##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R-4.3.0/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/R/R-4.3.0/site-library --timings HPiP_1.7.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.18-bioc/meat/HPiP.Rcheck’
* using R version 4.3.0 (2023-04-21)
* using platform: aarch64-unknown-linux-gnu (64-bit)
* R was compiled by
    gcc (Ubuntu 11.3.0-1ubuntu1~22.04) 11.3.0
    GNU Fortran (Ubuntu 11.3.0-1ubuntu1~22.04) 11.3.0
* running under: Ubuntu 22.04.2 LTS
* using session charset: UTF-8
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.7.0’
* 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 loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... 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       40.284  0.640  40.923
FSmethod      37.631  0.616  38.248
corr_plot     37.545  0.540  38.084
pred_ensembel 17.985  0.603  16.220
getFASTA       1.142  0.030  11.497
enrichfindP    0.429  0.048  14.626
* 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 ...
  ‘HPiP_tutorial.Rmd’ using ‘UTF-8’... OK
 NONE
* checking re-building of vignette outputs ... ERROR
Error(s) in re-building vignettes:
  ...
--- re-building ‘HPiP_tutorial.Rmd’ using rmarkdown

Quitting from lines 928-938 [unnamed-chunk-50] (HPiP_tutorial.Rmd)
Error: processing vignette 'HPiP_tutorial.Rmd' failed with diagnostics:
replacement has length zero
--- failed re-building ‘HPiP_tutorial.Rmd’

SUMMARY: processing the following file failed:
  ‘HPiP_tutorial.Rmd’

Error: Vignette re-building failed.
Execution halted

* checking PDF version of manual ... OK
* DONE

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

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R-4.3.0/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/R/R-4.3.0/site-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 4.3.0 (2023-04-21) -- "Already Tomorrow"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu (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
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 96.254122 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.708652 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.561843 
final  value 94.484053 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.807741 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.397946 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.605520 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.312456 
iter  10 value 94.466667
iter  10 value 94.466667
iter  10 value 94.466667
final  value 94.466667 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.204106 
final  value 94.467391 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.899284 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.704504 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.918009 
final  value 94.484210 
converged
Fitting Repeat 2 

