##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.20-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.20-bioc/R/site-library --timings HPiP_1.12.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck’
* using R version 4.4.2 (2024-10-31)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 13.2.0-23ubuntu4) 13.2.0
    GNU Fortran (Ubuntu 13.2.0-23ubuntu4) 13.2.0
* running under: Ubuntu 24.04.1 LTS
* using session charset: UTF-8
* 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 ...Warning: unable to access index for repository https://CRAN.R-project.org/src/contrib:
  cannot open URL 'https://CRAN.R-project.org/src/contrib/PACKAGES'
 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
Unknown package ‘ftrCOOL’ in Rd xrefs
* 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       32.768  0.309  33.078
FSmethod      32.202  0.486  32.691
corr_plot     31.907  0.330  32.238
pred_ensembel 12.702  0.316  11.748
enrichfindP    0.530  0.027   7.938
* 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 re-building of vignette outputs ... OK
* 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/bbs-3.20-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.20-bioc/R/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 4.4.2 (2024-10-31) -- "Pile of Leaves"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-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 101.601050 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.484077 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.680277 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.205774 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.595302 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.988953 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.531419 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.999273 
final  value 94.461207 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.385879 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.384020 
final  value 94.313816 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.687778 
final  value 94.103571 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.157033 
final  value 94.354396 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.922803 
iter  10 value 94.484298
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.574727 
iter  10 value 94.358982
iter  20 value 94.275411
final  value 94.275363 
converged
Fitting Repeat 5 

# weights:  507
initial  value 128.213697 
iter  10 value 93.835920
iter  20 value 93.518448
iter  30 value 93.120169
iter  40 value 92.657868
iter  50 value 92.628008
final  value 92.627913 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.040107 
iter  10 value 94.314026
iter  20 value 86.657855
iter  30 value 85.179541
iter  40 value 84.409225
iter  50 value 84.209924
iter  60 value 84.207332
final  value 84.207305 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.834661 
iter  10 value 94.486670
iter  20 value 94.160540
iter  30 value 94.150243
iter  40 value 90.788219
iter  50 value 89.250635
iter  60 value 87.476643
iter  70 value 85.003230
iter  80 value 84.635614
iter  90 value 84.560707
iter 100 value 84.512754
final  value 84.512754 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 102.031007 
iter  10 value 94.464212
iter  20 value 94.413458
iter  30 value 94.411852
iter  40 value 89.635135
iter  50 value 87.644569
iter  60 value 85.998798
iter  70 value 83.425313
iter  80 value 83.236257
iter  90 value 83.233954
final  value 83.233147 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.607894 
iter  10 value 94.640287
iter  20 value 94.493484
iter  30 value 94.035745
iter  40 value 90.681181
iter  50 value 89.138924
iter  60 value 85.533538
iter  70 value 84.422470
iter  80 value 83.437858
iter  90 value 83.263314
iter 100 value 83.233255
final  value 83.233255 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 107.673309 
iter  10 value 94.486604
iter  20 value 93.102671
iter  30 value 85.124999
iter  40 value 84.366769
iter  50 value 83.880608
iter  60 value 83.769211
final  value 83.766940 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.987709 
iter  10 value 94.312426
iter  20 value 89.689616
iter  30 value 87.198224
iter  40 value 84.120366
iter  50 value 82.594750
iter  60 value 80.912960
iter  70 value 80.596979
iter  80 value 80.572364
iter  90 value 80.532421
iter 100 value 80.514875
final  value 80.514875 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.969027 
iter  10 value 95.107606
iter  20 value 92.249496
iter  30 value 92.204346
iter  40 value 91.167008
iter  50 value 87.909670
iter  60 value 86.016730
iter  70 value 84.690414
iter  80 value 83.042667
iter  90 value 81.853250
iter 100 value 80.471622
final  value 80.471622 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.114693 
iter  10 value 94.266973
iter  20 value 86.009310
iter  30 value 84.779251
iter  40 value 84.623903
iter  50 value 84.000944
iter  60 value 83.572222
iter  70 value 83.090574
iter  80 value 81.531868
iter  90 value 80.991143
iter 100 value 80.081985
final  value 80.081985 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 113.262499 
iter  10 value 94.400470
iter  20 value 87.912922
iter  30 value 86.661404
iter  40 value 86.080346
iter  50 value 85.096349
iter  60 value 84.873169
iter  70 value 84.270728
iter  80 value 82.841297
iter  90 value 82.129469
iter 100 value 81.761398
final  value 81.761398 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 115.984919 
iter  10 value 94.611878
iter  20 value 85.075519
iter  30 value 84.150295
iter  40 value 82.491367
iter  50 value 82.394277
iter  60 value 82.136698
iter  70 value 81.842762
