##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings HPiP_1.14.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2025-02-19 r87757)
* using platform: aarch64-unknown-linux-gnu
* R was compiled by
    aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0
    GNU Fortran (GCC) 14.2.0
* running under: openEuler 24.03 (LTS-SP1)
* 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 loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... 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       39.436  0.335  39.841
corr_plot     37.187  0.320  37.582
FSmethod      36.730  0.228  37.029
pred_ensembel 18.006  0.556  17.360
enrichfindP    0.514  0.019  19.596
getFASTA       0.080  0.004   5.227
* 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
  ‘/home/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck/00check.log’
for details.

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


* installing to library ‘/home/biocbuild/R/R-devel_2025-02-19/site-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 Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu

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

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

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

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

# weights:  103
initial  value 94.621339 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.646015 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 108.179398 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 113.996264 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.045045 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.253459 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.949248 
final  value 94.052895 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.094453 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.786956 
iter  10 value 93.328267
final  value 93.328261 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.615083 
final  value 93.328261 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.659703 
iter  10 value 93.328261
iter  10 value 93.328261
iter  10 value 93.328261
final  value 93.328261 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.367503 
iter  10 value 91.038936
final  value 91.038932 
converged
Fitting Repeat 3 

# weights:  507
initial  value 129.951030 
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 113.910149 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.148834 
iter  10 value 93.328263
final  value 93.328261 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.596602 
iter  10 value 94.067835
iter  20 value 90.905654
iter  30 value 85.515280
iter  40 value 80.033388
iter  50 value 77.411800
iter  60 value 77.020688
iter  70 value 76.986550
iter  80 value 76.209608
iter  90 value 75.833310
iter 100 value 75.814275
final  value 75.814275 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 108.897226 
iter  10 value 94.126239
iter  20 value 93.401710
iter  30 value 93.312067
iter  40 value 90.887350
iter  50 value 80.404149
iter  60 value 78.801169
iter  70 value 77.331754
iter  80 value 76.393874
iter  90 value 75.635302
iter 100 value 75.619281
final  value 75.619281 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.945681 
iter  10 value 93.361973
iter  20 value 93.288852
iter  30 value 87.088602
iter  40 value 85.310903
iter  50 value 79.782090
iter  60 value 77.434984
iter  70 value 75.972923
iter  80 value 75.628045
iter  90 value 75.618428
final  value 75.618342 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.527829 
iter  10 value 94.043483
iter  20 value 93.173949
iter  30 value 93.144563
iter  40 value 92.290068
iter  50 value 84.932048
iter  60 value 79.478756
iter  70 value 78.553496
iter  80 value 76.596402
iter  90 value 75.832493
iter 100 value 75.814242
final  value 75.814242 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.595597 
iter  10 value 92.712604
iter  20 value 84.924501
iter  30 value 80.032248
iter  40 value 78.488360
iter  50 value 78.138724
iter  60 value 77.805373
final  value 77.803879 
converged
Fitting Repeat 1 

# weights:  305
initial  value 120.536796 
iter  10 value 95.052553
iter  20 value 85.194762
iter  30 value 82.965477
iter  40 value 82.336048
iter  50 value 80.652673
iter  60 value 79.369367
iter  70 value 76.511152
iter  80 value 75.873670
iter  90 value 75.165049
iter 100 value 74.963057
final  value 74.963057 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.315942 
iter  10 value 92.855942
iter  20 value 91.485978
iter  30 value 84.368371
iter  40 value 79.288501
iter  50 value 75.549295
iter  60 value 75.175471
iter  70 value 75.133793
iter  80 value 74.633036
iter  90 value 74.025955
iter 100 value 73.918583
final  value 73.918583 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.151361 
iter  10 value 93.887607
iter  20 value 81.886619
iter  30 value 80.301292
iter  40 value 78.972885
iter  50 value 78.730516
iter  60 value 77.250144
iter  70 value 76.059680
iter  80 value 75.949439
iter  90 value 75.895246
iter 100 value 75.541983
final  value 75.541983 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.234500 
iter  10 value 93.766473
iter  20 value 83.422403
iter  30 value 80.431977
iter  40 value 76.662281
iter  50 value 76.064462
iter  60 value 75.531087
iter  70 value 75.211719
iter  80 value 74.994530
iter  90 value 74.813833
iter 100 value 74.621746
final  value 74.621746 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 114.679605 
iter  10 value 93.807912
iter  20 value 88.186909
iter  30 value 80.049741
iter  40 value 78.655714
iter  50 value 76.511301
iter  60 value 75.190223
iter  70 value 74.552118
iter  80 value 74.470462
iter  90 value 74.375553
iter 100 value 74.330373
final  value 74.330373 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 113.512030 
iter  10 value 89.821795
iter  20 value 81.672659
iter  30 value 79.471789
iter  40 value 78.776652
iter  50 value 78.666645
iter  60 value 78.442512
iter  70 value 76.751620
iter  80 value 75.942819
iter  90 value 75.639861
iter 100 value 75.083918
final  value 75.083918 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 110.263431 
iter  10 value 93.858417
iter  20 value 90.518567
iter  30 value 84.328756
iter  40 value 80.000640
iter  50 value 77.479679
iter  60 value 77.130568
iter  70 value 76.529029
iter  80 value 76.191242
iter  90 value 76.000165
iter 100 value 75.752116
final  value 75.752116 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 112.052475 
iter  10 value 93.280604
iter  20 value 91.155794
iter  30 value 86.958005
iter  40 value 84.180142
iter  50 value 81.603869
iter  60 value 79.729706
iter  70 value 79.195081
iter  80 value 78.525061
iter  90 value 78.232213
iter 100 value 77.942902
final  value 77.942902 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.671883 
iter  10 value 93.633579
iter  20 value 84.329297
iter  30 value 80.257005
iter  40 value 77.930001
iter  50 value 77.409124
iter  60 value 77.028688
iter  70 value 76.608587
iter  80 value 74.901600
iter  90 value 74.714350
iter 100 value 74.588938
final  value 74.588938 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.731331 
iter  10 value 94.050828
iter  20 value 93.120130
iter  30 value 87.689691
iter  40 value 82.926561
iter  50 value 80.992913
iter  60 value 78.680467
iter  70 value 77.104233
iter  80 value 75.752526
iter  90 value 74.832100
iter 100 value 74.539774
final  value 74.539774 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.649766 
iter  10 value 94.054608
iter  20 value 94.052774
iter  30 value 93.329077
final  value 93.329071 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.969523 
final  value 94.054554 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.411913 
iter  10 value 93.330389
iter  20 value 93.330127
iter  30 value 93.329158
iter  40 value 93.329007
final  value 93.328984 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.521831 
iter  10 value 84.022619
iter  20 value 83.984284
iter  30 value 83.023254
iter  40 value 83.020741
iter  50 value 83.006356
iter  60 value 81.750005
iter  70 value 78.815559
iter  80 value 78.682275
iter  80 value 78.682274
iter  80 value 78.682274
final  value 78.682274 
converged
Fitting Repeat 5 

