##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:HPiP.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings HPiP_1.11.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck’
* using R version 4.4.1 RC (2024-06-06 r86719)
* using platform: x86_64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 12.2.0
* running under: macOS Monterey 12.7.1
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.11.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
var_imp       35.841  1.747  37.881
FSmethod      34.250  1.622  36.137
corr_plot     34.048  1.635  35.913
pred_ensembel 14.289  0.562  10.762
enrichfindP    0.491  0.063   8.991
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 3 NOTEs
See
  ‘/Users/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck/00check.log’
for details.

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


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library’
* installing *source* package ‘HPiP’ ...
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R version 4.4.1 RC (2024-06-06 r86719) -- "Race for Your Life"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20

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

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

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

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

# weights:  103
initial  value 98.253828 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.515798 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.318304 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.878601 
final  value 94.008696 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.184600 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.543733 
iter  10 value 93.535112
iter  10 value 93.535112
iter  10 value 93.535112
final  value 93.535112 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.237949 
iter  10 value 89.949827
iter  20 value 82.566988
iter  30 value 81.149997
iter  40 value 79.662072
iter  50 value 79.479503
final  value 79.478665 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.323180 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.798794 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.082543 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 127.454482 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 129.681915 
final  value 94.008696 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.869373 
final  value 94.008696 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.130468 
final  value 94.008696 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.839759 
final  value 93.810010 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.997838 
iter  10 value 93.722573
iter  20 value 93.468619
iter  30 value 85.639081
iter  40 value 84.559355
iter  50 value 83.749040
iter  60 value 83.245646
iter  70 value 82.749394
iter  80 value 81.281999
iter  90 value 81.094456
final  value 81.093711 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.049476 
iter  10 value 94.106833
iter  20 value 94.056666
iter  30 value 93.181090
iter  40 value 84.721601
iter  50 value 83.981249
iter  60 value 83.844286
iter  70 value 83.377277
iter  80 value 83.311565
iter  90 value 83.306637
final  value 83.306615 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.601308 
iter  10 value 93.889706
iter  20 value 89.899464
iter  30 value 87.085079
iter  40 value 85.499468
iter  50 value 84.858568
iter  60 value 84.670388
final  value 84.670059 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.468342 
iter  10 value 94.055392
iter  20 value 93.871988
iter  30 value 93.584780
iter  40 value 93.220290
iter  50 value 88.478524
iter  60 value 83.455204
iter  70 value 82.610470
iter  80 value 81.836711
iter  90 value 81.705512
iter 100 value 81.654461
final  value 81.654461 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.122106 
iter  10 value 94.056656
iter  20 value 93.836065
iter  30 value 88.250323
iter  40 value 85.242474
iter  50 value 83.536824
iter  60 value 83.319008
iter  70 value 83.309426
iter  70 value 83.309425
iter  70 value 83.309425
final  value 83.309425 
converged
Fitting Repeat 1 

