##############################################################################
##############################################################################
###
### 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-mac-arm64/meat/HPiP.Rcheck’
* using R version 4.4.0 (2024-04-24)
* using platform: aarch64-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 Ventura 13.6.5
* 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       17.594  0.509  18.106
FSmethod      17.309  0.569  17.881
corr_plot     16.676  0.549  17.227
pred_ensembel  5.659  0.473   4.274
enrichfindP    0.161  0.029   9.945
* 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-mac-arm64/meat/HPiP.Rcheck/00check.log’
for details.

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


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/library’
* installing *source* package ‘HPiP’ ...
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R version 4.4.0 (2024-04-24) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-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 99.073143 
final  value 93.836066 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.099533 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.637790 
iter  10 value 93.988238
final  value 93.988096 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.509894 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.281113 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.820591 
iter  10 value 90.094000
iter  20 value 89.911442
iter  30 value 89.910281
iter  30 value 89.910281
iter  30 value 89.910281
final  value 89.910281 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.415442 
final  value 93.988095 
converged
Fitting Repeat 3 

# weights:  305
initial  value 119.669658 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.674978 
final  value 93.836066 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.397782 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.230689 
iter  10 value 93.536481
iter  20 value 93.437578
iter  30 value 92.276910
iter  40 value 91.328718
iter  50 value 91.316206
final  value 91.316188 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.097071 
final  value 93.836066 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.282777 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 124.271974 
iter  10 value 93.835714
iter  10 value 93.835714
iter  10 value 93.835714
final  value 93.835714 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.881672 
final  value 93.671508 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.896642 
iter  10 value 93.651609
iter  20 value 87.256001
iter  30 value 86.452842
iter  40 value 85.575212
iter  50 value 84.301804
iter  60 value 84.068432
iter  70 value 83.792217
iter  80 value 83.600979
final  value 83.558555 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.764476 
iter  10 value 93.979783
iter  20 value 91.175350
iter  30 value 90.824779
iter  40 value 89.548880
iter  50 value 89.376138
iter  60 value 88.834894
iter  70 value 86.975081
iter  80 value 86.537859
iter  90 value 86.194472
iter 100 value 86.185424
final  value 86.185424 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 99.668474 
iter  10 value 94.056691
iter  20 value 93.898205
iter  30 value 93.840222
iter  40 value 91.641217
iter  50 value 89.426009
iter  60 value 89.144337
iter  70 value 86.140033
iter  80 value 85.085956
iter  90 value 84.710007
iter 100 value 84.352940
final  value 84.352940 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 98.214784 
iter  10 value 94.049472
iter  20 value 88.271720
iter  30 value 86.935217
iter  40 value 86.845454
iter  50 value 86.737820
iter  60 value 86.569647
iter  70 value 85.601338
iter  80 value 85.519970
iter  90 value 85.340119
iter 100 value 85.194103
final  value 85.194103 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 100.173914 
iter  10 value 94.041784
iter  20 value 89.323864
iter  30 value 88.176509
iter  40 value 87.209653
iter  50 value 86.549214
iter  60 value 86.441523
final  value 86.441457 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.275176 
iter  10 value 93.903591
iter  20 value 93.532363
iter  30 value 90.063867
iter  40 value 89.467105
iter  50 value 89.209140
iter  60 value 87.130502
iter  70 value 84.512523
iter  80 value 83.350565
iter  90 value 82.896974
iter 100 value 82.833678
final  value 82.833678 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 114.420855 
iter  10 value 93.823442
iter  20 value 87.852942
iter  30 value 86.809654
iter  40 value 86.237750
iter  50 value 85.068586
iter  60 value 84.131258
iter  70 value 82.765784
iter  80 value 82.396247
iter  90 value 82.225254
iter 100 value 81.939192
final  value 81.939192 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 109.379084 
iter  10 value 93.943714
iter  20 value 91.340152
iter  30 value 89.064929
iter  40 value 87.976477
iter  50 value 86.931769
iter  60 value 86.729346
iter  70 value 85.447876
iter  80 value 84.978264
iter  90 value 83.911797
iter 100 value 83.491717
final  value 83.491717 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.324626 
iter  10 value 93.978734
iter  20 value 87.701061
iter  30 value 86.544055
iter  40 value 86.104881
iter  50 value 85.161064
iter  60 value 84.034444
iter  70 value 83.539479
iter  80 value 82.987290
iter  90 value 82.697687
iter 100 value 82.615568
final  value 82.615568 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 117.138504 
iter  10 value 93.897622
iter  20 value 88.224984
iter  30 value 87.289097
iter  40 value 86.862137
iter  50 value 86.521699
iter  60 value 86.039148
iter  70 value 84.970424
iter  80 value 83.962944
iter  90 value 83.368486
iter 100 value 83.154878
final  value 83.154878 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.328493 
iter  10 value 94.056209
iter  20 value 92.197908
iter  30 value 89.817303
iter  40 value 87.124423
iter  50 value 84.349119
iter  60 value 83.224308
iter  70 value 82.569753
iter  80 value 82.138351
iter  90 value 81.893251
iter 100 value 81.835705
final  value 81.835705 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.671750 
iter  10 value 93.897931
iter  20 value 89.037715
iter  30 value 86.465196
iter  40 value 85.482719
iter  50 value 84.844037
iter  60 value 83.713775
iter  70 value 83.169221
iter  80 value 82.983918
iter  90 value 82.937512
iter 100 value 82.882733
final  value 82.882733 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.220675 
iter  10 value 93.812308
iter  20 value 91.714695
iter  30 value 91.357776
iter  40 value 90.806558
iter  50 value 88.069036
iter  60 value 86.378868
iter  70 value 85.895411
iter  80 value 85.639551
iter  90 value 84.276988
iter 100 value 83.983115
final  value 83.983115 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 122.536531 
iter  10 value 93.759464
iter  20 value 88.931496
iter  30 value 86.084974
iter  40 value 83.413993
iter  50 value 83.061646
iter  60 value 82.668171
iter  70 value 82.224384
iter  80 value 82.020516
iter  90 value 81.972683
iter 100 value 81.926364
final  value 81.926364 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.431488 
iter  10 value 94.048141
iter  20 value 93.901850
iter  30 value 93.031852
iter  40 value 89.514348
iter  50 value 87.960167
iter  60 value 85.629096
iter  70 value 85.020249
iter  80 value 83.453329
iter  90 value 82.907808
iter 100 value 82.693202
final  value 82.693202 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.338246 
final  value 94.054508 
converged
Fitting Repeat 2 

