##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:HPiP.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings HPiP_1.10.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck’
* using R version 4.4.0 (2024-04-24)
* using platform: x86_64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 12.2.0
* running under: macOS Monterey 12.7.1
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.10.0’
* 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 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       34.745  1.808  36.762
FSmethod      33.184  1.798  35.098
corr_plot     33.195  1.680  34.986
pred_ensembel 13.744  0.506  10.159
enrichfindP    0.449  0.061   8.823
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

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

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


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library’
* installing *source* package ‘HPiP’ ...
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R version 4.4.0 (2024-04-24) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20

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

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

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

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

# weights:  103
initial  value 98.158285 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.802788 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.471831 
final  value 93.915746 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.383071 
iter  10 value 93.873759
final  value 93.873028 
converged
Fitting Repeat 5 

# weights:  103
initial  value 115.645371 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.367596 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.297565 
final  value 93.915746 
converged
Fitting Repeat 3 

# weights:  305
initial  value 108.328088 
iter  10 value 93.264204
iter  20 value 92.332967
iter  30 value 92.331664
final  value 92.331645 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.023805 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.570715 
iter  10 value 94.053352
final  value 94.052911 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.038836 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 110.678308 
final  value 93.511561 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.090910 
iter  10 value 87.852327
iter  20 value 86.872207
iter  30 value 86.872036
final  value 86.872031 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.957840 
final  value 93.697740 
converged
Fitting Repeat 5 

# weights:  507
initial  value 123.312580 
final  value 93.915746 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.286069 
iter  10 value 94.013634
iter  20 value 91.570867
iter  30 value 90.921915
iter  40 value 88.682066
iter  50 value 86.546398
iter  60 value 85.752856
iter  70 value 85.715725
iter  80 value 85.714121
iter  80 value 85.714120
iter  80 value 85.714120
final  value 85.714120 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.232323 
iter  10 value 93.942246
iter  20 value 89.467438
iter  30 value 88.986877
iter  40 value 88.773814
iter  50 value 86.256907
iter  60 value 85.184216
iter  70 value 84.264328
iter  80 value 83.818990
iter  90 value 83.736969
iter 100 value 83.678369
final  value 83.678369 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.245363 
iter  10 value 94.051360
iter  20 value 88.646019
iter  30 value 87.217344
iter  40 value 86.825577
iter  50 value 86.642767
iter  60 value 86.023312
iter  70 value 85.718244
final  value 85.714120 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.175922 
iter  10 value 94.056335
iter  20 value 93.137382
iter  30 value 91.604055
iter  40 value 88.459231
iter  50 value 85.856667
iter  60 value 85.548190
iter  70 value 84.611951
iter  80 value 84.327185
iter  90 value 84.265519
iter 100 value 84.239113
final  value 84.239113 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 100.740793 
iter  10 value 93.862607
iter  20 value 89.308360
iter  30 value 89.065611
iter  40 value 89.011476
iter  50 value 88.728845
iter  60 value 86.060530
iter  70 value 85.881820
iter  80 value 84.728097
iter  90 value 84.330217
iter 100 value 84.208055
final  value 84.208055 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 104.621063 
iter  10 value 94.068129
iter  20 value 93.822135
iter  30 value 93.742427
iter  40 value 89.326189
iter  50 value 89.222775
iter  60 value 85.081002
iter  70 value 84.172802
iter  80 value 83.591991
iter  90 value 83.153975
iter 100 value 83.000591
final  value 83.000591 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.671860 
iter  10 value 92.249331
iter  20 value 91.552082
iter  30 value 91.328605
iter  40 value 90.423035
iter  50 value 88.168175
iter  60 value 86.719017
iter  70 value 86.026261
iter  80 value 85.508710
iter  90 value 84.830868
iter 100 value 83.995039
final  value 83.995039 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.742973 
iter  10 value 94.502583
iter  20 value 91.864063
iter  30 value 85.053329
iter  40 value 83.736974
iter  50 value 83.511527
iter  60 value 83.226140
iter  70 value 83.211401
iter  80 value 83.145491
iter  90 value 83.119164
iter 100 value 83.101790
final  value 83.101790 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.159968 
iter  10 value 94.061491
iter  20 value 86.921058
iter  30 value 85.456981
iter  40 value 84.129751
iter  50 value 83.376021
iter  60 value 83.076176
iter  70 value 82.681587
iter  80 value 82.457843
iter  90 value 82.424100
iter 100 value 82.418357
final  value 82.418357 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.232851 
iter  10 value 94.025168
iter  20 value 92.973335
iter  30 value 86.056345
iter  40 value 84.713356
iter  50 value 83.367213
iter  60 value 82.904716
iter  70 value 82.697570
iter  80 value 82.507908
iter  90 value 82.336451
iter 100 value 82.239324
final  value 82.239324 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.362888 
iter  10 value 94.056048
iter  20 value 86.039621
iter  30 value 85.665703
iter  40 value 84.427912
iter  50 value 83.849088
iter  60 value 83.144665
iter  70 value 82.869798
iter  80 value 82.689361
iter  90 value 82.646447
iter 100 value 82.589017
final  value 82.589017 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.535350 
iter  10 value 91.680774
iter  20 value 87.162451
iter  30 value 86.058356
iter  40 value 85.574734
iter  50 value 84.871569
iter  60 value 83.863730
iter  70 value 83.142768
iter  80 value 82.883905
iter  90 value 82.711285
iter 100 value 82.584827
final  value 82.584827 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.575302 
iter  10 value 93.280111
iter  20 value 92.470847
iter  30 value 90.444371
iter  40 value 86.065163
iter  50 value 85.019368
iter  60 value 84.539488
iter  70 value 83.679043
iter  80 value 83.250118
iter  90 value 83.025714
iter 100 value 82.644592
final  value 82.644592 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.362537 
iter  10 value 93.954517
iter  20 value 87.937939
iter  30 value 86.843202
iter  40 value 84.364973
iter  50 value 83.645174
iter  60 value 83.240986
iter  70 value 82.894885
iter  80 value 82.680082
iter  90 value 82.531835
iter 100 value 82.414400
final  value 82.414400 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 132.294727 
iter  10 value 93.696932
iter  20 value 88.417370
iter  30 value 86.338600
iter  40 value 85.315610
iter  50 value 84.667456
iter  60 value 84.411005
iter  70 value 84.188150
iter  80 value 83.995148
iter  90 value 83.773393
iter 100 value 83.051681
final  value 83.051681 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 116.250269 
iter  10 value 92.277973
iter  20 value 91.427474
iter  30 value 91.352936
final  value 91.352579 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.415930 
final  value 94.054639 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.579459 
final  value 94.054479 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.940955 
iter  10 value 93.917504
iter  20 value 93.891459
iter  30 value 85.055774
iter  40 value 84.922215
iter  50 value 84.442317
iter  60 value 84.074552
final  value 84.074245 
converged
Fitting Repeat 5 