# weights:  507
initial  value 115.378626 
iter  10 value 94.089164
final  value 94.089147 
converged
Fitting Repeat 3 

# weights:  507
initial  value 111.009723 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.895974 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.736194 
iter  10 value 93.464318
iter  20 value 86.156590
iter  30 value 85.695949
iter  40 value 85.694120
final  value 85.694118 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.512123 
iter  10 value 94.301856
iter  20 value 86.154226
iter  30 value 83.925695
iter  40 value 83.650752
iter  50 value 82.657748
iter  60 value 82.015823
iter  70 value 81.910099
final  value 81.905179 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.188987 
iter  10 value 94.477508
iter  20 value 89.022652
iter  30 value 84.086595
iter  40 value 81.560518
iter  50 value 80.367580
iter  60 value 79.764501
iter  70 value 79.591667
iter  80 value 79.503467
iter  90 value 79.441893
final  value 79.441891 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.668402 
iter  10 value 94.516316
iter  20 value 94.478154
iter  30 value 88.226994
iter  40 value 87.511407
iter  50 value 83.713099
iter  60 value 82.417397
iter  70 value 82.273916
iter  80 value 82.079463
iter  90 value 82.021062
final  value 82.020096 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.594859 
iter  10 value 94.480772
iter  20 value 94.036322
iter  30 value 93.805796
iter  40 value 84.660958
iter  50 value 84.337296
iter  60 value 83.891562
iter  70 value 83.041792
iter  80 value 82.796007
iter  90 value 82.752644
iter  90 value 82.752644
iter  90 value 82.752644
final  value 82.752644 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.988120 
iter  10 value 94.891336
iter  20 value 94.491406
iter  30 value 94.439145
iter  40 value 91.474101
iter  50 value 85.847950
iter  60 value 85.632905
iter  70 value 83.227422
iter  80 value 82.707800
iter  90 value 82.373287
iter 100 value 82.338531
final  value 82.338531 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 111.351946 
iter  10 value 94.830251
iter  20 value 87.292692
iter  30 value 83.875831
iter  40 value 80.533009
iter  50 value 79.409972
iter  60 value 78.878559
iter  70 value 78.728772
iter  80 value 78.538941
iter  90 value 78.353470
iter 100 value 78.336834
final  value 78.336834 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.384431 
iter  10 value 94.489229
iter  20 value 90.525767
iter  30 value 85.810808
iter  40 value 82.964798
iter  50 value 82.389042
iter  60 value 81.212985
iter  70 value 79.261205
iter  80 value 78.385978
iter  90 value 78.163520
iter 100 value 78.099185
final  value 78.099185 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.303871 
iter  10 value 94.164857
iter  20 value 88.180133
iter  30 value 81.872283
iter  40 value 81.100149
iter  50 value 80.341630
iter  60 value 80.079402
iter  70 value 79.278566
iter  80 value 78.712678
iter  90 value 78.270189
iter 100 value 78.198786
final  value 78.198786 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 113.289247 
iter  10 value 93.918111
iter  20 value 87.401147
iter  30 value 86.670677
iter  40 value 85.555700
iter  50 value 83.908614
iter  60 value 83.820319
iter  70 value 83.117167
iter  80 value 82.623987
iter  90 value 81.427358
iter 100 value 80.828228
final  value 80.828228 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.225263 
iter  10 value 94.465442
iter  20 value 91.799582
iter  30 value 91.242434
iter  40 value 87.268484
iter  50 value 83.306501
iter  60 value 82.018852
iter  70 value 81.032794
iter  80 value 80.821766
iter  90 value 80.607720
iter 100 value 80.103898
final  value 80.103898 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 129.418910 
iter  10 value 94.496436
iter  20 value 89.609282
iter  30 value 84.036370
iter  40 value 83.298332
iter  50 value 82.316679
iter  60 value 78.971173
iter  70 value 78.475014
iter  80 value 78.240629
iter  90 value 77.798353
iter 100 value 77.684059
final  value 77.684059 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 115.597045 
iter  10 value 95.051311
iter  20 value 91.961549
iter  30 value 83.302884
iter  40 value 81.004454
iter  50 value 79.766491
iter  60 value 78.867818
iter  70 value 78.666157
iter  80 value 78.635893
iter  90 value 78.547678
iter 100 value 78.395145
final  value 78.395145 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 142.160604 
iter  10 value 93.961491
iter  20 value 89.175450
iter  30 value 85.640274
iter  40 value 83.521745
iter  50 value 80.383336
iter  60 value 79.898972
iter  70 value 78.974516
iter  80 value 78.453260
iter  90 value 77.828125
iter 100 value 77.703397
final  value 77.703397 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.839902 
iter  10 value 88.720370
iter  20 value 83.512608
iter  30 value 80.959017
iter  40 value 80.097745
iter  50 value 79.471862
iter  60 value 79.266083
iter  70 value 78.987967
iter  80 value 78.768486
iter  90 value 78.535430
iter 100 value 78.358431
final  value 78.358431 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.914213 
iter  10 value 97.966209
iter  20 value 91.867086
iter  30 value 85.439131
iter  40 value 81.274750
iter  50 value 80.668004
iter  60 value 78.919102
iter  70 value 78.399945
iter  80 value 77.979610
iter  90 value 77.884251
iter 100 value 77.679428
final  value 77.679428 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.876916 
final  value 94.485827 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.841667 
final  value 94.485618 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.100840 
final  value 94.485887 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.928423 
final  value 94.485607 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.430792 
final  value 94.485620 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.570174 
iter  10 value 94.331122
iter  20 value 86.625237
iter  30 value 82.825643
iter  40 value 82.816745
iter  50 value 82.754901
iter  60 value 82.730464
iter  70 value 82.729772
iter  80 value 82.648135
iter  90 value 82.521699
iter 100 value 81.789161
final  value 81.789161 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.982536 
iter  10 value 94.488909
iter  20 value 94.320785
iter  30 value 85.844129
final  value 85.844122 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.394314 
iter  10 value 94.489329
iter  20 value 94.349948
iter  30 value 86.111357
iter  40 value 86.075875
iter  50 value 86.020219
iter  60 value 86.017608
final  value 86.017584 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.473018 
iter  10 value 94.489003
iter  20 value 83.916982
iter  30 value 82.763670
final  value 82.761134 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.406130 
iter  10 value 94.489425
iter  20 value 94.419547
iter  30 value 91.669985
iter  40 value 82.358593
iter  50 value 82.353083
iter  60 value 81.199118
iter  70 value 81.123207
iter  80 value 81.122309
iter  90 value 81.025080
iter 100 value 81.003880
final  value 81.003880 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.217508 
iter  10 value 94.475221
iter  20 value 93.390717
iter  30 value 93.153008
iter  40 value 92.620457
iter  50 value 92.605329
iter  60 value 92.395446
iter  70 value 81.964117
iter  80 value 81.865520
iter  90 value 80.542003
iter 100 value 79.534095
final  value 79.534095 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 97.788145 
iter  10 value 94.491437
iter  20 value 92.873083
iter  30 value 91.137738
iter  40 value 91.120325
iter  50 value 91.055562
iter  60 value 89.781416
final  value 89.760215 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.617966 
iter  10 value 94.491752
iter  20 value 94.252037
iter  30 value 85.856844
iter  40 value 85.783325
iter  50 value 85.783227
iter  60 value 85.781830
final  value 84.522472 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.253921 
iter  10 value 94.475789
iter  20 value 94.469187
iter  30 value 94.453559
iter  40 value 94.324094
iter  50 value 91.181191
iter  60 value 91.092251
iter  70 value 91.088573
iter  80 value 91.082963
iter  90 value 91.075920
iter 100 value 91.073619
final  value 91.073619 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.496854 
iter  10 value 94.474810
iter  20 value 94.428156
iter  30 value 85.365566
iter  40 value 85.070018
iter  50 value 85.024252
iter  60 value 85.022183
iter  70 value 83.635882
iter  80 value 80.700929
iter  90 value 80.640082
iter 100 value 80.639254
final  value 80.639254 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.730921 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.162533 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.878646 
final  value 93.837464 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.525595 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.140440 
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.376837 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.499727 
iter  10 value 93.871479
iter  20 value 93.857541
iter  30 value 93.650110
final  value 93.649843 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.172733 
iter  10 value 93.856097
iter  20 value 83.117457
iter  30 value 82.214790
iter  40 value 82.100788
final  value 82.099569 
converged
Fitting Repeat 4 

# weights:  305
initial  value 119.925178 
iter  10 value 93.918906
iter  20 value 89.641531
iter  30 value 89.528598
final  value 89.528569 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.947693 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.663320 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.421670 
final  value 93.769960 
converged
Fitting Repeat 3 

# weights:  507
initial  value 118.417451 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 112.106884 
iter  10 value 94.502833
final  value 94.484212 
converged
Fitting Repeat 5 

# weights:  507
initial  value 117.755883 
iter  10 value 87.955529
iter  20 value 87.213384
iter  30 value 87.208321
iter  30 value 87.208320
iter  30 value 87.208320
final  value 87.208320 
converged
Fitting Repeat 1 

