##############################################################################
##############################################################################
###
### 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_1.14.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck’
* using R version 4.5.1 Patched (2025-06-14 r88325)
* using platform: aarch64-apple-darwin20
* R was compiled by
    Apple clang version 16.0.0 (clang-1600.0.26.6)
    GNU Fortran (GCC) 14.2.0
* running under: macOS Ventura 13.7.5
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.14.0’
* 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 ... INFO
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       53.069  2.215  55.386
corr_plot     51.755  1.963  53.768
FSmethod      49.918  2.126  52.226
pred_ensembel 16.271  0.393  15.036
enrichfindP    0.481  0.077   6.571
* 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: 2 NOTEs
See
  ‘/Users/biocbuild/bbs-3.21-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/4.5-arm64/Resources/library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.14.0’
** 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 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root"
Copyright (C) 2025 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 110.293773 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.467635 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.625756 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.089249 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 113.530529 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.235320 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.970682 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.907363 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.804116 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 113.493362 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.079443 
iter  10 value 93.393799
iter  20 value 93.184534
iter  30 value 93.184081
iter  30 value 93.184081
iter  30 value 93.184081
final  value 93.184081 
converged
Fitting Repeat 2 

# weights:  507
initial  value 116.908621 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.110216 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  507
initial  value 112.220853 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 112.476922 
iter  10 value 85.310654
iter  20 value 83.449785
final  value 83.449688 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.474029 
iter  10 value 94.409995
iter  20 value 85.469941
iter  30 value 84.372768
iter  40 value 84.116593
iter  50 value 83.742072
iter  60 value 83.546924
final  value 83.536421 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.262666 
iter  10 value 94.876144
iter  20 value 94.489593
iter  30 value 94.082743
iter  40 value 92.116548
iter  50 value 87.032756
iter  60 value 86.059690
iter  70 value 85.040086
iter  80 value 84.775112
iter  90 value 84.737028
iter 100 value 83.851064
final  value 83.851064 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.736821 
iter  10 value 94.523730
iter  20 value 94.475223
iter  30 value 93.353262
iter  40 value 91.757528
iter  50 value 91.354861
iter  60 value 91.167389
iter  70 value 90.974473
final  value 90.974454 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.709639 
iter  10 value 94.490458
iter  20 value 94.482284
iter  30 value 93.429553
iter  40 value 92.331457
iter  50 value 92.052283
iter  60 value 89.390633
iter  70 value 86.115734
iter  80 value 85.613336
iter  90 value 85.247639
iter 100 value 84.192540
final  value 84.192540 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 101.243347 
iter  10 value 94.488567
iter  20 value 93.691494
iter  30 value 91.647590
iter  40 value 91.299117
iter  50 value 91.278284
iter  60 value 91.032839
iter  70 value 90.979374
final  value 90.979324 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.862897 
iter  10 value 94.275794
iter  20 value 91.291820
iter  30 value 87.409515
iter  40 value 85.320373
iter  50 value 84.726186
iter  60 value 84.398898
iter  70 value 84.278800
iter  80 value 83.377858
iter  90 value 82.556771
iter 100 value 81.874414
final  value 81.874414 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.196187 
iter  10 value 92.569100
iter  20 value 85.088783
iter  30 value 84.173286
iter  40 value 83.616301
iter  50 value 83.410394
iter  60 value 83.364584
iter  70 value 83.144220
iter  80 value 82.279287
iter  90 value 81.506488
iter 100 value 81.111005
final  value 81.111005 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.037809 
iter  10 value 94.705290
iter  20 value 94.500970
iter  30 value 92.191405
iter  40 value 87.550433
iter  50 value 87.080075
iter  60 value 85.723786
iter  70 value 83.143572
iter  80 value 82.705117
iter  90 value 82.112348
iter 100 value 81.907662
final  value 81.907662 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.254598 
iter  10 value 93.188887
iter  20 value 91.035677
iter  30 value 84.650380
iter  40 value 84.240213
iter  50 value 83.956793
iter  60 value 83.564247
iter  70 value 83.468537
iter  80 value 82.784889
iter  90 value 82.269743
iter 100 value 81.900771
final  value 81.900771 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.894085 
iter  10 value 94.336240
iter  20 value 89.944084
iter  30 value 88.051570
iter  40 value 85.137673
iter  50 value 83.913430
iter  60 value 82.692812
iter  70 value 82.117188
iter  80 value 81.835851
iter  90 value 81.415495
iter 100 value 81.170294
final  value 81.170294 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.101761 
iter  10 value 91.335753
iter  20 value 85.199584
iter  30 value 82.964917
iter  40 value 82.031200
iter  50 value 81.527333
iter  60 value 81.219276
iter  70 value 81.027869
iter  80 value 80.948684
iter  90 value 80.906589
iter 100 value 80.895197
final  value 80.895197 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.412894 
iter  10 value 95.828662
iter  20 value 93.239935
iter  30 value 85.569165
iter  40 value 84.954589
iter  50 value 83.649389
iter  60 value 82.707649
iter  70 value 81.655060
iter  80 value 81.413027
iter  90 value 81.092624
iter 100 value 80.930917
final  value 80.930917 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.269397 
iter  10 value 94.023431
iter  20 value 90.226234
iter  30 value 88.698491
iter  40 value 85.062168
iter  50 value 81.632901
iter  60 value 81.241675
iter  70 value 80.926891
iter  80 value 80.741083
iter  90 value 80.730500
iter 100 value 80.713834
final  value 80.713834 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.684711 
iter  10 value 94.429514
iter  20 value 89.690041
iter  30 value 86.373690
iter  40 value 85.320479
iter  50 value 83.681375
iter  60 value 82.672824
iter  70 value 81.817898
iter  80 value 81.409865
iter  90 value 81.369234
iter 100 value 81.295437
final  value 81.295437 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.064848 
iter  10 value 94.064436
iter  20 value 86.602571
iter  30 value 84.661297
iter  40 value 84.199717
iter  50 value 84.051219
iter  60 value 83.502021
iter  70 value 82.872189
iter  80 value 81.685178
iter  90 value 81.333327
iter 100 value 81.283849
final  value 81.283849 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.681665 
final  value 94.485698 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.886924 
iter  10 value 94.485829
iter  20 value 94.206873
iter  30 value 93.175219
iter  40 value 92.276905
final  value 92.276903 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.757913 
final  value 94.485986 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.828180 
final  value 94.327449 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.900292 
final  value 94.485900 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.349607 
iter  10 value 94.489071
iter  20 value 94.336961
iter  30 value 86.745336
iter  40 value 84.795212
iter  50 value 84.469094
iter  60 value 84.465030
iter  70 value 84.398883
iter  80 value 84.398532
iter  90 value 83.120799
iter 100 value 82.383214
final  value 82.383214 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 111.104261 
iter  10 value 94.488819
iter  20 value 94.302612
iter  30 value 86.360584
iter  40 value 85.442017
iter  50 value 83.093100
iter  60 value 80.998964
iter  70 value 80.224465
iter  80 value 79.995507
iter  90 value 79.915357
iter 100 value 79.678565
final  value 79.678565 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 112.960904 
iter  10 value 94.489060
iter  20 value 94.208756
iter  30 value 84.791692
iter  40 value 84.030527
iter  50 value 83.965702
iter  60 value 83.965573
final  value 83.965568 
converged
Fitting Repeat 4 