# weights:  103
initial  value 118.260275 
final  value 94.054537 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.438381 
iter  10 value 94.058280
iter  20 value 94.053242
iter  30 value 92.502011
iter  40 value 87.322519
iter  50 value 85.425720
iter  60 value 85.172368
iter  70 value 85.171297
iter  70 value 85.171297
final  value 85.171297 
converged
Fitting Repeat 2 

# weights:  305
initial  value 130.032368 
iter  10 value 94.057759
iter  20 value 93.538265
iter  30 value 85.256711
final  value 85.241758 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.740326 
iter  10 value 94.062550
iter  20 value 94.047083
iter  30 value 88.365146
iter  40 value 84.882525
iter  50 value 84.154614
iter  60 value 83.910294
iter  70 value 83.377565
iter  80 value 82.470117
iter  90 value 82.234242
iter 100 value 82.232407
final  value 82.232407 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 111.297834 
iter  10 value 94.057150
iter  20 value 93.645294
iter  30 value 93.024268
iter  40 value 92.168032
iter  50 value 84.123025
iter  60 value 83.859945
iter  70 value 83.858845
iter  80 value 83.857819
iter  90 value 83.821636
iter 100 value 83.821527
final  value 83.821527 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.917783 
iter  10 value 94.057892
iter  20 value 93.814879
iter  30 value 93.697814
final  value 93.697630 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.271128 
iter  10 value 93.923698
iter  20 value 93.714741
iter  30 value 93.693135
iter  40 value 93.459870
iter  50 value 84.198049
iter  60 value 82.817405
iter  70 value 82.774981
iter  80 value 82.771283
iter  90 value 82.770961
iter 100 value 82.211596
final  value 82.211596 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 102.232694 
iter  10 value 93.649389
iter  20 value 90.384673
iter  30 value 86.105553
iter  40 value 86.029926
final  value 86.029221 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.625195 
iter  10 value 93.057399
iter  20 value 92.175381
iter  30 value 92.145690
iter  40 value 92.132047
iter  50 value 91.954714
iter  60 value 90.510174
iter  70 value 90.354288
iter  80 value 90.340573
iter  90 value 90.337605
iter 100 value 90.336985
final  value 90.336985 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 115.907730 
iter  10 value 94.059508
iter  20 value 93.822304
iter  30 value 88.559466
iter  40 value 88.025611
final  value 88.007826 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.279148 
iter  10 value 94.060888
iter  20 value 94.035760
iter  30 value 86.899059
iter  40 value 86.878026
final  value 86.877874 
converged
Fitting Repeat 1 