iter  80 value 81.778517
iter  90 value 81.757425
iter 100 value 81.708813
final  value 81.708813 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.639172 
iter  10 value 94.284872
iter  20 value 85.693792
iter  30 value 82.941668
iter  40 value 81.977516
iter  50 value 80.956460
iter  60 value 80.529011
iter  70 value 80.144271
iter  80 value 79.780803
iter  90 value 79.669429
iter 100 value 79.452729
final  value 79.452729 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 119.600072 
iter  10 value 93.469753
iter  20 value 86.081645
iter  30 value 84.421681
iter  40 value 84.297968
iter  50 value 84.212987
iter  60 value 83.306271
iter  70 value 82.583387
iter  80 value 81.201775
iter  90 value 80.949533
iter 100 value 80.583281
final  value 80.583281 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 116.771453 
iter  10 value 95.573344
iter  20 value 93.377082
iter  30 value 88.921771
iter  40 value 85.139405
iter  50 value 82.958887
iter  60 value 82.359227
iter  70 value 81.064490
iter  80 value 80.735837
iter  90 value 80.592047
iter 100 value 80.361332
final  value 80.361332 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 119.860507 
iter  10 value 94.468866
iter  20 value 87.457271
iter  30 value 86.089157
iter  40 value 83.787816
iter  50 value 83.708997
iter  60 value 83.526219
iter  70 value 82.004152
iter  80 value 81.338870
iter  90 value 80.821081
iter 100 value 80.325638
final  value 80.325638 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.442795 
iter  10 value 94.180660
iter  20 value 90.230125
iter  30 value 86.933402
iter  40 value 84.067417
iter  50 value 83.347297
iter  60 value 82.887428
iter  70 value 82.780141
iter  80 value 81.607008
iter  90 value 80.600546
iter 100 value 80.362520
final  value 80.362520 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.803848 
final  value 94.485695 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.187451 
final  value 94.485822 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.988254 
final  value 94.487085 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.505151 
final  value 94.486138 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.430861 
iter  10 value 94.485846
iter  20 value 94.483018
iter  30 value 86.930398
iter  40 value 84.865362
iter  50 value 84.864011
iter  60 value 84.863874
iter  70 value 84.862623
iter  80 value 84.862267
iter  90 value 84.862122
iter 100 value 83.835491
final  value 83.835491 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 97.676247 
iter  10 value 94.359535
iter  20 value 94.325215
final  value 94.323944 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.427989 
iter  10 value 94.361031
iter  20 value 94.074559
iter  30 value 88.371039
iter  40 value 88.358925
iter  50 value 88.358306
iter  60 value 88.358064
final  value 88.357901 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.688983 
iter  10 value 94.488195
iter  20 value 92.915272
iter  30 value 92.480984
final  value 92.477385 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.066052 
iter  10 value 92.745713
iter  20 value 92.744282
iter  30 value 92.165886
iter  40 value 92.146148
iter  50 value 92.142022
final  value 92.141844 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.252493 
iter  10 value 94.488907
iter  20 value 93.370070
final  value 84.861681 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.640396 
iter  10 value 94.492101
iter  20 value 94.380355
iter  30 value 92.753547
iter  40 value 91.516633
iter  50 value 91.331519
iter  60 value 82.891556
iter  70 value 80.645437
iter  80 value 80.396751
iter  90 value 80.344757
iter 100 value 80.309890
final  value 80.309890 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.717936 
iter  10 value 94.188347
iter  20 value 94.181180
iter  30 value 94.179787
iter  40 value 94.179134
iter  50 value 94.177290
iter  60 value 94.043271
iter  70 value 93.959622
iter  80 value 93.958178
iter  90 value 93.957814
iter 100 value 93.957249
final  value 93.957249 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 99.609758 
iter  10 value 94.492269
iter  20 value 94.426793
iter  30 value 86.883983
iter  40 value 84.038957
iter  50 value 83.944228
iter  60 value 83.678065
iter  70 value 83.254135
iter  80 value 81.435114
iter  90 value 80.214208
iter 100 value 79.966234
final  value 79.966234 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.676469 
iter  10 value 94.470039
iter  20 value 94.385740
iter  30 value 87.785099
iter  40 value 83.735614
iter  50 value 82.832940
iter  60 value 82.749919
iter  70 value 82.741248
iter  80 value 82.445193
iter  90 value 82.192852
final  value 82.192804 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.676645 
iter  10 value 94.491321
iter  20 value 92.958300
iter  30 value 86.251008
iter  40 value 82.913329
final  value 82.669840 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.803012 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.158923 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.056174 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.292836 
final  value 93.714286 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.097866 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.608829 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.243626 
iter  10 value 93.761844
final  value 93.643064 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.529893 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.306612 
iter  10 value 93.912644
iter  10 value 93.912644
iter  10 value 93.912644
final  value 93.912644 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.297819 
final  value 93.836066 
converged
Fitting Repeat 1 