# weights:  103
initial  value 113.573322 
iter  10 value 94.054782
iter  20 value 94.052919
final  value 94.052915 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.317344 
iter  10 value 94.032178
iter  20 value 94.026502
iter  30 value 83.575435
iter  40 value 82.583242
iter  50 value 82.583051
iter  60 value 81.533963
final  value 81.174745 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.006628 
iter  10 value 94.057850
iter  20 value 93.912965
iter  30 value 82.613062
iter  40 value 81.655905
iter  50 value 81.607611
iter  60 value 81.598921
final  value 81.597133 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.747357 
iter  10 value 94.058026
iter  20 value 94.029707
iter  30 value 93.235532
iter  40 value 84.964843
iter  50 value 84.941161
final  value 84.941085 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.670871 
iter  10 value 94.057908
iter  20 value 92.441726
iter  30 value 92.259750
final  value 92.259722 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.053458 
iter  10 value 93.314493
iter  20 value 93.313511
iter  30 value 85.792730
iter  40 value 81.038656
iter  50 value 80.100988
iter  60 value 80.059026
iter  70 value 79.999409
iter  80 value 79.987305
iter  90 value 79.219691
iter 100 value 79.099121
final  value 79.099121 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.541535 
iter  10 value 87.628392
iter  20 value 79.631024
iter  30 value 79.626476
iter  40 value 79.259463
iter  50 value 78.561351
iter  60 value 78.535391
iter  70 value 78.481324
iter  80 value 77.648321
iter  90 value 77.527596
iter 100 value 77.467147
final  value 77.467147 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.125554 
iter  10 value 94.061190
iter  20 value 93.946459
iter  30 value 86.007287
iter  40 value 85.523817
final  value 85.280218 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.225622 
iter  10 value 92.933575
iter  20 value 92.930163
iter  30 value 92.924343
iter  40 value 86.465707
iter  50 value 86.127174
iter  60 value 86.125975
iter  70 value 83.706401
iter  80 value 77.900957
iter  90 value 74.241363
iter 100 value 73.653425
final  value 73.653425 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 94.468342 
iter  10 value 94.061248
iter  20 value 94.052376
iter  30 value 90.754311
iter  40 value 85.966307
iter  50 value 84.850450
iter  60 value 84.848198
iter  70 value 84.050387
iter  80 value 81.806582
iter  90 value 81.710343
iter 100 value 81.687374
final  value 81.687374 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 100.449317 
iter  10 value 84.090603
iter  20 value 83.462404
iter  30 value 83.460344
iter  40 value 83.456896
iter  50 value 81.220283
iter  60 value 77.764814
iter  70 value 77.757590
iter  80 value 77.757230
iter  90 value 77.755799
iter 100 value 77.620296
final  value 77.620296 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 105.594405 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.694656 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 108.451705 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.753488 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.678432 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.181258 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.317995 
final  value 94.291892 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.834384 
final  value 94.291892 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.208484 
final  value 94.479532 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.491316 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.681374 
final  value 94.291892 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.492255 
iter  10 value 86.605092
iter  20 value 86.466440
iter  30 value 86.460074
final  value 86.460017 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.319286 
final  value 94.291892 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.162592 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.101463 
iter  10 value 93.937040
iter  20 value 93.250655
iter  30 value 91.694390
iter  40 value 91.683395
final  value 91.683258 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.129423 
iter  10 value 94.344286
iter  20 value 91.631879
iter  30 value 91.285484
iter  40 value 91.111541
iter  50 value 91.065242
iter  60 value 90.739662
iter  70 value 90.736079
iter  70 value 90.736078
iter  70 value 90.736078
final  value 90.736078 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.265763 
iter  10 value 94.175171
iter  20 value 93.916730
iter  30 value 93.894014
iter  40 value 92.592342
iter  50 value 91.834933
iter  60 value 89.075677
iter  70 value 85.817613
iter  80 value 85.543774
iter  90 value 85.044417
iter 100 value 84.850365
final  value 84.850365 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 100.820542 
iter  10 value 94.473432
iter  20 value 94.352180
iter  30 value 90.782943
iter  40 value 86.735609
iter  50 value 86.286568
iter  60 value 85.237597
iter  70 value 85.119967
final  value 85.119864 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.322905 
iter  10 value 94.487647