# weights:  103
initial  value 107.765411 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.531266 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 109.044948 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.715707 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.509433 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.611618 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.875771 
iter  10 value 93.728996
iter  20 value 93.726258
iter  30 value 93.090468
final  value 92.528601 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.906006 
final  value 94.275362 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.636989 
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.036315 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.237561 
iter  10 value 91.131380
iter  20 value 87.617901
iter  30 value 87.610929
iter  40 value 87.609555
iter  50 value 87.609464
iter  50 value 87.609464
iter  50 value 87.609464
final  value 87.609464 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.212901 
iter  10 value 94.483558
iter  20 value 92.166073
iter  30 value 91.671001
iter  40 value 91.667191
final  value 91.667169 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.040895 
final  value 93.903448 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.610190 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.425317 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 106.381681 
iter  10 value 94.490981
iter  20 value 94.305663
iter  30 value 93.582962
iter  40 value 93.370481
iter  50 value 93.346073
iter  60 value 92.438722
iter  70 value 90.758128
iter  80 value 88.059636
iter  90 value 86.390165
iter 100 value 85.196321
final  value 85.196321 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 106.258577 
iter  10 value 94.431565
iter  20 value 93.212691
iter  30 value 87.779043
iter  40 value 85.706709
iter  50 value 85.230340
iter  60 value 85.197181
iter  70 value 85.171122
iter  80 value 85.137272
iter  90 value 84.581682
iter 100 value 83.845320
final  value 83.845320 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 99.376719 
iter  10 value 94.479520
iter  20 value 90.647057
iter  30 value 85.801795
iter  40 value 84.958669
iter  50 value 84.709685
iter  60 value 84.574449
iter  70 value 84.552226
final  value 84.552216 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.306981 
iter  10 value 94.441641
iter  20 value 93.774019
iter  30 value 88.355195
iter  40 value 87.535494
iter  50 value 86.844714
iter  60 value 83.755727
iter  70 value 83.746169
final  value 83.745712 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.737808 
iter  10 value 94.480499
iter  20 value 94.017081
iter  30 value 93.778830
iter  40 value 93.669704
iter  50 value 85.563474
iter  60 value 83.625652
iter  70 value 82.657078
iter  80 value 82.042722
iter  90 value 81.529695
iter 100 value 81.370840
final  value 81.370840 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 105.704001 
iter  10 value 94.218329
iter  20 value 92.955535
iter  30 value 84.687176
iter  40 value 83.267466
iter  50 value 82.819780
iter  60 value 82.317386
iter  70 value 81.949710
iter  80 value 81.464303
iter  90 value 80.257559
iter 100 value 79.949572
final  value 79.949572 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.509838 
iter  10 value 94.487024
iter  20 value 94.452767
iter  30 value 93.716894
iter  40 value 85.151877
iter  50 value 82.512265
iter  60 value 81.972704
iter  70 value 80.657400
iter  80 value 80.077100
iter  90 value 79.862825
iter 100 value 79.707165
final  value 79.707165 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.007907 
iter  10 value 94.493922
iter  20 value 94.079364
iter  30 value 93.730254
iter  40 value 86.979887
iter  50 value 86.206289
iter  60 value 84.282979
iter  70 value 83.766964
iter  80 value 82.280913
iter  90 value 80.976124
iter 100 value 80.141567
final  value 80.141567 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 121.716789 
iter  10 value 94.770216
iter  20 value 94.546709
iter  30 value 87.762205
iter  40 value 85.687431
iter  50 value 84.533630
iter  60 value 83.950931
iter  70 value 83.541935
iter  80 value 83.487990
iter  90 value 83.033714
iter 100 value 81.937531
final  value 81.937531 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 113.458883 
iter  10 value 94.501311
iter  20 value 94.366401
iter  30 value 86.912192
iter  40 value 82.982898
iter  50 value 81.502879
iter  60 value 80.787545
iter  70 value 80.534196
iter  80 value 80.153350
iter  90 value 79.892600
iter 100 value 79.458696
final  value 79.458696 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.077012 
iter  10 value 94.494483
iter  20 value 91.726388
iter  30 value 86.352332
iter  40 value 84.022532
iter  50 value 81.566855
iter  60 value 79.880356
iter  70 value 79.515463
iter  80 value 79.277515
iter  90 value 79.014599
iter 100 value 78.814782
final  value 78.814782 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 121.339025 
iter  10 value 94.599047
iter  20 value 93.701037
iter  30 value 92.724117
iter  40 value 90.575319
iter  50 value 83.405939
iter  60 value 82.402040
iter  70 value 81.340020
iter  80 value 80.857324
iter  90 value 80.396954
iter 100 value 80.265021
final  value 80.265021 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.155621 
iter  10 value 94.549050
iter  20 value 94.342179
iter  30 value 91.605768
iter  40 value 84.202993
iter  50 value 81.362653
iter  60 value 80.881800
iter  70 value 80.612901
iter  80 value 80.385422
iter  90 value 80.040577
iter 100 value 79.580104
final  value 79.580104 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.641682 
iter  10 value 94.922281
iter  20 value 89.303107
iter  30 value 85.205043
iter  40 value 84.825426
iter  50 value 83.518173
iter  60 value 81.148512
iter  70 value 80.355854
iter  80 value 79.976319
iter  90 value 79.652931
iter 100 value 79.588415
final  value 79.588415 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.213789 
iter  10 value 95.644466
iter  20 value 85.705184
iter  30 value 84.934873
iter  40 value 83.548517
iter  50 value 82.958439
iter  60 value 81.734368
iter  70 value 81.033038
iter  80 value 80.990628
iter  90 value 80.934865
iter 100 value 80.912075
final  value 80.912075 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.416546 
final  value 94.485827 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.081729 
final  value 94.486110 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.200912 
final  value 94.485821 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.332776 
final  value 94.485706 
converged
Fitting Repeat 5 

# weights:  103
initial  value 109.284391 
iter  10 value 94.485932
iter  20 value 94.484236
iter  20 value 94.484235
iter  20 value 94.484235
final  value 94.484235 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.273900 
iter  10 value 93.256769
iter  20 value 88.320345
iter  30 value 87.093453
iter  40 value 87.000779
final  value 87.000659 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.144075 
iter  10 value 94.521627
iter  20 value 94.514166
iter  30 value 94.360160
iter  40 value 85.902964
iter  50 value 83.452072
iter  60 value 81.052758
iter  70 value 80.466223
iter  80 value 79.964524
iter  90 value 79.455208
iter 100 value 79.261010
final  value 79.261010 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.623046 
iter  10 value 94.438251
iter  20 value 92.610438
iter  30 value 91.685044
iter  40 value 87.096396
iter  50 value 85.615751
iter  60 value 84.732212
iter  70 value 84.728548
iter  80 value 84.294448
iter  90 value 84.256145
iter 100 value 84.231601
final  value 84.231601 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.002019 
iter  10 value 93.642726
iter  20 value 93.639339
iter  30 value 93.466588
iter  40 value 90.227695
iter  50 value 89.260291
iter  60 value 83.393402
iter  70 value 81.557183
iter  80 value 81.489316
final  value 81.489268 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.267767 
iter  10 value 94.110447
iter  20 value 94.100738
iter  30 value 94.085651
iter  40 value 93.655830
iter  50 value 93.474555
iter  60 value 93.439742
iter  70 value 93.335764
iter  80 value 90.371174
iter  90 value 90.028344
iter 100 value 82.180365
final  value 82.180365 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 101.048481 
iter  10 value 94.064565
iter  20 value 91.500041
iter  30 value 91.493273
iter  40 value 90.317514
iter  50 value 85.594113
iter  60 value 85.532411
iter  70 value 85.531719
iter  80 value 84.058164
iter  90 value 82.258038
iter 100 value 82.002273
final  value 82.002273 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.262133 
iter  10 value 94.492366
iter  20 value 94.484169
iter  30 value 94.048554
iter  40 value 93.550967
iter  50 value 84.427253
iter  60 value 83.866693
iter  70 value 83.864487
iter  80 value 83.863778
final  value 83.863383 
converged
Fitting Repeat 3 