# weights:  507
initial  value 120.982924 
final  value 93.836066 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.917162 
final  value 93.836066 
converged
Fitting Repeat 3 

# weights:  507
initial  value 117.361849 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 133.811706 
final  value 93.836066 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.453950 
iter  10 value 92.729917
iter  20 value 88.682989
iter  30 value 88.270964
final  value 88.268014 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.227195 
iter  10 value 94.038633
iter  20 value 93.304755
iter  30 value 93.163408
iter  40 value 92.278964
iter  50 value 92.249939
iter  60 value 92.247889
iter  70 value 92.247792
final  value 92.247790 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.259473 
iter  10 value 94.054902
iter  20 value 93.273074
iter  30 value 93.181709
iter  40 value 93.159481
iter  50 value 93.156036
iter  60 value 87.071707
iter  70 value 85.815787
iter  80 value 85.519096
iter  90 value 85.441352
iter 100 value 85.437903
final  value 85.437903 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 105.030714 
iter  10 value 94.057185
final  value 94.057093 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.210798 
iter  10 value 94.055011
iter  20 value 93.968504
iter  30 value 93.687873
iter  40 value 93.671276
iter  50 value 92.480057
iter  60 value 90.539704
iter  70 value 90.418607
iter  80 value 90.393367
iter  90 value 88.021224
iter 100 value 85.725996
final  value 85.725996 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.383079 
iter  10 value 93.464657
iter  20 value 87.748517
iter  30 value 87.353349
iter  40 value 84.585829
iter  50 value 84.252322
iter  60 value 84.173256
iter  70 value 84.111256
iter  80 value 84.093650
iter  90 value 84.030123
iter 100 value 83.904487
final  value 83.904487 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 99.544483 
iter  10 value 88.518267
iter  20 value 87.137824
iter  30 value 86.988354
iter  40 value 85.364080
iter  50 value 84.016280
iter  60 value 83.664995
iter  70 value 83.341399
iter  80 value 83.226167
iter  90 value 83.126410
iter 100 value 83.034483
final  value 83.034483 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.111202 
iter  10 value 94.063628
iter  20 value 93.541145
iter  30 value 88.917102
iter  40 value 85.818440
iter  50 value 84.766536
iter  60 value 84.078937
iter  70 value 83.634144
iter  80 value 83.556380
iter  90 value 83.508617
iter 100 value 83.357322
final  value 83.357322 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 111.700694 
iter  10 value 94.034007
iter  20 value 93.677099
iter  30 value 93.453392
iter  40 value 90.616062
iter  50 value 88.071993
iter  60 value 85.744481
iter  70 value 84.333922
iter  80 value 84.055621
iter  90 value 83.618607
iter 100 value 83.140947
final  value 83.140947 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 118.640386 
iter  10 value 93.655351
iter  20 value 90.429644
iter  30 value 88.837613
iter  40 value 86.426873
iter  50 value 86.099527
iter  60 value 85.837861
iter  70 value 85.433060
iter  80 value 85.299929
iter  90 value 84.316051
iter 100 value 83.585711
final  value 83.585711 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.887348 
iter  10 value 94.003884
iter  20 value 92.896889
iter  30 value 87.118486
iter  40 value 86.956333
iter  50 value 85.612683
iter  60 value 85.279712
iter  70 value 85.147032
iter  80 value 84.957725
iter  90 value 84.446628
iter 100 value 84.280544
final  value 84.280544 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.922644 
iter  10 value 94.094467
iter  20 value 89.244814
iter  30 value 86.373582
iter  40 value 85.566783
iter  50 value 84.878276
iter  60 value 83.455183
iter  70 value 83.280966
iter  80 value 83.261093
iter  90 value 82.971357
iter 100 value 82.821937
final  value 82.821937 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 120.686774 
iter  10 value 94.093677
iter  20 value 93.664459
iter  30 value 87.597578
iter  40 value 86.064880
iter  50 value 85.391158
iter  60 value 84.056994
iter  70 value 83.584361
iter  80 value 83.180414
iter  90 value 82.518445
iter 100 value 82.230350
final  value 82.230350 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.253152 
iter  10 value 96.104690
iter  20 value 94.412386
iter  30 value 92.793259
iter  40 value 89.272357
iter  50 value 86.986934
iter  60 value 86.181684
iter  70 value 85.706417
iter  80 value 83.910783
iter  90 value 83.252842
iter 100 value 83.017472
final  value 83.017472 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.954049 
iter  10 value 95.048295
iter  20 value 93.745245
iter  30 value 92.199626
iter  40 value 90.286245
iter  50 value 86.449952
iter  60 value 85.235497
iter  70 value 83.796490
iter  80 value 82.727842
iter  90 value 82.342194
iter 100 value 82.255399
final  value 82.255399 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 119.538552 
iter  10 value 96.270832
iter  20 value 87.755595
iter  30 value 87.076114
iter  40 value 86.108514
iter  50 value 84.973254
iter  60 value 83.921574
iter  70 value 83.384482
iter  80 value 83.223281
iter  90 value 82.905914
iter 100 value 82.787694
final  value 82.787694 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.428137 
iter  10 value 94.054537
iter  20 value 94.053000
final  value 94.052918 
converged
Fitting Repeat 2 

# weights:  103
initial  value 116.341752 
iter  10 value 94.054392
final  value 94.053062 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.551841 
final  value 94.054550 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.462783 
final  value 93.837561 
converged
Fitting Repeat 5 

# weights:  103
initial  value 107.541342 
final  value 94.054411 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.101441 
iter  10 value 94.057686
iter  20 value 94.052921
iter  30 value 92.642818
iter  40 value 87.376341
iter  50 value 87.256192
iter  60 value 87.255228
iter  70 value 86.929137
iter  80 value 86.690377
iter  90 value 86.687354
iter 100 value 86.605229
final  value 86.605229 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 95.507394 
iter  10 value 93.682752
iter  20 value 93.680613
iter  30 value 93.649943
iter  40 value 93.643657
iter  50 value 93.643565
iter  60 value 93.643495
iter  60 value 93.643495
iter  60 value 93.643494
final  value 93.643494 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.950889 
iter  10 value 94.057766
iter  20 value 93.850315
iter  30 value 93.786582
final  value 93.785952 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.471576 
iter  10 value 93.840974
iter  20 value 93.692888
final  value 93.617140 
converged
Fitting Repeat 5 

# weights:  305
initial  value 109.276368 
iter  10 value 93.841096
iter  20 value 93.822856
iter  30 value 92.520391
iter  40 value 86.033184
iter  50 value 85.990924
iter  60 value 85.538183
iter  70 value 85.185101
final  value 85.184952 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.017193 
iter  10 value 93.798178
iter  20 value 93.793009
iter  30 value 93.179922
iter  40 value 92.717850
iter  50 value 92.717278
final  value 92.716735 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.937430 
iter  10 value 93.793491
iter  20 value 92.467722
iter  30 value 88.034367
iter  40 value 87.131416
iter  50 value 87.128006
final  value 87.127268 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.750020 
iter  10 value 93.844434
iter  20 value 93.409152
iter  30 value 86.891282
iter  40 value 84.477792
iter  50 value 84.368084
final  value 84.367731 
converged
Fitting Repeat 4 