# weights:  103
initial  value 112.030864 
iter  10 value 93.883733
iter  20 value 86.275398
iter  30 value 85.984318
iter  40 value 85.724833
iter  50 value 85.405189
iter  60 value 85.197075
iter  70 value 84.915767
iter  80 value 84.854653
iter  90 value 83.090828
iter 100 value 82.429468
final  value 82.429468 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 102.430312 
iter  10 value 94.380861
iter  20 value 91.009216
iter  30 value 90.722317
iter  40 value 89.534730
iter  50 value 87.841609
iter  60 value 85.770517
iter  70 value 85.128411
iter  80 value 85.090970
iter  90 value 85.090441
final  value 85.090335 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.259779 
iter  10 value 94.418547
iter  20 value 90.543443
iter  30 value 88.697795
iter  40 value 88.399368
iter  50 value 86.025710
iter  60 value 84.814868
iter  70 value 84.450451
final  value 84.441524 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.841400 
iter  10 value 94.353912
iter  20 value 90.142531
iter  30 value 88.718864
iter  40 value 85.030544
iter  50 value 84.417028
iter  60 value 84.102186
final  value 84.079543 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.659617 
iter  10 value 94.492015
iter  20 value 94.437238
iter  30 value 93.855223
iter  40 value 93.469188
iter  50 value 89.926330
iter  60 value 89.275677
iter  70 value 85.953229
iter  80 value 85.685623
iter  90 value 85.178852
iter 100 value 84.877024
final  value 84.877024 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 103.421259 
iter  10 value 93.518081
iter  20 value 85.960169
iter  30 value 85.475050
iter  40 value 83.008617
iter  50 value 81.455916
iter  60 value 81.283567
iter  70 value 81.230344
iter  80 value 81.174385
iter  90 value 81.094229
iter 100 value 80.836451
final  value 80.836451 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 113.526058 
iter  10 value 94.841663
iter  20 value 94.338820
iter  30 value 89.096998
iter  40 value 85.782255
iter  50 value 84.769920
iter  60 value 83.187707
iter  70 value 82.411564
iter  80 value 81.739514
iter  90 value 81.698989
iter 100 value 81.349659
final  value 81.349659 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.205014 
iter  10 value 94.731105
iter  20 value 94.425625
iter  30 value 93.109878
iter  40 value 90.153614
iter  50 value 88.984903
iter  60 value 88.449764
iter  70 value 83.495503
iter  80 value 82.233065
iter  90 value 81.536705
iter 100 value 81.278807
final  value 81.278807 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.574494 
iter  10 value 94.397280
iter  20 value 93.902805
iter  30 value 88.067354
iter  40 value 84.573677
iter  50 value 83.865682
iter  60 value 83.641488
iter  70 value 83.598159
iter  80 value 83.377597
iter  90 value 82.440452
iter 100 value 81.901897
final  value 81.901897 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 114.988432 
iter  10 value 94.418162
iter  20 value 89.074686
iter  30 value 86.105803
iter  40 value 84.026607
iter  50 value 83.453757
iter  60 value 82.782470
iter  70 value 82.656454
iter  80 value 82.523281
iter  90 value 81.838510
iter 100 value 81.611702
final  value 81.611702 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 119.322606 
iter  10 value 94.493062
iter  20 value 91.745941
iter  30 value 87.851478
iter  40 value 85.433345
iter  50 value 85.236612
iter  60 value 85.173620
iter  70 value 85.078653
iter  80 value 84.735889
iter  90 value 84.418900
iter 100 value 83.830818
final  value 83.830818 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.501363 
iter  10 value 94.706568
iter  20 value 92.663378
iter  30 value 88.045817
iter  40 value 85.175691
iter  50 value 84.694086
iter  60 value 82.575378
iter  70 value 81.360973
iter  80 value 81.273919
iter  90 value 81.134885
iter 100 value 81.074760
final  value 81.074760 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.536520 
iter  10 value 94.546690
iter  20 value 93.871112
iter  30 value 88.257166
iter  40 value 84.622963
iter  50 value 82.637167
iter  60 value 82.060022
iter  70 value 81.764363
iter  80 value 81.670516
iter  90 value 81.282864
iter 100 value 81.158241
final  value 81.158241 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.378365 
iter  10 value 94.477863
iter  20 value 92.350428
iter  30 value 90.148680
iter  40 value 85.995296
iter  50 value 83.670619
iter  60 value 82.549122
iter  70 value 82.445765
iter  80 value 82.272105
iter  90 value 82.083660
iter 100 value 81.897551
final  value 81.897551 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 112.351099 
iter  10 value 94.608257
iter  20 value 92.741562
iter  30 value 91.577149
iter  40 value 83.622926
iter  50 value 83.319641
iter  60 value 83.039020
iter  70 value 81.905053
iter  80 value 81.450510
iter  90 value 81.378842
iter 100 value 81.194407
final  value 81.194407 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.615069 
final  value 94.486144 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.824387 
final  value 94.485899 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.410403 
final  value 94.485722 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.693678 
final  value 94.485850 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.881169 
final  value 94.485830 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.786542 
iter  10 value 94.489450
iter  20 value 93.951569
iter  30 value 93.788233
final  value 93.788224 
converged
Fitting Repeat 2 