# weights:  305
initial  value 119.145452 
iter  10 value 94.811476
iter  20 value 94.004951
iter  30 value 89.644903
iter  40 value 89.221429
iter  50 value 88.023312
iter  60 value 87.248134
iter  70 value 85.018760
iter  80 value 83.601054
iter  90 value 82.858767
iter 100 value 82.312056
final  value 82.312056 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.299053 
iter  10 value 93.917526
iter  20 value 93.053718
iter  30 value 88.380381
iter  40 value 87.712078
iter  50 value 86.251153
iter  60 value 82.967295
iter  70 value 81.816152
iter  80 value 80.817071
iter  90 value 80.602161
iter 100 value 80.264987
final  value 80.264987 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.304595 
iter  10 value 89.329888
iter  20 value 83.687376
iter  30 value 81.794590
iter  40 value 80.808378
iter  50 value 80.411091
iter  60 value 79.984603
iter  70 value 79.931345
iter  80 value 79.884655
iter  90 value 79.865641
iter 100 value 79.850994
final  value 79.850994 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.558828 
iter  10 value 93.942400
iter  20 value 91.619378
iter  30 value 88.194028
iter  40 value 83.141382
iter  50 value 81.495949
iter  60 value 81.218550
iter  70 value 81.042535
iter  80 value 80.700260
iter  90 value 80.240950
iter 100 value 80.217534
final  value 80.217534 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.103681 
iter  10 value 94.062941
iter  20 value 93.363584
iter  30 value 85.375432
iter  40 value 84.081337
iter  50 value 83.344293
iter  60 value 83.300525
iter  70 value 83.133345
iter  80 value 83.029006
iter  90 value 82.170103
iter 100 value 81.891119
final  value 81.891119 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.599981 
iter  10 value 94.411449
iter  20 value 94.084043
iter  30 value 93.603333
iter  40 value 93.471848
iter  50 value 89.403475
iter  60 value 87.988184
iter  70 value 84.899111
iter  80 value 81.590147
iter  90 value 81.154706
iter 100 value 80.715453
final  value 80.715453 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.865546 
iter  10 value 94.197913
iter  20 value 93.912305
iter  30 value 91.582132
iter  40 value 88.329237
iter  50 value 82.812720
iter  60 value 82.565840
iter  70 value 82.460350
iter  80 value 81.634878
iter  90 value 80.844460
iter 100 value 80.128790
final  value 80.128790 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.631775 
iter  10 value 94.075080
iter  20 value 93.045358
iter  30 value 88.271307
iter  40 value 87.253358
iter  50 value 84.500543
iter  60 value 82.619879
iter  70 value 82.173717
iter  80 value 81.082663
iter  90 value 80.882729
iter 100 value 80.740415
final  value 80.740415 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.465718 
iter  10 value 94.202861
iter  20 value 93.582564
iter  30 value 89.648044
iter  40 value 84.677767
iter  50 value 83.814315
iter  60 value 83.669865
iter  70 value 82.297531
iter  80 value 80.580964
iter  90 value 80.155305
iter 100 value 79.619200
final  value 79.619200 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 118.606507 
iter  10 value 94.423813
iter  20 value 93.541727
iter  30 value 86.607992
iter  40 value 82.539438
iter  50 value 81.942106
iter  60 value 81.174354
iter  70 value 80.928893
iter  80 value 80.771933
iter  90 value 80.548915
iter 100 value 80.424985
final  value 80.424985 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.707123 
final  value 94.054509 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.935854 
final  value 94.010420 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.638871 
final  value 94.054802 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.625819 
final  value 94.054801 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.967572 
iter  10 value 94.054681
iter  20 value 94.038320
iter  30 value 85.666455
iter  40 value 85.654284
iter  50 value 85.611902
iter  60 value 85.610389
iter  70 value 84.531336
iter  80 value 84.496395
final  value 84.494975 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.371788 
iter  10 value 94.058385
iter  20 value 94.052977
iter  30 value 92.558752
iter  40 value 91.434520
iter  50 value 91.430874
final  value 91.430499 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.020142 
iter  10 value 94.057375
iter  20 value 94.041758
iter  30 value 87.253693
iter  40 value 85.216680
iter  50 value 85.134355
final  value 85.134147 
converged
Fitting Repeat 3 

# weights:  305
initial  value 119.227846 
iter  10 value 94.057648
iter  20 value 93.697099
iter  30 value 93.535585
iter  40 value 93.535410
iter  40 value 93.535410
iter  40 value 93.535410
final  value 93.535410 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.518044 
iter  10 value 94.062166
iter  20 value 94.056407
final  value 94.056405 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.303251 
iter  10 value 94.013988
iter  20 value 94.010257
iter  30 value 94.008799
iter  40 value 93.543323
iter  50 value 91.554079
iter  60 value 84.550071
iter  70 value 84.457122
iter  80 value 84.433456
iter  90 value 84.423387
iter 100 value 83.183739
final  value 83.183739 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 94.715645 
iter  10 value 94.061245
iter  20 value 92.811563
iter  30 value 87.461031
iter  40 value 86.969981
iter  50 value 85.660481
iter  60 value 85.607857
iter  70 value 85.606245
iter  80 value 85.605515
iter  90 value 85.304304
iter 100 value 85.246450
final  value 85.246450 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.682139 
iter  10 value 94.061207
iter  20 value 94.051609
iter  30 value 93.720080
iter  40 value 93.517235
iter  50 value 93.474785
iter  60 value 84.342253
iter  70 value 83.407718
iter  80 value 83.404367
final  value 83.402593 
converged
Fitting Repeat 3 

