##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.19-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.19-bioc/R/site-library --timings HPiP_1.10.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck’
* using R version 4.4.1 (2024-06-14)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
    GNU Fortran (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
* running under: Ubuntu 22.04.4 LTS
* using session charset: UTF-8
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.10.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... 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       35.944  1.104  37.089
corr_plot     34.447  0.460  34.972
FSmethod      33.984  0.666  34.652
pred_ensembel 13.480  0.711  10.906
enrichfindP    0.455  0.035   8.728
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE

Status: 3 NOTEs
See
  ‘/home/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.19-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.19-bioc/R/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 4.4.1 (2024-06-14) -- "Race for Your Life"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> BiocGenerics:::testPackage('HPiP')
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
avNNet
Loading required package: ggplot2
Loading required package: lattice
Fitting Repeat 1 

# weights:  103
initial  value 97.453057 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.771286 
final  value 94.452424 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.633163 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.256934 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 112.933662 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.517560 
iter  10 value 94.275364
final  value 94.275362 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.297644 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.926173 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.245260 
iter  10 value 91.213296
iter  20 value 91.198760
final  value 91.198725 
converged
Fitting Repeat 5 

# weights:  305
initial  value 123.463973 
iter  10 value 94.275346
iter  10 value 94.275345
iter  10 value 94.275345
final  value 94.275345 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.563148 
final  value 94.275362 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.320976 
final  value 94.088890 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.586706 
iter  10 value 94.118836
iter  20 value 94.101618
final  value 94.101526 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.194632 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.848183 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.504344 
iter  10 value 94.402162
iter  20 value 88.102923
iter  30 value 87.276903
iter  40 value 84.297593
iter  50 value 82.871306
iter  60 value 82.326449
iter  70 value 82.273980
iter  80 value 82.030162
iter  90 value 81.735451
final  value 81.735033 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.029567 
iter  10 value 94.486501
iter  20 value 94.386305
iter  30 value 94.063893
iter  40 value 93.820340
iter  50 value 86.755263
iter  60 value 85.870753
iter  70 value 85.524164
iter  80 value 85.265457
iter  90 value 85.126737
iter 100 value 85.075160
final  value 85.075160 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.377071 
iter  10 value 94.489064
iter  20 value 94.072099
iter  30 value 94.017978
iter  40 value 93.459173
iter  50 value 86.983116
iter  60 value 83.195117
iter  70 value 82.462209
iter  80 value 82.290320
iter  90 value 81.932425
iter 100 value 81.913589
final  value 81.913589 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 100.751873 
iter  10 value 94.436174
iter  20 value 93.959874
iter  30 value 90.792721
iter  40 value 89.371494
iter  50 value 88.592642
iter  60 value 88.429420
iter  70 value 82.917416
iter  80 value 82.481007
iter  90 value 81.959443
iter 100 value 81.735169
final  value 81.735169 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 105.379942 
iter  10 value 93.751487
iter  20 value 87.447327
iter  30 value 86.630767
iter  40 value 84.735631
iter  50 value 84.334775
iter  60 value 84.130305
iter  70 value 84.100718
final  value 84.100654 
converged
Fitting Repeat 1 

# weights:  305
initial  value 125.033244 
iter  10 value 94.576828
iter  20 value 92.309846
iter  30 value 88.624138
iter  40 value 85.887399
iter  50 value 85.653871
iter  60 value 83.983938
iter  70 value 82.398919
iter  80 value 81.561174
iter  90 value 81.303427
iter 100 value 80.988264
final  value 80.988264 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.382442 
iter  10 value 94.616998
iter  20 value 94.484748
iter  30 value 94.354235
iter  40 value 94.257233
iter  50 value 93.841733
iter  60 value 93.799464
iter  70 value 89.895700
iter  80 value 88.939767
iter  90 value 85.515352
iter 100 value 83.746291
final  value 83.746291 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 109.148326 
iter  10 value 94.494626
iter  20 value 94.370251
iter  30 value 90.269915
iter  40 value 87.588354
iter  50 value 83.996767
iter  60 value 81.748613
iter  70 value 80.689354
iter  80 value 80.513387
iter  90 value 80.497272
iter 100 value 80.429297
final  value 80.429297 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.834348 
iter  10 value 94.495820
iter  20 value 90.648916
iter  30 value 85.603243
iter  40 value 85.269857
iter  50 value 84.315963
iter  60 value 83.492720
iter  70 value 82.962817
iter  80 value 82.775039
iter  90 value 82.524289
iter 100 value 82.442427
final  value 82.442427 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 112.689850 
iter  10 value 94.433721
iter  20 value 91.677489
iter  30 value 86.261797
iter  40 value 83.726207
iter  50 value 82.766835
iter  60 value 81.387956
iter  70 value 80.729966
iter  80 value 80.536246
iter  90 value 80.487515
iter 100 value 80.348934
final  value 80.348934 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.363133 
iter  10 value 94.457634
iter  20 value 93.951071
iter  30 value 87.310441
iter  40 value 85.245364
iter  50 value 82.840901
iter  60 value 81.999870
iter  70 value 81.468285
iter  80 value 80.995839
iter  90 value 80.786973
iter 100 value 80.656314
final  value 80.656314 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 114.493175 
iter  10 value 94.537564
iter  20 value 89.889277
iter  30 value 86.571807
iter  40 value 85.452709
iter  50 value 83.209483
iter  60 value 82.152048
iter  70 value 81.249361
iter  80 value 80.707922
iter  90 value 80.505593
iter 100 value 80.484004
final  value 80.484004 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.866072 
iter  10 value 94.558364
iter  20 value 93.677741
iter  30 value 86.718509
iter  40 value 85.415042
iter  50 value 84.607684
iter  60 value 84.073754
iter  70 value 82.231362
iter  80 value 81.504618
iter  90 value 81.148348
iter 100 value 81.050440
final  value 81.050440 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 126.483737 
iter  10 value 94.450900
iter  20 value 91.400959
iter  30 value 87.278875
iter  40 value 85.945176
iter  50 value 85.579638
iter  60 value 85.353035
iter  70 value 84.719754
iter  80 value 83.267733
iter  90 value 81.600546
iter 100 value 80.968155
final  value 80.968155 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.401655 
iter  10 value 96.766090
iter  20 value 92.977454
iter  30 value 87.918798
iter  40 value 86.400468
iter  50 value 85.186809
iter  60 value 82.318184
iter  70 value 81.809052
iter  80 value 81.331028
iter  90 value 81.067054
iter 100 value 80.693523
final  value 80.693523 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.496322 
final  value 94.277117 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.249871 
final  value 94.485846 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.349382 
iter  10 value 94.485927
final  value 94.484225 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.815563 
iter  10 value 94.485861
iter  20 value 94.484229
iter  30 value 93.185893
iter  40 value 91.324029
final  value 91.322724 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.448643 
final  value 94.485892 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.828326 
iter  10 value 94.491614
iter  20 value 94.491110
iter  30 value 94.487797
iter  40 value 94.396282
iter  50 value 88.701743
iter  60 value 88.641895
iter  70 value 88.624014
iter  80 value 88.591084
iter  90 value 88.586027
iter 100 value 88.223099
final  value 88.223099 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.387479 
iter  10 value 94.488990
iter  20 value 92.207475
iter  30 value 85.101028
iter  40 value 85.097411
iter  50 value 85.096242
iter  60 value 85.093757
iter  70 value 85.093170
iter  80 value 84.862166
iter  90 value 82.884058
iter 100 value 80.538636
final  value 80.538636 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 98.004609 
iter  10 value 91.074341
iter  20 value 91.065378
iter  30 value 90.535717
iter  40 value 90.533284
iter  50 value 90.533048
iter  60 value 90.532283
final  value 90.532232 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.665316 
iter  10 value 93.927555
iter  20 value 93.926004
iter  30 value 93.925160
iter  30 value 93.925160
final  value 93.925160 
converged
Fitting Repeat 5 