# weights:  507
initial  value 126.311974 
iter  10 value 94.492858
iter  20 value 94.485737
iter  30 value 92.592191
iter  40 value 90.274116
iter  50 value 90.250474
iter  60 value 88.234137
iter  70 value 82.707073
iter  80 value 81.950653
iter  90 value 81.848077
iter 100 value 81.847605
final  value 81.847605 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 98.340918 
iter  10 value 90.975430
iter  20 value 84.280146
iter  30 value 83.781283
iter  40 value 83.774466
iter  50 value 83.771489
final  value 83.770953 
converged
Fitting Repeat 5 

# weights:  507
initial  value 112.587252 
iter  10 value 93.645206
iter  20 value 93.639308
iter  30 value 93.467893
iter  40 value 93.409677
final  value 93.409570 
converged
Fitting Repeat 1 

# weights:  103
initial  value 108.164732 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.754180 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 110.788574 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.249601 
final  value 94.484210 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.762366 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.549171 
final  value 93.813953 
converged
Fitting Repeat 2 

# weights:  305
initial  value 110.039714 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.212376 
iter  10 value 93.784514
final  value 93.783647 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.367602 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.547886 
final  value 94.275362 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.781760 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 128.605840 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.428565 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 135.819402 
iter  10 value 94.275363
iter  10 value 94.275362
iter  10 value 94.275362
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.746528 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 107.261171 
iter  10 value 94.488302
iter  20 value 93.441762
iter  30 value 90.221450
iter  40 value 87.130954
iter  50 value 84.222928
iter  60 value 83.043090
iter  70 value 81.529855
iter  80 value 80.942789
iter  90 value 80.873321
final  value 80.873267 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.960206 
iter  10 value 94.488847
iter  20 value 94.412059
iter  30 value 87.046774
iter  40 value 85.235153
iter  50 value 83.722164
iter  60 value 83.105349
iter  70 value 83.019415
iter  80 value 82.962858
final  value 82.962421 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.715448 
iter  10 value 94.487822
iter  20 value 93.304012
iter  30 value 90.159590
iter  40 value 85.817724
iter  50 value 84.659057
iter  60 value 84.395522
iter  70 value 83.356401
final  value 83.086712 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.922733 
iter  10 value 94.492388
iter  20 value 87.512456
iter  30 value 85.860707
iter  40 value 85.442173
iter  50 value 84.243984
iter  60 value 83.256038
iter  70 value 82.963551
iter  80 value 82.962423
final  value 82.962421 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.199955 
iter  10 value 94.485819
iter  20 value 88.043304
iter  30 value 87.074576
iter  40 value 86.219063
final  value 86.137350 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.147521 
iter  10 value 94.740670
iter  20 value 94.440257
iter  30 value 94.094049
iter  40 value 93.878983
iter  50 value 89.928779
iter  60 value 85.936535
iter  70 value 82.911841
iter  80 value 81.273188
iter  90 value 80.864037
iter 100 value 80.550024
final  value 80.550024 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 114.926254 
iter  10 value 94.351479
iter  20 value 91.872939
iter  30 value 88.125581
iter  40 value 85.934169
iter  50 value 85.627018
iter  60 value 83.621805
iter  70 value 83.555219
iter  80 value 83.492557
iter  90 value 83.433746
iter 100 value 82.234150
final  value 82.234150 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.011665 
iter  10 value 93.614343
iter  20 value 84.614414
iter  30 value 83.703441
iter  40 value 83.171516
iter  50 value 82.509913
iter  60 value 82.043110
iter  70 value 81.579164
iter  80 value 81.383613
iter  90 value 81.002364
iter 100 value 80.364590
final  value 80.364590 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.123084 
iter  10 value 94.837589
iter  20 value 92.076627
iter  30 value 87.428263
iter  40 value 86.965207
iter  50 value 86.485505
iter  60 value 86.339409
iter  70 value 84.283019
iter  80 value 83.054963
iter  90 value 82.635302
iter 100 value 82.368638
final  value 82.368638 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.994766 
iter  10 value 94.346284
iter  20 value 93.957102
iter  30 value 87.973189
iter  40 value 87.816391
iter  50 value 86.302638
iter  60 value 84.635325
iter  70 value 82.315665
iter  80 value 81.082253
iter  90 value 80.521449
iter 100 value 80.067017
final  value 80.067017 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 124.855640 
iter  10 value 92.149912
iter  20 value 85.256161
iter  30 value 83.353827
iter  40 value 82.822884
iter  50 value 81.596827
iter  60 value 80.929940
iter  70 value 80.457568
iter  80 value 80.338237
iter  90 value 80.306752
iter 100 value 80.209445
final  value 80.209445 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.611747 
iter  10 value 94.500156
iter  20 value 91.788743
iter  30 value 91.560819
iter  40 value 88.927710
iter  50 value 85.562257
iter  60 value 82.570818
iter  70 value 81.307125
iter  80 value 81.176553
iter  90 value 80.815688
iter 100 value 80.254096
final  value 80.254096 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.742773 
iter  10 value 94.866653
iter  20 value 93.378445
iter  30 value 87.828184
iter  40 value 85.755517
iter  50 value 84.278469
iter  60 value 83.303359
iter  70 value 82.671830
iter  80 value 81.483109
iter  90 value 81.321834
iter 100 value 80.648901
final  value 80.648901 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 120.842395 
iter  10 value 94.974164
iter  20 value 90.673450
iter  30 value 83.932110
iter  40 value 83.368386
iter  50 value 83.053351
iter  60 value 82.562938
iter  70 value 81.887020
iter  80 value 80.712171
iter  90 value 80.395594
iter 100 value 80.222052
final  value 80.222052 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.476848 
iter  10 value 94.798944
iter  20 value 88.550432
iter  30 value 88.036952
iter  40 value 83.469891
iter  50 value 80.833602
iter  60 value 80.516825
iter  70 value 80.297944
iter  80 value 80.039984
iter  90 value 79.964168
iter 100 value 79.861538
final  value 79.861538 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 108.370006 
iter  10 value 94.276901
iter  10 value 94.276900
iter  10 value 94.276900
final  value 94.276900 
converged
Fitting Repeat 2 