# weights:  103
initial  value 111.340406 
final  value 94.054632 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.713458 
final  value 94.054577 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.256203 
final  value 94.054833 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.512211 
final  value 94.054729 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.733008 
iter  10 value 94.057376
iter  20 value 94.052930
iter  30 value 93.265361
iter  40 value 86.662872
iter  50 value 86.296460
final  value 86.290931 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.905681 
iter  10 value 94.057534
iter  20 value 94.033809
iter  30 value 93.671726
iter  30 value 93.671726
iter  30 value 93.671726
final  value 93.671726 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.060728 
iter  10 value 93.842281
iter  20 value 93.613638
iter  30 value 91.952045
iter  40 value 91.856487
iter  50 value 91.856189
iter  60 value 91.337840
iter  70 value 90.979168
iter  80 value 90.977917
iter  80 value 90.977916
final  value 90.977916 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.061953 
iter  10 value 94.057527
iter  20 value 93.968335
iter  30 value 93.622685
iter  40 value 90.976330
iter  50 value 90.935780
final  value 90.935753 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.290129 
iter  10 value 94.058324
iter  20 value 94.053166
final  value 94.052948 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.004542 
iter  10 value 93.509935
iter  20 value 92.981948
iter  30 value 92.964451
iter  40 value 92.942042
iter  50 value 92.941253
iter  60 value 92.406206
iter  70 value 91.495125
iter  80 value 91.483052
iter  90 value 91.481191
iter 100 value 91.478872
final  value 91.478872 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 96.722807 
iter  10 value 93.794101
iter  20 value 93.790812
iter  30 value 87.795777
iter  40 value 85.422779
iter  50 value 84.163714
iter  60 value 84.003702
iter  70 value 84.003055
iter  70 value 84.003054
final  value 84.003054 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.460536 
iter  10 value 94.060481
iter  20 value 93.944209
iter  30 value 92.387355
iter  40 value 91.417201
iter  50 value 91.014814
final  value 91.008760 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.744426 
iter  10 value 89.353612
iter  20 value 86.361746
iter  30 value 86.155380
iter  40 value 84.277870
iter  50 value 82.372918
iter  60 value 82.103067
iter  70 value 82.002132
iter  80 value 81.991984
iter  90 value 81.988248
iter 100 value 81.894018
final  value 81.894018 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 116.399386 
iter  10 value 94.061230
iter  20 value 93.941631
iter  30 value 93.138692
iter  40 value 89.922189
iter  50 value 86.497400
iter  60 value 86.014685
iter  70 value 84.468968
iter  80 value 84.326654
iter  90 value 83.028582
iter 100 value 81.871882
final  value 81.871882 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.298163 
iter  10 value 94.025896
final  value 93.923039 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.031009 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.948613 
iter  10 value 94.026543
final  value 94.026542 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.539948 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.440542 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.031678 
iter  10 value 89.515592
iter  20 value 89.199813
iter  30 value 89.013227
iter  40 value 88.834992
iter  50 value 88.198835
iter  60 value 88.133215
final  value 88.133185 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.002018 
final  value 93.923039 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.860755 
iter  10 value 93.929996
final  value 93.923039 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.287027 
iter  10 value 93.994665
final  value 93.976244 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.054306 
iter  10 value 87.951518
iter  10 value 87.951518
iter  10 value 87.951518
final  value 87.951518 
converged
Fitting Repeat 1 

