##############################################################################
##############################################################################
###
### 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_1.12.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck’
* using R version 4.4.3 (2025-02-28)
* 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)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.12.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
var_imp       34.008  0.347  34.434
FSmethod      34.130  0.200  34.406
corr_plot     33.924  0.324  34.319
pred_ensembel 17.566  0.187  16.540
enrichfindP    0.499  0.016  20.514
getFASTA       0.121  0.008   5.603
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 3 NOTEs
See
  ‘/home/biocbuild/bbs-3.20-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-4.4.3/site-library’
* installing *source* package ‘HPiP’ ...
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R version 4.4.3 (2025-02-28) -- "Trophy Case"
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 96.708437 
final  value 94.112570 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.567333 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.957667 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.736402 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.065594 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.730176 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.536638 
iter  10 value 93.394966
final  value 93.394928 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.940615 
iter  10 value 93.395047
final  value 93.394928 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.774869 
iter  10 value 93.394945
final  value 93.394928 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.592255 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.312631 
iter  10 value 93.042975
final  value 93.041991 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.764276 
iter  10 value 91.617612
iter  20 value 82.667072
iter  30 value 82.247843
iter  40 value 82.160616
iter  50 value 82.156803
final  value 82.156782 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.868742 
iter  10 value 93.394943
final  value 93.394928 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.863152 
iter  10 value 93.416453
final  value 93.394928 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.961445 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.818141 
iter  10 value 94.262488
iter  20 value 92.653705
iter  30 value 92.592329
iter  40 value 85.561327
iter  50 value 84.704354
iter  60 value 84.671510
iter  70 value 84.634529
iter  80 value 84.026663
iter  90 value 83.704805
iter 100 value 83.676713
final  value 83.676713 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 102.645693 
iter  10 value 94.488513
iter  20 value 94.386245
iter  30 value 93.787659
iter  40 value 93.725531
iter  50 value 93.704605
iter  60 value 93.683928
iter  70 value 93.680008
iter  80 value 93.483620
iter  90 value 93.086537
iter 100 value 91.820525
final  value 91.820525 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.606124 
iter  10 value 94.356109
iter  20 value 93.448091
iter  30 value 92.878966
iter  40 value 86.114446
iter  50 value 82.370947
iter  60 value 81.451135
iter  70 value 81.385212
iter  80 value 81.379061
iter  90 value 81.374882
iter  90 value 81.374881
iter  90 value 81.374881
final  value 81.374881 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.477353 
iter  10 value 94.183114
iter  20 value 85.932703
iter  30 value 84.964383
iter  40 value 84.141154
iter  50 value 83.888818
iter  60 value 83.752778
iter  70 value 83.677960
final  value 83.674309 
converged
Fitting Repeat 5 

# weights:  103
initial  value 107.866754 
iter  10 value 94.305140
iter  20 value 93.678005
iter  30 value 93.676225
iter  40 value 93.528139
iter  50 value 85.846972
iter  60 value 84.878998
iter  70 value 84.588415
iter  80 value 84.039867
iter  90 value 83.863726
iter 100 value 81.867090
final  value 81.867090 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 119.315249 
iter  10 value 94.892675
iter  20 value 90.971757
iter  30 value 83.711685
iter  40 value 82.207608
iter  50 value 81.147378
iter  60 value 80.349826
iter  70 value 79.839794
iter  80 value 79.600534
iter  90 value 79.523851
iter 100 value 79.508924
final  value 79.508924 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.771975 
iter  10 value 94.474891
iter  20 value 93.559206
iter  30 value 91.408257
iter  40 value 85.448410
iter  50 value 84.224443
iter  60 value 82.896112
iter  70 value 81.063378
iter  80 value 79.923016
iter  90 value 79.802731
iter 100 value 79.373622
final  value 79.373622 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.505951 
iter  10 value 95.804627
iter  20 value 90.400884
iter  30 value 84.864167
iter  40 value 84.225078
iter  50 value 84.072439
iter  60 value 83.516083
iter  70 value 83.230126
iter  80 value 82.803865
iter  90 value 81.011854
iter 100 value 80.348259
final  value 80.348259 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.000760 
iter  10 value 93.972263
iter  20 value 85.344088
iter  30 value 84.444855
iter  40 value 83.662316
iter  50 value 83.533011
iter  60 value 82.024011
iter  70 value 81.058113
iter  80 value 81.016733
iter  90 value 81.015527
iter 100 value 80.997609
final  value 80.997609 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 121.784068 
iter  10 value 94.736338
iter  20 value 94.171887
iter  30 value 88.525906
iter  40 value 84.419066
iter  50 value 83.261656
iter  60 value 82.698202
iter  70 value 82.270784
iter  80 value 81.588644
iter  90 value 80.757254
iter 100 value 80.583129
final  value 80.583129 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 114.426614 
iter  10 value 94.367862
iter  20 value 89.970668
iter  30 value 85.301811
iter  40 value 84.268485
iter  50 value 82.676967
iter  60 value 81.375067
iter  70 value 81.178455
iter  80 value 81.022649
iter  90 value 80.607168
iter 100 value 80.203371
final  value 80.203371 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 137.671429 
iter  10 value 94.281011
iter  20 value 93.524836
iter  30 value 92.494805
iter  40 value 84.338783
iter  50 value 82.925878
iter  60 value 81.712639
iter  70 value 80.758409
iter  80 value 80.008190
iter  90 value 79.702904
iter 100 value 79.597464
final  value 79.597464 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.960619 
iter  10 value 95.856218
iter  20 value 87.294147
iter  30 value 84.517392
iter  40 value 82.729243
iter  50 value 82.085382
iter  60 value 80.263378
iter  70 value 79.959015
iter  80 value 79.668414
iter  90 value 79.514733
iter 100 value 79.332999
final  value 79.332999 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.087001 
iter  10 value 94.593031
iter  20 value 93.711687
iter  30 value 92.206185
iter  40 value 85.540715
iter  50 value 84.429909
iter  60 value 83.479355
iter  70 value 81.502632
iter  80 value 79.919103
iter  90 value 79.567993
iter 100 value 79.405835
final  value 79.405835 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 120.016482 
iter  10 value 93.126715
iter  20 value 90.599911
iter  30 value 86.444247
iter  40 value 81.798686
iter  50 value 80.499130
iter  60 value 80.161528
iter  70 value 80.099714
iter  80 value 79.993112
iter  90 value 79.677401
iter 100 value 79.604287
final  value 79.604287 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 111.384088 
final  value 94.485862 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.990540 
final  value 94.485721 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.757594 
final  value 94.485959 
converged
Fitting Repeat 4 