# weights:  507
initial  value 130.912859 
iter  10 value 94.062580
iter  20 value 94.054532
iter  30 value 93.943474
iter  40 value 93.622563
iter  50 value 93.601053
iter  60 value 91.753514
iter  70 value 90.790846
iter  80 value 90.790404
iter  90 value 90.769447
iter 100 value 90.763860
final  value 90.763860 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 98.707981 
iter  10 value 93.173384
iter  20 value 91.900161
iter  30 value 91.854321
iter  40 value 91.850562
iter  50 value 89.288441
iter  60 value 88.112012
iter  70 value 88.092881
iter  80 value 86.456854
iter  90 value 86.016891
final  value 86.016759 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.479924 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.303948 
iter  10 value 86.620380
final  value 85.165665 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.629783 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.210672 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.724907 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.964106 
iter  10 value 92.053460
iter  20 value 91.049853
iter  30 value 91.030150
final  value 91.030067 
converged
Fitting Repeat 2 

# weights:  305
initial  value 112.936814 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.964158 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.669345 
iter  10 value 85.170682
final  value 85.165664 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.221492 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.067786 
final  value 94.484210 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.679722 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.198030 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.768673 
final  value 93.874286 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.289289 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.459435 
iter  10 value 94.514700
iter  20 value 94.236001
iter  30 value 93.406203
iter  40 value 93.380914
iter  50 value 92.545044
iter  60 value 90.381866
iter  70 value 84.529342
iter  80 value 84.478085
iter  90 value 83.314124
iter 100 value 81.790274
final  value 81.790274 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 102.216848 
iter  10 value 94.486848
iter  20 value 92.405343
iter  30 value 86.276847
iter  40 value 85.850509
iter  50 value 84.918371
iter  60 value 82.983466
iter  70 value 82.951681
iter  80 value 82.947962
final  value 82.947702 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.664031 
iter  10 value 94.409887
iter  20 value 92.762057
iter  30 value 90.601105
iter  40 value 85.237496
iter  50 value 83.570550
iter  60 value 83.546009
iter  70 value 83.221140
iter  80 value 82.932686
iter  90 value 82.930884
iter 100 value 82.929740
final  value 82.929740 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.763721 
iter  10 value 94.535347
iter  20 value 94.396203
iter  30 value 86.927234
iter  40 value 83.660095
iter  50 value 83.011437
iter  60 value 82.556326
final  value 82.544054 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.397377 
iter  10 value 94.480224
iter  20 value 84.526457
iter  30 value 84.458803
iter  40 value 83.078748
iter  50 value 82.640564
iter  60 value 82.549605
iter  70 value 82.543731
iter  70 value 82.543731
iter  70 value 82.543731
final  value 82.543731 
converged
Fitting Repeat 1 

# weights:  305
initial  value 132.261189 
iter  10 value 94.399598
iter  20 value 93.565049
iter  30 value 91.750884
iter  40 value 90.600284
iter  50 value 82.535709
iter  60 value 81.602478
iter  70 value 81.125528
iter  80 value 81.036103
iter  90 value 80.951479
iter 100 value 80.904242
final  value 80.904242 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.542234 
iter  10 value 94.497456
iter  20 value 93.569779
iter  30 value 85.512553
iter  40 value 82.018361
iter  50 value 81.479947
iter  60 value 80.457837
iter  70 value 80.180325
iter  80 value 79.661209
iter  90 value 79.379471
iter 100 value 79.307796
final  value 79.307796 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.823328 
iter  10 value 93.951889
iter  20 value 84.597882
iter  30 value 83.053787
iter  40 value 82.586731
iter  50 value 82.532393
iter  60 value 82.301047
iter  70 value 81.840258
iter  80 value 81.519360
iter  90 value 80.745315
iter 100 value 80.357522
final  value 80.357522 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.216777 
iter  10 value 89.334479
iter  20 value 85.541442
iter  30 value 84.880354
iter  40 value 84.330376
iter  50 value 81.883355
iter  60 value 81.568202
iter  70 value 81.043866
iter  80 value 80.584247
iter  90 value 80.389471
iter 100 value 80.152147
final  value 80.152147 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.838560 
iter  10 value 94.797870
iter  20 value 94.393658
iter  30 value 89.853674
iter  40 value 86.319944
iter  50 value 83.908778
iter  60 value 83.124371
iter  70 value 82.897060
iter  80 value 82.440953
iter  90 value 81.821062
iter 100 value 81.296090
final  value 81.296090 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.659837 
iter  10 value 95.201663
iter  20 value 94.181513
iter  30 value 89.018117
iter  40 value 86.259975
iter  50 value 85.898820
iter  60 value 85.318206
iter  70 value 83.233350
iter  80 value 82.702820
iter  90 value 81.173195
iter 100 value 80.317256
final  value 80.317256 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.564254 
iter  10 value 95.472814
iter  20 value 91.432142
iter  30 value 85.780664
iter  40 value 84.450591
iter  50 value 81.553049
iter  60 value 80.684392
iter  70 value 80.558329
iter  80 value 80.487681
iter  90 value 80.304423
iter 100 value 79.731094
final  value 79.731094 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.039699 
iter  10 value 94.625857
iter  20 value 91.041025
iter  30 value 87.681655
iter  40 value 84.154187
iter  50 value 83.296940
iter  60 value 81.353883
iter  70 value 80.499867
iter  80 value 80.104698
iter  90 value 79.484047
iter 100 value 79.395173
final  value 79.395173 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 125.713567 
iter  10 value 94.471116
iter  20 value 91.250380
iter  30 value 89.848838
iter  40 value 85.684599
iter  50 value 83.568968
iter  60 value 83.346128
iter  70 value 82.753228
iter  80 value 81.567729
iter  90 value 81.506750
iter 100 value 81.430450
final  value 81.430450 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.747423 
iter  10 value 94.221749
iter  20 value 93.569476
iter  30 value 89.524086
iter  40 value 82.824973
iter  50 value 81.826336
iter  60 value 80.690421
iter  70 value 80.263531
iter  80 value 79.697344
iter  90 value 79.444884
iter 100 value 79.361181
final  value 79.361181 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 108.779877 
final  value 94.485842 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.986108 
final  value 94.485836 
converged
Fitting Repeat 3 