# weights:  507
initial  value 118.839948 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 117.431784 
iter  10 value 94.026544
final  value 94.026542 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.183959 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.726781 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 116.485698 
iter  10 value 94.052434
iter  10 value 94.052434
iter  10 value 94.052434
final  value 94.052434 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.641972 
iter  10 value 94.462434
iter  20 value 89.972950
iter  30 value 86.540236
iter  40 value 85.051266
iter  50 value 84.504294
iter  60 value 84.468133
iter  70 value 84.440012
final  value 84.439571 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.322024 
iter  10 value 94.502304
iter  20 value 94.457358
iter  30 value 92.129367
iter  40 value 86.149297
iter  50 value 84.882490
iter  60 value 84.851464
iter  70 value 84.847205
final  value 84.846895 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.964207 
iter  10 value 94.580635
iter  20 value 94.486488
iter  30 value 94.050749
iter  40 value 89.028830
iter  50 value 85.173466
iter  60 value 85.062636
iter  70 value 85.053375
final  value 85.053365 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.976068 
iter  10 value 94.513679
iter  20 value 93.650242
iter  30 value 90.429919
iter  40 value 89.282870
iter  50 value 88.426707
iter  60 value 84.455629
iter  70 value 83.873750
iter  80 value 83.285480
iter  90 value 83.148674
final  value 83.146870 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.808246 
iter  10 value 94.458533
iter  20 value 94.235609
iter  30 value 94.041273
iter  40 value 93.910304
iter  50 value 92.610549
iter  60 value 89.837382
iter  70 value 88.706054
iter  80 value 88.263800
iter  90 value 88.034380
iter 100 value 83.331718
final  value 83.331718 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 110.544420 
iter  10 value 94.302903
iter  20 value 92.393289
iter  30 value 90.675733
iter  40 value 89.669675
iter  50 value 86.067802
iter  60 value 84.314850
iter  70 value 83.799894
iter  80 value 83.394245
iter  90 value 83.166529
iter 100 value 82.599591
final  value 82.599591 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 122.668238 
iter  10 value 94.322876
iter  20 value 88.588583
iter  30 value 87.771782
iter  40 value 85.253555
iter  50 value 84.497233
iter  60 value 83.933990
iter  70 value 83.428937
iter  80 value 82.370428
iter  90 value 81.872094
iter 100 value 81.783187
final  value 81.783187 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.886119 
iter  10 value 94.473407
iter  20 value 87.818842
iter  30 value 85.053360
iter  40 value 84.910163
iter  50 value 84.886886
iter  60 value 84.851070
iter  70 value 84.708179
iter  80 value 83.770173
iter  90 value 83.140326
iter 100 value 82.182441
final  value 82.182441 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.812007 
iter  10 value 94.903459
iter  20 value 92.022139
iter  30 value 85.600729
iter  40 value 85.081503
iter  50 value 83.423215
iter  60 value 82.688103
iter  70 value 82.341441
iter  80 value 82.211120
iter  90 value 82.204958
iter 100 value 82.200685
final  value 82.200685 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.879049 
iter  10 value 94.504733
iter  20 value 85.869919
iter  30 value 85.722476
iter  40 value 85.051675
iter  50 value 84.162596
iter  60 value 83.370580
iter  70 value 82.931246
iter  80 value 82.308806
iter  90 value 82.043294
iter 100 value 81.983470
final  value 81.983470 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 119.404116 
iter  10 value 96.954348
iter  20 value 87.793426
iter  30 value 85.021026
iter  40 value 84.228912
iter  50 value 84.075759
iter  60 value 84.039705
iter  70 value 84.030570
iter  80 value 83.942856
iter  90 value 83.702612
iter 100 value 82.693981
final  value 82.693981 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 110.892602 
iter  10 value 94.466787
iter  20 value 93.307915
iter  30 value 86.975657
iter  40 value 84.265660
iter  50 value 83.738576
iter  60 value 83.688191
iter  70 value 83.247294
iter  80 value 82.877787
iter  90 value 82.431765
iter 100 value 82.151149
final  value 82.151149 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 115.137306 
iter  10 value 94.385843
iter  20 value 88.826087
iter  30 value 88.259673
iter  40 value 87.132659
iter  50 value 84.519172
iter  60 value 82.962962
iter  70 value 82.357504
iter  80 value 82.196782
iter  90 value 81.874689
iter 100 value 81.541996
final  value 81.541996 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 120.666972 
iter  10 value 94.646610
iter  20 value 93.136102
iter  30 value 90.972989
iter  40 value 85.330757
iter  50 value 84.581993
iter  60 value 83.364535
iter  70 value 83.104742
iter  80 value 82.408136
iter  90 value 82.159158
iter 100 value 81.966309
final  value 81.966309 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 114.792925 
iter  10 value 92.529461
iter  20 value 86.855658
iter  30 value 85.904388
iter  40 value 85.046361
iter  50 value 84.584341
iter  60 value 83.987875
iter  70 value 83.047096
iter  80 value 82.704739
iter  90 value 82.333470
iter 100 value 82.024191
final  value 82.024191 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 109.164859 
final  value 94.485894 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.283909 
final  value 94.485840 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.825908 
final  value 94.485822 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.430319 
final  value 94.485997 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.201477 
final  value 94.485829 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.804503 
iter  10 value 94.094047
iter  20 value 87.950056
iter  30 value 87.557062
iter  40 value 85.056960
iter  50 value 85.011430
final  value 85.010318 
converged
Fitting Repeat 2 

# weights:  305
initial  value 119.414342 
iter  10 value 93.570272
iter  20 value 85.612691
iter  30 value 84.948204
iter  40 value 84.945396
iter  50 value 84.939249
iter  60 value 84.922726
iter  70 value 84.902034
iter  80 value 84.898235
final  value 84.898174 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.943020 
iter  10 value 94.489087
iter  20 value 94.484223
final  value 94.484217 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.183522 
iter  10 value 92.478578
iter  20 value 91.473399
iter  30 value 91.471749
iter  40 value 87.420212
iter  50 value 87.288885
iter  60 value 86.641975
final  value 86.621041 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.749500 
iter  10 value 86.743581
iter  20 value 84.133219
iter  30 value 83.990428
final  value 83.989077 
converged
Fitting Repeat 1 