iter  20 value 94.076317
iter  30 value 93.938642
iter  40 value 93.929357
iter  50 value 93.925991
iter  60 value 93.660972
iter  70 value 87.309528
iter  80 value 85.043913
iter  90 value 83.960400
iter 100 value 82.650085
final  value 82.650085 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 105.629594 
iter  10 value 94.581448
iter  20 value 94.105339
iter  30 value 84.666465
iter  40 value 84.339728
iter  50 value 84.232905
iter  60 value 83.225699
iter  70 value 82.059366
iter  80 value 81.561758
iter  90 value 81.549457
final  value 81.549451 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.380144 
iter  10 value 94.498952
iter  20 value 94.463650
iter  30 value 89.986701
iter  40 value 87.635659
iter  50 value 87.221145
iter  60 value 87.061239
iter  70 value 84.370343
iter  80 value 84.329260
iter  90 value 84.277911
iter 100 value 83.624751
final  value 83.624751 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 111.456898 
iter  10 value 93.482419
iter  20 value 85.998890
iter  30 value 85.629726
iter  40 value 84.418641
iter  50 value 83.707737
iter  60 value 82.805425
iter  70 value 81.952940
iter  80 value 80.860092
iter  90 value 80.594097
iter 100 value 80.502505
final  value 80.502505 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.266207 
iter  10 value 94.516563
iter  20 value 87.566123
iter  30 value 86.808735
iter  40 value 86.296337
iter  50 value 83.623320
iter  60 value 81.783461
iter  70 value 81.141174
iter  80 value 80.580211
iter  90 value 80.526426
iter 100 value 80.440040
final  value 80.440040 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 113.431769 
iter  10 value 97.535221
iter  20 value 94.561749
iter  30 value 94.003090
iter  40 value 90.735488
iter  50 value 87.558044
iter  60 value 86.702546
iter  70 value 83.182016
iter  80 value 82.120988
iter  90 value 81.535281
iter 100 value 81.453867
final  value 81.453867 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 118.709709 
iter  10 value 94.687644
iter  20 value 91.666342
iter  30 value 88.718302
iter  40 value 85.827884
iter  50 value 85.131923
iter  60 value 82.772412
iter  70 value 82.478652
iter  80 value 81.984272
iter  90 value 81.696820
iter 100 value 80.847395
final  value 80.847395 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 131.814261 
iter  10 value 95.894683
iter  20 value 86.413615
iter  30 value 84.453463
iter  40 value 84.044895
iter  50 value 83.761148
iter  60 value 82.112085
iter  70 value 80.923640
iter  80 value 80.523700
iter  90 value 80.417540
iter 100 value 80.336899
final  value 80.336899 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.410005 
iter  10 value 95.153107
iter  20 value 88.211861
iter  30 value 87.862262
iter  40 value 87.736108
iter  50 value 87.669351
iter  60 value 86.969444
iter  70 value 83.513151
iter  80 value 81.946287
iter  90 value 81.572273
iter 100 value 81.190779
final  value 81.190779 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 130.483529 
iter  10 value 95.064367
iter  20 value 91.950519
iter  30 value 86.843067
iter  40 value 85.587988
iter  50 value 85.230562
iter  60 value 83.702766
iter  70 value 82.015759
iter  80 value 80.804514
iter  90 value 80.647047
iter 100 value 80.436881
final  value 80.436881 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 129.433374 
iter  10 value 95.055497
iter  20 value 94.585300
iter  30 value 94.251330
iter  40 value 87.936226
iter  50 value 86.494285
iter  60 value 82.877962
iter  70 value 81.701500
iter  80 value 81.492753
iter  90 value 80.723649
iter 100 value 80.255919
final  value 80.255919 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 123.732602 
iter  10 value 94.388526
iter  20 value 85.477204
iter  30 value 83.434517
iter  40 value 82.964607
iter  50 value 82.897863
iter  60 value 82.279206
iter  70 value 81.424545
iter  80 value 80.679196
iter  90 value 80.468348
iter 100 value 80.214590
final  value 80.214590 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.011312 
final  value 94.485960 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.162341 
final  value 94.487862 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.643602 
final  value 94.293653 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.171150 
iter  10 value 94.485685
iter  20 value 94.484193
iter  30 value 94.291978
iter  30 value 94.291978
iter  30 value 94.291978
final  value 94.291978 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.803889 
final  value 94.293410 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.402948 
iter  10 value 94.489485
iter  20 value 94.420026
iter  30 value 90.282226
iter  40 value 90.246140
iter  50 value 90.213765
iter  60 value 89.937538
iter  70 value 89.920627
iter  80 value 89.920488
iter  90 value 89.182676
iter 100 value 89.182390
final  value 89.182390 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 97.189410 
iter  10 value 94.489160
iter  20 value 94.472516
iter  30 value 91.071415
iter  40 value 88.418250
iter  50 value 88.411468
final  value 88.411458 
converged
Fitting Repeat 3 