# weights:  305
initial  value 109.627392 
iter  10 value 94.359421
iter  20 value 94.355027
final  value 94.354737 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.418058 
iter  10 value 94.489046
iter  20 value 94.480462
iter  30 value 87.501480
iter  40 value 84.800645
iter  50 value 83.879352
iter  60 value 83.834095
iter  70 value 83.191564
iter  80 value 82.064870
iter  90 value 81.919707
iter 100 value 81.814574
final  value 81.814574 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.147016 
iter  10 value 94.488421
iter  20 value 94.484269
final  value 94.484216 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.319509 
iter  10 value 94.489324
iter  20 value 94.476982
iter  30 value 94.105979
iter  40 value 94.105384
final  value 94.105356 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.713129 
iter  10 value 94.362359
iter  20 value 94.356563
iter  30 value 94.208083
iter  40 value 93.690944
iter  50 value 92.537115
iter  60 value 87.443404
iter  70 value 83.218818
iter  80 value 81.770494
iter  90 value 81.692319
final  value 81.641377 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.326262 
iter  10 value 94.491334
iter  20 value 90.729847
iter  30 value 84.749974
iter  40 value 84.749369
iter  50 value 84.749057
final  value 84.749052 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.195152 
iter  10 value 93.703500
iter  20 value 93.702782
iter  30 value 93.587550
iter  40 value 86.718134
iter  50 value 85.405336
iter  60 value 84.694705
iter  70 value 84.274043
iter  80 value 83.996951
iter  90 value 83.499490
iter 100 value 83.264890
final  value 83.264890 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 95.761172 
iter  10 value 94.489304
iter  20 value 94.468883
iter  30 value 92.652042
iter  40 value 84.873608
iter  50 value 84.737557
iter  60 value 83.112601
iter  70 value 82.994216
iter  80 value 82.979144
iter  90 value 82.979112
iter 100 value 82.979009
final  value 82.979009 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 100.261323 
iter  10 value 94.132582
iter  20 value 94.108720
iter  30 value 93.896622
iter  40 value 89.474310
iter  50 value 84.719158
iter  60 value 84.432193
iter  70 value 84.178633
iter  80 value 84.177953
final  value 84.177526 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.113693 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.670191 
final  value 93.836066 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.557731 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.797684 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.962185 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.390112 
final  value 93.944596 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.513604 
final  value 94.052911 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.917959 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.116251 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 119.995619 
iter  10 value 93.838746
final  value 93.836066 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.510473 
final  value 93.836066 
converged
Fitting Repeat 2 

# weights:  507
initial  value 122.791014 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.386174 
final  value 93.836066 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.760792 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.341998 
final  value 93.183861 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.389130 
iter  10 value 94.055268
iter  20 value 93.647344
iter  30 value 91.506494
iter  40 value 91.407337
iter  50 value 85.162686
iter  60 value 84.088236
iter  70 value 83.294274
iter  80 value 81.614112
iter  90 value 81.480225
final  value 81.475611 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.985612 
iter  10 value 94.072027
iter  20 value 92.970773
iter  30 value 89.124368
iter  40 value 87.191589
iter  50 value 86.789379
iter  60 value 85.133947
iter  70 value 82.529665
iter  80 value 81.801553
iter  90 value 81.756699
iter 100 value 81.404477
final  value 81.404477 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 99.446967 
iter  10 value 94.056576
iter  20 value 93.648335
iter  30 value 89.858306
iter  40 value 87.182964
iter  50 value 86.015476
iter  60 value 84.998345
iter  70 value 84.488252
iter  80 value 83.904320
iter  90 value 83.722265
iter 100 value 83.710592
final  value 83.710592 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.274034 
iter  10 value 94.052183
iter  20 value 89.268706
iter  30 value 85.508646
iter  40 value 84.786958
iter  50 value 84.500179
iter  60 value 81.777960
iter  70 value 81.527835
iter  80 value 81.291678
final  value 81.281404 
converged
Fitting Repeat 5 