# weights:  507
initial  value 126.407187 
iter  10 value 94.492554
iter  20 value 94.484235
iter  30 value 94.364996
iter  40 value 94.026244
iter  50 value 93.923815
iter  60 value 93.923505
iter  60 value 93.923505
final  value 93.923505 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.084757 
iter  10 value 94.494787
iter  20 value 94.492213
iter  30 value 94.486676
iter  40 value 93.523862
iter  50 value 86.799436
iter  60 value 84.990639
iter  70 value 84.861051
iter  80 value 84.837237
iter  90 value 84.821490
iter 100 value 84.175801
final  value 84.175801 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 95.947061 
iter  10 value 94.393435
iter  20 value 93.903190
iter  30 value 92.289840
iter  40 value 92.160440
iter  50 value 92.159271
iter  60 value 91.676939
iter  70 value 91.671487
final  value 91.670896 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.613065 
iter  10 value 93.931343
iter  20 value 93.925929
iter  30 value 93.797931
iter  40 value 84.609308
iter  50 value 84.078712
final  value 84.078708 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.314449 
iter  10 value 92.857835
iter  20 value 85.207417
iter  30 value 84.495666
iter  40 value 84.208212
iter  50 value 83.661649
iter  60 value 83.498645
iter  70 value 83.495452
iter  80 value 83.493852
iter  90 value 82.487508
iter 100 value 82.259494
final  value 82.259494 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.733406 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.046623 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.464260 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.792282 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.385950 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.819215 
iter  10 value 87.073691
iter  20 value 86.836205
iter  30 value 86.812237
final  value 86.812076 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.211889 
iter  10 value 92.821566
iter  20 value 92.189443
iter  30 value 92.186405
final  value 92.186286 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.476405 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.388536 
final  value 93.900821 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.217910 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.141323 
final  value 93.915746 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.538545 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.247082 
final  value 93.913919 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.548518 
iter  10 value 93.917781
iter  20 value 93.915749
final  value 93.915746 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.976432 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 117.798212 
iter  10 value 94.055858
iter  20 value 93.930473
iter  30 value 90.921573
iter  40 value 90.231539
iter  50 value 90.023032
iter  60 value 83.207238
iter  70 value 80.837897
iter  80 value 79.920126
iter  90 value 79.827764
iter 100 value 79.720586
final  value 79.720586 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 100.394338 
iter  10 value 93.023485
iter  20 value 85.588611
iter  30 value 85.031086
iter  40 value 82.108508
iter  50 value 81.159380
iter  60 value 80.985543
iter  70 value 80.825794
iter  80 value 79.796013
iter  90 value 79.241754
final  value 79.236117 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.643455 
iter  10 value 94.613661
iter  20 value 94.056655
iter  30 value 82.930152
iter  40 value 82.724112
iter  50 value 82.473721
iter  60 value 82.093134
iter  70 value 81.982109
iter  80 value 81.653807
iter  90 value 81.392177
final  value 81.392081 
converged
Fitting Repeat 4 

# weights:  103
initial  value 114.398784 
iter  10 value 94.056086
iter  20 value 93.966850
iter  30 value 90.984698
iter  40 value 83.907711
iter  50 value 82.730453
iter  60 value 82.004106
iter  70 value 81.245051
iter  80 value 80.209761
iter  90 value 80.122901
iter 100 value 79.899108
final  value 79.899108 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.808946 
iter  10 value 94.072839
iter  20 value 89.496517
iter  30 value 84.979659
iter  40 value 83.948623
iter  50 value 83.425361
iter  60 value 83.337960
iter  70 value 83.327341
iter  80 value 83.228421
iter  90 value 83.207662
final  value 83.207591 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.572948 
iter  10 value 94.056349
iter  20 value 92.084854
iter  30 value 87.060684
iter  40 value 86.924461
iter  50 value 86.920438
iter  60 value 86.712188
iter  70 value 83.031050
iter  80 value 81.714077
iter  90 value 81.271425
iter 100 value 81.146482
final  value 81.146482 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.733823 
iter  10 value 93.979931
iter  20 value 82.893675
iter  30 value 82.574854
iter  40 value 82.045254
iter  50 value 79.378132
iter  60 value 78.818448
iter  70 value 78.400433
iter  80 value 78.190170
iter  90 value 78.017416
iter 100 value 77.996929
final  value 77.996929 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.115319 
iter  10 value 94.208908
iter  20 value 93.198775
iter  30 value 82.408632
iter  40 value 81.746559
iter  50 value 81.103494
iter  60 value 80.991586
iter  70 value 80.957239
iter  80 value 80.322432
iter  90 value 79.901134
iter 100 value 79.791592
final  value 79.791592 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.113346 
iter  10 value 94.028247
iter  20 value 87.310758
iter  30 value 83.447219
iter  40 value 82.482807
iter  50 value 80.887789
iter  60 value 80.503625
iter  70 value 80.267403
iter  80 value 79.435751
iter  90 value 78.809829
iter 100 value 78.586808
final  value 78.586808 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.678962 
iter  10 value 91.490188
iter  20 value 90.725216
iter  30 value 87.423360
iter  40 value 86.347209
iter  50 value 86.277237
iter  60 value 84.521424
iter  70 value 80.540771
iter  80 value 79.228618
iter  90 value 78.960636
iter 100 value 78.736274
final  value 78.736274 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.714251 
iter  10 value 94.070211
iter  20 value 90.327576
iter  30 value 85.588291
iter  40 value 84.377717
iter  50 value 83.882696
iter  60 value 83.715251
iter  70 value 82.616739
iter  80 value 81.681144
iter  90 value 80.715717
iter 100 value 79.790072
final  value 79.790072 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.449095 
iter  10 value 94.083968
iter  20 value 92.217808
iter  30 value 91.032680
iter  40 value 90.725309
iter  50 value 90.236533
iter  60 value 84.185842
iter  70 value 83.263337
iter  80 value 81.277915
iter  90 value 80.267008
iter 100 value 79.966450
final  value 79.966450 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 121.000781 
iter  10 value 94.269414
iter  20 value 90.664989
iter  30 value 89.822607
iter  40 value 89.767336
iter  50 value 89.672608
iter  60 value 88.160898
iter  70 value 82.897230
iter  80 value 80.066904
iter  90 value 79.512079
iter 100 value 79.165226
final  value 79.165226 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.373398 
iter  10 value 90.105129
iter  20 value 89.266016
iter  30 value 89.229089
iter  40 value 88.802155
iter  50 value 86.917623
iter  60 value 86.513238
iter  70 value 82.895500
iter  80 value 80.820612
iter  90 value 80.237030
iter 100 value 80.003636
final  value 80.003636 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.226177 
iter  10 value 94.069044
iter  20 value 93.761097
iter  30 value 91.799348
iter  40 value 88.687889
iter  50 value 83.453490
iter  60 value 80.205375
iter  70 value 78.565816
iter  80 value 78.198418
iter  90 value 78.025894
iter 100 value 77.900472
final  value 77.900472 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.596733 
final  value 94.054685 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.831902 
final  value 94.054697 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.519844 
final  value 94.054558 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.868895 
final  value 94.054445 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.768147 
iter  10 value 94.054461
iter  20 value 94.042871
iter  30 value 93.295340
final  value 93.289265 
converged
Fitting Repeat 1 