# weights:  103
initial  value 115.157516 
final  value 94.485639 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.255123 
final  value 94.486104 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.279487 
final  value 94.485781 
converged
Fitting Repeat 1 

# weights:  305
initial  value 114.070430 
iter  10 value 94.489258
iter  20 value 94.460140
iter  30 value 94.208200
iter  40 value 84.646577
iter  50 value 83.851677
final  value 83.820122 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.206711 
iter  10 value 94.471683
iter  20 value 90.700131
final  value 87.161412 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.972596 
iter  10 value 93.879380
iter  20 value 93.277695
iter  30 value 93.260916
iter  40 value 93.240841
final  value 93.077068 
converged
Fitting Repeat 4 

# weights:  305
initial  value 108.830943 
iter  10 value 94.471829
iter  20 value 94.351872
iter  30 value 87.892091
iter  40 value 87.871878
iter  50 value 87.177286
iter  60 value 87.168728
iter  70 value 85.898510
iter  80 value 83.337095
iter  90 value 82.290989
iter 100 value 82.268171
final  value 82.268171 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.612380 
iter  10 value 94.472534
iter  20 value 94.421448
iter  30 value 94.306597
iter  40 value 94.306298
iter  50 value 88.110413
iter  60 value 87.178627
final  value 87.178321 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.234638 
iter  10 value 94.492283
iter  20 value 94.468932
iter  30 value 85.270199
iter  40 value 84.436330
iter  50 value 84.410917
iter  60 value 84.399880
iter  70 value 84.182255
iter  80 value 81.625497
iter  90 value 79.901478
iter 100 value 79.770343
final  value 79.770343 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 96.768447 
iter  10 value 94.489819
iter  20 value 94.480412
iter  30 value 92.657213
iter  40 value 83.508739
iter  50 value 83.050329
iter  60 value 80.702232
iter  70 value 79.065898
iter  80 value 79.001663
iter  90 value 78.745664
iter 100 value 78.395463
final  value 78.395463 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 97.375888 
iter  10 value 94.362245
iter  20 value 94.356622
final  value 94.354485 
converged
Fitting Repeat 4 

# weights:  507
initial  value 108.375675 
iter  10 value 94.357649
iter  20 value 94.204968
iter  30 value 94.194212
iter  40 value 94.191448
iter  50 value 90.857148
iter  60 value 82.628024
iter  70 value 82.415029
iter  80 value 80.920505
iter  90 value 80.423054
iter 100 value 80.406448
final  value 80.406448 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.764316 
iter  10 value 94.475360
iter  20 value 94.467514
iter  30 value 87.894748
iter  40 value 85.526681
iter  50 value 85.525873
iter  60 value 84.771518
iter  70 value 84.394611
iter  80 value 82.491622
iter  90 value 82.479735
iter 100 value 82.423182
final  value 82.423182 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.980653 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.653666 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.280472 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.687659 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.225957 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.383992 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.497740 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.837094 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.073952 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 109.743414 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.980625 
iter  10 value 93.728733
iter  20 value 93.722227
final  value 93.722223 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.313620 
iter  10 value 93.472525
iter  20 value 92.738584
iter  30 value 92.735635
final  value 92.735633 
converged
Fitting Repeat 3 

# weights:  507
initial  value 136.276342 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.351754 
final  value 93.636782 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.068317 
final  value 94.050155 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.279157 
iter  10 value 92.583160
iter  20 value 86.632211
iter  30 value 83.438694
iter  40 value 82.780844
iter  50 value 82.700401
iter  60 value 82.698626
iter  70 value 82.594584
iter  80 value 82.544645
final  value 82.542089 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.233339 
iter  10 value 94.022163
iter  20 value 88.886967
iter  30 value 85.635783
iter  40 value 84.217961
iter  50 value 83.151442
iter  60 value 82.605999
iter  70 value 82.542109
final  value 82.542089 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.069240 
iter  10 value 94.037963
iter  20 value 88.120359
iter  30 value 86.693933
iter  40 value 83.902935
iter  50 value 79.236046
iter  60 value 78.225845
iter  70 value 77.830180
iter  80 value 77.768853
final  value 77.768693 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.037474 
iter  10 value 92.411631
iter  20 value 87.628477
iter  30 value 87.589736
iter  40 value 86.694669
iter  50 value 85.485276
iter  60 value 85.238419
iter  70 value 83.753822
iter  80 value 83.017659
iter  90 value 82.548391
iter 100 value 82.152480
final  value 82.152480 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.039348 
iter  10 value 94.060600
iter  20 value 91.233849
iter  30 value 81.557510
iter  40 value 79.992121
iter  50 value 79.205575
iter  60 value 78.831825
iter  70 value 78.821193
iter  70 value 78.821192
iter  70 value 78.821192
final  value 78.821192 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.641563 
iter  10 value 92.081987
iter  20 value 87.585175
iter  30 value 81.334528
iter  40 value 80.607579
iter  50 value 79.717527
iter  60 value 78.222031
iter  70 value 77.160262
iter  80 value 76.985439
iter  90 value 76.913102
final  value 76.911683 
converged
Fitting Repeat 2 