# weights:  507
initial  value 125.407260 
iter  10 value 93.789459
iter  20 value 93.712974
iter  30 value 93.706165
iter  40 value 93.676003
iter  50 value 93.670326
iter  60 value 93.667019
iter  70 value 93.398869
iter  80 value 93.345709
iter  90 value 93.333441
iter 100 value 93.333356
final  value 93.333356 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 101.182498 
iter  10 value 94.061332
iter  20 value 94.012891
iter  30 value 94.009112
iter  40 value 86.140554
iter  50 value 84.341063
iter  60 value 81.368146
iter  70 value 80.483641
iter  80 value 80.143831
iter  90 value 78.104399
iter 100 value 78.021306
final  value 78.021306 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 130.146038 
iter  10 value 93.891146
iter  20 value 93.650048
iter  30 value 93.645874
iter  40 value 93.643953
iter  50 value 93.517243
iter  60 value 93.386211
iter  70 value 93.356797
iter  80 value 93.333535
iter  90 value 88.794069
iter 100 value 87.342506
final  value 87.342506 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 113.826874 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.856850 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.244482 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.204332 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.575399 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.684665 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.337845 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.471420 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.199408 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.252819 
iter  10 value 91.249848
iter  20 value 86.505346
iter  30 value 84.482951
iter  40 value 84.158680
iter  50 value 83.763069
iter  60 value 83.756131
iter  70 value 80.670042
iter  80 value 79.908775
final  value 79.908640 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.593808 
iter  10 value 91.499783
iter  20 value 82.760924
iter  30 value 82.464794
iter  40 value 82.464693
final  value 82.464672 
converged
Fitting Repeat 2 

# weights:  507
initial  value 111.208278 
iter  10 value 93.582319
iter  20 value 92.820218
iter  30 value 92.818769
final  value 92.818726 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.586143 
iter  10 value 92.568223
iter  20 value 88.430972
iter  30 value 88.382380
iter  40 value 88.378829
iter  50 value 88.373477
iter  50 value 88.373477
iter  50 value 88.373477
final  value 88.373477 
converged
Fitting Repeat 4 