# weights:  305
initial  value 108.341542 
iter  10 value 93.665117
iter  20 value 93.061310
iter  30 value 93.029073
iter  40 value 92.515337
iter  50 value 92.226250
iter  60 value 92.055533
iter  70 value 92.027614
iter  80 value 92.025346
iter  90 value 92.023874
final  value 92.023747 
converged
Fitting Repeat 4 

# weights:  305
initial  value 114.428525 
iter  10 value 94.489185
iter  20 value 94.481945
iter  30 value 85.783623
iter  40 value 85.176052
iter  50 value 83.733087
iter  60 value 83.340221
iter  70 value 83.288585
final  value 83.288411 
converged
Fitting Repeat 5 

# weights:  305
initial  value 116.936397 
iter  10 value 94.488997
iter  20 value 94.484862
iter  30 value 94.263469
iter  40 value 90.979553
iter  50 value 85.867974
iter  60 value 84.843426
iter  70 value 83.233165
iter  80 value 83.232541
final  value 83.232313 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.579640 
iter  10 value 94.492318
iter  20 value 91.815000
iter  30 value 87.475665
iter  40 value 87.057617
iter  50 value 86.218401
iter  60 value 86.217730
iter  70 value 86.216837
final  value 86.216570 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.757598 
iter  10 value 94.300385
iter  20 value 94.292466
final  value 94.292197 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.873701 
iter  10 value 94.299612
iter  20 value 94.292695
final  value 94.292257 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.648287 
iter  10 value 94.299928
iter  20 value 94.292065
iter  30 value 94.136235
iter  40 value 90.640893
iter  50 value 87.268948
iter  60 value 87.225343
iter  70 value 87.225006
iter  80 value 86.908870
iter  90 value 85.728724
iter 100 value 85.557905
final  value 85.557905 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.678435 
iter  10 value 94.492781
iter  20 value 94.485477
iter  30 value 94.261213
iter  40 value 93.304936
iter  50 value 93.188793
iter  60 value 89.486930
iter  70 value 89.313238
iter  80 value 88.635475
iter  90 value 88.381593
iter 100 value 88.377470
final  value 88.377470 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.237176 
final  value 94.011429 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.055956 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.733006 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.636045 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.146364 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.398973 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.449161 
iter  10 value 94.033176
final  value 94.033149 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.609729 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.279027 
final  value 94.032967 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.346892 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 111.526559 
final  value 93.988095 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.199787 
final  value 93.988095 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.280692 
final  value 93.988095 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.779926 
iter  10 value 93.869756
iter  10 value 93.869755
iter  10 value 93.869755
final  value 93.869755 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.180475 
iter  10 value 93.988300
final  value 93.988095 
converged
Fitting Repeat 1 

# weights:  103
initial  value 107.539359 
iter  10 value 94.034323
iter  20 value 91.029299
iter  30 value 90.278581
iter  40 value 88.642183
iter  50 value 87.575298
iter  60 value 87.309940
final  value 87.308021 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.843287 
iter  10 value 91.483841
iter  20 value 88.181069
iter  30 value 87.625460
iter  40 value 87.556115
iter  50 value 87.314312
iter  60 value 87.257371
iter  60 value 87.257371
iter  60 value 87.257371
final  value 87.257371 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.091792 
iter  10 value 94.056758
iter  20 value 92.725349
iter  30 value 91.170643
iter  40 value 90.352085
iter  50 value 86.771646
iter  60 value 85.963850
iter  70 value 85.710618
iter  80 value 85.265717
iter  90 value 84.750434
iter 100 value 84.613454
final  value 84.613454 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 94.691035 
iter  10 value 89.778006
iter  20 value 88.467261
iter  30 value 86.209065
iter  40 value 85.869400
iter  50 value 85.801480
iter  60 value 85.799966
final  value 85.799965 
converged
Fitting Repeat 5 

# weights:  103
initial  value 120.443580 
iter  10 value 93.945333
iter  20 value 91.007807
iter  30 value 88.124298
iter  40 value 87.440235
iter  50 value 87.175381
iter  60 value 87.161283
iter  60 value 87.161283
final  value 87.161283 
converged
Fitting Repeat 1 

# weights:  305
initial  value 118.152147 
iter  10 value 95.622652
iter  20 value 87.566636
iter  30 value 87.323443
iter  40 value 87.206905
iter  50 value 87.116669
iter  60 value 86.278536
iter  70 value 84.284984
iter  80 value 83.804081
iter  90 value 83.590112
iter 100 value 83.495405
final  value 83.495405 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 116.658683 
iter  10 value 94.163994
iter  20 value 91.982676
iter  30 value 90.046104
iter  40 value 87.530466
iter  50 value 86.663153
iter  60 value 86.500069
iter  70 value 85.601429
iter  80 value 84.795321
iter  90 value 84.375067
iter 100 value 83.845707
final  value 83.845707 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.202224 
iter  10 value 94.036489
iter  20 value 88.094624
iter  30 value 86.599793
iter  40 value 85.955694
iter  50 value 85.010899
iter  60 value 84.852412
iter  70 value 83.835497
iter  80 value 83.477178
iter  90 value 83.081628
iter 100 value 82.972827
final  value 82.972827 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.998946 
iter  10 value 94.080116
iter  20 value 93.235094
iter  30 value 92.994801
iter  40 value 92.926639
iter  50 value 91.051001
iter  60 value 89.619363
iter  70 value 87.623175
iter  80 value 86.453545
iter  90 value 85.975072
iter 100 value 85.479250
final  value 85.479250 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.404959 
iter  10 value 94.074071
iter  20 value 90.824933
iter  30 value 88.560905
iter  40 value 87.758037
iter  50 value 87.236084
iter  60 value 86.469321
iter  70 value 85.636925
iter  80 value 85.569809
iter  90 value 85.507427
iter 100 value 84.386450
final  value 84.386450 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.071616 
iter  10 value 98.602120
iter  20 value 91.234964
iter  30 value 89.826757
iter  40 value 89.617720
iter  50 value 88.822966
iter  60 value 85.956708
iter  70 value 84.443902
iter  80 value 84.033245
iter  90 value 83.801427
iter 100 value 83.521154
final  value 83.521154 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.907218 
iter  10 value 94.159264
iter  20 value 93.974559
iter  30 value 88.818710
iter  40 value 86.424483
iter  50 value 85.318936
iter  60 value 85.200457
iter  70 value 84.968139
iter  80 value 84.239429
iter  90 value 83.824405
iter 100 value 83.492766
final  value 83.492766 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 128.934303 
iter  10 value 93.831533
iter  20 value 87.243112
iter  30 value 85.635800
iter  40 value 85.167434
iter  50 value 84.515070
iter  60 value 83.493779
iter  70 value 83.151670
iter  80 value 82.951603
iter  90 value 82.870294
iter 100 value 82.862435
final  value 82.862435 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 118.648280 
iter  10 value 94.119081
iter  20 value 93.923630
iter  30 value 88.562408
iter  40 value 87.253929
iter  50 value 85.817221
iter  60 value 85.729808
iter  70 value 85.437913
iter  80 value 84.331022
iter  90 value 83.747309
iter 100 value 83.462679
final  value 83.462679 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.633444 
iter  10 value 94.012603
iter  20 value 91.380413
iter  30 value 87.594310
iter  40 value 86.678876
iter  50 value 86.369785
iter  60 value 86.228857
iter  70 value 85.511488
iter  80 value 84.134666
iter  90 value 83.472909
iter 100 value 83.374270
final  value 83.374270 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.518933 
final  value 94.054675 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.365568 
iter  10 value 94.054424
iter  20 value 94.052952
final  value 94.052919 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.284096 
final  value 94.054511 
converged
Fitting Repeat 4 