# weights:  305
initial  value 109.062882 
iter  10 value 93.591008
iter  20 value 83.410179
iter  30 value 82.474645
iter  40 value 80.162499
iter  50 value 77.736411
iter  60 value 76.629267
iter  70 value 75.898825
iter  80 value 75.723971
iter  90 value 75.528543
iter 100 value 75.500623
final  value 75.500623 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.869683 
iter  10 value 94.055069
iter  20 value 92.220174
iter  30 value 83.319561
iter  40 value 81.806289
iter  50 value 81.517743
iter  60 value 81.359997
iter  70 value 81.187239
iter  80 value 80.206135
iter  90 value 78.409185
iter 100 value 76.990492
final  value 76.990492 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 134.927591 
iter  10 value 93.650477
iter  20 value 84.941651
iter  30 value 80.903719
iter  40 value 79.145987
iter  50 value 76.498406
iter  60 value 76.184702
iter  70 value 75.864839
iter  80 value 75.832591
iter  90 value 75.799223
iter 100 value 75.628225
final  value 75.628225 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.039583 
iter  10 value 93.829676
iter  20 value 91.367119
iter  30 value 88.843459
iter  40 value 88.326126
iter  50 value 88.179221
iter  60 value 87.006562
iter  70 value 82.432468
iter  80 value 80.458731
iter  90 value 77.794969
iter 100 value 76.753474
final  value 76.753474 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.459442 
iter  10 value 96.838960
iter  20 value 87.289668
iter  30 value 81.328459
iter  40 value 80.592531
iter  50 value 79.983197
iter  60 value 77.704855
iter  70 value 77.248329
iter  80 value 76.640756
iter  90 value 76.101346
iter 100 value 75.797419
final  value 75.797419 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 118.569721 
iter  10 value 94.051532
iter  20 value 91.769072
iter  30 value 86.609467
iter  40 value 81.449212
iter  50 value 80.436314
iter  60 value 79.995903
iter  70 value 78.849124
iter  80 value 77.538102
iter  90 value 76.882938
iter 100 value 76.610858
final  value 76.610858 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 117.060018 
iter  10 value 95.726529
iter  20 value 89.283456
iter  30 value 84.808662
iter  40 value 82.856102
iter  50 value 80.545712
iter  60 value 78.837349
iter  70 value 77.588187
iter  80 value 77.419837
iter  90 value 77.156864
iter 100 value 77.055246
final  value 77.055246 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.065342 
iter  10 value 94.154293
iter  20 value 86.596731
iter  30 value 84.039630
iter  40 value 78.372350
iter  50 value 77.225587
iter  60 value 76.828076
iter  70 value 76.601360
iter  80 value 76.414823
iter  90 value 76.228593
iter 100 value 76.051673
final  value 76.051673 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 116.246477 
iter  10 value 94.262166
iter  20 value 85.209458
iter  30 value 83.447486
iter  40 value 80.053904
iter  50 value 78.428235
iter  60 value 77.964288
iter  70 value 77.350056
iter  80 value 77.227807
iter  90 value 76.606783
iter 100 value 75.967121
final  value 75.967121 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 109.784540 
final  value 94.054712 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.581323 
iter  10 value 94.054590
iter  20 value 94.040282
iter  30 value 91.394488
iter  40 value 90.780050
iter  50 value 90.721269
iter  60 value 90.008690
iter  70 value 89.941657
iter  80 value 89.941343
iter  90 value 83.392001
iter 100 value 82.477495
final  value 82.477495 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 95.565407 
final  value 93.723945 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.688661 
final  value 94.054633 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.213865 
final  value 94.054612 
converged
Fitting Repeat 1 

# weights:  305
initial  value 115.871711 
iter  10 value 94.013997
iter  20 value 94.010681
iter  30 value 90.218984
iter  40 value 89.759787
iter  50 value 89.759378
iter  60 value 87.082363
iter  70 value 78.733630
iter  80 value 78.461559
iter  90 value 77.642256
iter 100 value 77.641407
final  value 77.641407 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 98.884417 
iter  10 value 92.962197
iter  20 value 92.936876
iter  30 value 92.931604
iter  40 value 92.928139
iter  40 value 92.928138
iter  40 value 92.928138
final  value 92.928138 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.960476 
iter  10 value 94.019427
iter  20 value 94.014138
final  value 94.013896 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.250494 
iter  10 value 94.057754
iter  20 value 94.052859
iter  30 value 93.372641
iter  30 value 93.372641
iter  30 value 93.372641
final  value 93.372641 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.664853 
iter  10 value 94.056231
iter  20 value 92.602117
iter  30 value 85.631925
iter  40 value 84.336276
iter  50 value 83.866857
iter  60 value 83.863044
iter  70 value 83.856820
iter  80 value 83.855827
final  value 83.855553 
converged
Fitting Repeat 1 