# weights:  507
initial  value 118.376546 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 114.422931 
iter  10 value 93.628453
iter  10 value 93.628453
iter  10 value 93.628453
final  value 93.628453 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.957534 
iter  10 value 93.844989
iter  20 value 85.957439
iter  30 value 84.995938
iter  40 value 82.584277
iter  50 value 82.455660
iter  60 value 82.213177
iter  70 value 81.664489
iter  80 value 80.726348
iter  90 value 80.462735
iter 100 value 80.070459
final  value 80.070459 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 98.807975 
iter  10 value 94.055041
final  value 94.054860 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.875548 
iter  10 value 94.008426
iter  20 value 93.112520
iter  30 value 91.904818
iter  40 value 85.117907
iter  50 value 84.156863
iter  60 value 81.849734
iter  70 value 80.706310
iter  80 value 80.423303
iter  90 value 80.015262
iter 100 value 79.997842
final  value 79.997842 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 101.820921 
iter  10 value 93.490324
iter  20 value 85.157024
iter  30 value 84.359263
iter  40 value 83.806931
iter  50 value 83.421984
iter  60 value 83.356044
final  value 83.355983 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.999768 
iter  10 value 94.008177
iter  20 value 84.558418
iter  30 value 83.050872
iter  40 value 82.743762
iter  50 value 82.227694
iter  60 value 81.843260
iter  70 value 81.757378
iter  80 value 81.727522
iter  90 value 81.702255
final  value 81.696989 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.812487 
iter  10 value 91.380748
iter  20 value 88.423540
iter  30 value 82.149876
iter  40 value 80.610799
iter  50 value 79.577346
iter  60 value 79.124447
iter  70 value 78.922516
iter  80 value 78.737340
iter  90 value 78.624910
iter 100 value 78.557123
final  value 78.557123 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 124.813891 
iter  10 value 94.899325
iter  20 value 89.499762
iter  30 value 86.326916
iter  40 value 85.869876
iter  50 value 82.784813
iter  60 value 81.325909
iter  70 value 81.058480
iter  80 value 81.021890
iter  90 value 80.428140
iter 100 value 79.544326
final  value 79.544326 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.575747 
iter  10 value 93.769155
iter  20 value 88.389126
iter  30 value 82.816857
iter  40 value 81.909579
iter  50 value 80.654909
iter  60 value 80.040749
iter  70 value 79.843626
iter  80 value 79.499279
iter  90 value 79.345799
iter 100 value 79.203167
final  value 79.203167 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.208854 
iter  10 value 93.625562
iter  20 value 87.291091
iter  30 value 84.934160
iter  40 value 82.448320
iter  50 value 81.990464
iter  60 value 80.936066
iter  70 value 79.643281
iter  80 value 79.084225
iter  90 value 79.019863
iter 100 value 78.903709
final  value 78.903709 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.776721 
iter  10 value 93.903046
iter  20 value 86.395512
iter  30 value 84.938029
iter  40 value 84.250153
iter  50 value 83.857264
iter  60 value 81.856435
iter  70 value 81.017476
iter  80 value 80.931284
iter  90 value 80.766151
iter 100 value 79.672044
final  value 79.672044 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 111.684592 
iter  10 value 92.560054
iter  20 value 88.808515
iter  30 value 84.652031
iter  40 value 82.545181
iter  50 value 80.925559
iter  60 value 80.336724
iter  70 value 79.507126
iter  80 value 79.294754
iter  90 value 79.087484
iter 100 value 78.961362
final  value 78.961362 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.988467 
iter  10 value 94.702283
iter  20 value 93.496240
iter  30 value 85.220392
iter  40 value 84.395523
iter  50 value 83.929217
iter  60 value 83.461005
iter  70 value 80.382338
iter  80 value 79.368072
iter  90 value 79.090445
iter 100 value 79.047079
final  value 79.047079 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 152.823025 
iter  10 value 98.101196
iter  20 value 90.515309
iter  30 value 86.917183
iter  40 value 85.780923
iter  50 value 81.893846
iter  60 value 79.858783
iter  70 value 79.564141
iter  80 value 79.439610
iter  90 value 78.960106
iter 100 value 78.629971
final  value 78.629971 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.713187 
iter  10 value 93.117876
iter  20 value 92.921127
iter  30 value 92.240487
iter  40 value 89.798304
iter  50 value 88.120211
iter  60 value 86.330071
iter  70 value 82.258195
iter  80 value 80.483181
iter  90 value 80.258128
iter 100 value 79.945881
final  value 79.945881 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.237882 
iter  10 value 93.951148
iter  20 value 89.757119
iter  30 value 85.136438
iter  40 value 81.051120
iter  50 value 80.993616
iter  60 value 80.481427
iter  70 value 80.140712
iter  80 value 79.508005
iter  90 value 79.290842
iter 100 value 79.204843
final  value 79.204843 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.882803 
final  value 94.054682 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.125969 
final  value 94.054529 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.898967 
final  value 93.584158 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.361477 
iter  10 value 93.584138
final  value 93.584133 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.291305 
final  value 94.054581 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.219836 
iter  10 value 94.057926
iter  20 value 93.604365
iter  30 value 92.917181
iter  40 value 89.106557
iter  50 value 81.698669
iter  60 value 81.601013
iter  70 value 81.199922
iter  80 value 80.430984
iter  90 value 80.123186
iter 100 value 79.962452
final  value 79.962452 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 97.433419 
iter  10 value 93.587581
iter  20 value 93.584866
iter  30 value 92.893876
iter  40 value 92.862213
final  value 92.862126 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.106536 
iter  10 value 94.057250
iter  20 value 93.934668
final  value 92.862615 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.127786 
iter  10 value 93.466819
iter  20 value 93.453424
iter  30 value 92.879036
iter  40 value 92.823273
iter  50 value 92.820728
iter  60 value 90.464739
iter  70 value 86.575138
iter  80 value 82.233735
iter  90 value 80.613751
iter 100 value 80.376838
final  value 80.376838 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.606729 
iter  10 value 93.293625
iter  20 value 93.289299
iter  30 value 90.430426
iter  40 value 85.487341
iter  50 value 85.482843
iter  60 value 85.443392
iter  70 value 85.434084
iter  80 value 85.433567
final  value 85.433195 
converged
Fitting Repeat 1 