# weights:  103
initial  value 92.428675 
iter  10 value 86.451113
iter  20 value 85.790709
iter  30 value 85.790507
iter  40 value 85.789614
iter  50 value 85.789208
final  value 85.788951 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.520375 
final  value 94.485979 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.076107 
iter  10 value 94.489416
iter  20 value 94.117582
iter  30 value 93.323596
iter  40 value 93.296227
iter  50 value 93.156958
iter  60 value 93.151310
iter  70 value 93.131434
iter  80 value 92.236152
iter  90 value 92.205527
iter 100 value 92.204327
final  value 92.204327 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 112.118350 
iter  10 value 94.489444
iter  20 value 94.483140
iter  30 value 93.940765
iter  40 value 92.162340
iter  50 value 90.548658
iter  60 value 90.524293
iter  70 value 90.524136
iter  80 value 90.523134
iter  90 value 90.522733
iter 100 value 90.327209
final  value 90.327209 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 94.673872 
iter  10 value 94.489086
iter  20 value 93.757610
final  value 93.395854 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.166295 
iter  10 value 94.489009
iter  20 value 94.484264
iter  20 value 94.484263
final  value 94.484263 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.039126 
iter  10 value 94.489140
iter  20 value 94.484233
final  value 94.484222 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.463901 
iter  10 value 93.163704
iter  20 value 93.162298
iter  30 value 93.155393
iter  40 value 86.415325
iter  50 value 86.264614
iter  60 value 85.316769
iter  70 value 84.971843
iter  80 value 84.970204
final  value 84.968273 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.735693 
iter  10 value 94.490540
iter  20 value 93.405591
final  value 93.397244 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.736724 
iter  10 value 94.492806
iter  20 value 94.387930
final  value 93.395518 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.088664 
iter  10 value 93.932828
iter  20 value 90.502587
iter  30 value 90.498852
iter  40 value 90.497811
iter  50 value 90.357769
iter  60 value 90.355706
iter  70 value 87.191143
iter  80 value 82.917013
iter  90 value 82.161373
iter 100 value 82.161265
final  value 82.161265 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.893791 
iter  10 value 93.403564
iter  20 value 93.398735
iter  30 value 93.151202
iter  40 value 93.020490
iter  50 value 83.797734
iter  60 value 79.899528
iter  70 value 78.227382
iter  80 value 77.765990
iter  90 value 77.648234
iter 100 value 77.645194
final  value 77.645194 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.357185 
iter  10 value 93.859254
iter  20 value 93.838820
final  value 93.838814 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.579224 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.969201 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.811173 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.132290 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.649876 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.770811 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.414979 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.139407 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.136814 
iter  10 value 94.432883
iter  20 value 94.430235
final  value 94.430233 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.174165 
final  value 94.467391 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.996846 
iter  10 value 94.427936
final  value 94.427933 
converged
Fitting Repeat 3 