# weights:  507
initial  value 112.096348 
iter  10 value 94.017372
iter  20 value 94.009422
final  value 94.009092 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.923441 
iter  10 value 91.432244
iter  20 value 90.426988
iter  30 value 90.423719
iter  40 value 90.418094
iter  50 value 90.416424
final  value 90.416416 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.519782 
iter  10 value 94.059383
iter  20 value 90.534265
iter  30 value 86.999779
iter  40 value 86.998047
iter  50 value 86.013910
iter  60 value 85.489748
iter  70 value 85.488438
iter  80 value 85.487184
final  value 85.487181 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.816020 
iter  10 value 93.705761
iter  20 value 93.662425
iter  30 value 93.638286
iter  40 value 93.618463
final  value 93.612148 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.302579 
iter  10 value 94.060721
iter  20 value 93.461850
iter  30 value 83.949502
iter  40 value 83.447905
iter  50 value 83.423060
iter  60 value 83.394869
iter  70 value 83.394399
iter  80 value 83.393596
final  value 83.392439 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.969114 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.081738 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 114.040767 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.445752 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.796149 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.067292 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.859217 
final  value 94.443243 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.762864 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.383995 
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.441242 
iter  10 value 88.906319
iter  20 value 86.907111
iter  30 value 86.712400
iter  40 value 86.710673
final  value 86.710659 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.700931 
final  value 94.484210 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.585687 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 119.451931 
final  value 93.822880 
converged
Fitting Repeat 4 

# weights:  507
initial  value 133.298281 
iter  10 value 93.385614
final  value 93.383632 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.375703 
final  value 94.275362 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.850816 
iter  10 value 94.033741
iter  20 value 91.944698
iter  30 value 90.303136
iter  40 value 88.194971
iter  50 value 85.945738
iter  60 value 85.249450
iter  70 value 83.025595
iter  80 value 82.475796
iter  90 value 82.357796
iter 100 value 82.351472
final  value 82.351472 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 103.865784 
iter  10 value 94.298607
iter  20 value 93.717074
iter  30 value 93.708308
iter  40 value 90.696502
iter  50 value 85.303561
iter  60 value 85.163192
iter  70 value 84.833720
iter  80 value 83.707620
iter  90 value 83.643631
final  value 83.643610 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.544498 
iter  10 value 94.257837
iter  20 value 93.380711
iter  30 value 93.287914
iter  40 value 93.254523
iter  50 value 87.162144
iter  60 value 86.861938
iter  70 value 86.611417
iter  80 value 86.422863
iter  90 value 86.390506
final  value 86.390074 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.463806 
iter  10 value 94.488977
iter  20 value 88.287248
iter  30 value 85.208181
iter  40 value 85.084911
iter  50 value 84.734085
iter  60 value 83.734857
iter  70 value 83.645552
iter  80 value 83.643611
final  value 83.643610 
converged
Fitting Repeat 5 

# weights:  103
initial  value 114.811396 
iter  10 value 94.414422
iter  20 value 93.636540
iter  30 value 93.630466
iter  40 value 86.859239
iter  50 value 84.107959
iter  60 value 83.420561
iter  70 value 82.865931
iter  80 value 82.478231
iter  90 value 82.417342
iter 100 value 82.369488
final  value 82.369488 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 105.952140 
iter  10 value 94.881375
iter  20 value 93.234952
iter  30 value 92.248120
iter  40 value 86.955416
iter  50 value 84.502455
iter  60 value 83.845680
iter  70 value 83.248619
iter  80 value 82.853287
iter  90 value 81.706280
iter 100 value 81.363528
final  value 81.363528 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 149.526763 
iter  10 value 94.780357
iter  20 value 90.485103
iter  30 value 87.835763
iter  40 value 85.265349
iter  50 value 83.360569
iter  60 value 82.180223
iter  70 value 81.739634
iter  80 value 81.277963
iter  90 value 81.106208
iter 100 value 80.985518
final  value 80.985518 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 117.779480 
iter  10 value 100.443490
iter  20 value 94.076838
iter  30 value 93.746468
iter  40 value 93.685976
iter  50 value 89.041458
iter  60 value 87.153965
iter  70 value 86.154840
iter  80 value 85.543713
iter  90 value 81.956561
iter 100 value 81.739307
final  value 81.739307 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.172236 
iter  10 value 94.223178
iter  20 value 93.628745
iter  30 value 86.687015
iter  40 value 84.381881
iter  50 value 83.987232
iter  60 value 82.834087
iter  70 value 82.008131
iter  80 value 81.830928
iter  90 value 81.624555
iter 100 value 81.494835
final  value 81.494835 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.723176 
iter  10 value 94.391790
iter  20 value 92.032849
iter  30 value 91.700823
iter  40 value 91.514543
iter  50 value 87.159971
iter  60 value 85.792847
iter  70 value 84.454556
iter  80 value 84.042387
iter  90 value 83.520663
iter 100 value 82.253386
final  value 82.253386 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 114.597224 
iter  10 value 91.980641
iter  20 value 84.282472
iter  30 value 83.815400
iter  40 value 83.588354
iter  50 value 82.774794
iter  60 value 81.791636
iter  70 value 81.602271
iter  80 value 81.573862
iter  90 value 81.541021
iter 100 value 81.456647
final  value 81.456647 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 110.947259 
iter  10 value 90.526633
iter  20 value 87.959882
iter  30 value 85.512831
iter  40 value 85.277815
iter  50 value 85.208142
iter  60 value 84.803630
iter  70 value 83.748585
iter  80 value 83.369300
iter  90 value 82.914433
iter 100 value 82.612610
final  value 82.612610 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.650445 
iter  10 value 94.806638
iter  20 value 93.805739
iter  30 value 93.553914
iter  40 value 90.775610
iter  50 value 89.510264
iter  60 value 86.819222
iter  70 value 82.360044
iter  80 value 81.698778
iter  90 value 81.425831
iter 100 value 81.246599
final  value 81.246599 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.298672 
iter  10 value 94.459790
iter  20 value 93.681147
iter  30 value 93.202202
iter  40 value 86.090555
iter  50 value 85.596665
iter  60 value 83.971506
iter  70 value 81.773121
iter  80 value 81.444452
iter  90 value 81.311036
iter 100 value 81.232229
final  value 81.232229 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.685649 
iter  10 value 94.182783
iter  20 value 91.691958
iter  30 value 88.409060
iter  40 value 85.670259
iter  50 value 84.119788
iter  60 value 83.403374
iter  70 value 81.840806
iter  80 value 81.362045
iter  90 value 81.100196
iter 100 value 81.024441
final  value 81.024441 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.659062 
final  value 94.146114 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.381985 
final  value 94.486063 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.792828 
final  value 94.485807 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.013748 
final  value 94.485896 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.870290 
iter  10 value 94.277113
iter  20 value 94.275927
iter  30 value 92.548418
iter  40 value 84.919575
iter  50 value 84.005597
iter  60 value 83.890011
iter  70 value 83.804022
final  value 83.803152 
converged
Fitting Repeat 1 