# weights:  103
initial  value 116.237800 
final  value 94.485771 
converged
Fitting Repeat 3 

# weights:  103
initial  value 112.785330 
final  value 94.485876 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.336500 
final  value 94.486011 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.566041 
iter  10 value 94.485874
iter  20 value 94.484124
iter  30 value 88.601409
iter  40 value 88.264918
iter  50 value 88.173339
final  value 88.169480 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.433988 
iter  10 value 85.188199
iter  20 value 85.109967
iter  30 value 84.984220
iter  40 value 84.962996
iter  50 value 84.962168
iter  60 value 84.960973
iter  70 value 84.960245
iter  70 value 84.960245
final  value 84.960245 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.110407 
iter  10 value 86.444197
iter  20 value 85.736228
iter  30 value 84.818529
iter  40 value 84.661422
iter  50 value 84.660455
iter  60 value 84.658421
iter  70 value 84.656975
iter  80 value 84.651017
iter  90 value 84.494616
final  value 84.488525 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.169562 
iter  10 value 94.280506
iter  20 value 94.276170
iter  30 value 94.125626
iter  40 value 86.556702
iter  50 value 86.510373
iter  60 value 84.557159
iter  70 value 84.528580
iter  80 value 84.525170
iter  90 value 84.524585
iter 100 value 84.306989
final  value 84.306989 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 127.635840 
iter  10 value 94.489786
iter  20 value 94.324064
iter  30 value 87.086427
iter  40 value 84.662292
iter  50 value 83.564115
iter  60 value 83.556154
iter  70 value 83.555340
iter  80 value 83.552078
iter  90 value 82.338097
iter 100 value 80.615413
final  value 80.615413 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 96.136369 
iter  10 value 93.819376
iter  20 value 93.815287
iter  30 value 93.665957
iter  40 value 85.193928
iter  50 value 84.749748
iter  60 value 84.689866
iter  70 value 84.494396
final  value 84.493740 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.327649 
iter  10 value 91.764591
iter  20 value 84.314716
iter  30 value 84.242525
iter  40 value 84.240870
iter  50 value 84.239224
iter  60 value 84.228249
iter  70 value 84.148927
iter  80 value 83.387088
iter  90 value 83.001355
iter 100 value 82.998617
final  value 82.998617 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.374387 
iter  10 value 94.492624
iter  20 value 94.441925
iter  30 value 88.048888
iter  40 value 87.860249
iter  50 value 86.872480
iter  60 value 86.826395
final  value 86.826389 
converged
Fitting Repeat 3 

# weights:  507
initial  value 122.041234 
iter  10 value 91.008523
iter  20 value 90.854254
iter  30 value 90.757839
final  value 90.737372 
converged
Fitting Repeat 4 

# weights:  507
initial  value 113.779034 
iter  10 value 94.283481
iter  20 value 93.573103
iter  30 value 83.447322
iter  40 value 82.869608
iter  50 value 80.523262
iter  60 value 79.661065
iter  70 value 79.375420
iter  80 value 79.237163
iter  90 value 78.936652
iter 100 value 78.701283
final  value 78.701283 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 96.622241 
iter  10 value 94.283503
iter  20 value 93.934709
iter  30 value 85.819913
iter  40 value 81.704237
iter  50 value 80.738381
iter  60 value 80.076122
iter  70 value 78.485437
iter  80 value 78.283043
iter  90 value 77.986238
iter 100 value 77.856677
final  value 77.856677 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 106.450705 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.887143 
final  value 94.443243 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.553614 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 113.107884 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.477697 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.012578 
final  value 94.430233 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.294563 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.229761 
iter  10 value 93.720836
iter  10 value 93.720836
iter  10 value 93.720836
final  value 93.720836 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.445000 
final  value 94.032968 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.939457 
iter  10 value 94.174634
iter  20 value 94.165770
final  value 94.165746 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.232440 
final  value 94.443243 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.588753 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 115.610869 
final  value 94.443243 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.631528 
iter  10 value 92.993716
final  value 92.929414 
converged
Fitting Repeat 5 

# weights:  507
initial  value 123.795341 
final  value 94.443243 
converged
Fitting Repeat 1 

# weights:  103
initial  value 113.637485 
iter  10 value 94.454918
iter  20 value 82.556066
iter  30 value 81.680188
iter  40 value 81.377640
iter  50 value 81.178609
iter  60 value 81.082165
iter  70 value 78.286596
iter  80 value 78.043214
final  value 78.042086 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.623181 
iter  10 value 94.490667
iter  20 value 94.287974
iter  30 value 85.177953
iter  40 value 81.981921
iter  50 value 81.379467
iter  60 value 79.506919
iter  70 value 79.487561
final  value 79.487559 
converged
Fitting Repeat 3 