# weights:  103
initial  value 117.357271 
iter  10 value 94.054877
iter  20 value 93.615917
iter  30 value 93.303349
iter  40 value 93.276342
iter  50 value 87.561326
iter  60 value 86.134193
iter  70 value 84.824223
iter  80 value 84.703621
iter  90 value 84.133064
iter 100 value 82.518088
final  value 82.518088 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 99.434854 
iter  10 value 94.073196
iter  20 value 93.901749
iter  30 value 92.032989
iter  40 value 91.806955
iter  50 value 91.292057
iter  60 value 90.898285
iter  70 value 90.311780
iter  80 value 86.022048
iter  90 value 84.132010
iter 100 value 83.103665
final  value 83.103665 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.727428 
iter  10 value 92.585912
iter  20 value 87.738574
iter  30 value 87.311750
iter  40 value 85.085163
iter  50 value 83.647106
iter  60 value 83.208312
iter  70 value 82.382577
iter  80 value 81.508494
iter  90 value 81.131458
iter 100 value 81.013267
final  value 81.013267 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 98.727427 
iter  10 value 90.827936
iter  20 value 86.807799
iter  30 value 84.017975
iter  40 value 83.483092
iter  50 value 83.449890
iter  60 value 83.337548
iter  70 value 82.968305
iter  80 value 82.668699
iter  90 value 81.385364
iter 100 value 80.902012
final  value 80.902012 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.590434 
iter  10 value 93.648272
iter  20 value 90.581219
iter  30 value 89.434781
iter  40 value 89.186080
iter  50 value 86.744307
iter  60 value 85.759687
iter  70 value 85.557899
iter  80 value 85.433017
iter  90 value 85.330061
iter 100 value 82.633723
final  value 82.633723 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.804423 
iter  10 value 94.121276
iter  20 value 93.713576
iter  30 value 93.504879
iter  40 value 89.495518
iter  50 value 86.272489
iter  60 value 83.566948
iter  70 value 82.979006
iter  80 value 82.432966
iter  90 value 82.302996
iter 100 value 82.089243
final  value 82.089243 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.432364 
iter  10 value 94.185040
iter  20 value 93.952573
iter  30 value 93.385450
iter  40 value 88.459931
iter  50 value 84.929828
iter  60 value 84.037399
iter  70 value 82.276012
iter  80 value 81.623252
iter  90 value 80.648055
iter 100 value 80.337036
final  value 80.337036 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 120.418479 
iter  10 value 94.078544
iter  20 value 86.661072
iter  30 value 84.131543
iter  40 value 82.702686
iter  50 value 81.780595
iter  60 value 81.329427
iter  70 value 81.031129
iter  80 value 80.774555
iter  90 value 80.654418
iter 100 value 80.476969
final  value 80.476969 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.868456 
iter  10 value 92.218022
iter  20 value 88.157367
iter  30 value 86.420570
iter  40 value 85.217936
iter  50 value 82.985669
iter  60 value 82.274509
iter  70 value 82.075808
iter  80 value 81.460827
iter  90 value 80.956048
iter 100 value 80.542297
final  value 80.542297 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 126.467842 
iter  10 value 94.054395
iter  20 value 87.092187
iter  30 value 85.663439
iter  40 value 82.403427
iter  50 value 81.328888
iter  60 value 80.972554
iter  70 value 80.767390
iter  80 value 80.673804
iter  90 value 80.587232
iter 100 value 80.527774
final  value 80.527774 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.604101 
iter  10 value 93.858148
iter  20 value 85.127604
iter  30 value 84.618874
iter  40 value 82.439033
iter  50 value 80.901514
iter  60 value 80.453832
iter  70 value 80.232014
iter  80 value 80.061074
iter  90 value 79.873623
iter 100 value 79.753940
final  value 79.753940 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 106.738149 
final  value 94.054520 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.726569 
final  value 94.054684 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.589974 
iter  10 value 93.569461
iter  20 value 93.536733
iter  30 value 93.535855
final  value 93.535557 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.492627 
final  value 94.051336 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.626881 
iter  10 value 94.054426
iter  20 value 94.052927
iter  30 value 93.918177
iter  40 value 86.038368
iter  50 value 86.037681
iter  60 value 86.035480
iter  70 value 86.035296
iter  80 value 86.035100
iter  90 value 83.836028
iter 100 value 83.647080
final  value 83.647080 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 99.232869 
iter  10 value 94.058246
iter  20 value 94.048399
iter  30 value 83.700265
iter  40 value 83.192983
iter  50 value 83.018407
iter  60 value 82.991589
iter  70 value 82.977611
iter  80 value 82.773607
iter  90 value 81.717438
iter 100 value 81.652419
final  value 81.652419 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.068004 
iter  10 value 94.057240
iter  20 value 94.032093
iter  30 value 87.966197
iter  40 value 85.617021
iter  50 value 84.643159
iter  60 value 84.434661
iter  70 value 83.556066
iter  80 value 83.488682
iter  90 value 83.488314
iter 100 value 83.487787
final  value 83.487787 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 94.606661 
iter  10 value 93.840813
iter  20 value 93.836424
final  value 93.836405 
converged
Fitting Repeat 4 

# weights:  305
initial  value 116.847407 
iter  10 value 94.056607
iter  20 value 93.858787
final  value 93.830762 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.282121 
iter  10 value 93.841101
iter  20 value 92.550639
iter  30 value 90.738610
iter  40 value 90.736641
iter  50 value 90.736338
iter  60 value 89.653621
iter  70 value 89.594280
final  value 89.594138 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.020140 
iter  10 value 93.844165
iter  20 value 93.420733
iter  30 value 86.036814
iter  40 value 86.035231
iter  50 value 86.034917
iter  60 value 85.689184
iter  70 value 85.457979
iter  80 value 85.432806
final  value 85.432761 
converged
Fitting Repeat 2 

# weights:  507
initial  value 117.653797 
iter  10 value 93.007374
iter  20 value 90.218364
iter  30 value 86.139667
iter  40 value 86.055056
iter  50 value 86.048161
iter  60 value 86.043933
iter  70 value 86.042849
iter  80 value 86.042637
iter  90 value 86.039072
iter 100 value 86.038873
final  value 86.038873 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 97.166991 
iter  10 value 93.709707
iter  20 value 93.580113
final  value 93.435381 
converged
Fitting Repeat 4 