# weights:  305
initial  value 127.962429 
iter  10 value 94.489296
iter  20 value 92.896161
iter  30 value 86.467027
iter  40 value 80.174688
iter  50 value 79.885705
iter  60 value 79.840273
iter  70 value 79.783245
iter  80 value 79.732446
iter  90 value 79.697143
iter 100 value 79.695571
final  value 79.695571 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 97.731284 
iter  10 value 94.491805
iter  20 value 94.484254
iter  30 value 94.221494
iter  40 value 85.611125
iter  50 value 85.276461
iter  60 value 85.253964
iter  70 value 85.253446
iter  70 value 85.253446
final  value 85.253446 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.365952 
iter  10 value 94.445052
iter  20 value 92.879978
final  value 89.145046 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.563237 
iter  10 value 93.989213
iter  20 value 93.896062
iter  30 value 93.842485
iter  40 value 93.496477
iter  50 value 90.273140
iter  60 value 89.848928
iter  70 value 89.817761
iter  80 value 89.815580
iter  90 value 89.398045
iter 100 value 89.309349
final  value 89.309349 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 114.035837 
iter  10 value 93.106521
iter  20 value 93.102474
iter  30 value 85.068389
iter  40 value 85.053323
iter  50 value 85.051528
iter  60 value 85.036791
iter  70 value 83.219457
iter  80 value 83.214129
iter  90 value 83.210484
iter 100 value 83.040467
final  value 83.040467 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 95.142364 
iter  10 value 94.491091
iter  20 value 93.248211
iter  30 value 91.871683
iter  40 value 85.890325
iter  50 value 82.782058
iter  60 value 82.427782
iter  70 value 81.466242
iter  80 value 80.609524
iter  90 value 80.552049
iter 100 value 80.550799
final  value 80.550799 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.881021 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.635111 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.914784 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.899065 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.133356 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.736307 
iter  10 value 94.386930
iter  20 value 94.385584
iter  20 value 94.385584
iter  20 value 94.385584
final  value 94.385584 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.382379 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.472885 
iter  10 value 94.392008
final  value 94.391992 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.943635 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.438111 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.717648 
iter  10 value 94.432114
final  value 94.428837 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.621988 
final  value 94.445714 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.431681 
final  value 94.428839 
converged
Fitting Repeat 4 