# weights:  507
initial  value 111.664016 
iter  10 value 93.995926
iter  20 value 93.789895
final  value 93.583608 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.023987 
iter  10 value 94.061186
iter  20 value 94.049409
iter  30 value 94.039582
iter  40 value 91.722906
iter  50 value 87.738608
iter  60 value 85.770775
iter  70 value 84.352514
iter  80 value 82.183814
iter  90 value 82.066246
iter 100 value 82.065049
final  value 82.065049 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.533767 
iter  10 value 94.061206
iter  20 value 94.052162
iter  30 value 92.863631
iter  30 value 92.863630
iter  30 value 92.863630
final  value 92.863630 
converged
Fitting Repeat 4 

# weights:  507
initial  value 116.423464 
iter  10 value 93.590991
iter  20 value 93.583247
final  value 93.582805 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.415262 
iter  10 value 90.078570
iter  20 value 89.055999
iter  30 value 89.050847
iter  40 value 89.016506
iter  50 value 85.551916
iter  60 value 84.623437
iter  70 value 84.613394
iter  80 value 84.612779
iter  90 value 83.942973
iter 100 value 81.862437
final  value 81.862437 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.012363 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.946135 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.715740 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.654782 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.294596 
final  value 94.428839 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.183444 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 118.903794 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.707790 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 109.669473 
iter  10 value 92.379303
final  value 88.350679 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.715984 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 110.843570 
iter  10 value 94.441295
iter  10 value 94.441294
iter  10 value 94.441294
final  value 94.441294 
converged
Fitting Repeat 2 

# weights:  507
initial  value 125.691806 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.910391 
iter  10 value 94.442772
iter  20 value 94.442074
iter  20 value 94.442073
iter  20 value 94.442073
final  value 94.442073 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.203982 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.750809 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.112408 
iter  10 value 94.543098
iter  20 value 94.272231
iter  30 value 90.073274
iter  40 value 87.188587
iter  50 value 85.251428
iter  60 value 85.044446
iter  70 value 84.999309
iter  80 value 83.728699
iter  90 value 83.189205
iter 100 value 83.047419
final  value 83.047419 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 98.328167 
iter  10 value 94.488289
iter  20 value 94.475345
iter  30 value 94.274677
iter  40 value 94.235305
iter  50 value 90.560152
iter  60 value 88.529144
iter  70 value 88.087350
iter  80 value 87.757083
iter  90 value 87.711422
iter 100 value 87.639399
final  value 87.639399 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.607417 
iter  10 value 94.480020
iter  20 value 93.694585
iter  30 value 89.423769
iter  40 value 88.037374
iter  50 value 86.921843
iter  60 value 86.781052
iter  70 value 86.589626
iter  80 value 86.403558
iter  90 value 86.207653
final  value 86.204867 
converged
Fitting Repeat 4 