# weights:  103
initial  value 112.667557 
final  value 94.054693 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.764488 
final  value 94.054442 
converged
Fitting Repeat 1 

# weights:  305
initial  value 122.975002 
iter  10 value 91.204346
iter  20 value 90.758300
iter  30 value 90.412589
iter  40 value 90.410349
iter  50 value 90.406071
iter  60 value 90.405868
iter  70 value 88.063127
iter  80 value 85.878468
iter  90 value 85.504159
iter 100 value 85.442830
final  value 85.442830 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.901369 
iter  10 value 94.039184
iter  20 value 93.894816
iter  30 value 93.809723
iter  40 value 87.457774
iter  50 value 86.108848
iter  60 value 85.637015
iter  70 value 85.634530
final  value 85.634365 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.664912 
iter  10 value 94.058463
iter  20 value 94.000499
iter  30 value 93.703400
iter  40 value 91.619783
iter  50 value 91.617072
iter  60 value 91.616782
iter  70 value 91.616441
iter  80 value 91.254076
iter  90 value 90.932621
iter 100 value 90.931969
final  value 90.931969 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.314361 
iter  10 value 94.057361
iter  20 value 94.052924
iter  30 value 94.008368
iter  40 value 93.129936
iter  50 value 90.800706
iter  60 value 90.778633
final  value 90.778550 
converged
Fitting Repeat 5 

# weights:  305
initial  value 123.159097 
iter  10 value 92.623937
iter  20 value 92.279359
iter  30 value 92.181410
iter  40 value 92.155870
iter  50 value 92.154432
iter  60 value 92.148976
iter  70 value 92.147803
iter  80 value 92.147139
iter  90 value 92.139066
iter 100 value 91.386191
final  value 91.386191 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 116.176272 
iter  10 value 94.024296
iter  20 value 94.018260
iter  30 value 93.781394
iter  40 value 93.754423
iter  50 value 93.749121
iter  60 value 93.747984
iter  70 value 90.258043
iter  80 value 86.856511
iter  90 value 86.855923
iter 100 value 85.894750
final  value 85.894750 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 94.437339 
iter  10 value 94.041114
iter  20 value 93.138768
iter  30 value 91.114982
iter  40 value 91.113227
iter  50 value 90.592551
iter  60 value 90.588252
iter  70 value 90.586123
iter  80 value 90.545080
iter  90 value 84.661224
iter 100 value 84.121650
final  value 84.121650 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 96.566894 
iter  10 value 94.057028
iter  20 value 92.140044
iter  30 value 88.908793
iter  40 value 88.906771
iter  50 value 88.622615
iter  60 value 88.622006
iter  70 value 88.525056
final  value 88.513427 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.520072 
iter  10 value 93.995976
iter  20 value 93.931955
iter  30 value 93.510747
iter  40 value 91.783860
iter  50 value 91.538463
iter  60 value 91.538180
iter  70 value 91.525234
iter  80 value 91.349728
iter  90 value 91.333603
final  value 91.330442 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.902303 
iter  10 value 94.060115
iter  20 value 94.048534
iter  30 value 89.274549
iter  40 value 88.898556
iter  50 value 86.892862
iter  60 value 86.132414
iter  70 value 86.033584
iter  80 value 84.850814
iter  90 value 84.682199
iter 100 value 84.106180
final  value 84.106180 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.762733 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.347416 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.185029 
iter  10 value 81.733744
iter  20 value 81.362538
final  value 81.362488 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.569166 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.076774 
iter  10 value 94.052172
final  value 93.999229 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.549483 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.730951 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.639599 
iter  10 value 89.845642
iter  20 value 87.119044
iter  30 value 85.643479
final  value 85.643401 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.513982 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.144471 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.194162 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.296357 
iter  10 value 91.644132
iter  20 value 87.286850
iter  30 value 87.195353
iter  30 value 87.195353
iter  30 value 87.195353
final  value 87.195353 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.561736 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 123.204042 
iter  10 value 94.308203
final  value 94.308192 
converged
Fitting Repeat 5 