# weights:  507
initial  value 116.575490 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.770550 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.141536 
iter  10 value 94.455409
iter  20 value 88.526384
iter  30 value 88.291688
iter  40 value 88.215841
iter  50 value 87.806815
iter  60 value 86.864562
iter  70 value 82.957989
iter  80 value 82.890851
iter  90 value 82.854522
iter 100 value 82.542205
final  value 82.542205 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 103.104122 
iter  10 value 94.513702
iter  20 value 94.486276
iter  30 value 94.237671
iter  40 value 90.901505
iter  50 value 85.617240
iter  60 value 84.843109
iter  70 value 84.398598
iter  80 value 83.982598
iter  90 value 83.954304
iter 100 value 83.858067
final  value 83.858067 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 111.800562 
iter  10 value 94.478948
iter  20 value 93.236325
iter  30 value 86.171015
iter  40 value 84.602695
iter  50 value 84.171414
iter  60 value 83.943952
iter  70 value 83.858372
iter  80 value 83.833096
final  value 83.833079 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.366125 
iter  10 value 94.626359
iter  20 value 84.345357
iter  30 value 82.939139
iter  40 value 82.608699
iter  50 value 82.596463
iter  60 value 82.552074
iter  70 value 82.488250
iter  80 value 82.480163
iter  90 value 82.462742
final  value 82.462672 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.316641 
iter  10 value 92.628953
iter  20 value 84.304958
iter  30 value 84.015553
iter  40 value 83.879968
iter  50 value 83.840888
iter  60 value 83.790820
iter  60 value 83.790819
iter  60 value 83.790819
final  value 83.790819 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.616854 
iter  10 value 94.530140
iter  20 value 93.783833
iter  30 value 88.271723
iter  40 value 84.936093
iter  50 value 84.147665
iter  60 value 83.111211
iter  70 value 82.858664
iter  80 value 82.552106
iter  90 value 82.275226
iter 100 value 82.206063
final  value 82.206063 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.486880 
iter  10 value 94.535828
iter  20 value 94.458372
iter  30 value 89.720874
iter  40 value 86.939008
iter  50 value 85.909846
iter  60 value 85.496661
iter  70 value 83.977362
iter  80 value 82.041771
iter  90 value 81.240241
iter 100 value 80.694350
final  value 80.694350 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.701107 
iter  10 value 93.656299
iter  20 value 89.340307
iter  30 value 86.971188
iter  40 value 84.138055
iter  50 value 83.839363
iter  60 value 82.263904
iter  70 value 81.150582
iter  80 value 80.523167
iter  90 value 80.336071
iter 100 value 80.263631
final  value 80.263631 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.336049 
iter  10 value 94.460354
iter  20 value 93.348303
iter  30 value 90.620994
iter  40 value 86.986336
iter  50 value 83.726099
iter  60 value 82.546796
iter  70 value 82.076944
iter  80 value 81.209400
iter  90 value 80.774048
iter 100 value 80.398415
final  value 80.398415 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.901491 
iter  10 value 97.950873
iter  20 value 88.666753
iter  30 value 87.812562
iter  40 value 85.476865
iter  50 value 81.870521
iter  60 value 80.830953
iter  70 value 80.500454
iter  80 value 80.122384
iter  90 value 79.928717
iter 100 value 79.882989
final  value 79.882989 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 117.659520 
iter  10 value 94.520562
iter  20 value 85.078322
iter  30 value 83.664147
iter  40 value 82.755517
iter  50 value 82.700176
iter  60 value 82.095017
iter  70 value 81.997486
iter  80 value 81.963325
iter  90 value 81.573410
iter 100 value 81.234111
final  value 81.234111 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 121.178082 
iter  10 value 94.288019
iter  20 value 88.650090
iter  30 value 88.088004
iter  40 value 87.846476
iter  50 value 86.482252
iter  60 value 82.840596
iter  70 value 81.420692
iter  80 value 80.496118
iter  90 value 80.230934
iter 100 value 79.977596
final  value 79.977596 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.354914 
iter  10 value 94.703922
iter  20 value 94.100866
iter  30 value 86.252116
iter  40 value 83.342882
iter  50 value 82.853900
iter  60 value 82.545169
iter  70 value 81.535818
iter  80 value 81.201973
iter  90 value 81.127671
iter 100 value 81.101336
final  value 81.101336 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.179254 
iter  10 value 94.748051
iter  20 value 93.990210
iter  30 value 89.355792
iter  40 value 83.888080
iter  50 value 83.578297
iter  60 value 83.054129
iter  70 value 81.882565
iter  80 value 81.263313
iter  90 value 81.041726
iter 100 value 80.620770
final  value 80.620770 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.481822 
iter  10 value 94.368291
iter  20 value 91.475637
iter  30 value 88.220192
iter  40 value 87.300027
iter  50 value 86.074465
iter  60 value 84.608507
iter  70 value 82.816552
iter  80 value 82.284341
iter  90 value 82.072724
iter 100 value 81.990379
final  value 81.990379 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.308781 
final  value 94.485872 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.125391 
final  value 94.485734 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.368332 
iter  10 value 94.485674
iter  20 value 94.484188
iter  30 value 94.280490
iter  40 value 92.804874
iter  50 value 92.697791
iter  60 value 92.697007
iter  60 value 92.697006
iter  60 value 92.697006
final  value 92.697006 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.600973 
final  value 94.485929 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.234252 
iter  10 value 94.485877
iter  20 value 94.484255
final  value 94.484215 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.392427 
iter  10 value 94.471613
iter  20 value 94.419461
iter  30 value 94.163390
iter  40 value 87.490665
iter  50 value 85.794922
iter  60 value 85.648317
iter  70 value 85.645621
iter  80 value 85.643591
iter  90 value 85.639022
iter 100 value 85.415202
final  value 85.415202 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.180299 
iter  10 value 89.230345
iter  20 value 88.561002
iter  30 value 88.554131
final  value 88.553848 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.309738 
iter  10 value 94.486675
iter  20 value 94.478067
iter  30 value 94.077677
iter  40 value 88.424499
final  value 88.152714 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.352156 
iter  10 value 94.489424
iter  20 value 94.484641
final  value 94.484636 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.559458 
iter  10 value 94.472288
iter  20 value 94.322918
iter  30 value 93.311334
iter  40 value 86.460336
iter  50 value 85.784501
iter  60 value 85.783948
iter  70 value 85.707894
iter  80 value 85.374830
iter  80 value 85.374829
iter  80 value 85.374829
final  value 85.374829 
converged
Fitting Repeat 1 

# weights:  507
initial  value 118.607854 
iter  10 value 94.474745
iter  20 value 94.467470
final  value 94.467414 
converged
Fitting Repeat 2 