# weights:  103
initial  value 108.063682 
iter  10 value 94.476780
iter  20 value 87.513065
iter  30 value 82.769055
iter  40 value 82.595550
iter  50 value 81.793055
iter  60 value 78.859659
iter  70 value 78.466368
iter  80 value 78.242629
iter  90 value 78.160551
iter 100 value 78.065151
final  value 78.065151 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.750186 
iter  10 value 88.047609
iter  20 value 81.310514
iter  30 value 78.562661
iter  40 value 78.242958
iter  50 value 78.166193
iter  60 value 78.047471
iter  70 value 78.045414
final  value 78.045342 
converged
Fitting Repeat 5 

# weights:  103
initial  value 112.790835 
iter  10 value 94.423028
iter  20 value 83.965952
iter  30 value 81.373193
iter  40 value 81.261670
iter  50 value 78.811925
iter  60 value 78.083943
final  value 78.042085 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.624160 
iter  10 value 94.547700
iter  20 value 94.427989
iter  30 value 92.203394
iter  40 value 85.163226
iter  50 value 82.157499
iter  60 value 80.702142
iter  70 value 79.473827
iter  80 value 76.484949
iter  90 value 75.988750
iter 100 value 75.457663
final  value 75.457663 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.144103 
iter  10 value 94.523941
iter  20 value 94.302859
iter  30 value 93.938094
iter  40 value 93.842959
iter  50 value 89.430284
iter  60 value 79.956221
iter  70 value 79.083397
iter  80 value 77.021313
iter  90 value 76.327326
iter 100 value 76.149481
final  value 76.149481 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 113.428741 
iter  10 value 94.442965
iter  20 value 86.497119
iter  30 value 82.297222
iter  40 value 78.856492
iter  50 value 78.039366
iter  60 value 77.515783
iter  70 value 77.283784
iter  80 value 77.027982
iter  90 value 76.847902
iter 100 value 76.777733
final  value 76.777733 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.713893 
iter  10 value 94.741744
iter  20 value 89.271517
iter  30 value 83.122591
iter  40 value 80.767970
iter  50 value 80.567181
iter  60 value 79.601162
iter  70 value 79.166695
iter  80 value 78.623853
iter  90 value 78.467980
iter 100 value 78.251649
final  value 78.251649 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.631753 
iter  10 value 94.008481
iter  20 value 82.167111
iter  30 value 79.233531
iter  40 value 78.744029
iter  50 value 77.846901
iter  60 value 76.895820
iter  70 value 76.689676
iter  80 value 76.400381
iter  90 value 76.336768
iter 100 value 76.048101
final  value 76.048101 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.089199 
iter  10 value 94.591347
iter  20 value 94.364342
iter  30 value 93.382361
iter  40 value 90.818437
iter  50 value 88.823679
iter  60 value 83.522432
iter  70 value 78.327899
iter  80 value 75.819249
iter  90 value 75.466411
iter 100 value 75.132568
final  value 75.132568 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 125.363477 
iter  10 value 94.750850
iter  20 value 93.909612
iter  30 value 83.368364
iter  40 value 81.826560
iter  50 value 79.384058
iter  60 value 78.232540
iter  70 value 77.884109
iter  80 value 77.077339
iter  90 value 76.524295
iter 100 value 75.692824
final  value 75.692824 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.247639 
iter  10 value 94.463725
iter  20 value 82.101311
iter  30 value 81.216276
iter  40 value 81.096213
iter  50 value 79.688231
iter  60 value 76.408529
iter  70 value 75.876064
iter  80 value 75.771715
iter  90 value 75.693479
iter 100 value 75.596767
final  value 75.596767 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.342023 
iter  10 value 97.770723
iter  20 value 89.260883
iter  30 value 87.224214
iter  40 value 79.386477
iter  50 value 76.425142
iter  60 value 76.063099
iter  70 value 75.919332
iter  80 value 75.785636
iter  90 value 75.697217
iter 100 value 75.692697
final  value 75.692697 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.801155 
iter  10 value 95.092202
iter  20 value 93.525566
iter  30 value 89.738826
iter  40 value 86.233205
iter  50 value 80.821698
iter  60 value 78.899777
iter  70 value 77.367805
iter  80 value 76.763147
iter  90 value 76.217028
iter 100 value 75.898083
final  value 75.898083 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.233128 
final  value 94.485951 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.158789 
final  value 94.485750 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.630068 
final  value 94.485976 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.610788 
iter  10 value 94.485781
iter  20 value 94.484228
final  value 94.484215 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.391416 
final  value 94.485800 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.349551 
iter  10 value 94.488915
iter  20 value 94.328087
iter  30 value 86.359379
iter  40 value 80.460616
iter  50 value 80.446890
iter  60 value 78.286649
iter  70 value 77.025954
iter  80 value 76.856863
iter  90 value 76.803655
iter 100 value 76.165072
final  value 76.165072 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.815078 
iter  10 value 94.485350
iter  20 value 90.467525
iter  30 value 80.883158
iter  40 value 80.839906
iter  50 value 80.714996
iter  60 value 80.704602
iter  70 value 79.917398
iter  80 value 79.445977
iter  90 value 79.428899
iter 100 value 79.422880
final  value 79.422880 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.134618 
iter  10 value 94.489811
iter  20 value 94.343323
iter  30 value 92.839218
iter  40 value 89.980276
iter  50 value 89.915597
iter  60 value 89.521382
final  value 89.408282 
converged
Fitting Repeat 4 