# weights:  305
initial  value 115.006778 
iter  10 value 94.057251
iter  20 value 94.052992
iter  30 value 93.968780
iter  40 value 93.862536
iter  50 value 85.228653
iter  60 value 84.205496
iter  70 value 83.553046
final  value 83.549890 
converged
Fitting Repeat 2 

# weights:  305
initial  value 108.157790 
iter  10 value 93.920808
iter  20 value 93.916073
iter  30 value 91.000842
iter  40 value 89.968162
iter  50 value 89.960906
iter  50 value 89.960906
iter  50 value 89.960906
final  value 89.960906 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.234888 
iter  10 value 94.054895
iter  20 value 94.048452
iter  30 value 91.240402
iter  40 value 90.897131
iter  50 value 90.553591
iter  60 value 88.347922
iter  70 value 85.900899
iter  80 value 84.987754
iter  90 value 84.790456
iter 100 value 84.790349
final  value 84.790349 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.149510 
iter  10 value 87.721063
iter  20 value 82.452439
iter  30 value 82.123805
iter  40 value 82.068281
final  value 82.068185 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.929316 
iter  10 value 94.056488
iter  20 value 94.052921
iter  30 value 91.880713
iter  40 value 90.838729
final  value 90.757338 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.348462 
iter  10 value 85.915754
iter  20 value 83.307362
iter  30 value 80.974940
iter  40 value 80.556695
final  value 80.553144 
converged
Fitting Repeat 2 

# weights:  507
initial  value 116.026984 
final  value 94.060786 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.435448 
iter  10 value 85.652812
iter  20 value 80.612890
iter  30 value 78.778221
iter  40 value 78.641012
iter  50 value 78.360989
iter  60 value 78.335691
iter  70 value 78.330135
final  value 78.330091 
converged
Fitting Repeat 4 

# weights:  507
initial  value 111.366519 
iter  10 value 94.060384
iter  20 value 91.681119
iter  30 value 85.787394
iter  40 value 79.289100
iter  50 value 76.864041
iter  60 value 76.501943
iter  70 value 76.457981
iter  80 value 76.447396
iter  90 value 76.406258
iter 100 value 76.385728
final  value 76.385728 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.213500 
iter  10 value 94.061215
iter  20 value 93.974275
iter  30 value 85.283060
iter  40 value 82.116426
iter  50 value 82.038278
iter  60 value 79.699665
iter  70 value 78.663818
iter  80 value 77.055909
iter  90 value 76.548527
iter 100 value 76.491879
final  value 76.491879 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.914545 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.714781 
iter  10 value 94.264222
final  value 94.263148 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.394462 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.956300 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.924989 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.970818 
iter  10 value 94.443244
iter  10 value 94.443243
iter  10 value 94.443243
final  value 94.443243 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.242844 
final  value 94.443243 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.398237 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.216940 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.555912 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.492422 
iter  10 value 94.294010
final  value 94.263148 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.431719 
final  value 94.264858 
converged
Fitting Repeat 3 

# weights:  507
initial  value 115.683421 
iter  10 value 93.538035
iter  20 value 92.768885
iter  30 value 92.767217
final  value 92.767215 
converged
Fitting Repeat 4 

