 86.302837
iter 100 value 86.301973
final  value 86.301973 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 98.918638 
iter  10 value 94.317535
iter  20 value 94.313311
iter  30 value 94.312479
iter  40 value 94.303929
iter  50 value 94.289415
final  value 94.289382 
converged
Fitting Repeat 3 

# weights:  305
initial  value 110.700276 
iter  10 value 94.488811
iter  20 value 94.468779
iter  30 value 93.302740
iter  40 value 86.924256
iter  50 value 85.484375
iter  60 value 85.271699
iter  70 value 85.265661
iter  80 value 85.265233
iter  80 value 85.265233
iter  80 value 85.265233
final  value 85.265233 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.880702 
iter  10 value 94.471723
iter  20 value 93.225324
iter  30 value 93.216673
iter  40 value 93.205002
iter  50 value 93.203205
iter  60 value 93.201547
final  value 93.201478 
converged
Fitting Repeat 5 

# weights:  305
initial  value 116.687414 
iter  10 value 94.471493
iter  20 value 94.053366
iter  30 value 89.221267
iter  40 value 88.559345
iter  50 value 88.445535
iter  60 value 87.219672
iter  70 value 85.451160
iter  80 value 85.246562
iter  90 value 84.905046
iter 100 value 84.623951
final  value 84.623951 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 97.853682 
iter  10 value 94.461464
iter  20 value 94.320144
iter  30 value 94.179810
iter  40 value 92.848113
iter  50 value 92.609979
iter  60 value 92.606389
iter  70 value 90.808142
iter  80 value 90.777142
iter  90 value 90.771967
iter 100 value 90.755700
final  value 90.755700 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 97.337767 
iter  10 value 89.453726
iter  20 value 87.602610
iter  30 value 87.502259
final  value 87.501958 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.730632 
iter  10 value 94.488752
iter  20 value 92.576148
iter  30 value 89.345845
iter  40 value 89.223954
iter  50 value 89.209718
iter  60 value 88.603027
iter  70 value 85.847443
iter  80 value 85.517823
iter  90 value 85.497758
iter 100 value 85.484001
final  value 85.484001 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 96.208624 
iter  10 value 94.475482
iter  20 value 94.340114
iter  30 value 94.300620
iter  40 value 94.097100
iter  50 value 94.076206
iter  60 value 94.070363
iter  70 value 94.054685
final  value 94.054585 
converged
Fitting Repeat 5 

# weights:  507
initial  value 116.676299 
iter  10 value 94.476037
iter  20 value 94.333260
iter  30 value 92.576321
iter  40 value 89.472229
iter  50 value 87.606684
iter  60 value 86.167948
iter  70 value 85.251492
iter  80 value 84.689959
iter  90 value 84.473534
iter 100 value 84.215480
final  value 84.215480 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 135.378197 
iter  10 value 117.809369
iter  20 value 113.397455
iter  30 value 109.673209
iter  40 value 108.821133
iter  50 value 108.530953
iter  60 value 105.859777
iter  70 value 104.486534
iter  80 value 103.048232
iter  90 value 101.663201
iter 100 value 101.374138
final  value 101.374138 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 140.147514 
iter  10 value 117.914791
iter  20 value 116.604792
iter  30 value 112.396371
iter  40 value 110.175405
iter  50 value 106.142796
iter  60 value 105.358677
iter  70 value 104.753431
iter  80 value 103.337003
iter  90 value 102.278780
iter 100 value 101.317909
final  value 101.317909 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 156.515406 
iter  10 value 117.383356
iter  20 value 106.279592
iter  30 value 104.793780
iter  40 value 104.115954
iter  50 value 103.588207
iter  60 value 103.090249
iter  70 value 102.680217
iter  80 value 102.558113
iter  90 value 102.079008
iter 100 value 101.397457
final  value 101.397457 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 130.011097 
iter  10 value 114.411801
iter  20 value 106.463184
iter  30 value 105.900442
iter  40 value 103.809510
iter  50 value 103.206731
iter  60 value 102.358734
iter  70 value 102.077611
iter  80 value 101.993389
iter  90 value 101.960257
iter 100 value 101.830182
final  value 101.830182 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 142.256383 
iter  10 value 117.309463
iter  20 value 108.773385
iter  30 value 105.785509
iter  40 value 105.135192
iter  50 value 104.920498
iter  60 value 104.275289
iter  70 value 102.059518
iter  80 value 101.575139
iter  90 value 101.308490
iter 100 value 101.145154
final  value 101.145154 
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 -- Wed Oct 18 01:10:57 2023 
*********************************************** 
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 
 45.545   1.186  75.636