# weights:  507
initial  value 112.832931 
iter  10 value 94.059929
iter  20 value 94.052477
iter  30 value 84.208018
iter  40 value 82.637386
iter  50 value 80.141228
iter  60 value 79.454229
iter  70 value 79.196145
iter  80 value 79.194862
final  value 79.193134 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.306938 
iter  10 value 94.028928
iter  20 value 93.952271
iter  30 value 93.470264
iter  40 value 93.090143
final  value 93.075103 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.762773 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.128585 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.133284 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.347414 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.024145 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.119457 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.881397 
iter  10 value 94.051397
final  value 94.043243 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.704086 
final  value 93.900000 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.199497 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.723802 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 114.918154 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.976009 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.119268 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.248187 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.358472 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.028232 
iter  10 value 94.060346
iter  20 value 93.772743
iter  30 value 93.683944
iter  40 value 93.455029
iter  50 value 89.313689
iter  60 value 87.137981
iter  70 value 86.372355
iter  80 value 85.684309
iter  90 value 85.457589
iter 100 value 85.330981
final  value 85.330981 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 100.353337 
iter  10 value 94.070031
iter  20 value 93.742081
iter  30 value 93.709173
iter  40 value 93.683963
iter  50 value 88.901424
iter  60 value 87.132569
iter  70 value 86.202435
iter  80 value 85.685873
iter  90 value 85.081450
iter 100 value 84.854992
final  value 84.854992 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 105.843410 
iter  10 value 94.025421
iter  20 value 93.697362
iter  30 value 89.011204
iter  40 value 88.738598
iter  50 value 88.649752
iter  60 value 87.517830
iter  70 value 86.474007
iter  80 value 85.779887
iter  90 value 85.396347
iter 100 value 85.340883
final  value 85.340883 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.921453 
iter  10 value 94.025170
iter  20 value 92.971278
iter  30 value 92.683985
iter  40 value 92.607068
iter  50 value 92.404619
iter  60 value 92.349534
iter  70 value 85.262472
iter  80 value 84.951467
iter  90 value 84.767057
iter 100 value 84.530207
final  value 84.530207 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.971568 
iter  10 value 94.027930
iter  20 value 93.201943
iter  30 value 91.717504
iter  40 value 91.327343
iter  50 value 90.171007
iter  60 value 87.717746
iter  70 value 86.384239
iter  80 value 85.665747
iter  90 value 85.613740
iter 100 value 84.628929
final  value 84.628929 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 115.946198 
iter  10 value 94.130760
iter  20 value 93.677387
iter  30 value 91.954913
iter  40 value 88.161325
iter  50 value 85.533301
iter  60 value 84.379097
iter  70 value 84.284734
iter  80 value 84.179683
iter  90 value 83.978027
iter 100 value 83.469018
final  value 83.469018 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.677997 
iter  10 value 94.048133
iter  20 value 93.633806
iter  30 value 92.790658
iter  40 value 90.589622
iter  50 value 87.636298
iter  60 value 86.063042
iter  70 value 85.392251
iter  80 value 85.215666
iter  90 value 85.120237
iter 100 value 84.937661
final  value 84.937661 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 110.169198 
iter  10 value 94.047725
iter  20 value 88.833553
iter  30 value 87.306006
iter  40 value 86.897465
iter  50 value 86.477116
iter  60 value 84.723286
iter  70 value 84.210439
iter  80 value 83.620151
iter  90 value 83.222234
iter 100 value 82.964634
final  value 82.964634 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.651651 
iter  10 value 98.276711
iter  20 value 94.325890
iter  30 value 93.135884
iter  40 value 92.657463
iter  50 value 92.430723
iter  60 value 92.071614
iter  70 value 92.002295
iter  80 value 86.877798
iter  90 value 86.717965
iter 100 value 85.770683
final  value 85.770683 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.796154 
iter  10 value 94.474828
iter  20 value 94.295607
iter  30 value 93.835552
iter  40 value 93.719082
iter  50 value 93.143965
iter  60 value 89.776342
iter  70 value 86.682212
iter  80 value 84.373189
iter  90 value 84.137930
iter 100 value 83.856287
final  value 83.856287 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.547444 
iter  10 value 94.564626
iter  20 value 93.507222
iter  30 value 92.731353
iter  40 value 92.527092
iter  50 value 91.625904
iter  60 value 88.462872
iter  70 value 86.903726
iter  80 value 85.211677
iter  90 value 83.851772
iter 100 value 83.215490
final  value 83.215490 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 114.599888 
iter  10 value 94.047953
iter  20 value 92.401618
iter  30 value 87.592192
iter  40 value 86.688796
iter  50 value 85.006932
iter  60 value 83.842132
iter  70 value 83.526321
iter  80 value 83.020733
iter  90 value 82.660372
iter 100 value 82.471915
final  value 82.471915 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.073675 
iter  10 value 95.602280
iter  20 value 92.968631
iter  30 value 88.573066
iter  40 value 88.086320
iter  50 value 86.654647
iter  60 value 85.639051
iter  70 value 85.342073
iter  80 value 85.238798
iter  90 value 85.033728
iter 100 value 84.589319
final  value 84.589319 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 119.781091 
iter  10 value 96.121889
iter  20 value 95.576361
iter  30 value 92.001996
iter  40 value 87.159217
iter  50 value 85.018409
iter  60 value 83.648588
iter  70 value 83.254256
iter  80 value 82.993374
iter  90 value 82.661140
iter 100 value 82.430886
final  value 82.430886 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 114.200611 
iter  10 value 94.097497
iter  20 value 91.585131
iter  30 value 90.693242
iter  40 value 89.177633
iter  50 value 85.832701
iter  60 value 85.295468
iter  70 value 84.710585
iter  80 value 84.025728
iter  90 value 83.600866
iter 100 value 83.406754
final  value 83.406754 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 114.376261 
final  value 94.054791 
converged
Fitting Repeat 2 

# weights:  103
initial  value 113.998289 
final  value 94.054862 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.553929 
iter  10 value 94.054678
final  value 94.052928 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.716756 
final  value 94.054455 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.740726 
final  value 94.054421 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.431139 
iter  10 value 93.587470
iter  20 value 93.585781
iter  30 value 93.584011
iter  40 value 93.577239
iter  50 value 87.710719
iter  60 value 87.081522
iter  70 value 86.409039
iter  80 value 86.285147
iter  90 value 86.284776
iter 100 value 86.284353
final  value 86.284353 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 94.837654 
iter  10 value 93.465430
iter  20 value 93.464060
iter  30 value 93.228671
iter  40 value 92.501679
iter  50 value 92.474596
iter  60 value 92.474419
final  value 92.474374 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.121725 
iter  10 value 93.324323
iter  20 value 93.322160
iter  30 value 93.307244
iter  40 value 93.305143
iter  50 value 93.299947
iter  60 value 93.278060
iter  70 value 88.705723
iter  80 value 86.819843
iter  90 value 86.474134
final  value 86.474122 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.268928 
iter  10 value 94.058310
iter  20 value 93.989808
iter  30 value 93.583342
iter  30 value 93.583341
iter  30 value 93.583341
final  value 93.583341 
converged
Fitting Repeat 5 