# weights:  507
initial  value 134.364287 
iter  10 value 94.497992
iter  20 value 94.467619
iter  30 value 94.103992
iter  40 value 88.761512
iter  50 value 88.429355
iter  60 value 84.711202
iter  70 value 83.917170
iter  80 value 83.875313
iter  90 value 83.863415
iter 100 value 82.794801
final  value 82.794801 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 112.276793 
iter  10 value 94.394010
iter  20 value 94.392583
iter  30 value 87.304672
iter  40 value 85.845790
iter  50 value 85.216353
iter  60 value 85.208823
iter  60 value 85.208823
final  value 85.208823 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.482680 
iter  10 value 94.474995
iter  20 value 91.991848
iter  30 value 88.120708
iter  40 value 87.311873
iter  50 value 85.806868
iter  60 value 85.174560
iter  70 value 84.215025
iter  80 value 84.032332
iter  90 value 83.978941
iter 100 value 82.617055
final  value 82.617055 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 102.275068 
iter  10 value 94.474983
iter  20 value 94.370153
iter  30 value 94.345393
iter  40 value 91.369026
iter  50 value 81.027276
iter  60 value 80.725567
iter  70 value 80.666077
iter  80 value 80.632102
final  value 80.632051 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.361287 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.266418 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.678587 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.152349 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.785451 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.284221 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.813145 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.658458 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.025541 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.809573 
final  value 93.900000 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.185841 
final  value 93.288889 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.842157 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.380730 
iter  10 value 93.312211
iter  20 value 93.300326
iter  30 value 93.299763
final  value 93.299758 
converged
Fitting Repeat 4 

# weights:  507
initial  value 113.441250 
final  value 94.011561 
converged
Fitting Repeat 5 

# weights:  507
initial  value 123.353916 
iter  10 value 93.370426
iter  20 value 93.330516
final  value 93.330102 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.458302 
iter  10 value 94.042914
iter  20 value 87.823056
iter  30 value 84.722996
iter  40 value 84.654889
iter  50 value 84.616411
final  value 84.591595 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.571497 
iter  10 value 94.056845
iter  20 value 93.795490
iter  30 value 84.741724
iter  40 value 84.342531
iter  50 value 83.429846
iter  60 value 82.576074
iter  70 value 81.951298
iter  80 value 81.826456
final  value 81.826433 
converged
Fitting Repeat 3 

# weights:  103
initial  value 108.951755 
iter  10 value 93.984481
iter  20 value 92.603649
iter  30 value 91.181463
iter  40 value 90.763088
iter  50 value 84.509645
iter  60 value 83.733648
iter  70 value 82.983371
iter  80 value 82.423567
iter  90 value 82.031229
iter 100 value 81.827514
final  value 81.827514 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 106.904769 
iter  10 value 94.070405
iter  20 value 94.019610
iter  30 value 92.470337
iter  40 value 92.071918
iter  50 value 91.725878
iter  60 value 90.908700
iter  70 value 90.766405
iter  80 value 87.780445
iter  90 value 87.338812
iter 100 value 85.452315
final  value 85.452315 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 104.064139 
iter  10 value 93.595002
iter  20 value 90.281960
iter  30 value 85.319734
iter  40 value 84.873709
iter  50 value 84.123150
iter  60 value 83.402693
iter  70 value 82.702632
iter  80 value 82.144029
iter  90 value 81.869215
iter 100 value 81.660226
final  value 81.660226 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 102.763361 
iter  10 value 94.079441
iter  20 value 87.441916
iter  30 value 84.050842
iter  40 value 83.597932
iter  50 value 82.224011
iter  60 value 81.941293
iter  70 value 81.285741
iter  80 value 80.855723
iter  90 value 80.770835
iter 100 value 80.758976
final  value 80.758976 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 139.672813 
iter  10 value 93.915566
iter  20 value 88.543778
iter  30 value 84.648870
iter  40 value 84.210838
iter  50 value 82.759142
iter  60 value 82.421070
iter  70 value 82.084891
iter  80 value 81.680182
iter  90 value 81.666464
iter 100 value 81.651098
final  value 81.651098 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 114.452657 
iter  10 value 94.204830
iter  20 value 88.323560
iter  30 value 88.073152
iter  40 value 87.558325
iter  50 value 85.115472
iter  60 value 83.678634
iter  70 value 82.115475
iter  80 value 80.880684
iter  90 value 80.544553
iter 100 value 80.209638
final  value 80.209638 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 123.184397 
iter  10 value 94.058649
iter  20 value 93.269343
iter  30 value 87.230179
iter  40 value 84.807185
iter  50 value 84.055442
iter  60 value 83.161014
iter  70 value 82.703232
iter  80 value 82.434834
iter  90 value 81.862706
iter 100 value 80.898434
final  value 80.898434 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.103328 
iter  10 value 94.076930
iter  20 value 92.798992
iter  30 value 91.123478
iter  40 value 87.094938
iter  50 value 83.814271
iter  60 value 82.949613
iter  70 value 82.758019
iter  80 value 82.638152
iter  90 value 82.440945
iter 100 value 82.406417
final  value 82.406417 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.852004 
iter  10 value 94.070007
iter  20 value 87.994988
iter  30 value 85.031701
iter  40 value 83.836778
iter  50 value 83.111892
iter  60 value 82.627402
iter  70 value 82.346800
iter  80 value 81.772454
iter  90 value 80.949337
iter 100 value 80.202353
final  value 80.202353 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.763056 
iter  10 value 94.378152
iter  20 value 87.708841
iter  30 value 86.521861
iter  40 value 86.136691
iter  50 value 84.682821
iter  60 value 84.375677
iter  70 value 84.315706
iter  80 value 84.272828
iter  90 value 84.253579
iter 100 value 84.144730
final  value 84.144730 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.894610 
iter  10 value 93.280482
iter  20 value 89.546944
iter  30 value 86.277946
iter  40 value 85.294914
iter  50 value 83.314580
iter  60 value 82.194322
iter  70 value 81.997354
iter  80 value 81.730701
iter  90 value 81.027747
iter 100 value 80.567175
final  value 80.567175 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.866093 
iter  10 value 93.987431
iter  20 value 91.013111
iter  30 value 85.740585
iter  40 value 83.420076
iter  50 value 82.933618
iter  60 value 81.458011
iter  70 value 80.830805
iter  80 value 80.587018
iter  90 value 80.467231
iter 100 value 80.428486
final  value 80.428486 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.102096 
iter  10 value 92.250747
iter  20 value 86.165467
iter  30 value 85.373351
iter  40 value 81.720580
iter  50 value 80.782194
iter  60 value 80.731591
iter  70 value 80.568436
iter  80 value 80.397716
iter  90 value 80.287308
iter 100 value 80.246756
final  value 80.246756 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.367885 
final  value 94.034608 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.480182 
final  value 94.054519 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.662122 
final  value 94.054549 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.879370 
final  value 94.054376 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.754829 
iter  10 value 94.034568
iter  20 value 94.032981
iter  30 value 93.186616
iter  40 value 85.969986
iter  50 value 84.027573
iter  60 value 82.903399
iter  70 value 81.973067
iter  80 value 81.645074
iter  90 value 81.643759
iter  90 value 81.643759
final  value 81.643759 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.429299 
iter  10 value 94.037997
iter  20 value 94.033692
final  value 94.033658 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.451731 
iter  10 value 94.057778
iter  20 value 94.042366
iter  30 value 86.199385
iter  40 value 84.856051
iter  50 value 84.838767
final  value 84.838558 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.039966 
iter  10 value 93.651991
iter  20 value 92.007103
iter  30 value 88.949363
iter  40 value 88.927744
iter  50 value 88.925514
iter  60 value 87.713937
iter  70 value 84.809418
iter  80 value 83.228648
iter  90 value 83.170379
iter 100 value 83.164389
final  value 83.164389 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.580848 
iter  10 value 94.057931
iter  20 value 94.052961
iter  30 value 86.274041
iter  40 value 85.422068
iter  50 value 84.182493
iter  60 value 83.459487
iter  70 value 82.771102
iter  80 value 81.421560
iter  90 value 81.093505
iter 100 value 80.983761
final  value 80.983761 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 95.389422 
iter  10 value 94.057518
iter  20 value 93.977838
iter  30 value 93.558802
iter  40 value 93.072694
iter  50 value 93.030877
final  value 93.029465 
converged
Fitting Repeat 1 