# weights:  507
initial  value 112.866650 
iter  10 value 94.484211
iter  10 value 94.484211
iter  10 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 130.389822 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.123983 
final  value 94.449439 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.694305 
iter  10 value 94.527694
iter  20 value 94.466407
iter  30 value 90.701172
iter  40 value 89.635509
iter  50 value 88.366441
iter  60 value 87.537498
iter  70 value 85.852246
iter  80 value 85.574404
iter  90 value 85.289357
iter 100 value 84.553582
final  value 84.553582 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 101.077245 
iter  10 value 94.406923
iter  20 value 86.560615
iter  30 value 86.214343
iter  40 value 85.625147
iter  50 value 85.054558
iter  60 value 84.511165
iter  70 value 84.389987
final  value 84.356280 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.293791 
iter  10 value 94.486688
iter  20 value 89.628553
iter  30 value 87.401544
iter  40 value 87.094648
iter  50 value 86.104500
iter  60 value 85.459132
iter  70 value 85.034587
iter  80 value 84.952569
iter  90 value 84.510469
iter 100 value 84.356313
final  value 84.356313 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 102.711861 
iter  10 value 94.487745
iter  20 value 89.504918
iter  30 value 88.007291
iter  40 value 86.857545
iter  50 value 86.324553
iter  60 value 85.848362
iter  70 value 85.671953
iter  80 value 85.557051
final  value 85.549717 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.726037 
iter  10 value 89.511289
iter  20 value 88.800243
iter  30 value 87.865327
iter  40 value 85.796942
iter  50 value 85.155589
iter  60 value 85.094030
iter  70 value 85.025740
iter  80 value 84.861155
iter  90 value 84.612147
iter 100 value 84.436150
final  value 84.436150 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 106.064880 
iter  10 value 94.554417
iter  20 value 94.488437
iter  30 value 90.504609
iter  40 value 87.384332
iter  50 value 84.537035
iter  60 value 82.983726
iter  70 value 82.573001
iter  80 value 82.174770
iter  90 value 81.995678
iter 100 value 81.915222
final  value 81.915222 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.991344 
iter  10 value 93.410434
iter  20 value 92.531092
iter  30 value 89.778878
iter  40 value 87.928893
iter  50 value 84.884407
iter  60 value 82.801611
iter  70 value 82.318173
iter  80 value 82.074697
iter  90 value 81.767658
iter 100 value 81.635930
final  value 81.635930 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 114.891483 
iter  10 value 94.452266
iter  20 value 90.871782
iter  30 value 88.901985
iter  40 value 86.117650
iter  50 value 83.051807
iter  60 value 82.659758
iter  70 value 82.443035
iter  80 value 82.338449
iter  90 value 82.104232
iter 100 value 81.914918
final  value 81.914918 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.394990 
iter  10 value 94.564538
iter  20 value 94.478565
iter  30 value 88.241140
iter  40 value 87.142445
iter  50 value 86.690941
iter  60 value 86.102033
iter  70 value 84.928938
iter  80 value 82.923147
iter  90 value 82.231300
iter 100 value 81.671661
final  value 81.671661 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.367306 
iter  10 value 94.549565
iter  20 value 94.268338
iter  30 value 93.364722
iter  40 value 92.988343
iter  50 value 87.550298
iter  60 value 85.807173
iter  70 value 84.992910
iter  80 value 84.021032
iter  90 value 83.339540
iter 100 value 82.856768
final  value 82.856768 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 114.789840 
iter  10 value 94.887197
iter  20 value 89.089662
iter  30 value 84.399717
iter  40 value 83.224431
iter  50 value 82.357138
iter  60 value 82.008014
iter  70 value 81.970809
iter  80 value 81.837301
iter  90 value 81.818280
iter 100 value 81.734681
final  value 81.734681 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.961638 
iter  10 value 91.348876
iter  20 value 88.155290
iter  30 value 86.913033
iter  40 value 86.198609
iter  50 value 85.991265
iter  60 value 85.914038
iter  70 value 85.566598
iter  80 value 84.459559
iter  90 value 83.328577
iter 100 value 83.105706
final  value 83.105706 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.410763 
iter  10 value 94.058482
iter  20 value 93.762204
iter  30 value 93.643474
iter  40 value 91.394520
iter  50 value 84.999348
iter  60 value 84.356480
iter  70 value 83.914439
iter  80 value 83.481010
iter  90 value 82.503293
iter 100 value 82.332079
final  value 82.332079 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 119.484432 
iter  10 value 97.612934
iter  20 value 93.804243
iter  30 value 90.698228
iter  40 value 88.566571
iter  50 value 87.010638
iter  60 value 84.716667
iter  70 value 82.941880
iter  80 value 81.747107
iter  90 value 81.416859
iter 100 value 81.353450
final  value 81.353450 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.818560 
iter  10 value 99.466730
iter  20 value 90.849188
iter  30 value 87.378234
iter  40 value 83.837871
iter  50 value 82.801646
iter  60 value 82.456657
iter  70 value 81.884294
iter  80 value 81.333340
iter  90 value 81.255073
iter 100 value 81.028988
final  value 81.028988 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.334265 
iter  10 value 94.515990
iter  20 value 94.513155
iter  30 value 94.485199
iter  40 value 94.484224
final  value 94.484214 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.925833 
iter  10 value 94.432296
final  value 94.431985 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.287231 
iter  10 value 94.485788
iter  20 value 94.484231
iter  30 value 94.132277
iter  40 value 93.895745
iter  50 value 93.862025
iter  60 value 93.767453
iter  70 value 93.766781
iter  70 value 93.766781
final  value 93.766781 
converged
Fitting Repeat 4 

# weights:  103
initial  value 109.430372 
final  value 94.324439 
converged
Fitting Repeat 5 

# weights:  103
initial  value 122.616788 
final  value 94.485946 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.122831 
iter  10 value 94.489626
iter  20 value 94.487827
iter  30 value 93.961519
iter  40 value 88.424895
final  value 86.691789 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.241123 
iter  10 value 94.488928
iter  20 value 94.253131
iter  30 value 93.846972
iter  40 value 93.794231
final  value 93.794191 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.396970 
iter  10 value 94.488796
iter  20 value 93.264257
iter  30 value 86.459142
iter  40 value 86.390616
iter  50 value 86.387003
iter  60 value 86.380190
iter  70 value 86.029033
iter  80 value 82.586889
iter  90 value 80.408227
iter 100 value 79.944739
final  value 79.944739 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 95.877205 
iter  10 value 94.488608
iter  20 value 94.466744
iter  30 value 93.164802
iter  40 value 93.117575
iter  50 value 93.117304
iter  60 value 93.117071
final  value 93.116960 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.980292 
iter  10 value 93.683620
iter  20 value 92.941509
iter  30 value 92.939570
iter  40 value 92.928295
iter  50 value 92.921557
iter  60 value 92.788824
iter  70 value 92.732186
final  value 92.731887 
converged
Fitting Repeat 1 