# weights:  305
initial  value 116.128164 
iter  10 value 94.029987
iter  20 value 94.012306
iter  30 value 93.873661
iter  40 value 93.770052
iter  50 value 87.569773
iter  60 value 87.392455
iter  70 value 87.046224
iter  80 value 86.468875
iter  90 value 86.363116
final  value 86.363006 
converged
Fitting Repeat 1 

# weights:  507
initial  value 121.897908 
iter  10 value 93.480873
iter  20 value 87.014056
iter  30 value 86.937376
iter  40 value 86.121858
final  value 86.121836 
converged
Fitting Repeat 2 

# weights:  507
initial  value 94.559432 
iter  10 value 86.403141
iter  20 value 85.704670
iter  30 value 84.963200
iter  40 value 84.616993
iter  50 value 84.545449
iter  60 value 84.544194
iter  70 value 83.659666
iter  80 value 83.279449
iter  90 value 83.278819
iter 100 value 83.275931
final  value 83.275931 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 99.831213 
iter  10 value 94.060957
iter  20 value 94.045368
iter  30 value 93.791705
final  value 93.582721 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.359086 
iter  10 value 93.676302
iter  20 value 93.590926
iter  30 value 93.535882
iter  40 value 88.857885
iter  50 value 88.037468
iter  60 value 87.749143
iter  70 value 87.452908
iter  80 value 85.603470
iter  90 value 83.200979
iter 100 value 83.124529
final  value 83.124529 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 112.425308 
iter  10 value 93.591498
iter  20 value 93.584206
iter  30 value 93.583482
final  value 93.583457 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.280700 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.219777 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.022101 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.369681 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.486961 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.048519 
iter  10 value 94.109864
iter  20 value 93.684427
iter  30 value 93.672370
final  value 93.670383 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.264086 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 112.629006 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 110.954469 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.376413 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.237981 
iter  10 value 93.362987
final  value 93.285720 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.836036 
final  value 94.443243 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.660488 
final  value 94.443243 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.791097 
iter  10 value 93.452494
iter  20 value 88.127008
iter  30 value 84.774671
final  value 84.766416 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.536163 
final  value 94.443243 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.027950 
iter  10 value 94.488766
iter  20 value 93.986062
iter  30 value 93.914332
iter  40 value 92.069108
iter  50 value 84.328205
iter  60 value 84.200270
iter  70 value 84.144794
iter  80 value 84.098326
iter  90 value 84.092114
final  value 84.092095 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.110674 
iter  10 value 94.489582
iter  20 value 93.259075
iter  30 value 84.216054
iter  40 value 84.127853
iter  50 value 84.101630
iter  60 value 83.684828
iter  70 value 83.532375
final  value 83.530131 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.466623 
iter  10 value 94.486710
iter  20 value 94.399176
iter  30 value 90.784870
iter  40 value 84.198485
iter  50 value 84.159813
iter  60 value 83.576795
iter  70 value 83.526082
iter  80 value 83.523604
final  value 83.523600 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.834466 
iter  10 value 94.201528
iter  20 value 87.689755
iter  30 value 86.749057
iter  40 value 86.273822
iter  50 value 83.187821
iter  60 value 83.076458
iter  70 value 83.064465
final  value 83.064037 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.208970 
iter  10 value 94.482241
iter  20 value 91.535432
iter  30 value 84.746647
iter  40 value 84.156487
iter  50 value 83.890365
iter  60 value 83.809244
final  value 83.805596 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.303287 
iter  10 value 94.483069
iter  20 value 93.932701
iter  30 value 92.997699
iter  40 value 86.734012
iter  50 value 85.276290
iter  60 value 81.074523
iter  70 value 79.742275
iter  80 value 79.058200
iter  90 value 77.998519
iter 100 value 77.599500
final  value 77.599500 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.083231 
iter  10 value 94.493252
iter  20 value 88.248331
iter  30 value 86.335429
iter  40 value 86.096237
iter  50 value 82.559693
iter  60 value 80.762503
iter  70 value 79.457296
iter  80 value 79.278559
iter  90 value 78.971725
iter 100 value 78.424970
final  value 78.424970 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.952748 
iter  10 value 94.369708
iter  20 value 91.725461
iter  30 value 87.565064
iter  40 value 83.229794
iter  50 value 79.579985
iter  60 value 78.202244
iter  70 value 78.084488
iter  80 value 77.894988
iter  90 value 77.826152
iter 100 value 77.797104
final  value 77.797104 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.924313 
iter  10 value 96.967671
iter  20 value 85.527085
iter  30 value 81.471291
iter  40 value 80.405575
iter  50 value 79.174833
iter  60 value 78.607775
iter  70 value 78.344731
iter  80 value 78.322108
iter  90 value 78.313083
final  value 78.312662 
converged
Fitting Repeat 5 