# weights:  507
initial  value 117.582146 
iter  10 value 92.891798
iter  20 value 90.791982
iter  30 value 90.742710
iter  40 value 90.679533
iter  50 value 90.678902
iter  60 value 90.672995
iter  70 value 90.672349
final  value 90.672199 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.295604 
iter  10 value 94.040685
iter  20 value 93.671565
iter  30 value 85.377904
final  value 85.376777 
converged
Fitting Repeat 3 

# weights:  507
initial  value 116.164910 
iter  10 value 93.732855
iter  20 value 92.704168
iter  30 value 88.472940
iter  40 value 87.441636
iter  50 value 86.793200
iter  60 value 86.618896
iter  70 value 86.616961
iter  80 value 86.608570
iter  90 value 82.693007
iter 100 value 80.921837
final  value 80.921837 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 99.736571 
iter  10 value 94.040890
iter  20 value 94.034644
iter  30 value 93.112018
iter  40 value 86.414421
iter  50 value 84.590464
iter  60 value 83.917017
iter  70 value 83.767972
final  value 83.764977 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.053548 
iter  10 value 90.285183
iter  20 value 90.024389
iter  30 value 89.996494
iter  30 value 89.996493
final  value 89.996493 
converged
Fitting Repeat 1 

# weights:  103
initial  value 94.151326 
final  value 94.032967 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.719023 
final  value 94.032967 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.674788 
final  value 94.032967 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.929020 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.849235 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.366594 
iter  10 value 93.670692
iter  20 value 93.521107
final  value 93.324531 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.934282 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.152156 
final  value 93.278282 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.312023 
final  value 94.032967 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.422194 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.872143 
iter  10 value 93.697274
final  value 93.697146 
converged
Fitting Repeat 2 