# weights:  305
initial  value 109.633696 
iter  10 value 94.489226
iter  20 value 94.471973
iter  30 value 93.753600
iter  40 value 87.911246
iter  50 value 86.491266
iter  60 value 86.353569
final  value 86.350653 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.122510 
iter  10 value 92.623514
iter  20 value 92.110175
iter  30 value 91.790897
iter  40 value 81.348638
iter  50 value 81.321839
iter  60 value 80.458614
iter  70 value 79.599976
iter  80 value 79.596966
final  value 79.596949 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.131504 
iter  10 value 94.333591
iter  20 value 94.326149
iter  30 value 84.441458
iter  40 value 84.405582
iter  50 value 84.402948
final  value 84.402940 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.379786 
iter  10 value 94.491517
iter  20 value 93.814320
iter  30 value 92.109123
iter  40 value 90.587286
final  value 90.549188 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.886224 
iter  10 value 94.490294
iter  20 value 93.902767
iter  30 value 85.826433
iter  40 value 81.338138
iter  50 value 79.732015
iter  60 value 79.315853
iter  70 value 79.256464
iter  80 value 79.212381
iter  90 value 79.210811
iter 100 value 79.207650
final  value 79.207650 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 100.686392 
iter  10 value 94.491571
iter  20 value 92.280697
iter  30 value 83.552158
iter  40 value 82.812258
iter  50 value 78.049120
iter  60 value 76.986863
iter  70 value 76.519048
iter  80 value 75.902774
final  value 75.887373 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.772987 
iter  10 value 90.426002
iter  20 value 89.739994
iter  30 value 89.159564
iter  40 value 89.105808
iter  50 value 88.664842
iter  60 value 88.647521
iter  70 value 88.646093
iter  80 value 88.639312
iter  90 value 80.836331
iter 100 value 77.799961
final  value 77.799961 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.133040 
final  value 94.052909 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.594748 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.360700 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.471404 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.087986 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 117.018243 
final  value 94.032967 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.928745 
final  value 93.714286 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.597832 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.913302 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 121.443090 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 110.283940 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.751330 
iter  10 value 93.538438
final  value 93.538420 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.461324 
iter  10 value 93.994407
iter  20 value 93.991529
final  value 93.991526 
converged
Fitting Repeat 4 

# weights:  507
initial  value 115.070541 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.218559 
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  103
initial  value 115.735087 
iter  10 value 93.973434
iter  20 value 88.557569
iter  30 value 86.678604
iter  40 value 85.493959
iter  50 value 85.121095
iter  60 value 83.663312
iter  70 value 83.596375
iter  80 value 83.265378
iter  90 value 83.144384
final  value 83.142865 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.749184 
iter  10 value 94.060091
iter  20 value 94.054888
iter  30 value 93.704922
iter  40 value 93.219853
iter  50 value 90.227961
iter  60 value 86.886515
iter  70 value 85.383979
iter  80 value 84.990221
iter  90 value 84.795891
final  value 84.794175 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.742345 
iter  10 value 94.055665
iter  20 value 94.055019
iter  30 value 93.154915
iter  40 value 86.226603
iter  50 value 85.724671
iter  60 value 85.559840
iter  70 value 85.119132
iter  80 value 84.848688
iter  90 value 84.574873
iter 100 value 84.557789
final  value 84.557789 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 101.297506 
iter  10 value 93.994609
iter  20 value 93.577034
iter  30 value 87.629125
iter  40 value 87.189976
iter  50 value 87.062009
iter  60 value 85.198890
iter  70 value 85.006284
iter  80 value 84.978468
final  value 84.978361 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.463388 
iter  10 value 93.973039
iter  20 value 93.733812
iter  30 value 93.687822
iter  40 value 89.756332
iter  50 value 85.849268
iter  60 value 85.160830
iter  70 value 84.749112
iter  80 value 84.550551
iter  90 value 83.891609
iter 100 value 83.718915
final  value 83.718915 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 104.845337 
iter  10 value 94.036360
iter  20 value 93.729005
iter  30 value 93.292718
iter  40 value 87.864346
iter  50 value 87.292297
iter  60 value 87.108960
iter  70 value 86.292777
iter  80 value 85.560416
iter  90 value 84.885450
iter 100 value 84.769113
final  value 84.769113 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 122.340315 
iter  10 value 94.206308
iter  20 value 85.856781
iter  30 value 85.353143
iter  40 value 84.997029
iter  50 value 84.569310
iter  60 value 83.050898
iter  70 value 82.439559
iter  80 value 82.109720
iter  90 value 81.695600
iter 100 value 81.611870
final  value 81.611870 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.006577 
iter  10 value 95.070989
iter  20 value 86.376339
iter  30 value 85.628845
iter  40 value 85.384114
iter  50 value 85.147152
iter  60 value 84.705968
iter  70 value 84.618758
iter  80 value 84.581462
iter  90 value 84.538218
iter 100 value 84.452618
final  value 84.452618 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.143374 
iter  10 value 94.087389
iter  20 value 92.695274
iter  30 value 92.473232
iter  40 value 91.884161
iter  50 value 88.271118
iter  60 value 85.402671
iter  70 value 84.803127
iter  80 value 84.185275
iter  90 value 83.980344
iter 100 value 83.726538
final  value 83.726538 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.196333 
iter  10 value 92.849844
iter  20 value 87.283064
iter  30 value 85.279944
iter  40 value 84.960362
iter  50 value 84.696132
iter  60 value 84.375462
iter  70 value 84.249822
iter  80 value 83.677996
iter  90 value 82.762269
iter 100 value 82.593236
final  value 82.593236 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.927408 
iter  10 value 95.763601
iter  20 value 94.720298
iter  30 value 91.035474
iter  40 value 87.063970
iter  50 value 86.747867
iter  60 value 85.992460
iter  70 value 83.780317
iter  80 value 82.107829
iter  90 value 81.877885
iter 100 value 81.661745
final  value 81.661745 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.906333 
iter  10 value 94.407087
iter  20 value 93.237797
iter  30 value 89.149423
iter  40 value 86.550812
iter  50 value 84.851313
iter  60 value 83.297182
iter  70 value 81.739717
iter  80 value 81.350796
iter  90 value 81.103630
iter 100 value 80.948090
final  value 80.948090 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 135.274226 
iter  10 value 94.434862
iter  20 value 94.071099
iter  30 value 89.395333
iter  40 value 85.402482
iter  50 value 84.944006
iter  60 value 84.760711
iter  70 value 84.656514
iter  80 value 84.653645
iter  90 value 84.601371
iter 100 value 83.161693
final  value 83.161693 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.341000 
iter  10 value 93.607848
iter  20 value 91.439400
iter  30 value 89.147361
iter  40 value 83.809704
iter  50 value 82.443208
iter  60 value 81.952623
iter  70 value 81.852057
iter  80 value 81.654872
iter  90 value 81.533824
iter 100 value 81.461424
final  value 81.461424 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 115.492082 
iter  10 value 94.026267
iter  20 value 91.233827
iter  30 value 88.564203
iter  40 value 84.879493
iter  50 value 84.058464
iter  60 value 83.677442
iter  70 value 82.577738
iter  80 value 82.027875
iter  90 value 81.839692
iter 100 value 81.595847
final  value 81.595847 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.488492 
final  value 94.054551 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.580156 
final  value 93.658974 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.081323 
iter  10 value 94.054644
iter  20 value 94.052927
final  value 94.052911 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.257306 
final  value 94.054491 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.549423 
final  value 94.054595 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.259667 
iter  10 value 84.908883
iter  20 value 83.859892
iter  30 value 83.412157
iter  40 value 83.411137
iter  50 value 83.407510
iter  60 value 83.258116
iter  70 value 83.165055
final  value 83.163916 
converged
Fitting Repeat 2 