# weights:  507
initial  value 121.247414 
iter  10 value 94.284255
iter  20 value 87.630490
iter  30 value 87.340546
iter  30 value 87.340546
iter  30 value 87.340546
final  value 87.340546 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.311687 
iter  10 value 87.233767
iter  20 value 84.480646
iter  30 value 84.480047
final  value 84.480000 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.362960 
iter  10 value 94.460270
iter  20 value 86.532241
iter  30 value 86.017712
iter  40 value 85.480820
iter  50 value 85.307115
iter  60 value 84.418794
iter  70 value 83.091558
iter  80 value 82.875060
iter  90 value 82.824780
iter 100 value 82.804015
final  value 82.804015 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.784510 
iter  10 value 94.489485
iter  20 value 94.370339
iter  30 value 93.438290
iter  40 value 93.075043
iter  50 value 92.935607
iter  60 value 82.642519
iter  70 value 80.792007
iter  80 value 80.617196
iter  90 value 79.984559
iter 100 value 79.673735
final  value 79.673735 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 103.056120 
iter  10 value 94.266033
iter  20 value 87.296016
iter  30 value 86.372269
iter  40 value 84.961458
iter  50 value 83.484939
iter  60 value 82.926589
iter  70 value 82.914686
final  value 82.914683 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.428147 
iter  10 value 94.491523
iter  20 value 87.314722
iter  30 value 83.185889
iter  40 value 83.111056
iter  50 value 82.638631
iter  60 value 82.438232
iter  70 value 82.413798
iter  80 value 82.411939
final  value 82.411932 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.772416 
iter  10 value 94.224360
iter  20 value 83.830167
iter  30 value 83.138031
iter  40 value 83.011073
iter  50 value 82.971302
iter  60 value 82.931307
iter  70 value 82.919241
final  value 82.919238 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.183699 
iter  10 value 94.242709
iter  20 value 85.166322
iter  30 value 82.840548
iter  40 value 82.200602
iter  50 value 81.898658
iter  60 value 81.798987
iter  70 value 81.773500
iter  80 value 81.722212
iter  90 value 81.691336
iter 100 value 81.639738
final  value 81.639738 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.106283 
iter  10 value 94.866895
iter  20 value 92.273046
iter  30 value 86.623423
iter  40 value 85.910159
iter  50 value 85.454962
iter  60 value 85.107212
iter  70 value 83.079660
iter  80 value 81.458596
iter  90 value 79.760968
iter 100 value 79.091306
final  value 79.091306 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.024278 
iter  10 value 94.005304
iter  20 value 83.796791
iter  30 value 83.231179
iter  40 value 81.759448
iter  50 value 80.820122
iter  60 value 80.066992
iter  70 value 78.764684
iter  80 value 78.490001
iter  90 value 78.196178
iter 100 value 78.134844
final  value 78.134844 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.578330 
iter  10 value 94.496035
iter  20 value 93.714383
iter  30 value 93.237367
iter  40 value 86.336627
iter  50 value 84.221774
iter  60 value 81.969721
iter  70 value 80.617793
iter  80 value 79.555820
iter  90 value 79.050412
iter 100 value 78.845084
final  value 78.845084 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.978659 
iter  10 value 95.064553
iter  20 value 83.502509
iter  30 value 83.246533
iter  40 value 82.703770
iter  50 value 82.621331
iter  60 value 82.518840
iter  70 value 82.226582
iter  80 value 80.777418
iter  90 value 79.495128
iter 100 value 78.611019
final  value 78.611019 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 120.131995 
iter  10 value 95.084666
iter  20 value 94.405374
iter  30 value 90.020347
iter  40 value 83.950910
iter  50 value 80.345593
iter  60 value 79.508696
iter  70 value 78.654569
iter  80 value 78.281692
iter  90 value 77.888912
iter 100 value 77.624143
final  value 77.624143 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 114.060132 
iter  10 value 93.646691
iter  20 value 84.574698
iter  30 value 82.408582
iter  40 value 80.069465
iter  50 value 78.737906
iter  60 value 78.192185
iter  70 value 77.982244
iter  80 value 77.826467
iter  90 value 77.643020
iter 100 value 77.443512
final  value 77.443512 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.225352 
iter  10 value 94.661185
iter  20 value 85.576702
iter  30 value 84.419286
iter  40 value 83.780784
iter  50 value 83.342650
iter  60 value 81.901683
iter  70 value 80.168972
iter  80 value 80.107014
iter  90 value 79.726342
iter 100 value 78.822110
final  value 78.822110 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.117077 
iter  10 value 90.678153
iter  20 value 83.370223
iter  30 value 83.016282
iter  40 value 82.947832
iter  50 value 82.683601
iter  60 value 82.213306
iter  70 value 81.158927
iter  80 value 79.635310
iter  90 value 79.468523
iter 100 value 78.658356
final  value 78.658356 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.807719 
iter  10 value 94.433604
iter  20 value 93.387483
iter  30 value 93.071364
iter  40 value 92.228465
iter  50 value 89.323952
iter  60 value 84.901097
iter  70 value 82.739351
iter  80 value 82.361831
iter  90 value 81.520104
iter 100 value 81.338640
final  value 81.338640 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.625730 
iter  10 value 93.569438
iter  10 value 93.569437
iter  10 value 93.569437
final  value 93.569437 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.739774 
iter  10 value 94.485948
final  value 94.484218 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.670663 
final  value 94.485896 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.066817 
final  value 94.485697 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.502349 
iter  10 value 94.444725
iter  20 value 93.933253
iter  30 value 85.303201
iter  40 value 85.095094
iter  50 value 85.093158
iter  60 value 85.055197
iter  70 value 84.922062
iter  80 value 84.920519
final  value 84.920494 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.375071 
iter  10 value 94.489094
iter  20 value 94.460750
iter  30 value 92.161689
iter  40 value 89.299457
iter  50 value 89.291369
iter  60 value 89.174155
iter  70 value 89.166868
iter  80 value 87.930467
iter  90 value 87.881455
iter 100 value 87.188952
final  value 87.188952 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.190183 
iter  10 value 94.489265
final  value 94.484923 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.973569 
iter  10 value 94.429064
iter  20 value 93.813691
final  value 93.568223 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.217682 
iter  10 value 94.489187
iter  20 value 94.374537
iter  30 value 85.328006
iter  40 value 85.292344
iter  50 value 85.279165
iter  60 value 85.278762
iter  70 value 84.982695
iter  80 value 81.730170
iter  90 value 81.601458
iter 100 value 81.599130
final  value 81.599130 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 98.493835 
iter  10 value 94.489462
iter  20 value 94.416902
iter  30 value 83.766771
iter  40 value 83.246688
iter  40 value 83.246688
iter  40 value 83.246688
final  value 83.246688 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.914231 
iter  10 value 87.888251
iter  20 value 87.069988
iter  30 value 86.364412
iter  40 value 86.127173
iter  50 value 86.056355
iter  60 value 86.055146
iter  70 value 85.877255
iter  80 value 85.541266
iter  90 value 84.837823
iter 100 value 81.942160
final  value 81.942160 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 116.398956 
iter  10 value 93.546812
iter  20 value 93.542210
iter  30 value 87.864566
iter  40 value 87.700293
final  value 87.700288 
converged
Fitting Repeat 3 