# weights:  507
initial  value 113.762834 
iter  10 value 93.316397
final  value 93.300000 
converged
Fitting Repeat 1 

# weights:  103
initial  value 116.192334 
iter  10 value 94.403850
iter  20 value 93.970073
iter  30 value 92.975527
iter  40 value 85.477414
iter  50 value 84.749750
iter  60 value 82.778460
iter  70 value 82.521045
iter  80 value 81.999978
iter  90 value 81.563623
iter 100 value 81.343966
final  value 81.343966 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 107.282287 
iter  10 value 94.169204
iter  20 value 86.803198
iter  30 value 84.460274
iter  40 value 83.961317
iter  50 value 83.124021
iter  60 value 81.702801
iter  70 value 81.255512
iter  80 value 80.998638
iter  90 value 80.732054
final  value 80.729398 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.132287 
iter  10 value 94.352877
iter  20 value 92.739663
iter  30 value 88.854836
iter  40 value 83.006409
iter  50 value 81.765493
iter  60 value 81.154180
iter  70 value 80.943787
iter  80 value 80.791327
iter  90 value 80.729452
final  value 80.729398 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.170298 
iter  10 value 94.384528
iter  20 value 86.574988
iter  30 value 83.027816
iter  40 value 82.668396
iter  50 value 82.552919
iter  60 value 82.512402
iter  70 value 82.507504
iter  80 value 82.416297
iter  90 value 81.590671
iter 100 value 80.967011
final  value 80.967011 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 98.733265 
iter  10 value 93.578679
iter  20 value 86.862185
iter  30 value 84.221415
iter  40 value 82.873218
iter  50 value 82.838098
iter  60 value 82.799471
iter  70 value 82.786858
iter  80 value 82.686240
iter  90 value 82.526559
iter 100 value 82.508291
final  value 82.508291 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 102.895635 
iter  10 value 94.426875
iter  20 value 86.167315
iter  30 value 82.861562
iter  40 value 82.646472
iter  50 value 81.557891
iter  60 value 80.612535
iter  70 value 80.367964
iter  80 value 80.282051
iter  90 value 80.163653
iter 100 value 79.937167
final  value 79.937167 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 114.148600 
iter  10 value 86.654083
iter  20 value 83.267599
iter  30 value 81.052580
iter  40 value 80.140133
iter  50 value 79.886607
iter  60 value 79.797068
iter  70 value 79.684191
iter  80 value 79.529204
iter  90 value 79.271631
iter 100 value 79.258728
final  value 79.258728 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.462055 
iter  10 value 91.521077
iter  20 value 84.509719
iter  30 value 83.349178
iter  40 value 82.516098
iter  50 value 81.292717
iter  60 value 79.404728
iter  70 value 78.973165
iter  80 value 78.878218
iter  90 value 78.814007
iter 100 value 78.785246
final  value 78.785246 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.290766 
iter  10 value 93.960431
iter  20 value 89.646572
iter  30 value 84.982815
iter  40 value 84.321228
iter  50 value 82.944364
iter  60 value 82.604181
iter  70 value 82.258148
iter  80 value 81.780303
iter  90 value 80.759739
iter 100 value 79.539146
final  value 79.539146 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 117.468360 
iter  10 value 94.315112
iter  20 value 87.443406
iter  30 value 87.012400
iter  40 value 86.547642
iter  50 value 83.137824
iter  60 value 81.321247
iter  70 value 80.979922
iter  80 value 80.596847
iter  90 value 80.441699
iter 100 value 79.926119
final  value 79.926119 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.762494 
iter  10 value 89.539771
iter  20 value 85.049557
iter  30 value 82.849204
iter  40 value 82.201532
iter  50 value 82.080685
iter  60 value 81.636638
iter  70 value 80.559235
iter  80 value 80.179513
iter  90 value 79.991534
iter 100 value 79.743382
final  value 79.743382 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.831079 
iter  10 value 94.910292
iter  20 value 92.480564
iter  30 value 83.227218
iter  40 value 81.118529
iter  50 value 80.762413
iter  60 value 80.226756
iter  70 value 79.933285
iter  80 value 79.673605
iter  90 value 79.033166
iter 100 value 78.837833
final  value 78.837833 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.131473 
iter  10 value 94.219510
iter  20 value 93.929688
iter  30 value 89.871082
iter  40 value 85.407082
iter  50 value 82.838866
iter  60 value 81.066631
iter  70 value 80.375740
iter  80 value 80.121341
iter  90 value 80.051943
iter 100 value 79.760924
final  value 79.760924 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.351815 
iter  10 value 94.539745
iter  20 value 85.491324
iter  30 value 83.267026
iter  40 value 82.452474
iter  50 value 81.080020
iter  60 value 79.881322
iter  70 value 79.768106
iter  80 value 79.491505
iter  90 value 79.393786
iter 100 value 79.323199
final  value 79.323199 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.044473 
iter  10 value 94.262577
iter  20 value 93.933365
iter  30 value 90.329867
iter  40 value 84.789568
iter  50 value 83.205297
iter  60 value 82.506322
iter  70 value 82.408688
iter  80 value 82.261753
iter  90 value 81.442564
iter 100 value 80.441413
final  value 80.441413 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.409366 
final  value 94.485935 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.843564 
final  value 94.356170 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.776129 
final  value 94.485929 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.463712 
iter  10 value 94.485982
iter  20 value 94.484279
iter  30 value 93.871824
iter  30 value 93.871824
iter  30 value 93.871823
final  value 93.871823 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.706404 
final  value 94.485831 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.018505 
iter  10 value 94.058730
iter  20 value 94.055961
iter  30 value 94.055279
iter  40 value 94.053481
final  value 94.053003 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.609770 
iter  10 value 94.358773
iter  20 value 94.354586
iter  30 value 93.909594
iter  40 value 83.786713
iter  50 value 83.305147
iter  60 value 82.685380
iter  70 value 82.530302
iter  80 value 81.443074
iter  90 value 79.350849
iter 100 value 79.309485
final  value 79.309485 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.675706 
iter  10 value 94.489092
iter  20 value 94.481208
iter  30 value 93.982535
iter  40 value 91.593425
iter  50 value 91.524136
iter  60 value 90.381509
iter  70 value 82.011329
iter  80 value 79.492486
iter  90 value 79.471533
iter 100 value 79.250229
final  value 79.250229 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 98.372102 
iter  10 value 94.317279
iter  20 value 94.312714
iter  30 value 93.872101
iter  30 value 93.872101
iter  30 value 93.872101
final  value 93.872101 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.485915 
iter  10 value 94.275238
iter  20 value 93.988317
iter  30 value 93.979118
iter  40 value 93.975190
iter  50 value 93.746546
iter  60 value 93.364824
iter  70 value 90.605812
iter  80 value 83.787300
final  value 83.778211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.213304 
iter  10 value 93.877253
iter  20 value 93.860187
iter  30 value 93.852256
iter  40 value 93.839873
iter  50 value 91.717302
iter  60 value 81.474873
iter  70 value 79.475976
iter  80 value 78.476586
iter  90 value 77.821180
iter 100 value 76.977440
final  value 76.977440 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 100.801923 
iter  10 value 92.622798
iter  20 value 87.127510
iter  30 value 81.271995
iter  40 value 80.075383
iter  50 value 79.585534
iter  60 value 79.320828
iter  70 value 79.166933
iter  80 value 79.165718
iter  90 value 79.160756
iter 100 value 78.933364
final  value 78.933364 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.030874 
iter  10 value 90.861952
iter  20 value 83.494751
iter  30 value 83.482929
iter  40 value 83.475841
iter  50 value 83.465249
iter  60 value 83.462322
final  value 83.462103 
converged
Fitting Repeat 4 