# weights:  305
initial  value 117.917470 
iter  10 value 94.489155
iter  20 value 94.484457
iter  30 value 93.913026
final  value 93.912021 
converged
Fitting Repeat 2 

# weights:  305
initial  value 117.985484 
iter  10 value 94.186707
iter  20 value 93.818701
iter  30 value 93.501887
iter  40 value 93.493634
iter  50 value 93.491552
final  value 93.489907 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.638100 
iter  10 value 94.272190
iter  20 value 94.178800
iter  30 value 93.912320
iter  40 value 93.907838
iter  50 value 93.548105
iter  60 value 93.517663
iter  70 value 93.359585
iter  80 value 85.912330
iter  90 value 85.679651
iter 100 value 85.527882
final  value 85.527882 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 94.058070 
iter  10 value 93.551537
iter  20 value 93.524929
iter  30 value 93.522450
iter  40 value 93.521212
iter  50 value 93.520891
final  value 93.520543 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.467553 
iter  10 value 94.300262
iter  20 value 94.279304
final  value 94.275508 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.017779 
iter  10 value 91.394944
iter  20 value 86.815957
iter  30 value 86.763710
iter  40 value 86.756643
final  value 86.755239 
converged
Fitting Repeat 2 

# weights:  507
initial  value 110.770789 
iter  10 value 94.492288
iter  20 value 94.394907
iter  30 value 88.240364
iter  40 value 84.767477
final  value 84.631952 
converged
Fitting Repeat 3 

# weights:  507
initial  value 110.691978 
iter  10 value 93.915878
iter  20 value 93.908783
iter  30 value 93.697415
iter  40 value 88.883939
iter  50 value 86.703677
iter  60 value 86.435852
iter  70 value 86.019882
iter  80 value 86.019738
final  value 86.019735 
converged
Fitting Repeat 4 

# weights:  507
initial  value 110.234917 
iter  10 value 89.490964
iter  20 value 88.234533
iter  30 value 88.213140
iter  40 value 88.211345
iter  50 value 87.699141
iter  60 value 86.630122
iter  70 value 86.493564
iter  80 value 86.484234
iter  80 value 86.484234
final  value 86.484234 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.051668 
iter  10 value 94.283401
iter  20 value 92.001428
iter  30 value 85.530535
iter  40 value 83.818723
iter  50 value 83.549791
iter  60 value 83.338265
iter  70 value 82.271290
iter  80 value 81.551210
iter  90 value 81.458757
iter 100 value 81.426836
final  value 81.426836 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 130.430710 
iter  10 value 117.767005
iter  20 value 117.759628
iter  30 value 113.651017
iter  40 value 107.699225
iter  50 value 106.963580
final  value 106.963570 
converged
Fitting Repeat 2 

# weights:  507
initial  value 130.256888 
iter  10 value 117.130877
iter  20 value 111.081180
iter  30 value 111.049177
iter  40 value 109.230304
iter  50 value 107.720695
iter  60 value 103.062848
iter  70 value 101.001170
iter  80 value 99.704874
iter  90 value 99.604210
iter 100 value 99.561127
final  value 99.561127 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 124.364517 
iter  10 value 117.898571
iter  20 value 117.890374
iter  30 value 110.499949
iter  40 value 107.926608
iter  50 value 107.066440
iter  60 value 105.363050
iter  70 value 105.105055
iter  80 value 104.854467
iter  90 value 104.823433
iter 100 value 104.821739
final  value 104.821739 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 120.943610 
iter  10 value 117.766716
iter  20 value 113.875677
iter  30 value 104.641807
iter  40 value 104.410897
iter  50 value 104.068740
iter  60 value 104.058343
iter  70 value 104.057908
final  value 104.057811 
converged
Fitting Repeat 5 

# weights:  507
initial  value 154.089981 
iter  10 value 117.898480
iter  20 value 117.848811
iter  30 value 108.581941
final  value 107.003786 
converged
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Fri Dec 20 01:20:48 2024 
*********************************************** 
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 
Warning messages:
1: `repeats` has no meaning for this resampling method. 
2: executing %dopar% sequentially: no parallel backend registered 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
 37.225   1.428  44.890