# weights:  507
initial  value 123.374962 
iter  10 value 94.452475
iter  20 value 94.444830
iter  30 value 92.927889
iter  40 value 85.649086
iter  50 value 85.518217
iter  60 value 85.515719
iter  70 value 85.512696
iter  80 value 85.511909
iter  90 value 85.510910
iter 100 value 84.975291
final  value 84.975291 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.909558 
iter  10 value 94.490385
iter  20 value 86.476530
iter  30 value 85.276653
final  value 85.276567 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.898948 
iter  10 value 94.491871
iter  20 value 91.370596
iter  30 value 84.494011
iter  40 value 84.486331
iter  50 value 84.485841
iter  60 value 84.476999
iter  70 value 83.558013
iter  80 value 79.015195
iter  90 value 77.943021
iter 100 value 77.136255
final  value 77.136255 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.660492 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.309760 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.838894 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.057830 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.382573 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.431733 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.777477 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.399116 
final  value 94.484210 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.547984 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 91.696212 
iter  10 value 85.749367
iter  20 value 85.492611
iter  30 value 85.421280
iter  40 value 85.403618
final  value 85.403598 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.784530 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 111.207565 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.548809 
iter  10 value 94.343244
final  value 94.046703 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.920913 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 111.204905 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.529712 
iter  10 value 94.461524
iter  20 value 88.304571
iter  30 value 86.896808
iter  40 value 86.240709
iter  50 value 86.040230
iter  60 value 85.781533
iter  70 value 84.767745
iter  80 value 82.417404
iter  90 value 82.347707
iter 100 value 82.322728
final  value 82.322728 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 103.298512 
iter  10 value 94.858952
iter  20 value 92.957791
iter  30 value 87.823881
iter  40 value 86.773636
iter  50 value 86.412671
iter  60 value 86.027356
iter  70 value 84.791376
iter  80 value 83.156420
iter  90 value 82.689279
iter 100 value 82.510887
final  value 82.510887 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 106.592265 
iter  10 value 93.058656
iter  20 value 89.537235
iter  30 value 87.210140
iter  40 value 85.360681
iter  50 value 84.696656
iter  60 value 84.597048
iter  70 value 84.431771
iter  80 value 84.269051
iter  90 value 83.820129
iter 100 value 83.648176
final  value 83.648176 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 98.648248 
iter  10 value 94.475679
iter  20 value 94.357627
iter  30 value 93.026524
iter  40 value 86.347268
iter  50 value 85.078110
iter  60 value 84.932005
iter  70 value 83.920132
iter  80 value 83.594271
iter  90 value 83.114053
iter 100 value 82.231600
final  value 82.231600 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 111.426434 
iter  10 value 89.478074
iter  20 value 86.528581
iter  30 value 85.485197
iter  40 value 84.321389
iter  50 value 83.269468
iter  60 value 83.131785
final  value 83.127089 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.662238 
iter  10 value 94.558307
iter  20 value 94.262502
iter  30 value 87.005750
iter  40 value 86.910961
iter  50 value 86.002438
iter  60 value 84.969591
iter  70 value 83.617832
iter  80 value 82.945798
iter  90 value 82.800963
iter 100 value 82.704907
final  value 82.704907 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.335332 
iter  10 value 95.868007
iter  20 value 93.020648
iter  30 value 87.146968
iter  40 value 85.404190
iter  50 value 84.539474
iter  60 value 83.877516
iter  70 value 83.483784
iter  80 value 83.371379
iter  90 value 83.301172
iter 100 value 82.804482
final  value 82.804482 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 110.990679 
iter  10 value 94.364598
iter  20 value 89.684141
iter  30 value 86.254202
iter  40 value 83.293467
iter  50 value 82.407731
iter  60 value 82.269309
iter  70 value 81.924185
iter  80 value 81.511878
iter  90 value 81.406486
iter 100 value 81.134309
final  value 81.134309 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.037755 
iter  10 value 94.573808
iter  20 value 91.864549
iter  30 value 88.778263
iter  40 value 87.321371
iter  50 value 82.346478
iter  60 value 81.804886
iter  70 value 81.163915
iter  80 value 80.873972
iter  90 value 80.793604
iter 100 value 80.721843
final  value 80.721843 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.767949 
iter  10 value 94.490762
iter  20 value 88.011410
iter  30 value 86.047703
iter  40 value 84.978081
iter  50 value 84.057643
iter  60 value 83.060271
iter  70 value 82.086955
iter  80 value 81.943471
iter  90 value 81.790770
iter 100 value 81.775540
final  value 81.775540 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.978329 
iter  10 value 89.877232
iter  20 value 84.618099
iter  30 value 83.261247
iter  40 value 82.096424
iter  50 value 81.906861
iter  60 value 81.673732
iter  70 value 81.344984
iter  80 value 81.225754
iter  90 value 80.909893
iter 100 value 80.170377
final  value 80.170377 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 120.071700 
iter  10 value 94.699704
iter  20 value 90.961653
iter  30 value 87.513856
iter  40 value 86.762446
iter  50 value 86.589054
iter  60 value 84.491993
iter  70 value 84.197194
iter  80 value 83.887006
iter  90 value 81.732217
iter 100 value 81.115585
final  value 81.115585 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 127.134992 
iter  10 value 94.602390
iter  20 value 94.484381
iter  30 value 89.798347
iter  40 value 87.746606
iter  50 value 86.271066
iter  60 value 86.085599
iter  70 value 84.428075
iter  80 value 82.844924
iter  90 value 81.801985
iter 100 value 81.363196
final  value 81.363196 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.222793 
iter  10 value 94.682393
iter  20 value 91.270590
iter  30 value 87.138101
iter  40 value 83.463462
iter  50 value 83.052392
iter  60 value 82.150827
iter  70 value 81.786152
iter  80 value 81.422954
iter  90 value 81.089698
iter 100 value 80.710253
final  value 80.710253 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.954955 
iter  10 value 94.433266
iter  20 value 87.184654
iter  30 value 86.243082
iter  40 value 85.913696
iter  50 value 85.669351
iter  60 value 84.372833
iter  70 value 81.949674
iter  80 value 81.572296
iter  90 value 81.021819
iter 100 value 80.888838
final  value 80.888838 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.364115 
final  value 94.430697 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.877216 
final  value 94.486765 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.843028 
iter  10 value 87.071531
iter  20 value 86.114764
iter  30 value 86.114076
iter  40 value 85.971017
iter  50 value 85.785850
final  value 85.785773 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.428751 
final  value 94.486157 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.669585 
final  value 94.485626 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.684607 
iter  10 value 94.051078
iter  20 value 94.026793
iter  30 value 94.025471
iter  40 value 94.023226
iter  50 value 87.128277
iter  60 value 86.325918
iter  70 value 83.148701
iter  80 value 80.458532
iter  90 value 79.990930
iter 100 value 79.721938
final  value 79.721938 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.198222 
iter  10 value 94.488938
final  value 94.485125 
converged
Fitting Repeat 3 