# weights:  305
initial  value 113.597882 
iter  10 value 94.605905
iter  20 value 94.345206
iter  30 value 93.550303
iter  40 value 84.290788
iter  50 value 83.125114
iter  60 value 82.983963
iter  70 value 82.727111
iter  80 value 82.603432
iter  90 value 82.497902
iter 100 value 81.699248
final  value 81.699248 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.131923 
iter  10 value 94.693384
iter  20 value 87.325640
iter  30 value 85.121366
iter  40 value 84.175759
iter  50 value 83.150688
iter  60 value 82.407590
iter  70 value 80.149586
iter  80 value 78.693493
iter  90 value 77.831822
iter 100 value 77.570045
final  value 77.570045 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 131.967962 
iter  10 value 95.366485
iter  20 value 94.408590
iter  30 value 88.068746
iter  40 value 83.709392
iter  50 value 82.915731
iter  60 value 82.496677
iter  70 value 81.125358
iter  80 value 79.837090
iter  90 value 79.114120
iter 100 value 78.968750
final  value 78.968750 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.236887 
iter  10 value 94.400550
iter  20 value 84.126459
iter  30 value 81.922228
iter  40 value 81.497932
iter  50 value 80.850395
iter  60 value 80.468307
iter  70 value 80.287638
iter  80 value 79.600227
iter  90 value 78.810233
iter 100 value 78.012552
final  value 78.012552 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.773844 
iter  10 value 94.710932
iter  20 value 94.291624
iter  30 value 91.076099
iter  40 value 82.370930
iter  50 value 80.464410
iter  60 value 79.826125
iter  70 value 79.164258
iter  80 value 78.049793
iter  90 value 77.641236
iter 100 value 77.584751
final  value 77.584751 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.879899 
iter  10 value 94.452407
iter  20 value 92.077465
iter  30 value 82.902098
iter  40 value 81.794698
iter  50 value 80.238882
iter  60 value 78.663454
iter  70 value 78.326363
iter  80 value 78.294898
iter  90 value 78.272125
iter 100 value 78.166213
final  value 78.166213 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.221535 
final  value 94.444833 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.143298 
iter  10 value 94.487700
final  value 94.485901 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.152811 
iter  10 value 93.975322
iter  20 value 86.230092
iter  30 value 86.060080
iter  40 value 86.054919
iter  50 value 86.054680
final  value 86.054677 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.904100 
iter  10 value 94.485696
iter  20 value 94.301073
final  value 94.105975 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.394646 
final  value 94.485731 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.604072 
iter  10 value 90.320756
iter  20 value 90.226313
iter  30 value 90.203878
iter  40 value 90.175919
iter  50 value 90.171826
iter  60 value 90.171507
final  value 90.171332 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.770490 
iter  10 value 94.489119
iter  20 value 94.251012
iter  30 value 92.940847
iter  40 value 92.938982
iter  50 value 92.937620
iter  60 value 92.937510
final  value 92.937443 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.094398 
iter  10 value 94.496594
iter  20 value 87.686118
iter  30 value 86.068535
iter  40 value 86.060069
iter  50 value 86.057070
iter  60 value 83.671233
iter  70 value 83.031616
iter  80 value 83.030662
final  value 83.026681 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.437250 
iter  10 value 94.448183
iter  20 value 94.443496
final  value 94.443314 
converged
Fitting Repeat 5 

# weights:  305
initial  value 121.512398 
iter  10 value 94.447682
iter  20 value 94.443634
iter  30 value 93.320481
iter  40 value 85.674884
iter  50 value 85.673054
final  value 85.672802 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.403791 
iter  10 value 91.260812
iter  20 value 89.125503
iter  30 value 89.077270
iter  40 value 89.074716
iter  50 value 89.069272
final  value 89.069234 
converged
Fitting Repeat 2 

# weights:  507
initial  value 113.906096 
iter  10 value 94.493822
iter  20 value 94.487207
iter  30 value 94.485204
iter  40 value 94.416214
final  value 94.106547 
converged
Fitting Repeat 3 

# weights:  507
initial  value 119.506704 
iter  10 value 94.452269
iter  20 value 94.443542
iter  30 value 94.404708
iter  40 value 85.254199
iter  50 value 83.029420
iter  60 value 82.999748
iter  70 value 82.998949
final  value 82.998948 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.724563 
iter  10 value 94.489887
iter  20 value 93.293367
iter  30 value 85.761812
iter  40 value 85.683128
iter  50 value 85.648474
iter  60 value 85.626226
iter  70 value 85.625114
final  value 85.622984 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.187846 
iter  10 value 94.153237
iter  20 value 94.096747
iter  30 value 93.686677
iter  40 value 93.671531
iter  50 value 93.671201
final  value 93.670793 
converged
Fitting Repeat 1 

# weights:  305
initial  value 131.469728 
iter  10 value 119.391297
iter  20 value 115.091752
iter  30 value 106.805197
iter  40 value 105.609879
iter  50 value 105.393983
iter  60 value 105.240056
iter  70 value 104.336511
iter  80 value 103.275206
iter  90 value 103.137816
iter 100 value 102.833555
final  value 102.833555 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 127.077836 
iter  10 value 117.568482
iter  20 value 112.521780
iter  30 value 106.807467
iter  40 value 105.282369
iter  50 value 104.675882
iter  60 value 103.834625
iter  70 value 102.044234
iter  80 value 100.891671
iter  90 value 100.533661
iter 100 value 100.440812
final  value 100.440812 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 129.030288 
iter  10 value 117.714242
iter  20 value 112.074281
iter  30 value 106.846360
iter  40 value 105.210047
iter  50 value 103.892018
iter  60 value 102.665832
iter  70 value 101.511656
iter  80 value 101.130755
iter  90 value 101.116340
iter 100 value 101.074947
final  value 101.074947 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 145.080401 
iter  10 value 120.908329
iter  20 value 117.903666
iter  30 value 117.894522
iter  40 value 114.880375
iter  50 value 111.935099
iter  60 value 110.068169
iter  70 value 106.431930
iter  80 value 105.890765
iter  90 value 104.088840
iter 100 value 102.438971
final  value 102.438971 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 125.246071 
iter  10 value 117.960938
iter  20 value 116.124458
iter  30 value 109.755488
iter  40 value 107.671631
iter  50 value 106.503666
iter  60 value 106.449073
iter  70 value 106.372965
iter  80 value 104.543534
iter  90 value 102.836683
iter 100 value 101.868407
final  value 101.868407 
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 -- Tue May 30 09:53:15 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 
 51.206   1.728  63.794