# weights:  507
initial  value 116.040308 
iter  10 value 94.491934
iter  20 value 94.483325
iter  30 value 89.438147
iter  40 value 85.819575
iter  50 value 85.555728
iter  60 value 85.513902
iter  70 value 85.505765
iter  80 value 85.307749
iter  90 value 85.276243
iter 100 value 85.266211
final  value 85.266211 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.899520 
iter  10 value 94.491967
iter  20 value 94.248667
iter  30 value 93.227406
iter  40 value 93.119915
iter  50 value 87.664674
iter  60 value 84.701305
iter  70 value 82.769009
iter  80 value 82.646267
iter  90 value 82.640502
iter 100 value 82.640307
final  value 82.640307 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 118.961961 
iter  10 value 94.331379
iter  20 value 94.072576
iter  30 value 87.633612
iter  40 value 87.209474
iter  50 value 87.206860
iter  60 value 86.116558
iter  70 value 84.647760
iter  80 value 83.629244
iter  90 value 83.574417
iter 100 value 83.574142
final  value 83.574142 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 95.780986 
iter  10 value 94.492316
iter  20 value 94.397628
iter  30 value 90.817709
iter  40 value 85.192304
iter  50 value 84.713060
iter  60 value 82.615137
iter  70 value 81.969876
iter  80 value 81.968796
iter  90 value 81.456587
iter 100 value 81.156231
final  value 81.156231 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 93.879875 
iter  10 value 87.931708
iter  20 value 85.078761
iter  30 value 83.133539
iter  40 value 82.666480
iter  50 value 82.622138
iter  60 value 82.616536
iter  70 value 82.615081
iter  80 value 82.567169
iter  90 value 82.420673
iter 100 value 82.410243
final  value 82.410243 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.796769 
final  value 94.008696 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.953743 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.862308 
final  value 94.011429 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.307038 
iter  10 value 89.795706
iter  20 value 87.804043
iter  30 value 87.803850
final  value 87.803838 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.396067 
final  value 94.008696 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.028205 
iter  10 value 93.971006
iter  20 value 93.963182
final  value 93.963025 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.433616 
final  value 94.008696 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.193874 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.332479 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.550362 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.341053 
iter  10 value 93.861590
final  value 93.861587 
converged
Fitting Repeat 2 

# weights:  507
initial  value 112.061461 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.486161 
iter  10 value 93.717253
final  value 93.664372 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.202535 
iter  10 value 94.008696
iter  10 value 94.008696
iter  10 value 94.008696
final  value 94.008696 
converged
Fitting Repeat 5 

# weights:  507
initial  value 119.566222 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.937863 
iter  10 value 94.059110
iter  20 value 93.808827
iter  30 value 88.954693
iter  40 value 85.150024
iter  50 value 84.569960
iter  60 value 84.110617
iter  70 value 83.993071
iter  80 value 83.943874
iter  90 value 83.928172
final  value 83.928151 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.346486 
iter  10 value 94.057508
iter  20 value 91.501727
iter  30 value 85.700575
iter  40 value 84.733725
iter  50 value 84.461028
iter  60 value 84.043410
iter  70 value 83.941151
iter  80 value 83.497458
iter  90 value 83.487096
final  value 83.486162 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.591688 
iter  10 value 93.969313
iter  20 value 92.617109
iter  30 value 89.888769
iter  40 value 87.122449
iter  50 value 84.843661
iter  60 value 84.281887
iter  70 value 83.142708
iter  80 value 82.582219
iter  90 value 82.340494
iter 100 value 81.760420
final  value 81.760420 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 98.605934 
iter  10 value 94.056298
iter  20 value 93.792436
iter  30 value 93.334702
iter  40 value 85.838450
iter  50 value 85.299646
iter  60 value 84.069116
iter  70 value 83.939290
iter  80 value 83.928151
iter  80 value 83.928151
iter  80 value 83.928151
final  value 83.928151 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.874061 
iter  10 value 94.059048
iter  20 value 91.102493
iter  30 value 88.185033
iter  40 value 86.585228
iter  50 value 85.776343
iter  60 value 85.498368
iter  70 value 85.116799
iter  80 value 84.652879
iter  90 value 84.466442
iter 100 value 84.458536
final  value 84.458536 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 101.792641 
iter  10 value 94.719075
iter  20 value 90.541604
iter  30 value 86.868153
iter  40 value 85.750896
iter  50 value 85.278098
iter  60 value 83.213614
iter  70 value 82.751687
iter  80 value 82.622302
iter  90 value 82.213330
iter 100 value 81.895325
final  value 81.895325 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.487765 
iter  10 value 94.020062
iter  20 value 89.809209
iter  30 value 84.912668
iter  40 value 84.290117
iter  50 value 83.860552
iter  60 value 83.377875
iter  70 value 82.191912
iter  80 value 81.608960
iter  90 value 80.816853
iter 100 value 80.350901
final  value 80.350901 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.381603 
iter  10 value 93.463696
iter  20 value 91.061079
iter  30 value 86.439181
iter  40 value 83.168930
iter  50 value 82.221882
iter  60 value 81.783312
iter  70 value 81.687291
iter  80 value 81.376480
iter  90 value 80.597108
iter 100 value 80.412871
final  value 80.412871 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.927632 
iter  10 value 88.673170
iter  20 value 85.151000
iter  30 value 84.887453
iter  40 value 82.578518
iter  50 value 81.772393
iter  60 value 81.141225
iter  70 value 80.972735
iter  80 value 80.876578
iter  90 value 80.551873
iter 100 value 80.278626
final  value 80.278626 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 113.111066 
iter  10 value 94.763392
iter  20 value 94.135437
iter  30 value 94.059620
iter  40 value 87.294030
iter  50 value 85.896165
iter  60 value 85.166162
iter  70 value 84.889251
iter  80 value 82.957622
iter  90 value 82.490634
iter 100 value 82.069219
final  value 82.069219 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.639738 
iter  10 value 93.947698
iter  20 value 87.744913
iter  30 value 86.878844
iter  40 value 83.874813
iter  50 value 82.111589
iter  60 value 81.784823
iter  70 value 81.416000
iter  80 value 81.096748
iter  90 value 80.371041
iter 100 value 80.214917
final  value 80.214917 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 110.061385 
iter  10 value 94.087126
iter  20 value 92.777485
iter  30 value 86.445563
iter  40 value 85.783982
iter  50 value 83.573636
iter  60 value 81.328394
iter  70 value 81.059796
iter  80 value 80.690383
iter  90 value 80.437570
iter 100 value 80.358417
final  value 80.358417 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 115.115250 
iter  10 value 94.076309
iter  20 value 87.232574
iter  30 value 85.796289
iter  40 value 85.110654
iter  50 value 84.784862
iter  60 value 84.332539
iter  70 value 83.141158
iter  80 value 80.932354
iter  90 value 80.433637
iter 100 value 80.185644
final  value 80.185644 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 118.001873 
iter  10 value 94.206902
iter  20 value 93.988597
iter  30 value 88.085728
iter  40 value 87.731013
iter  50 value 86.830325
iter  60 value 84.359464
iter  70 value 84.011041
iter  80 value 83.767526
iter  90 value 82.390192
iter 100 value 80.900739
final  value 80.900739 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 124.163131 
iter  10 value 94.980118
iter  20 value 86.678248
iter  30 value 85.447483
iter  40 value 84.757289
iter  50 value 84.521427
iter  60 value 83.204911
iter  70 value 82.263848
iter  80 value 81.937425
iter  90 value 81.453848
iter 100 value 80.538657
final  value 80.538657 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 108.835269 
iter  10 value 94.054649
final  value 94.052929 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.493274 
final  value 94.054614 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.483550 
final  value 94.054411 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.759997 
final  value 94.054449 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.443722 
final  value 94.054480 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.437572 
iter  10 value 93.973557
iter  20 value 93.647301
iter  30 value 92.565673
iter  40 value 92.535250
iter  50 value 92.393259
iter  60 value 92.391831
final  value 92.389940 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.974023 
iter  10 value 94.013699
iter  20 value 93.958450
iter  20 value 93.958450
iter  30 value 89.042449
iter  40 value 86.861244
iter  50 value 85.899760
iter  60 value 85.897616
final  value 85.897584 
converged
Fitting Repeat 3 