# weights:  305
initial  value 111.354886 
iter  10 value 94.488852
iter  20 value 86.817498
iter  30 value 85.837136
iter  40 value 85.660412
iter  50 value 85.659169
iter  60 value 85.552957
iter  70 value 85.361646
iter  80 value 83.425785
iter  90 value 83.112734
iter  90 value 83.112734
iter  90 value 83.112734
final  value 83.112734 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.183096 
iter  10 value 94.488784
iter  20 value 94.391080
iter  30 value 91.201782
iter  40 value 90.222508
final  value 90.222194 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.153593 
iter  10 value 94.119293
iter  20 value 93.164488
iter  30 value 92.573468
final  value 92.568439 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.765432 
iter  10 value 94.055004
iter  20 value 94.049346
iter  30 value 94.048850
iter  40 value 92.595327
iter  50 value 83.207795
iter  60 value 83.053606
iter  70 value 83.052929
iter  80 value 82.631730
iter  90 value 82.407354
final  value 82.407329 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.638636 
iter  10 value 94.492657
iter  20 value 94.484256
iter  30 value 92.192420
iter  40 value 87.566759
iter  50 value 85.665976
iter  60 value 85.662092
iter  60 value 85.662092
final  value 85.662092 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.131555 
iter  10 value 94.492787
iter  20 value 94.471876
iter  30 value 94.470515
iter  40 value 94.441346
iter  50 value 92.895078
iter  60 value 89.745024
iter  70 value 89.686105
iter  80 value 89.682147
final  value 89.681905 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.513848 
iter  10 value 94.491618
iter  20 value 94.467351
iter  30 value 94.110350
iter  40 value 89.167714
iter  50 value 85.175741
iter  60 value 83.735662
iter  70 value 83.507965
iter  80 value 83.266102
iter  90 value 80.877202
iter 100 value 80.603348
final  value 80.603348 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.023329 
iter  10 value 94.492436
iter  20 value 94.411619
iter  30 value 92.888675
iter  40 value 92.860941
iter  50 value 92.622218
iter  60 value 91.588626
iter  70 value 89.522033
iter  80 value 89.158426
iter  90 value 88.868164
iter 100 value 88.867602
final  value 88.867602 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 152.482199 
iter  10 value 117.957093
iter  20 value 115.049997
iter  30 value 106.771907
iter  40 value 105.984859
iter  50 value 105.432911
iter  60 value 105.047632
iter  70 value 103.337894
iter  80 value 102.541047
iter  90 value 101.523246
iter 100 value 100.980519
final  value 100.980519 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 141.048778 
iter  10 value 118.301206
iter  20 value 117.648530
iter  30 value 107.996864
iter  40 value 103.556366
iter  50 value 102.497897
iter  60 value 102.257420
iter  70 value 101.535265
iter  80 value 101.435714
iter  90 value 101.311287
iter 100 value 101.014996
final  value 101.014996 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 126.860612 
iter  10 value 117.876962
iter  20 value 112.662921
iter  30 value 106.523275
iter  40 value 105.953139
iter  50 value 103.684663
iter  60 value 102.580356
iter  70 value 102.520202
iter  80 value 102.489166
iter  90 value 102.296633
iter 100 value 101.411771
final  value 101.411771 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 131.352221 
iter  10 value 117.916834
iter  20 value 117.221230
iter  30 value 113.419339
iter  40 value 109.957576
iter  50 value 107.994486
iter  60 value 103.366821
iter  70 value 102.538684
iter  80 value 102.227652
iter  90 value 101.588832
iter 100 value 101.202445
final  value 101.202445 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 141.016629 
iter  10 value 117.870939
iter  20 value 117.610998
iter  30 value 117.531461
iter  40 value 112.679130
iter  50 value 108.980662
iter  60 value 108.716599
iter  70 value 108.385620
iter  80 value 106.544566
iter  90 value 105.702125
iter 100 value 105.597726
final  value 105.597726 
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 May  6 22:18:03 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 
 16.974   1.215  25.944