# weights:  305
initial  value 116.274574 
iter  10 value 94.489502
iter  20 value 94.407120
iter  30 value 92.284841
iter  40 value 92.235971
iter  50 value 84.056643
iter  60 value 83.994843
iter  70 value 83.744649
iter  80 value 82.731751
iter  90 value 82.579765
final  value 82.574648 
converged
Fitting Repeat 5 

# weights:  305
initial  value 127.516425 
iter  10 value 94.487725
iter  20 value 94.485347
iter  30 value 86.196384
iter  40 value 84.141870
iter  50 value 84.043637
iter  60 value 84.042274
iter  70 value 84.040630
iter  80 value 83.975387
iter  90 value 82.748254
iter 100 value 81.465883
final  value 81.465883 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 102.610375 
iter  10 value 94.292452
iter  20 value 93.387926
iter  30 value 84.103016
iter  40 value 84.095170
iter  50 value 83.986202
iter  60 value 83.964693
final  value 83.964630 
converged
Fitting Repeat 2 

# weights:  507
initial  value 115.350188 
iter  10 value 94.492504
iter  20 value 94.476657
iter  30 value 94.473242
iter  40 value 92.871540
iter  50 value 89.441269
iter  60 value 88.813520
iter  70 value 88.808556
iter  80 value 86.024304
final  value 86.023690 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.777096 
iter  10 value 94.485118
iter  20 value 86.964675
iter  30 value 85.104770
iter  40 value 84.791945
iter  50 value 84.787327
iter  60 value 84.786144
iter  70 value 84.454793
iter  80 value 84.174670
iter  90 value 84.173518
iter 100 value 84.171414
final  value 84.171414 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 126.074332 
iter  10 value 94.492019
iter  20 value 94.484895
final  value 94.484234 
converged
Fitting Repeat 5 

# weights:  507
initial  value 112.353183 
iter  10 value 94.475544
iter  20 value 94.390673
iter  30 value 91.158957
iter  40 value 91.146307
iter  50 value 91.145790
final  value 91.145371 
converged
Fitting Repeat 1 

# weights:  103
initial  value 92.352062 
iter  10 value 85.321844
iter  20 value 85.321393
final  value 85.321379 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.947073 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.678971 
final  value 93.653870 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.429688 
iter  10 value 93.328330
final  value 93.328261 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.081178 
iter  10 value 93.328272
final  value 93.328261 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.500371 
iter  10 value 93.328267
final  value 93.328263 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.325625 
iter  10 value 92.805875
final  value 92.803260 
converged
Fitting Repeat 3 

# weights:  305
initial  value 118.087939 
iter  10 value 93.199102
final  value 93.198901 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.522208 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.959117 
final  value 94.052908 
converged
Fitting Repeat 1 