# weights:  305
initial  value 113.740150 
iter  10 value 94.016537
iter  20 value 94.011669
iter  30 value 92.579009
iter  40 value 85.666473
iter  50 value 85.505946
final  value 85.496177 
converged
Fitting Repeat 4 

# weights:  305
initial  value 110.010253 
iter  10 value 94.057925
iter  20 value 93.991564
iter  30 value 84.680046
iter  40 value 84.022796
iter  50 value 84.012621
iter  60 value 83.856678
iter  70 value 83.852411
final  value 83.852330 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.490675 
iter  10 value 89.484524
iter  20 value 89.479096
iter  30 value 89.432010
iter  40 value 89.424528
iter  50 value 88.206541
iter  60 value 86.956747
iter  70 value 86.898664
iter  80 value 86.584439
iter  90 value 86.220664
iter 100 value 86.213192
final  value 86.213192 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 95.909270 
iter  10 value 87.880425
iter  20 value 83.167388
iter  30 value 81.874908
iter  40 value 81.597573
iter  50 value 81.595784
iter  60 value 81.593838
iter  70 value 81.165900
iter  80 value 80.985283
iter  90 value 80.977429
final  value 80.977280 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.369868 
iter  10 value 93.971025
iter  20 value 93.941276
iter  30 value 87.703603
iter  40 value 87.184195
iter  50 value 87.179923
iter  50 value 87.179922
iter  50 value 87.179922
final  value 87.179922 
converged
Fitting Repeat 3 

# weights:  507
initial  value 113.410497 
iter  10 value 94.019220
iter  20 value 94.018391
iter  30 value 94.011939
iter  40 value 84.192947
iter  50 value 83.991759
iter  60 value 83.510796
iter  70 value 83.424776
iter  80 value 82.457663
iter  90 value 82.176867
iter 100 value 81.862351
final  value 81.862351 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.038151 
iter  10 value 88.770685
iter  20 value 87.530424
iter  30 value 86.006717
iter  40 value 85.567242
iter  50 value 85.545048
iter  60 value 84.234592
iter  70 value 83.974858
iter  80 value 83.968102
iter  90 value 83.879647
iter 100 value 83.731603
final  value 83.731603 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 99.060792 
iter  10 value 92.162424
iter  20 value 84.090458
iter  30 value 82.895982
iter  40 value 82.858797
iter  50 value 82.822150
iter  60 value 82.820641
iter  70 value 82.817004
iter  80 value 81.848400
iter  90 value 81.127972
iter 100 value 81.045221
final  value 81.045221 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.088937 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.891437 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.690815 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.805872 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.242304 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.531238 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.061731 
iter  10 value 93.109894
final  value 93.109890 
converged
Fitting Repeat 3 

# weights:  305
initial  value 113.496262 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.050608 
final  value 94.354396 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.534656 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.048187 
final  value 94.406131 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.712027 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 113.797145 
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.407603 
final  value 94.289216 
converged
Fitting Repeat 5 