# weights:  507
initial  value 119.850182 
final  value 94.052911 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.171892 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 112.500593 
iter  10 value 86.427024
iter  20 value 84.398755
iter  30 value 84.395292
final  value 84.395208 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.262189 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 106.429200 
iter  10 value 93.372946
iter  20 value 92.964950
iter  30 value 92.949581
iter  40 value 92.931808
final  value 92.931272 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.752061 
iter  10 value 94.055188
iter  20 value 93.994414
iter  30 value 91.318150
iter  40 value 89.246091
iter  50 value 86.661873
iter  60 value 86.147594
iter  70 value 84.234411
iter  80 value 82.695435
iter  90 value 82.628405
final  value 82.627433 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.123682 
iter  10 value 94.056690
iter  20 value 93.382250
iter  30 value 89.834315
iter  40 value 87.924829
iter  50 value 85.694516
iter  60 value 85.554201
iter  70 value 85.449225
iter  80 value 85.227510
iter  90 value 85.145830
final  value 85.142789 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.181031 
iter  10 value 93.934190
iter  20 value 91.212619
iter  30 value 90.259283
iter  40 value 86.325140
iter  50 value 85.508082
iter  60 value 84.811076
iter  70 value 83.286787
iter  80 value 83.193101
iter  90 value 83.093146
iter 100 value 82.991096
final  value 82.991096 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 103.907701 
iter  10 value 94.003324
iter  20 value 89.129462
iter  30 value 87.359691
iter  40 value 85.999133
iter  50 value 85.891965
iter  60 value 85.342301
iter  70 value 85.164918
final  value 85.142787 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.541469 
iter  10 value 93.690893
iter  20 value 89.600182
iter  30 value 86.311783
iter  40 value 85.571039
iter  50 value 85.256115
iter  60 value 84.958439
iter  70 value 83.261192
iter  80 value 82.814580
iter  90 value 81.621802
iter 100 value 81.361393
final  value 81.361393 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.289187 
iter  10 value 93.914078
iter  20 value 93.185835
iter  30 value 86.400743
iter  40 value 84.096358
iter  50 value 83.628034
iter  60 value 83.167323
iter  70 value 82.906719
iter  80 value 82.799487
iter  90 value 82.729973
iter 100 value 82.622636
final  value 82.622636 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.514934 
iter  10 value 90.840236
iter  20 value 86.523047
iter  30 value 85.895262
iter  40 value 85.674225
iter  50 value 84.049476
iter  60 value 82.687789
iter  70 value 82.198926
iter  80 value 81.957681
iter  90 value 81.924261
iter 100 value 81.693161
final  value 81.693161 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 111.334275 
iter  10 value 94.133105
iter  20 value 91.496460
iter  30 value 90.524289
iter  40 value 86.463216
iter  50 value 85.968341
iter  60 value 85.507672
iter  70 value 85.164471
iter  80 value 85.035829
iter  90 value 85.016568
iter 100 value 84.964297
final  value 84.964297 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.115406 
iter  10 value 93.011208
iter  20 value 88.209159
iter  30 value 87.575974
iter  40 value 87.318974
iter  50 value 87.211994
iter  60 value 85.655796
iter  70 value 84.224357
iter  80 value 83.838321
iter  90 value 82.908802
iter 100 value 82.553606
final  value 82.553606 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.410796 
iter  10 value 94.129375
iter  20 value 93.934595
iter  30 value 89.855843
iter  40 value 85.620130
iter  50 value 85.230011
iter  60 value 83.614772
iter  70 value 83.315706
iter  80 value 83.074417
iter  90 value 82.042615
iter 100 value 81.244389
final  value 81.244389 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 134.314659 
iter  10 value 93.749015
iter  20 value 86.739069
iter  30 value 85.235501
iter  40 value 82.804994
iter  50 value 82.371976
iter  60 value 82.097518
iter  70 value 81.660657
iter  80 value 81.009105
iter  90 value 80.870352
iter 100 value 80.824292
final  value 80.824292 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.616807 
iter  10 value 94.443287
iter  20 value 90.907668
iter  30 value 87.365082
iter  40 value 86.344220
iter  50 value 85.981145
iter  60 value 84.851976
iter  70 value 84.063953
iter  80 value 83.882634
iter  90 value 83.730104
iter 100 value 83.372389
final  value 83.372389 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.210348 
iter  10 value 94.118417
iter  20 value 89.346448
iter  30 value 85.379543
iter  40 value 85.052214
iter  50 value 84.838886
iter  60 value 84.685229
iter  70 value 84.153061
iter  80 value 82.464553
iter  90 value 82.196754
iter 100 value 81.929667
final  value 81.929667 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 114.260048 
iter  10 value 94.364573
iter  20 value 90.487977
iter  30 value 86.876439
iter  40 value 85.922164
iter  50 value 85.056000
iter  60 value 84.917329
iter  70 value 84.901086
iter  80 value 84.752058
iter  90 value 84.254232
iter 100 value 83.040755
final  value 83.040755 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 120.754834 
final  value 94.054292 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.944832 
final  value 94.054716 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.539240 
final  value 94.054423 
converged
Fitting Repeat 4 

# weights:  103
initial  value 111.883414 
final  value 94.054278 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.047841 
final  value 94.054530 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.933129 
iter  10 value 94.055336
iter  20 value 94.052949
iter  20 value 94.052948
iter  20 value 94.052948
final  value 94.052948 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.256016 
iter  10 value 94.080255
iter  20 value 94.056391
iter  30 value 89.077372
iter  40 value 87.078208
iter  50 value 85.712984
iter  60 value 85.568272
iter  70 value 83.864807
iter  80 value 83.259493
iter  90 value 83.223556
iter 100 value 83.219709
final  value 83.219709 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 110.340996 
iter  10 value 88.221659
iter  20 value 85.085562
iter  30 value 84.835819
iter  40 value 84.834296
iter  50 value 84.831495
iter  60 value 84.829669
iter  60 value 84.829669
final  value 84.829669 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.004616 
iter  10 value 94.057202
iter  20 value 93.413031
iter  30 value 85.461557
iter  40 value 85.266413
iter  50 value 85.266039
final  value 85.265615 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.806555 
iter  10 value 91.800624
iter  20 value 84.909361
iter  30 value 84.908234
iter  40 value 84.873880
iter  50 value 84.860911
iter  60 value 84.860277
iter  70 value 84.859742
iter  80 value 84.295650
iter  90 value 83.972085
iter 100 value 83.971808
final  value 83.971808 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 102.061306 
iter  10 value 94.040711
iter  20 value 94.034183
iter  30 value 88.030394
iter  40 value 84.875828
iter  50 value 84.840926
iter  60 value 84.349517
iter  70 value 83.863300
iter  80 value 82.002713
iter  90 value 81.305164
iter 100 value 81.197738
final  value 81.197738 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 100.772601 
iter  10 value 94.041671
iter  20 value 91.550525
iter  30 value 86.621146
iter  40 value 86.557886
iter  50 value 86.554685
iter  60 value 85.290309
final  value 85.266251 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.559002 
iter  10 value 93.286676
iter  20 value 93.241772
iter  30 value 92.247685
iter  40 value 91.751551
iter  50 value 91.723330
final  value 91.723062 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.348040 
iter  10 value 94.054321
final  value 94.033391 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.772218 
iter  10 value 94.040853
iter  20 value 93.391558
iter  30 value 86.840975
iter  40 value 86.728578
iter  50 value 86.275522
iter  60 value 86.099975
iter  70 value 84.965755
iter  80 value 84.251631
iter  90 value 83.908590
iter 100 value 83.860677
final  value 83.860677 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.391082 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.806767 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 113.247789 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.890087 
iter  10 value 91.209947
final  value 91.088745 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.068062 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.372811 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 111.911152 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 109.083082 
iter  10 value 93.490971
final  value 93.490686 
converged
Fitting Repeat 4 