# weights:  507
initial  value 111.172933 
iter  10 value 94.362561
iter  20 value 94.352990
iter  30 value 91.025174
iter  40 value 81.586513
final  value 81.586394 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.407195 
iter  10 value 93.024859
iter  20 value 93.023083
iter  30 value 92.635993
iter  40 value 92.600148
iter  50 value 92.599667
iter  60 value 92.595548
iter  70 value 91.335686
iter  80 value 88.343567
iter  90 value 87.832933
iter 100 value 86.687907
final  value 86.687907 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 113.303756 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.427625 
final  value 94.026542 
converged
Fitting Repeat 3 

# weights:  103
initial  value 114.334863 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.467645 
final  value 94.427726 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.492425 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.941988 
iter  10 value 94.510693
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.430214 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 115.261128 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.084125 
iter  10 value 86.612550
iter  20 value 86.601786
iter  20 value 86.601786
iter  20 value 86.601786
final  value 86.601786 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.296983 
final  value 94.026542 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.023355 
final  value 94.026542 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.380327 
iter  10 value 89.935226
iter  20 value 86.146844
iter  30 value 85.292021
iter  40 value 85.094604
iter  50 value 84.317525
iter  60 value 84.315579
iter  70 value 84.315503
iter  70 value 84.315503
final  value 84.315503 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.887173 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.377522 
iter  10 value 88.943834
iter  20 value 87.566995
final  value 87.529748 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.214059 
iter  10 value 94.058472
iter  20 value 94.052446
final  value 94.052435 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.354728 
iter  10 value 94.386973
iter  20 value 93.191505
iter  30 value 89.933942
iter  40 value 89.612457
iter  50 value 86.975019
iter  60 value 84.332568
iter  70 value 83.800033
iter  80 value 83.763884
iter  90 value 83.752804
final  value 83.752802 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.795667 
iter  10 value 94.472258
iter  20 value 89.046676
iter  30 value 88.477641
iter  40 value 85.415756
iter  50 value 85.253239
iter  60 value 84.775151
iter  70 value 84.474815
iter  80 value 84.406785
final  value 84.406666 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.043977 
iter  10 value 94.688935
iter  20 value 94.466572
iter  30 value 85.551533
iter  40 value 84.191916
iter  50 value 82.764917
iter  60 value 82.532097
iter  70 value 82.292834
iter  80 value 82.082812
final  value 82.081328 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.056509 
iter  10 value 94.318887
iter  20 value 86.995614
iter  30 value 86.605048
iter  40 value 86.169150
iter  50 value 85.792036
iter  60 value 84.251421
iter  70 value 83.773976
iter  80 value 83.594057
iter  90 value 83.511838
final  value 83.500298 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.770242 
iter  10 value 94.501988
iter  20 value 94.173229
iter  30 value 92.409600
iter  40 value 90.856899
iter  50 value 84.447936
iter  60 value 82.510382
iter  70 value 82.384747
iter  80 value 82.165215
iter  90 value 82.081474
final  value 82.081329 
converged
Fitting Repeat 1 

# weights:  305
initial  value 121.115830 
iter  10 value 94.077747
iter  20 value 87.650531
iter  30 value 85.289819
iter  40 value 82.451958
iter  50 value 81.759795
iter  60 value 80.877769
iter  70 value 80.628282
iter  80 value 80.594790
iter  90 value 80.583087
iter 100 value 80.578940
final  value 80.578940 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.817539 
iter  10 value 94.426852
iter  20 value 88.787586
iter  30 value 87.932427
iter  40 value 83.416280
iter  50 value 82.762513
iter  60 value 82.427255
iter  70 value 82.340587
iter  80 value 82.244508
iter  90 value 82.144155
iter 100 value 81.647851
final  value 81.647851 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.229082 
iter  10 value 93.950917
iter  20 value 88.639748
iter  30 value 87.310307
iter  40 value 86.143630
iter  50 value 85.305657
iter  60 value 83.396539
iter  70 value 82.710351
iter  80 value 82.381302
iter  90 value 82.034478
iter 100 value 81.993546
final  value 81.993546 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.903068 
iter  10 value 94.514096
iter  20 value 88.715823
iter  30 value 87.084449
iter  40 value 85.146405
iter  50 value 84.721207
iter  60 value 84.617959
iter  70 value 84.480259
iter  80 value 84.333904
iter  90 value 84.185421
iter 100 value 83.808472
final  value 83.808472 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.700690 
iter  10 value 94.450078
iter  20 value 93.435143
iter  30 value 86.536621
iter  40 value 84.788260
iter  50 value 84.007126
iter  60 value 82.941485
iter  70 value 82.753796
iter  80 value 82.566702
iter  90 value 82.445546
iter 100 value 82.394105
final  value 82.394105 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.006219 
iter  10 value 92.978407
iter  20 value 87.269538
iter  30 value 86.554485
iter  40 value 85.518107
iter  50 value 83.602558
iter  60 value 82.799501
iter  70 value 82.466198
iter  80 value 81.932416
iter  90 value 81.358622
iter 100 value 81.060432
final  value 81.060432 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.763554 
iter  10 value 94.558371
iter  20 value 93.972995
iter  30 value 91.693397
iter  40 value 88.341718
iter  50 value 86.988578
iter  60 value 84.334932
iter  70 value 82.717358
iter  80 value 81.833374
iter  90 value 81.396900
iter 100 value 81.166002
final  value 81.166002 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 115.437374 
iter  10 value 94.913909
iter  20 value 93.843257
iter  30 value 86.063527
iter  40 value 85.388959
iter  50 value 82.881459
iter  60 value 82.601202
iter  70 value 81.933912
iter  80 value 81.582403
iter  90 value 81.439874
iter 100 value 80.958079
final  value 80.958079 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 114.415178 
iter  10 value 95.331486
iter  20 value 86.171249
iter  30 value 85.263187
iter  40 value 83.583431
iter  50 value 81.879161
iter  60 value 81.115241
iter  70 value 80.804557
iter  80 value 80.680060
iter  90 value 80.549001
iter 100 value 80.450635
final  value 80.450635 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 123.528525 
iter  10 value 94.335190
iter  20 value 92.407539
iter  30 value 91.444297
iter  40 value 90.202906
iter  50 value 89.086710
iter  60 value 88.909411
iter  70 value 85.611802
iter  80 value 83.430403
iter  90 value 82.327820
iter 100 value 81.120811
final  value 81.120811 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 105.689922 
final  value 94.485638 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.360647 
final  value 94.485709 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.417409 
final  value 94.485701 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.081470 
final  value 94.485720 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.431189 
final  value 94.499455 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.942882 
iter  10 value 91.571163
iter  20 value 87.598250
iter  30 value 87.239140
iter  40 value 86.483380
final  value 86.481007 
converged
Fitting Repeat 2 