# weights:  507
initial  value 122.872782 
iter  10 value 93.383169
final  value 93.080392 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.454055 
iter  10 value 94.353005
iter  20 value 87.938033
iter  30 value 86.915398
iter  40 value 86.732911
iter  50 value 86.466559
iter  60 value 84.933295
iter  70 value 84.802702
iter  80 value 84.668743
iter  90 value 84.621487
final  value 84.621481 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.433172 
iter  10 value 93.853999
iter  20 value 87.869152
iter  30 value 87.278937
iter  40 value 85.664739
iter  50 value 85.214426
iter  60 value 85.014232
iter  70 value 84.988658
iter  80 value 84.964727
iter  90 value 84.734590
iter 100 value 84.622341
final  value 84.622341 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 103.027720 
iter  10 value 94.484857
iter  20 value 92.765572
iter  30 value 87.660273
iter  40 value 86.258060
iter  50 value 85.182606
iter  60 value 85.072088
iter  70 value 84.987193
iter  80 value 84.745986
iter  90 value 84.712328
iter 100 value 84.640455
final  value 84.640455 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 102.557901 
iter  10 value 94.486723
iter  20 value 94.158333
iter  30 value 90.304577
iter  40 value 86.262105
iter  50 value 85.769974
iter  60 value 85.588625
iter  70 value 85.504843
iter  80 value 85.255853
iter  90 value 85.064606
final  value 85.063694 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.766194 
iter  10 value 93.966934
iter  20 value 86.965739
iter  30 value 86.899967
iter  40 value 86.845375
iter  50 value 85.114358
iter  60 value 84.830563
iter  70 value 84.782227
iter  80 value 84.637996
iter  90 value 84.621727
final  value 84.621481 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.572039 
iter  10 value 94.413684
iter  20 value 87.399893
iter  30 value 86.706250
iter  40 value 85.061227
iter  50 value 83.942015
iter  60 value 82.488853
iter  70 value 82.001504
iter  80 value 81.912936
iter  90 value 81.749859
iter 100 value 81.599638
final  value 81.599638 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.192993 
iter  10 value 94.492092
iter  20 value 94.203084
iter  30 value 88.843952
iter  40 value 86.742221
iter  50 value 86.255355
iter  60 value 84.118907
iter  70 value 82.821418
iter  80 value 82.612747
iter  90 value 82.530858
iter 100 value 82.492378
final  value 82.492378 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.813362 
iter  10 value 93.988103
iter  20 value 92.058755
iter  30 value 85.486952
iter  40 value 85.085671
iter  50 value 83.972105
iter  60 value 83.781025
iter  70 value 83.758896
iter  80 value 83.740222
iter  90 value 83.632430
iter 100 value 82.912197
final  value 82.912197 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.917764 
iter  10 value 94.608118
iter  20 value 88.156523
iter  30 value 84.959108
iter  40 value 84.033916
iter  50 value 83.220226
iter  60 value 83.075844
iter  70 value 82.873408
iter  80 value 82.776981
iter  90 value 82.025596
iter 100 value 81.667056
final  value 81.667056 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.467744 
iter  10 value 94.463656
iter  20 value 94.341150
iter  30 value 94.298448
iter  40 value 94.025481
iter  50 value 90.960265
iter  60 value 90.040507
iter  70 value 89.640520
iter  80 value 87.206114
iter  90 value 85.730868
iter 100 value 85.416818
final  value 85.416818 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 102.671088 
iter  10 value 91.679621
iter  20 value 87.700648
iter  30 value 85.049232
iter  40 value 84.554084
iter  50 value 83.696110
iter  60 value 82.393518
iter  70 value 82.070911
iter  80 value 81.991551
iter  90 value 81.880209
iter 100 value 81.801430
final  value 81.801430 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.400569 
iter  10 value 94.613948
iter  20 value 89.460562
iter  30 value 86.775066
iter  40 value 86.535844
iter  50 value 85.143965
iter  60 value 84.414458
iter  70 value 84.374612
iter  80 value 84.222111
iter  90 value 83.537682
iter 100 value 83.335214
final  value 83.335214 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 115.648791 
iter  10 value 94.594127
iter  20 value 94.470744
iter  30 value 94.388406
iter  40 value 89.891870
iter  50 value 86.647674
iter  60 value 86.480126
iter  70 value 86.420147
iter  80 value 84.797872
iter  90 value 82.987942
iter 100 value 82.658978
final  value 82.658978 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 119.982267 
iter  10 value 94.632544
iter  20 value 86.325405
iter  30 value 83.247834
iter  40 value 82.631677
iter  50 value 81.914147
iter  60 value 81.585074
iter  70 value 81.295599
iter  80 value 81.080284
iter  90 value 80.997923
iter 100 value 80.949965
final  value 80.949965 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.778097 
iter  10 value 99.492824
iter  20 value 94.123058
iter  30 value 93.528805
iter  40 value 88.188596
iter  50 value 85.949679
iter  60 value 84.409090
iter  70 value 84.217817
iter  80 value 84.012852
iter  90 value 83.914084
iter 100 value 83.530097
final  value 83.530097 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.489778 
final  value 94.486211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.290972 
final  value 94.485618 
converged
Fitting Repeat 3 

# weights:  103
initial  value 108.212258 
final  value 94.485969 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.590038 
final  value 94.485708 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.227662 
final  value 94.485719 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.621510 
iter  10 value 94.359555
iter  20 value 86.332414
iter  30 value 83.909118
iter  40 value 83.732663
iter  50 value 83.717568
iter  60 value 83.555229
iter  70 value 83.498981
final  value 83.498490 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.213465 
iter  10 value 94.489246
iter  20 value 94.484248
iter  30 value 94.368980
iter  40 value 92.546306
iter  50 value 92.231253
iter  60 value 92.228885
iter  70 value 92.226103
iter  80 value 91.729961
final  value 91.693226 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.587763 
iter  10 value 94.489389
iter  20 value 94.481704
iter  30 value 94.290900
final  value 94.289633 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.913840 
iter  10 value 94.144446
iter  20 value 94.140595
iter  30 value 87.698165
iter  40 value 86.743898
iter  50 value 86.713728
iter  60 value 86.712922
iter  70 value 84.382071
iter  80 value 83.981885
iter  90 value 83.838732
iter 100 value 83.811315
final  value 83.811315 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.834536 
iter  10 value 94.359514
iter  20 value 94.052694
iter  30 value 88.351255
iter  40 value 85.683171
iter  50 value 85.616887
iter  60 value 85.581167
iter  70 value 85.578087
iter  80 value 85.571540
iter  90 value 85.498462
iter 100 value 85.484047
final  value 85.484047 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 148.574293 
iter  10 value 94.362952
iter  20 value 94.352477
iter  30 value 93.341166
iter  40 value 85.851873
iter  50 value 85.815771
iter  60 value 85.547701
iter  70 value 85.498432
iter  80 value 85.407364
iter  90 value 85.314877
iter 100 value 85.314198
final  value 85.314198 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 129.950829 
iter  10 value 94.031004
iter  20 value 85.838564
iter  30 value 85.819123
iter  40 value 85.692669
iter  50 value 85.689331
final  value 85.689182 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.877828 
iter  10 value 94.489226
iter  20 value 94.377995
iter  30 value 93.570164
iter  40 value 85.852936
iter  50 value 84.950247
iter  60 value 84.693845
iter  70 value 84.480848
iter  80 value 84.478076
iter  90 value 84.477760
iter 100 value 84.477480
final  value 84.477480 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 101.820313 
iter  10 value 92.010795
iter  20 value 91.540341
iter  30 value 91.306466
iter  40 value 90.856936
iter  50 value 90.846099
iter  60 value 90.844986
final  value 90.843947 
converged
Fitting Repeat 5 