# weights:  305
initial  value 110.015504 
iter  10 value 92.303922
iter  20 value 92.300971
final  value 92.149580 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.167455 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.387091 
iter  10 value 93.773011
final  value 93.772973 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.999772 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.856388 
iter  10 value 93.773113
final  value 93.772973 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.077543 
iter  10 value 93.722181
final  value 93.720301 
converged
Fitting Repeat 5 

# weights:  507
initial  value 119.466080 
iter  10 value 93.551526
final  value 93.551515 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.708685 
iter  10 value 94.495558
iter  20 value 85.924686
iter  30 value 82.962748
iter  40 value 82.251092
iter  50 value 82.224290
iter  60 value 82.159411
iter  70 value 82.139214
iter  70 value 82.139214
iter  70 value 82.139214
final  value 82.139214 
converged
Fitting Repeat 2 

# weights:  103
initial  value 112.825846 
iter  10 value 94.488307
iter  20 value 94.486678
iter  30 value 92.582675
iter  40 value 85.984461
iter  50 value 84.692860
iter  60 value 83.204869
iter  70 value 82.340267
iter  80 value 81.847252
iter  90 value 81.833730
final  value 81.833726 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.886055 
iter  10 value 93.663277
iter  20 value 89.993595
iter  30 value 84.756538
iter  40 value 84.458859
iter  50 value 83.299441
iter  60 value 83.246856
iter  70 value 83.235437
iter  80 value 83.178407
iter  90 value 79.866716
iter 100 value 78.530147
final  value 78.530147 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 101.781249 
iter  10 value 94.440862
iter  20 value 93.753389
iter  30 value 92.817435
iter  40 value 87.049594
iter  50 value 86.234257
iter  60 value 85.731619
iter  70 value 83.325761
iter  80 value 82.612681
iter  90 value 81.994989
iter 100 value 81.851723
final  value 81.851723 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 98.661126 
iter  10 value 94.197561
iter  20 value 90.152425
iter  30 value 89.581995
iter  40 value 89.524096
iter  50 value 89.504544
iter  60 value 89.503384
final  value 89.503219 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.416181 
iter  10 value 94.162681
iter  20 value 93.783425
iter  30 value 93.698912
iter  40 value 93.458269
iter  50 value 92.112487
iter  60 value 88.469591
iter  70 value 85.792368
iter  80 value 85.070007
iter  90 value 82.725758
iter 100 value 82.145355
final  value 82.145355 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.282992 
iter  10 value 94.173307
iter  20 value 93.896402
iter  30 value 87.493270
iter  40 value 85.575952
iter  50 value 85.199056
iter  60 value 84.524185
iter  70 value 83.884100
iter  80 value 82.587183
iter  90 value 81.454309
iter 100 value 81.184108
final  value 81.184108 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.871902 
iter  10 value 94.171731
iter  20 value 93.285195
iter  30 value 87.357487
iter  40 value 87.098384
iter  50 value 81.814673
iter  60 value 80.329646
iter  70 value 80.144865
iter  80 value 79.586868
iter  90 value 79.304167
iter 100 value 78.438766
final  value 78.438766 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.132539 
iter  10 value 94.480707
iter  20 value 84.088481
iter  30 value 83.821215
iter  40 value 82.402552
iter  50 value 82.047272
iter  60 value 81.871500
iter  70 value 81.601802
iter  80 value 81.218806
iter  90 value 78.880415
iter 100 value 78.295644
final  value 78.295644 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.125208 
iter  10 value 94.376917
iter  20 value 83.974098
iter  30 value 80.960449
iter  40 value 79.939357
iter  50 value 79.362851
iter  60 value 79.140930
iter  70 value 79.109261
iter  80 value 79.086236
iter  90 value 78.988384
iter 100 value 78.912633
final  value 78.912633 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 116.808682 
iter  10 value 96.136628
iter  20 value 95.204679
iter  30 value 94.598544
iter  40 value 87.041145
iter  50 value 84.993883
iter  60 value 83.789300
iter  70 value 82.142093
iter  80 value 80.489461
iter  90 value 78.023394
iter 100 value 77.792535
final  value 77.792535 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.708853 
iter  10 value 99.095144
iter  20 value 88.926972
iter  30 value 86.463060
iter  40 value 82.028950
iter  50 value 79.950828
iter  60 value 79.078896
iter  70 value 78.908738
iter  80 value 78.752718
iter  90 value 78.473478
iter 100 value 78.306098
final  value 78.306098 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.073733 
iter  10 value 94.574582
iter  20 value 92.833103
iter  30 value 89.460491
iter  40 value 82.214688
iter  50 value 80.197606
iter  60 value 79.705392
iter  70 value 79.180427
iter  80 value 79.079849
iter  90 value 78.898222
iter 100 value 78.644339
final  value 78.644339 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 119.370518 
iter  10 value 94.487142
iter  20 value 82.830263
iter  30 value 81.969529
iter  40 value 80.630181
iter  50 value 79.286445
iter  60 value 78.569337
iter  70 value 77.879002
iter  80 value 77.649324
iter  90 value 77.481876
iter 100 value 77.432102
final  value 77.432102 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.238762 
iter  10 value 94.492052
iter  20 value 90.785468
iter  30 value 83.638729
iter  40 value 82.956414
iter  50 value 82.272167
iter  60 value 79.330218
iter  70 value 79.190003
iter  80 value 79.122466
iter  90 value 79.082087
iter 100 value 79.025394
final  value 79.025394 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 109.003299 
final  value 94.485671 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.881332 
final  value 94.485668 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.946554 
final  value 94.485826 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.575917 
final  value 94.485693 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.710254 
iter  10 value 93.775069
iter  20 value 93.774826
iter  30 value 93.745220
iter  40 value 91.651406
iter  50 value 83.885842
iter  60 value 82.159228
iter  70 value 82.001024
iter  80 value 81.930308
iter  90 value 81.929399
iter 100 value 81.928699
final  value 81.928699 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 111.359350 
iter  10 value 80.601417
iter  20 value 79.845937
iter  30 value 79.843691
iter  40 value 79.608899
iter  50 value 79.557555
final  value 79.557483 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.129374 
iter  10 value 93.778581
iter  20 value 93.764198
iter  30 value 93.490392
iter  40 value 93.461217
iter  50 value 81.542655
iter  60 value 78.721336
iter  70 value 77.655610
iter  80 value 77.518920
iter  90 value 77.393957
iter 100 value 77.305545
final  value 77.305545 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.840429 
iter  10 value 93.765085
iter  20 value 93.725576
iter  30 value 93.721332
final  value 93.720740 
converged
Fitting Repeat 4 