# weights:  507
initial  value 111.172691 
final  value 93.328261 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.906624 
final  value 93.328261 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.298613 
iter  10 value 93.328261
iter  10 value 93.328261
iter  10 value 93.328261
final  value 93.328261 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.679586 
final  value 93.328261 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.984504 
iter  10 value 93.745659
iter  20 value 91.169183
iter  30 value 91.083463
iter  40 value 91.079778
iter  50 value 91.057023
iter  60 value 81.281367
iter  70 value 79.004822
iter  80 value 78.755825
iter  90 value 78.512058
final  value 78.511755 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.848966 
iter  10 value 93.618118
iter  20 value 88.957188
iter  30 value 85.987834
iter  40 value 85.278419
iter  50 value 82.355748
iter  60 value 81.517602
iter  70 value 81.422243
final  value 81.411146 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.386477 
iter  10 value 94.068236
iter  20 value 94.054876
iter  30 value 93.494101
iter  40 value 93.296412
iter  50 value 93.099367
iter  60 value 83.931486
iter  70 value 81.678434
iter  80 value 81.206776
iter  90 value 79.670300
iter 100 value 78.705557
final  value 78.705557 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.159134 
iter  10 value 94.057087
iter  20 value 88.736800
iter  30 value 85.869681
iter  40 value 84.310522
iter  50 value 83.138225
final  value 83.132768 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.520671 
iter  10 value 94.024525
iter  20 value 93.720253
iter  30 value 93.669344
iter  40 value 90.830019
iter  50 value 89.476306
iter  60 value 85.556135
iter  70 value 85.472413
iter  80 value 82.903735
iter  90 value 82.702171
final  value 82.701762 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.272217 
iter  10 value 93.573653
iter  20 value 93.379237
iter  30 value 84.860115
iter  40 value 83.918452
iter  50 value 83.557861
iter  60 value 83.313680
iter  70 value 83.158937
iter  80 value 83.132769
iter  80 value 83.132768
iter  80 value 83.132768
final  value 83.132768 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.852176 
iter  10 value 94.024763
iter  20 value 86.294196
iter  30 value 85.317085
iter  40 value 83.501412
iter  50 value 82.902369
iter  60 value 82.679121
iter  70 value 82.319574
iter  80 value 80.061482
iter  90 value 79.506134
iter 100 value 79.327463
final  value 79.327463 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.071824 
iter  10 value 94.700338
iter  20 value 84.109174
iter  30 value 82.717074
iter  40 value 81.535831
iter  50 value 80.803727
iter  60 value 79.084866
iter  70 value 78.899962
iter  80 value 78.833808
iter  90 value 78.394901
iter 100 value 77.872638
final  value 77.872638 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 110.091000 
iter  10 value 94.047610
iter  20 value 87.703648
iter  30 value 86.041991
iter  40 value 81.907448
iter  50 value 80.857049
iter  60 value 80.185266
iter  70 value 78.085531
iter  80 value 77.752265
iter  90 value 77.107535
iter 100 value 76.842712
final  value 76.842712 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 114.007224 
iter  10 value 94.445854
iter  20 value 93.597594
iter  30 value 92.199938
iter  40 value 84.534257
iter  50 value 81.497439
iter  60 value 79.316721
iter  70 value 78.958267
iter  80 value 78.444837
iter  90 value 77.576981
iter 100 value 77.279475
final  value 77.279475 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 122.596653 
iter  10 value 94.092945
iter  20 value 93.956515
iter  30 value 93.500172
iter  40 value 82.822394
iter  50 value 82.154438
iter  60 value 80.782087
iter  70 value 79.642727
iter  80 value 78.492638
iter  90 value 77.874010
iter 100 value 77.600668
final  value 77.600668 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.893906 
iter  10 value 93.682207
iter  20 value 82.527227
iter  30 value 80.258471
iter  40 value 79.250694
iter  50 value 78.806285
iter  60 value 78.672875
iter  70 value 78.519787
iter  80 value 78.486856
iter  90 value 78.423943
iter 100 value 78.036548
final  value 78.036548 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.854228 
iter  10 value 94.097736
iter  20 value 91.860681
iter  30 value 91.616767
iter  40 value 87.795437
iter  50 value 81.378064
iter  60 value 79.220877
iter  70 value 78.189196
iter  80 value 77.416693
iter  90 value 77.364957
iter 100 value 77.359695
final  value 77.359695 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 117.533749 
iter  10 value 94.011881
iter  20 value 91.675191
iter  30 value 83.240286
iter  40 value 81.158637
iter  50 value 78.748012
iter  60 value 77.747772
iter  70 value 77.519080
iter  80 value 77.152662
iter  90 value 76.948006
iter 100 value 76.858470
final  value 76.858470 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.728028 
iter  10 value 95.865299
iter  20 value 85.878875
iter  30 value 85.252882
iter  40 value 84.087903
iter  50 value 82.288146
iter  60 value 78.293916
iter  70 value 77.864560
iter  80 value 77.556619
iter  90 value 77.132408
iter 100 value 76.932480
final  value 76.932480 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 121.840343 
iter  10 value 93.686971
iter  20 value 90.641267
iter  30 value 86.193045
iter  40 value 85.489656
iter  50 value 84.939732
iter  60 value 81.413394
iter  70 value 78.338210
iter  80 value 77.643650
iter  90 value 77.078034
iter 100 value 76.899966
final  value 76.899966 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.140957 
iter  10 value 93.222642
iter  20 value 93.211439
final  value 93.209713 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.645321 
final  value 94.054687 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.378151 
final  value 94.054648 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.700136 
iter  10 value 93.750763
iter  20 value 88.167150
iter  30 value 87.711001
iter  40 value 87.472612
iter  50 value 87.471359
iter  60 value 85.400503
iter  70 value 85.102795
final  value 85.100457 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.001290 
iter  10 value 94.054713
iter  20 value 94.052908
iter  30 value 84.482188
iter  40 value 83.319183
final  value 83.318296 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.769738 
iter  10 value 94.057959
iter  20 value 94.052932
iter  30 value 93.648166
iter  40 value 93.521142
final  value 93.521099 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.420291 
iter  10 value 93.544115
iter  20 value 93.522779
iter  30 value 93.499612
iter  40 value 93.496579
iter  50 value 93.486692
iter  60 value 84.816496
iter  70 value 84.348198
final  value 84.348173 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.239228 
iter  10 value 94.057246
iter  20 value 94.006231
iter  30 value 92.129269
iter  40 value 84.656213
iter  50 value 84.403262
iter  60 value 84.401727
final  value 84.401699 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.157942 
iter  10 value 94.057568
iter  20 value 94.017798
iter  30 value 94.011592
iter  40 value 93.945058
iter  50 value 93.330206
iter  60 value 93.236491
final  value 93.210177 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.854501 
iter  10 value 93.333384
iter  20 value 93.327836
iter  30 value 86.236206
iter  40 value 85.173823
final  value 85.170900 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.811956 
iter  10 value 94.061136
iter  20 value 94.050928
iter  30 value 85.206443
iter  40 value 83.545624
iter  50 value 79.415532
iter  60 value 78.048148
iter  70 value 77.459908
iter  80 value 77.240928
iter  90 value 77.238379
iter 100 value 77.053521
final  value 77.053521 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 97.296607 
iter  10 value 93.276982
iter  20 value 93.151794
iter  30 value 93.147044
iter  40 value 93.135107
iter  50 value 89.604452
iter  60 value 81.581657
iter  70 value 81.291719
iter  80 value 81.248820
iter  90 value 81.224531
iter 100 value 80.562556
final  value 80.562556 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 95.036488 
iter  10 value 94.060680
iter  20 value 83.098092
iter  30 value 82.558612
iter  40 value 82.555896
iter  50 value 82.554295
iter  60 value 82.304789
final  value 82.299153 
converged
Fitting Repeat 4 