# weights:  507
initial  value 117.116530 
iter  10 value 94.492028
iter  20 value 94.483551
iter  30 value 89.868857
iter  40 value 88.029344
iter  50 value 86.831593
iter  60 value 86.286477
iter  70 value 86.189128
final  value 86.189059 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.271198 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.857677 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.510178 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.035729 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.542965 
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.959294 
final  value 94.032967 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.696843 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.131400 
iter  10 value 82.381683
iter  20 value 81.922257
iter  30 value 81.533875
iter  30 value 81.533875
iter  30 value 81.533875
final  value 81.533875 
converged
Fitting Repeat 4 

# weights:  305
initial  value 112.886161 
iter  10 value 93.653870
iter  10 value 93.653870
iter  10 value 93.653870
final  value 93.653870 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.786619 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.157031 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.995493 
final  value 92.701657 
converged
Fitting Repeat 3 

# weights:  507
initial  value 132.702206 
iter  10 value 93.573671
final  value 93.573670 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.026833 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.431950 
final  value 94.052911 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.318389 
iter  10 value 94.055277
iter  20 value 93.190467
iter  30 value 84.288525
iter  40 value 83.496945
iter  50 value 83.026398
iter  60 value 82.665334
iter  70 value 82.646428
iter  70 value 82.646427
iter  70 value 82.646427
final  value 82.646427 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.405327 
iter  10 value 94.056672
iter  20 value 93.699854
iter  30 value 93.308520
iter  40 value 93.247622
iter  50 value 93.201144
iter  60 value 91.941996
iter  70 value 86.974865
iter  80 value 86.532198
iter  90 value 82.777584
iter 100 value 82.271175
final  value 82.271175 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.039777 
iter  10 value 93.978412
iter  20 value 93.233839
iter  30 value 83.546610
iter  40 value 82.430127
iter  50 value 82.109687
iter  60 value 82.065330
iter  70 value 82.064532
final  value 82.064523 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.917693 
iter  10 value 93.260031
iter  20 value 83.703599
iter  30 value 82.260962
iter  40 value 82.103835
iter  50 value 82.076701
iter  60 value 82.064524
final  value 82.064522 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.512011 
iter  10 value 93.954827
iter  20 value 86.557743
iter  30 value 82.823607
iter  40 value 81.022091
iter  50 value 80.490212
iter  60 value 79.731755
iter  70 value 79.625696
iter  80 value 79.568883
iter  90 value 79.202179
iter 100 value 78.907897
final  value 78.907897 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 108.928941 
iter  10 value 93.893470
iter  20 value 86.424988
iter  30 value 86.146377
iter  40 value 84.316640
iter  50 value 82.333721
iter  60 value 80.276248
iter  70 value 79.024835
iter  80 value 78.742342
iter  90 value 77.782046
iter 100 value 77.251732
final  value 77.251732 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.862819 
iter  10 value 93.982983
iter  20 value 87.554371
iter  30 value 83.635835
iter  40 value 82.330872
iter  50 value 82.148189
iter  60 value 82.013546
iter  70 value 81.243005
iter  80 value 80.218877
iter  90 value 79.481289
iter 100 value 79.138445
final  value 79.138445 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 113.332280 
iter  10 value 93.259755
iter  20 value 83.624561
iter  30 value 83.435583
iter  40 value 82.430842
iter  50 value 80.479676
iter  60 value 79.727871
iter  70 value 78.583291
iter  80 value 77.730962
iter  90 value 77.605883
iter 100 value 77.597205
final  value 77.597205 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.455420 
iter  10 value 93.743155
iter  20 value 93.227755
iter  30 value 92.872821
iter  40 value 84.733997
iter  50 value 83.237649
iter  60 value 82.740615
iter  70 value 81.282010
iter  80 value 79.935585
iter  90 value 79.722990
iter 100 value 79.019709
final  value 79.019709 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.375820 
iter  10 value 94.212379
iter  20 value 93.766816
iter  30 value 91.552262
iter  40 value 87.969578
iter  50 value 86.500780
iter  60 value 82.418608
iter  70 value 81.705205
iter  80 value 80.059295
iter  90 value 79.905185
iter 100 value 79.403885
final  value 79.403885 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 119.958463 
iter  10 value 93.755504
iter  20 value 89.195990
iter  30 value 83.020820
iter  40 value 81.042655
iter  50 value 79.387259
iter  60 value 79.021089
iter  70 value 78.537904
iter  80 value 77.928972
iter  90 value 77.844586
iter 100 value 77.782485
final  value 77.782485 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 125.340970 
iter  10 value 95.143360
iter  20 value 89.246471
iter  30 value 84.892325
iter  40 value 83.109068
iter  50 value 82.087336
iter  60 value 80.389430
iter  70 value 79.304822
iter  80 value 78.154713
iter  90 value 77.422024
iter 100 value 77.184230
final  value 77.184230 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 124.707950 
iter  10 value 94.809371
iter  20 value 84.891290
iter  30 value 81.554140
iter  40 value 79.426204
iter  50 value 78.062667
iter  60 value 77.740704
iter  70 value 77.476146
iter  80 value 77.200222
iter  90 value 76.862933
iter 100 value 76.730507
final  value 76.730507 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.477040 
iter  10 value 93.987031
iter  20 value 83.659422
iter  30 value 82.214744
iter  40 value 81.703967
iter  50 value 80.551261
iter  60 value 79.210014
iter  70 value 77.894249
iter  80 value 77.648385
iter  90 value 77.314388
iter 100 value 77.140940
final  value 77.140940 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.505614 
iter  10 value 93.777241
iter  20 value 92.858661
iter  30 value 82.218579
iter  40 value 81.738059
iter  50 value 81.350327
iter  60 value 79.766523
iter  70 value 78.884184
iter  80 value 78.404877
iter  90 value 78.146615
iter 100 value 77.841694
final  value 77.841694 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.160820 
final  value 94.054631 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.148149 
iter  10 value 94.054713
iter  20 value 94.052897
iter  30 value 93.126413
iter  40 value 92.497680
iter  50 value 86.456165
iter  60 value 86.422342
iter  70 value 86.418139
iter  80 value 86.416437
iter  90 value 86.416017
iter 100 value 86.415482
final  value 86.415482 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.400987 
final  value 93.606328 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.182062 
final  value 94.054453 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.259080 
final  value 94.054417 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.320147 
iter  10 value 94.058348
iter  20 value 94.053212
iter  30 value 92.897619
final  value 92.893090 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.051664 
iter  10 value 94.037943
iter  20 value 93.839884
iter  30 value 80.984556
iter  40 value 80.961613
iter  50 value 78.620471
iter  60 value 78.614318
iter  70 value 78.610495
iter  80 value 78.609439
iter  90 value 78.607937
final  value 78.607893 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.734702 
iter  10 value 94.037942
iter  20 value 93.698865
iter  30 value 93.093760
iter  40 value 93.091108
final  value 93.091106 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.604203 
iter  10 value 94.095649
iter  20 value 94.080016
iter  30 value 83.906803
iter  40 value 81.008989
iter  50 value 81.007962
iter  60 value 81.004793
iter  70 value 80.792576
iter  80 value 80.781414
iter  90 value 79.641483
iter 100 value 77.858185
final  value 77.858185 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 110.213397 
iter  10 value 93.609641
iter  20 value 93.605204
iter  30 value 93.573941
final  value 93.573878 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.701405 
iter  10 value 91.825610
iter  20 value 82.138049
iter  30 value 82.031626
iter  40 value 81.964417
iter  50 value 80.720603
iter  60 value 80.693767
iter  70 value 80.689048
iter  80 value 80.663762
iter  90 value 80.663332
iter 100 value 80.661899
final  value 80.661899 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.313457 
iter  10 value 94.061570
iter  20 value 94.052252
iter  30 value 92.703161
final  value 92.702932 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.366780 
iter  10 value 92.436903
iter  20 value 90.428721
iter  30 value 84.972901
iter  40 value 83.737633
final  value 83.734265 
converged
Fitting Repeat 4 