# weights:  305
initial  value 115.762167 
iter  10 value 94.470588
iter  20 value 92.991225
iter  30 value 92.917416
iter  40 value 91.151771
iter  50 value 87.690888
iter  60 value 87.662358
iter  70 value 87.658665
iter  80 value 87.236214
iter  90 value 87.233292
iter 100 value 87.232428
final  value 87.232428 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.316486 
iter  10 value 94.488867
iter  20 value 94.027147
final  value 94.027001 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.980078 
iter  10 value 94.488994
iter  20 value 94.480743
iter  30 value 94.017918
final  value 93.976524 
converged
Fitting Repeat 5 

# weights:  305
initial  value 113.609242 
iter  10 value 94.488964
iter  20 value 94.408223
iter  30 value 87.696059
iter  40 value 87.688872
iter  50 value 87.688242
iter  60 value 87.567087
iter  70 value 87.382083
iter  80 value 87.156170
iter  90 value 86.839317
final  value 86.833906 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.077167 
iter  10 value 93.699137
iter  20 value 93.312433
iter  30 value 93.306670
iter  40 value 92.802694
iter  50 value 86.453168
iter  60 value 84.938004
iter  70 value 84.552557
iter  80 value 84.440584
iter  90 value 84.438808
iter  90 value 84.438808
final  value 84.438808 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.136133 
iter  10 value 94.492878
iter  20 value 94.458808
iter  30 value 93.657812
iter  40 value 86.352176
iter  50 value 86.145174
final  value 86.109662 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.720284 
iter  10 value 94.035283
iter  20 value 94.026915
iter  30 value 93.809383
iter  40 value 92.264326
iter  50 value 86.101679
iter  60 value 84.933059
iter  70 value 84.820275
iter  80 value 81.538958
iter  90 value 80.926523
iter 100 value 80.751175
final  value 80.751175 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.057350 
iter  10 value 94.035409
iter  20 value 94.027358
iter  30 value 93.993075
iter  40 value 91.008361
iter  50 value 90.127899
iter  60 value 87.946812
iter  70 value 87.417845
iter  80 value 87.382573
iter  90 value 87.230472
iter 100 value 87.230284
final  value 87.230284 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 102.100490 
iter  10 value 94.492556
iter  20 value 94.475358
iter  30 value 87.599819
iter  40 value 86.902658
iter  50 value 86.847476
iter  60 value 86.844754
iter  70 value 86.844294
iter  80 value 86.843448
iter  80 value 86.843448
final  value 86.843448 
converged
Fitting Repeat 1 

# weights:  507
initial  value 129.818380 
iter  10 value 118.828027
iter  20 value 118.315551
iter  30 value 111.991954
iter  40 value 104.623586
iter  50 value 102.469955
iter  60 value 101.902771
iter  70 value 101.690975
iter  80 value 101.367826
iter  90 value 101.230153
iter 100 value 101.176757
final  value 101.176757 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 171.565717 
iter  10 value 117.852080
iter  20 value 108.111584
iter  30 value 105.551499
iter  40 value 102.582353
iter  50 value 102.266003
iter  60 value 102.081980
iter  70 value 101.134834
iter  80 value 100.732627
iter  90 value 100.665244
iter 100 value 100.659063
final  value 100.659063 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 135.322543 
iter  10 value 117.818183
iter  20 value 107.846314
iter  30 value 106.995855
iter  40 value 104.606035
iter  50 value 102.327233
iter  60 value 101.537337
iter  70 value 101.378455
iter  80 value 100.917614
iter  90 value 100.484331
iter 100 value 100.332814
final  value 100.332814 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 136.209956 
iter  10 value 117.784172
iter  20 value 110.231007
iter  30 value 109.783802
iter  40 value 108.141764
iter  50 value 105.185511
iter  60 value 102.563906
iter  70 value 102.153435
iter  80 value 101.537877
iter  90 value 100.940213
iter 100 value 100.566879
final  value 100.566879 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 133.627394 
iter  10 value 117.905868
iter  20 value 112.220581
iter  30 value 106.875194
iter  40 value 106.680551
iter  50 value 106.127282
iter  60 value 103.456945
iter  70 value 102.699072
iter  80 value 102.162433
iter  90 value 101.967663
iter 100 value 101.630533
final  value 101.630533 
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 Aug 19 10:15:19 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 
 56.504   1.556 118.196