# weights:  507
initial  value 114.175628 
iter  10 value 93.349193
iter  20 value 93.336652
iter  30 value 93.144848
iter  40 value 82.526588
iter  50 value 81.799292
final  value 81.788298 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.134147 
iter  10 value 93.284090
iter  20 value 93.116923
iter  30 value 92.070597
iter  40 value 82.721907
iter  50 value 82.009290
iter  60 value 78.850324
iter  70 value 78.471799
iter  80 value 78.450610
final  value 78.450556 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.933376 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.932251 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.488213 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.932863 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.297329 
final  value 94.430233 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.130516 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.030211 
final  value 94.057229 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.167209 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.609898 
final  value 94.354396 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.711779 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.498537 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.856012 
iter  10 value 94.240912
iter  20 value 94.199646
iter  30 value 94.196991
final  value 94.196989 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.882973 
iter  10 value 94.331125
iter  20 value 94.325916
iter  30 value 94.311428
final  value 94.311251 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.694509 
iter  10 value 89.883315
iter  20 value 82.478741
iter  30 value 82.440663
final  value 82.440657 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.753826 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 94.437055 
iter  10 value 88.062880
iter  20 value 84.582103
iter  30 value 82.920794
iter  40 value 82.873188
iter  50 value 82.698537
iter  60 value 82.371345
iter  70 value 82.178710
iter  80 value 82.116391
final  value 82.116323 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.584534 
iter  10 value 94.571807
iter  20 value 94.488274
iter  30 value 94.097897
iter  40 value 94.062839
iter  50 value 88.186880
iter  60 value 87.573312
iter  70 value 85.874708
iter  80 value 83.924995
iter  90 value 83.887081
iter 100 value 83.876361
final  value 83.876361 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.235831 
iter  10 value 94.284705
iter  20 value 93.040046
iter  30 value 91.261788
iter  40 value 90.904905
iter  50 value 90.888696
final  value 90.888691 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.486803 
iter  10 value 94.571344
iter  20 value 94.185549
iter  30 value 88.116462
iter  40 value 85.999950
iter  50 value 84.089511
iter  60 value 83.243374
iter  70 value 83.120717
iter  80 value 83.091689
final  value 83.091673 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.615335 
iter  10 value 94.489909
iter  20 value 94.427471
iter  30 value 94.135158
iter  40 value 94.129934
iter  50 value 93.640257
iter  60 value 91.389513
iter  70 value 90.293205
iter  80 value 87.220257
iter  90 value 87.010661
iter 100 value 86.957745
final  value 86.957745 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 102.596913 
iter  10 value 94.451940
iter  20 value 92.883626
iter  30 value 89.119027
iter  40 value 85.629624
iter  50 value 83.523339
iter  60 value 82.781602
iter  70 value 81.667669
iter  80 value 80.720764
iter  90 value 80.323568
iter 100 value 79.938409
final  value 79.938409 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.860293 
iter  10 value 94.349328
iter  20 value 94.100908
iter  30 value 94.002019
iter  40 value 86.216850
iter  50 value 85.641089
iter  60 value 84.100095
iter  70 value 82.467237
iter  80 value 81.606719
iter  90 value 80.688925
iter 100 value 80.451425
final  value 80.451425 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 111.307387 
iter  10 value 94.506860
iter  20 value 87.363735
iter  30 value 85.503597
iter  40 value 84.831017
iter  50 value 84.359111
iter  60 value 83.045809
iter  70 value 81.401893
iter  80 value 81.130159
iter  90 value 80.561143
iter 100 value 80.051899
final  value 80.051899 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.763534 
iter  10 value 94.519683
iter  20 value 91.267467
iter  30 value 87.146987
iter  40 value 87.100791
iter  50 value 85.788437
iter  60 value 84.159199
iter  70 value 80.494369
iter  80 value 79.876674
iter  90 value 79.820715
iter 100 value 79.766467
final  value 79.766467 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 114.701200 
iter  10 value 93.961489
iter  20 value 89.097334
iter  30 value 87.852386
iter  40 value 85.088145
iter  50 value 83.746737
iter  60 value 83.104203
iter  70 value 81.811981
iter  80 value 81.747654
iter  90 value 81.196332
iter 100 value 80.297900
final  value 80.297900 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 125.636990 
iter  10 value 94.766612
iter  20 value 88.449973
iter  30 value 87.959452
iter  40 value 87.784450
iter  50 value 86.460437
iter  60 value 83.000358
iter  70 value 80.373593
iter  80 value 79.761931
iter  90 value 79.537804
iter 100 value 79.356391
final  value 79.356391 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.051309 
iter  10 value 94.587796
iter  20 value 94.493379
iter  30 value 93.925380
iter  40 value 88.569699
iter  50 value 80.730526
iter  60 value 79.947482
iter  70 value 79.751587
iter  80 value 79.431660
iter  90 value 79.166961
iter 100 value 79.081083
final  value 79.081083 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.986320 
iter  10 value 94.547246
iter  20 value 93.859622
iter  30 value 88.681358
iter  40 value 87.272717
iter  50 value 87.078939
iter  60 value 83.978665
iter  70 value 81.704706
iter  80 value 80.624022
iter  90 value 80.156493
iter 100 value 79.821697
final  value 79.821697 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 116.097414 
iter  10 value 94.504063
iter  20 value 93.947624
iter  30 value 92.077933
iter  40 value 90.750180
iter  50 value 87.774029
iter  60 value 84.568985
iter  70 value 83.030855
iter  80 value 82.802107
iter  90 value 82.694709
iter 100 value 82.654063
final  value 82.654063 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.214854 
iter  10 value 94.344039
iter  20 value 87.167606
iter  30 value 85.464565
iter  40 value 82.486883
iter  50 value 81.616881
iter  60 value 80.648088
iter  70 value 79.465712
iter  80 value 79.331018
iter  90 value 79.272600
iter 100 value 79.263500
final  value 79.263500 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.063368 
iter  10 value 94.485942
iter  20 value 94.483506
iter  30 value 90.701928
iter  40 value 87.460619
final  value 87.284851 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.876122 
iter  10 value 94.059121
iter  20 value 94.058627
iter  30 value 94.050034
final  value 94.049793 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.429301 
final  value 94.355757 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.157490 
final  value 94.485676 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.217032 
final  value 94.487003 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.046207 
iter  10 value 94.489099
iter  20 value 94.484353
iter  30 value 94.046709
iter  40 value 88.003319
iter  50 value 87.074444
iter  50 value 87.074444
final  value 87.074444 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.321503 
iter  10 value 93.767308
iter  20 value 87.687843
iter  30 value 87.341000
iter  40 value 87.307026
iter  50 value 83.984402
iter  60 value 81.762519
iter  70 value 81.761870
iter  80 value 81.752775
iter  90 value 81.698080
iter 100 value 81.494116
final  value 81.494116 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 96.115517 
iter  10 value 94.489139
final  value 94.485469 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.691185 
iter  10 value 94.106047
iter  20 value 94.062075
iter  30 value 94.054862
iter  40 value 86.684478
iter  50 value 85.894353
iter  60 value 85.871646
iter  70 value 85.870020
iter  80 value 85.869915
iter  90 value 82.767086
iter 100 value 81.548299
final  value 81.548299 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.040514 
iter  10 value 94.525106
iter  20 value 94.382496
iter  30 value 94.081592
iter  40 value 94.077683
iter  50 value 94.070738
iter  60 value 94.051444
iter  70 value 93.984936
iter  80 value 90.724459
iter  90 value 90.526363
iter 100 value 89.726324
final  value 89.726324 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 98.194213 
iter  10 value 94.492237
iter  20 value 94.382522
iter  30 value 84.740764
iter  40 value 83.390843
iter  50 value 83.379354
iter  60 value 83.379181
iter  70 value 83.362229
iter  80 value 81.246474
iter  90 value 80.550214
iter 100 value 80.539523
final  value 80.539523 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 132.161264 
iter  10 value 94.362639
iter  20 value 92.988813
iter  30 value 83.028010
final  value 83.027982 
converged
Fitting Repeat 3 