# weights:  507
initial  value 111.161822 
iter  10 value 94.060647
iter  20 value 93.619637
iter  30 value 90.495135
iter  40 value 90.064936
final  value 90.061268 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.228515 
iter  10 value 94.040603
iter  20 value 93.769532
iter  30 value 86.363217
iter  40 value 82.516121
iter  50 value 82.088725
iter  60 value 81.471551
iter  70 value 80.969511
iter  80 value 80.893058
iter  90 value 80.891318
iter 100 value 80.830489
final  value 80.830489 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 141.392511 
iter  10 value 118.042462
iter  20 value 110.961356
iter  30 value 106.486366
iter  40 value 105.880208
iter  50 value 105.478796
iter  60 value 101.745929
iter  70 value 101.373265
iter  80 value 100.949142
iter  90 value 100.565022
iter 100 value 100.387078
final  value 100.387078 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 129.950853 
iter  10 value 118.303222
iter  20 value 112.282174
iter  30 value 105.229899
iter  40 value 103.800555
iter  50 value 102.838299
iter  60 value 101.809254
iter  70 value 100.798056
iter  80 value 100.587388
iter  90 value 100.372906
iter 100 value 100.159336
final  value 100.159336 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 199.257331 
iter  10 value 119.077091
iter  20 value 117.463666
iter  30 value 107.955275
iter  40 value 106.362533
iter  50 value 105.788312
iter  60 value 103.981750
iter  70 value 102.335355
iter  80 value 101.459662
iter  90 value 101.248446
iter 100 value 100.958583
final  value 100.958583 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 144.992140 
iter  10 value 117.903280
iter  20 value 107.896514
iter  30 value 106.138432
iter  40 value 103.214636
iter  50 value 102.029836
iter  60 value 101.482025
iter  70 value 101.373079
iter  80 value 101.238811
iter  90 value 100.755382
iter 100 value 100.371944
final  value 100.371944 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 127.068861 
iter  10 value 117.817621
iter  20 value 116.282670
iter  30 value 109.536422
iter  40 value 105.620466
iter  50 value 104.387447
iter  60 value 103.897359
iter  70 value 103.777625
iter  80 value 102.835265
iter  90 value 102.208300
iter 100 value 101.455244
final  value 101.455244 
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 Mar 18 08:39:33 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 
 52.637   1.062 144.087