# weights:  305
initial  value 115.522864 
iter  10 value 94.057712
iter  20 value 94.053634
iter  30 value 93.991856
iter  40 value 93.077876
final  value 93.069581 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.741309 
iter  10 value 94.010738
iter  20 value 94.004945
iter  30 value 94.002192
iter  40 value 92.528094
final  value 92.418313 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.825438 
iter  10 value 94.028506
iter  20 value 94.024252
iter  30 value 93.780006
iter  40 value 93.749851
iter  50 value 93.749659
iter  60 value 93.657834
iter  70 value 93.651514
final  value 93.651150 
converged
Fitting Repeat 5 

# weights:  305
initial  value 115.179691 
iter  10 value 94.057635
iter  20 value 93.971105
iter  30 value 88.903570
iter  40 value 84.279500
iter  50 value 84.103475
iter  60 value 83.851252
iter  70 value 83.743271
final  value 83.743165 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.822651 
iter  10 value 93.913194
iter  20 value 92.414204
iter  30 value 84.296822
iter  40 value 83.646595
iter  50 value 83.621055
iter  60 value 81.686151
iter  70 value 80.965535
iter  80 value 80.041273
iter  90 value 79.934312
iter 100 value 79.921002
final  value 79.921002 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.924369 
iter  10 value 94.040788
iter  20 value 94.034108
iter  30 value 93.732159
iter  40 value 93.217235
iter  50 value 93.216689
iter  60 value 92.903019
iter  70 value 84.338903
iter  80 value 84.003261
iter  90 value 83.625755
iter 100 value 83.615534
final  value 83.615534 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 97.122941 
iter  10 value 93.621482
iter  20 value 93.617916
iter  30 value 93.607880
iter  40 value 93.272674
iter  50 value 91.557723
iter  60 value 91.003463
iter  70 value 90.402961
iter  80 value 90.400358
iter  90 value 90.399348
iter 100 value 90.398297
final  value 90.398297 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.639232 
iter  10 value 93.996573
iter  20 value 93.994707
iter  30 value 93.987136
iter  40 value 93.827301
iter  50 value 92.089920
iter  60 value 91.749529
iter  70 value 91.682636
iter  80 value 91.682442
iter  80 value 91.682441
iter  80 value 91.682441
final  value 91.682441 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.927894 
iter  10 value 94.101491
iter  20 value 94.059998
iter  30 value 94.040909
iter  40 value 94.038906
iter  50 value 94.037167
iter  60 value 94.035632
iter  70 value 93.615959
iter  80 value 92.916741
iter  90 value 91.456693
iter 100 value 85.147952
final  value 85.147952 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 122.389158 
iter  10 value 117.968506
iter  20 value 117.958735
iter  30 value 117.890366
final  value 117.890332 
converged
Fitting Repeat 2 

# weights:  305
initial  value 125.656936 
iter  10 value 117.894638
iter  20 value 117.877308
iter  30 value 116.670149
iter  40 value 108.194894
iter  50 value 105.161858
iter  60 value 102.990174
iter  70 value 102.116158
iter  80 value 100.272855
iter  90 value 100.071035
iter 100 value 99.990322
final  value 99.990322 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 120.418478 
iter  10 value 117.763986
iter  20 value 117.376956
final  value 117.208275 
converged
Fitting Repeat 4 

# weights:  305
initial  value 119.982260 
iter  10 value 117.763480
iter  20 value 117.758336
iter  30 value 109.635027
iter  40 value 104.926843
iter  50 value 104.132265
iter  60 value 104.024313
iter  70 value 104.019931
iter  80 value 104.003827
iter  90 value 103.442676
iter 100 value 100.552095
final  value 100.552095 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 120.631816 
iter  10 value 116.871963
iter  20 value 116.805304
iter  30 value 116.804821
iter  40 value 116.800540
iter  50 value 115.963050
final  value 115.957511 
converged
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Sun Jun  9 21:01:03 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 
 41.364   1.897  42.527