# weights:  507
initial  value 137.806601 
iter  10 value 94.362381
iter  20 value 94.355032
iter  30 value 87.606449
iter  40 value 85.156368
iter  50 value 85.143794
iter  60 value 85.126371
iter  70 value 85.126007
iter  80 value 85.125911
final  value 85.125905 
converged
Fitting Repeat 4 

# weights:  507
initial  value 120.931964 
iter  10 value 94.058432
iter  20 value 94.056045
iter  30 value 94.051346
iter  40 value 94.050861
iter  50 value 94.048412
iter  60 value 93.886870
iter  70 value 90.739606
iter  80 value 88.468689
iter  90 value 83.078769
iter 100 value 82.654065
final  value 82.654065 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 117.929333 
iter  10 value 94.363347
iter  20 value 94.354683
final  value 94.354595 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.304098 
iter  10 value 94.052920
final  value 94.052911 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.249173 
iter  10 value 93.836067
final  value 93.836066 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.175629 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.242694 
final  value 93.836066 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.791356 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 120.792497 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.539965 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 120.767860 
final  value 93.988095 
converged
Fitting Repeat 4 

# weights:  305
initial  value 109.853434 
final  value 93.836066 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.648168 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 133.722361 
iter  10 value 93.836062
final  value 93.835715 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.136694 
iter  10 value 93.759127
final  value 93.745930 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.098347 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.463481 
iter  10 value 88.816841
iter  20 value 85.153623
final  value 85.046177 
converged
Fitting Repeat 5 