# weights:  305
initial  value 109.162651 
iter  10 value 94.488407
iter  20 value 94.484223
iter  30 value 92.815954
iter  40 value 85.902916
iter  50 value 85.616210
iter  60 value 85.560163
iter  70 value 83.120409
iter  80 value 82.966660
iter  90 value 82.833638
iter 100 value 81.708576
final  value 81.708576 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 96.269402 
iter  10 value 94.487947
iter  20 value 92.051480
iter  30 value 87.297554
iter  40 value 87.166469
iter  50 value 87.166120
iter  60 value 85.556098
iter  70 value 85.534985
iter  80 value 83.123966
iter  90 value 82.814092
iter 100 value 82.812500
final  value 82.812500 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.337841 
iter  10 value 94.493642
iter  20 value 94.484933
iter  30 value 94.067471
iter  40 value 87.170782
iter  50 value 86.863908
iter  60 value 86.858906
iter  70 value 85.538465
iter  80 value 83.270653
iter  90 value 82.697123
final  value 82.690114 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.691433 
iter  10 value 93.783734
iter  20 value 93.778505
iter  30 value 93.543757
iter  40 value 93.543309
final  value 93.542805 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.702684 
iter  10 value 93.782272
iter  20 value 93.774853
iter  30 value 82.824014
iter  40 value 80.884321
iter  50 value 80.615401
iter  60 value 80.608749
final  value 80.608714 
converged
Fitting Repeat 4 

# weights:  507
initial  value 107.818044 
iter  10 value 93.728639
iter  20 value 93.721869
iter  30 value 93.634540
iter  40 value 89.850266
iter  50 value 84.290842
iter  60 value 79.712040
iter  70 value 79.150523
iter  80 value 78.387946
iter  90 value 77.740276
iter 100 value 77.739575
final  value 77.739575 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 125.767840 
iter  10 value 91.985858
iter  20 value 91.973455
iter  30 value 91.888241
iter  40 value 91.886282
iter  50 value 91.885375
iter  60 value 90.408593
iter  70 value 90.183607
iter  80 value 90.175553
iter  90 value 90.158024
iter 100 value 90.155365
final  value 90.155365 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 134.497310 
iter  10 value 117.899218
iter  20 value 117.881193
iter  30 value 105.571469
final  value 104.908393 
converged
Fitting Repeat 2 

# weights:  507
initial  value 122.947398 
iter  10 value 117.676975
iter  20 value 117.674787
iter  30 value 117.460683
iter  40 value 116.926354
iter  50 value 116.713751
iter  60 value 116.712484
iter  70 value 116.712370
final  value 116.712352 
converged
Fitting Repeat 3 

# weights:  507
initial  value 133.182315 
iter  10 value 117.775666
iter  20 value 117.634431
iter  30 value 117.554038
iter  40 value 117.532349
final  value 117.528375 
converged
Fitting Repeat 4 

# weights:  507
initial  value 120.184356 
iter  10 value 117.778544
iter  20 value 117.760919
final  value 117.728652 
converged
Fitting Repeat 5 

# weights:  507
initial  value 121.763866 
iter  10 value 117.893625
iter  20 value 117.571837
iter  30 value 114.381257
iter  40 value 104.337840
iter  50 value 104.265842
iter  60 value 103.058689
iter  70 value 102.043389
iter  80 value 102.026494
iter  90 value 102.015131
iter 100 value 102.006781
final  value 102.006781 
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 -- Mon Jul 22 01:22:33 2024 
*********************************************** 
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 
Warning messages:
1: `repeats` has no meaning for this resampling method. 
2: executing %dopar% sequentially: no parallel backend registered 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
 41.686   2.087  42.671