# weights:  507
initial  value 110.963047 
iter  10 value 94.011548
iter  20 value 93.973817
iter  30 value 93.969054
final  value 93.969041 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.461432 
iter  10 value 94.073675
iter  20 value 94.028699
iter  30 value 93.756840
iter  40 value 90.067859
iter  50 value 87.370837
iter  60 value 86.251122
iter  70 value 85.030897
final  value 85.027874 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.408433 
iter  10 value 93.695384
iter  20 value 88.254820
iter  30 value 86.654725
iter  40 value 86.413336
iter  50 value 86.268782
iter  60 value 86.229293
iter  70 value 86.114696
final  value 86.112439 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.308323 
iter  10 value 94.055628
iter  20 value 93.335728
iter  30 value 89.388247
iter  40 value 87.663215
iter  50 value 87.102754
iter  60 value 86.680208
iter  70 value 86.447459
iter  80 value 85.668660
iter  90 value 85.060359
iter 100 value 85.028452
final  value 85.028452 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.173489 
iter  10 value 94.057033
iter  20 value 91.258059
iter  30 value 89.732590
iter  40 value 89.070134
iter  50 value 87.523710
iter  60 value 87.036099
iter  70 value 87.028403
iter  70 value 87.028402
iter  70 value 87.028402
final  value 87.028402 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.007915 
iter  10 value 94.045891
iter  20 value 93.914415
iter  30 value 92.727165
iter  40 value 88.847867
iter  50 value 88.571591
iter  60 value 87.657184
iter  70 value 87.075073
final  value 87.069553 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.921781 
iter  10 value 94.120002
iter  20 value 91.961493
iter  30 value 89.789605
iter  40 value 88.209886
iter  50 value 84.339175
iter  60 value 84.009299
iter  70 value 83.724788
iter  80 value 83.647992
iter  90 value 83.631649
iter 100 value 83.629804
final  value 83.629804 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.152533 
iter  10 value 94.030225
iter  20 value 89.149259
iter  30 value 88.064986
iter  40 value 87.493163
iter  50 value 85.835238
iter  60 value 85.786313
iter  70 value 85.719731
iter  80 value 84.944328
iter  90 value 83.869343
iter 100 value 83.435163
final  value 83.435163 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 107.568938 
iter  10 value 95.170486
iter  20 value 94.682099
iter  30 value 94.331487
iter  40 value 92.223784
iter  50 value 88.889646
iter  60 value 88.647892
iter  70 value 88.422132
iter  80 value 86.227245
iter  90 value 85.696327
iter 100 value 85.427960
final  value 85.427960 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.765504 
iter  10 value 94.036012
iter  20 value 90.812722
iter  30 value 89.138304
iter  40 value 86.708354
iter  50 value 86.206806
iter  60 value 85.750498
iter  70 value 84.243335
iter  80 value 83.778820
iter  90 value 83.517932
iter 100 value 83.422494
final  value 83.422494 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.428120 
iter  10 value 93.120643
iter  20 value 91.877466
iter  30 value 91.308089
iter  40 value 87.510930
iter  50 value 86.833266
iter  60 value 86.333015
iter  70 value 86.051899
iter  80 value 85.833259
iter  90 value 85.048195
iter 100 value 83.784935
final  value 83.784935 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.104430 
iter  10 value 93.842650
iter  20 value 87.658957
iter  30 value 87.443434
iter  40 value 87.062453
iter  50 value 85.997166
iter  60 value 85.875216
iter  70 value 85.669265
iter  80 value 84.743500
iter  90 value 84.272769
iter 100 value 83.905462
final  value 83.905462 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.695038 
iter  10 value 94.033657
iter  20 value 87.792413
iter  30 value 87.154133
iter  40 value 86.982499
iter  50 value 85.880212
iter  60 value 84.406513
iter  70 value 84.026954
iter  80 value 83.704103
iter  90 value 83.583326
iter 100 value 83.512213
final  value 83.512213 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 112.007272 
iter  10 value 93.992029
iter  20 value 89.884770
iter  30 value 86.576827
iter  40 value 85.827743
iter  50 value 85.502452
iter  60 value 84.842235
iter  70 value 84.449686
iter  80 value 83.797548
iter  90 value 83.414188
iter 100 value 83.222597
final  value 83.222597 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 138.575164 
iter  10 value 96.200115
iter  20 value 92.266487
iter  30 value 88.851427
iter  40 value 88.274919
iter  50 value 85.927897
iter  60 value 85.318329
iter  70 value 84.344452
iter  80 value 84.008412
iter  90 value 83.916282
iter 100 value 83.888070
final  value 83.888070 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 124.567432 
iter  10 value 94.105999
iter  20 value 93.219541
iter  30 value 90.776149
iter  40 value 90.372542
iter  50 value 87.534843
iter  60 value 86.419982
iter  70 value 84.699591
iter  80 value 83.889126
iter  90 value 83.652930
iter 100 value 83.600736
final  value 83.600736 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.587524 
final  value 94.054301 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.386326 
iter  10 value 93.787453
iter  20 value 93.785367
iter  30 value 88.841927
iter  40 value 86.993400
iter  50 value 86.992954
iter  50 value 86.992953
iter  50 value 86.992953
final  value 86.992953 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.564638 
final  value 94.054554 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.565327 
iter  10 value 85.758160
iter  20 value 84.730922
iter  30 value 84.368249
iter  40 value 84.367888
final  value 84.367455 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.638701 
final  value 94.054737 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.844017 
iter  10 value 94.056791
iter  20 value 92.925796
iter  30 value 87.042526
iter  40 value 86.991929
final  value 86.991845 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.548640 
iter  10 value 94.057722
iter  20 value 94.056927
iter  30 value 94.039021
iter  40 value 93.083146
iter  50 value 93.005171
iter  60 value 93.002178
final  value 93.002099 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.985059 
iter  10 value 94.057628
iter  20 value 93.909186
iter  30 value 92.412820
iter  40 value 89.387516
iter  50 value 89.188116
iter  60 value 89.146279
iter  70 value 89.060898
iter  80 value 89.059354
iter  90 value 89.058312
iter 100 value 89.057635
final  value 89.057635 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 120.137435 
iter  10 value 94.057361
iter  20 value 94.025747
iter  30 value 92.707871
iter  40 value 88.430752
iter  50 value 88.234157
iter  60 value 85.435907
iter  70 value 84.448399
final  value 84.271950 
converged
Fitting Repeat 5 

# weights:  305
initial  value 114.809344 
iter  10 value 94.058122
iter  20 value 94.053116
final  value 94.052930 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.555653 
iter  10 value 93.952282
iter  20 value 93.801293
iter  30 value 88.795917
iter  40 value 87.250001
iter  50 value 85.358462
iter  60 value 84.492700
iter  70 value 83.879607
iter  80 value 83.833965
iter  90 value 83.833213
final  value 83.833204 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.742693 
iter  10 value 93.826810
iter  20 value 93.820573
iter  30 value 92.977842
iter  40 value 88.364409
iter  50 value 86.076445
iter  60 value 84.021883
iter  70 value 83.832063
iter  80 value 83.814042
iter  90 value 83.810408
iter 100 value 83.808679
final  value 83.808679 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.561312 
iter  10 value 94.061675
iter  20 value 94.053170
final  value 94.053057 
converged
Fitting Repeat 4 

# weights:  507
initial  value 107.211197 
iter  10 value 93.829373
iter  20 value 93.759986
iter  30 value 90.190920
iter  40 value 89.186514
iter  50 value 85.763379
iter  60 value 83.478998
iter  70 value 83.285080
iter  80 value 83.087797
iter  90 value 83.083858
iter 100 value 83.083222
final  value 83.083222 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.420904 
iter  10 value 94.060960
iter  20 value 94.054066
final  value 94.053794 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.354730 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.126617 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 109.678218 
iter  10 value 93.567527
final  value 93.567525 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.369212 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.921455 
iter  10 value 93.772981
final  value 93.772976 
converged
Fitting Repeat 1 

# weights:  305
initial  value 117.873466 
final  value 94.252920 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.515267 
iter  10 value 86.408098
iter  20 value 86.054679
iter  30 value 85.563580
iter  40 value 85.562872
iter  40 value 85.562871
iter  40 value 85.562871
final  value 85.562871 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.859389 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.308370 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.111903 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.900823 
iter  10 value 92.783002
iter  20 value 90.324480
iter  30 value 90.306393
iter  40 value 90.025643
iter  50 value 89.996759
final  value 89.996747 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.411102 
iter  10 value 94.467391
iter  10 value 94.467391
iter  10 value 94.467391
final  value 94.467391 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.286420 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.345688 
iter  10 value 94.465747
iter  20 value 94.418981
iter  30 value 94.416674
iter  30 value 94.416673
iter  30 value 94.416673
final  value 94.416673 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.184424 
iter  10 value 94.421976
iter  20 value 94.420728
iter  30 value 93.803770
iter  40 value 93.763129
final  value 93.762185 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.067031 
iter  10 value 94.419008
iter  20 value 87.049987
iter  30 value 85.522361
iter  40 value 85.070318
iter  50 value 84.939190
iter  60 value 82.634834
iter  70 value 82.528362
final  value 82.458355 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.889721 
iter  10 value 94.433807
iter  20 value 86.801098
iter  30 value 85.019495
iter  40 value 83.816764
iter  50 value 83.122220
iter  60 value 83.016727
final  value 82.978387 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.381594 
iter  10 value 94.486952
iter  20 value 93.771419
iter  30 value 87.441467
iter  40 value 85.072182
iter  50 value 84.393135
iter  60 value 84.100664
iter  70 value 83.928343
iter  80 value 83.680675
iter  90 value 80.839367
iter 100 value 80.312047
final  value 80.312047 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.985225 
iter  10 value 94.477779
iter  20 value 91.956999
iter  30 value 89.223917
iter  40 value 86.760374
iter  50 value 83.679552
iter  60 value 83.392746
iter  70 value 83.269111
iter  80 value 83.000414
final  value 82.978350 
converged
Fitting Repeat 5 

# weights:  103
initial  value 115.555031 
iter  10 value 88.766597
iter  20 value 84.879119
iter  30 value 84.843452
iter  40 value 83.456913
iter  50 value 82.981193
iter  60 value 82.978364
final  value 82.978350 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.253400 
iter  10 value 94.280102
iter  20 value 93.871449
iter  30 value 93.792350
iter  40 value 88.212582
iter  50 value 85.521174
iter  60 value 84.729854
iter  70 value 82.251594
iter  80 value 80.984446
iter  90 value 79.979552
iter 100 value 79.570438
final  value 79.570438 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.883463 
iter  10 value 94.346980
iter  20 value 85.951271
iter  30 value 83.248448
iter  40 value 82.197778
iter  50 value 81.326598
iter  60 value 80.826940
iter  70 value 80.018613
iter  80 value 79.822734
iter  90 value 79.077748
iter 100 value 78.502901
final  value 78.502901 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 111.636335 
iter  10 value 94.570091
iter  20 value 94.503479
iter  30 value 93.994432
iter  40 value 86.288844
iter  50 value 85.465368
iter  60 value 82.526550
iter  70 value 81.016355
iter  80 value 80.019832
iter  90 value 78.682118
iter 100 value 78.547576
final  value 78.547576 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.416681 
iter  10 value 96.461550
iter  20 value 86.142371
iter  30 value 83.956377
iter  40 value 80.939441
iter  50 value 79.776664
iter  60 value 79.353787
iter  70 value 79.300001
iter  80 value 79.232756
iter  90 value 78.811090
iter 100 value 78.319595
final  value 78.319595 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 115.776611 
iter  10 value 94.000594
iter  20 value 83.811122
iter  30 value 82.371898
iter  40 value 80.993369
iter  50 value 80.379831
iter  60 value 79.606921
iter  70 value 78.932196
iter  80 value 78.413218
iter  90 value 78.245467
iter 100 value 78.166168
final  value 78.166168 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.138920 
iter  10 value 96.459939
iter  20 value 86.133552
iter  30 value 81.634400
iter  40 value 79.660239
iter  50 value 79.089143
iter  60 value 78.299688
iter  70 value 77.985486
iter  80 value 77.887644
iter  90 value 77.851799
iter 100 value 77.675631
final  value 77.675631 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 116.696672 
iter  10 value 94.983714
iter  20 value 94.569477
iter  30 value 87.317676
iter  40 value 85.153983
iter  50 value 83.033101
iter  60 value 80.723459
iter  70 value 79.671197
iter  80 value 79.485859
iter  90 value 79.281546
iter 100 value 79.204195
final  value 79.204195 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.015764 
iter  10 value 94.500580
iter  20 value 88.127523
iter  30 value 86.197367
iter  40 value 81.704185
iter  50 value 79.983578
iter  60 value 78.740300
iter  70 value 78.308321
iter  80 value 78.144177
iter  90 value 78.112068
iter 100 value 78.004204
final  value 78.004204 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.377221 
iter  10 value 93.796866
iter  20 value 91.107322
iter  30 value 90.884903
iter  40 value 85.738302
iter  50 value 84.492473
iter  60 value 82.216276
iter  70 value 80.416924
iter  80 value 78.811069
iter  90 value 78.070925
iter 100 value 77.870432
final  value 77.870432 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.055764 
iter  10 value 93.190123
iter  20 value 84.763615
iter  30 value 82.976526
iter  40 value 82.633953
iter  50 value 81.357737
iter  60 value 80.077162
iter  70 value 78.943378
iter  80 value 78.239488
iter  90 value 78.106441
iter 100 value 78.031840
final  value 78.031840 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.488639 
final  value 94.485818 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.109788 
final  value 94.485694 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.529813 
final  value 94.485819 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.881078 
final  value 94.485844 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.028945 
final  value 94.486263 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.080025 
iter  10 value 94.489152
iter  20 value 94.454203
iter  30 value 92.145597
iter  40 value 92.107738
final  value 92.107724 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.924971 
iter  10 value 94.489375
iter  20 value 94.445784
iter  30 value 94.322643
iter  40 value 83.047604
iter  50 value 81.703615
iter  60 value 81.303196
iter  70 value 80.893994
iter  80 value 80.677672
final  value 80.677665 
converged
Fitting Repeat 3 

# weights:  305
initial  value 110.212577 
iter  10 value 94.390500
iter  20 value 93.751477
iter  30 value 84.703849
iter  40 value 83.764992
iter  50 value 83.709565
iter  60 value 83.617636
iter  70 value 83.607255
final  value 83.607228 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.807719 
iter  10 value 94.486569
iter  20 value 93.951372
iter  30 value 93.684984
iter  30 value 93.684984
iter  30 value 93.684984
final  value 93.684984 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.853935 
iter  10 value 94.472317
iter  20 value 94.467715
iter  30 value 94.355888
iter  40 value 83.944042
iter  50 value 81.986385
iter  60 value 81.877613
iter  70 value 81.672232
iter  80 value 81.668183
iter  90 value 81.151821
iter 100 value 80.192124
final  value 80.192124 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 96.794564 
iter  10 value 94.260936
iter  20 value 94.256725
final  value 94.256674 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.172507 
iter  10 value 89.036974
iter  20 value 86.063853
iter  30 value 84.715698
iter  40 value 83.821268
iter  50 value 83.819546
iter  60 value 83.719775
iter  70 value 83.536924
iter  80 value 82.657084
iter  90 value 82.220427
iter 100 value 82.061280
final  value 82.061280 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 97.456884 
iter  10 value 92.017030
iter  20 value 90.597255
iter  30 value 90.505267
iter  40 value 90.501646
iter  50 value 90.493292
iter  60 value 90.488005
iter  70 value 90.457445
iter  80 value 90.395431
final  value 90.394742 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.661258 
iter  10 value 94.476079
iter  20 value 94.469209
iter  30 value 91.441002
final  value 90.948162 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.419012 
iter  10 value 94.489768
iter  20 value 94.475580
iter  30 value 94.472928
iter  40 value 92.356537
iter  50 value 90.641548
iter  60 value 90.548984
final  value 90.548488 
converged
Fitting Repeat 1 

# weights:  507
initial  value 127.964277 
iter  10 value 118.059175
iter  20 value 107.276020
iter  30 value 106.025505
iter  40 value 104.066143
iter  50 value 103.134957
iter  60 value 102.922470
iter  70 value 102.545624
iter  80 value 101.923888
iter  90 value 101.349948
iter 100 value 101.239345
final  value 101.239345 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 131.632243 
iter  10 value 118.125823
iter  20 value 109.786451
iter  30 value 106.205068
iter  40 value 105.694099
iter  50 value 105.208589
iter  60 value 105.158532
iter  70 value 105.046741
iter  80 value 105.009850
iter  90 value 104.933647
iter 100 value 103.629390
final  value 103.629390 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 150.509651 
iter  10 value 118.071706
iter  20 value 117.823518
iter  30 value 117.127998
iter  40 value 108.198043
iter  50 value 104.071284
iter  60 value 103.328199
iter  70 value 102.830748
iter  80 value 102.696646
iter  90 value 102.511169
iter 100 value 102.083936
final  value 102.083936 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 142.591625 
iter  10 value 117.257431
iter  20 value 115.549547
iter  30 value 115.006874
iter  40 value 114.465459
iter  50 value 110.615541
iter  60 value 107.027843
iter  70 value 106.164062
iter  80 value 105.263954
iter  90 value 104.126737
iter 100 value 103.439866
final  value 103.439866 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 144.601276 
iter  10 value 117.931648
iter  20 value 116.394149
iter  30 value 112.795082
iter  40 value 110.300765
iter  50 value 106.844287
iter  60 value 104.615775
iter  70 value 103.787074
iter  80 value 102.942107
iter  90 value 102.673646
iter 100 value 102.272392
final  value 102.272392 
stopped after 100 iterations
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Tue Sep  9 23:51:20 2025 
*********************************************** 
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 
 55.723   1.769 141.583