# weights:  103
initial  value 109.490823 
iter  10 value 94.482411
iter  20 value 93.751316
iter  30 value 88.477137
iter  40 value 87.996939
iter  50 value 86.357957
iter  60 value 85.422780
iter  70 value 85.012762
iter  80 value 84.998050
final  value 84.998048 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.750686 
iter  10 value 94.474160
iter  20 value 93.199676
iter  30 value 91.056885
iter  40 value 87.961809
iter  50 value 85.714260
iter  60 value 84.016431
iter  70 value 83.591849
iter  80 value 83.543707
final  value 83.542191 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.460456 
iter  10 value 92.539190
iter  20 value 92.234719
iter  30 value 92.205040
iter  40 value 89.917545
iter  50 value 87.806779
iter  60 value 86.569266
iter  70 value 84.568367
iter  80 value 84.043799
iter  90 value 83.802903
iter 100 value 83.760348
final  value 83.760348 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.231814 
iter  10 value 94.491174
iter  20 value 94.318735
iter  30 value 92.724226
iter  40 value 92.179834
iter  50 value 92.049825
iter  60 value 87.342515
iter  70 value 85.915988
iter  80 value 84.938144
iter  90 value 84.111565
iter 100 value 83.643067
final  value 83.643067 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 117.297391 
iter  10 value 95.372049
iter  20 value 88.648140
iter  30 value 86.544253
iter  40 value 84.736078
iter  50 value 83.974509
iter  60 value 83.831743
iter  70 value 83.721738
iter  80 value 83.598275
iter  90 value 83.051174
iter 100 value 82.954245
final  value 82.954245 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.783117 
iter  10 value 94.581469
iter  20 value 94.377506
iter  30 value 88.209172
iter  40 value 87.605213
iter  50 value 86.504164
iter  60 value 85.762650
iter  70 value 84.126589
iter  80 value 82.566427
iter  90 value 81.932637
iter 100 value 81.789286
final  value 81.789286 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.989108 
iter  10 value 94.501271
iter  20 value 93.909908
iter  30 value 93.265096
iter  40 value 87.863198
iter  50 value 86.190129
iter  60 value 85.103636
iter  70 value 84.821735
iter  80 value 84.751719
iter  90 value 84.053727
iter 100 value 83.820233
final  value 83.820233 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 121.992606 
iter  10 value 91.187794
iter  20 value 86.872880
iter  30 value 86.416423
iter  40 value 85.954674
iter  50 value 83.532328
iter  60 value 83.236532
iter  70 value 83.036489
iter  80 value 82.957598
iter  90 value 82.766635
iter 100 value 82.436331
final  value 82.436331 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.841368 
iter  10 value 95.054346
iter  20 value 91.594967
iter  30 value 90.279334
iter  40 value 90.149424
iter  50 value 88.959446
iter  60 value 88.111009
iter  70 value 87.227056
iter  80 value 85.537087
iter  90 value 83.972478
iter 100 value 83.425356
final  value 83.425356 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.952166 
iter  10 value 93.106923
iter  20 value 89.536624
iter  30 value 87.475554
iter  40 value 83.030651
iter  50 value 81.508389
iter  60 value 81.285386
iter  70 value 81.250156
iter  80 value 81.226325
iter  90 value 81.203122
iter 100 value 81.200861
final  value 81.200861 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.029285 
iter  10 value 94.445918
iter  20 value 93.851640
iter  30 value 91.185419
iter  40 value 86.859746
iter  50 value 84.625014
iter  60 value 83.217701
iter  70 value 82.597382
iter  80 value 82.274646
iter  90 value 82.050593
iter 100 value 81.712362
final  value 81.712362 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.417564 
iter  10 value 94.603078
iter  20 value 91.561455
iter  30 value 89.388422
iter  40 value 86.262524
iter  50 value 84.892636
iter  60 value 82.571994
iter  70 value 82.000820
iter  80 value 81.838196
iter  90 value 81.573825
iter 100 value 81.323990
final  value 81.323990 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.414210 
final  value 94.485837 
converged
Fitting Repeat 2 

# weights:  103
initial  value 111.734695 
final  value 94.486052 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.011710 
final  value 94.486049 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.970981 
final  value 94.485994 
converged
Fitting Repeat 5 

# weights:  103
initial  value 115.629969 
final  value 94.486181 
converged
Fitting Repeat 1 

# weights:  305
initial  value 111.844278 
iter  10 value 94.471808
iter  20 value 94.467604
iter  30 value 88.660523
iter  40 value 87.924673
iter  50 value 87.923247
iter  60 value 87.772528
iter  70 value 87.700668
iter  80 value 85.956572
iter  90 value 85.649602
iter 100 value 85.648831
final  value 85.648831 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 97.380673 
iter  10 value 94.472040
iter  20 value 94.466975
iter  30 value 94.466950
final  value 94.466944 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.291293 
iter  10 value 94.488502
iter  20 value 94.463658
iter  30 value 86.780052
iter  40 value 86.477657
iter  50 value 86.472136
iter  60 value 86.472057
final  value 86.472010 
converged
Fitting Repeat 4 

# weights:  305
initial  value 111.662714 
iter  10 value 94.490835
iter  20 value 94.427644
iter  30 value 92.258656
iter  40 value 88.545643
iter  50 value 88.542898
iter  60 value 87.348690
iter  70 value 85.580201
iter  80 value 85.573915
iter  90 value 85.407637
iter 100 value 84.533636
final  value 84.533636 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.507777 
iter  10 value 88.557211
iter  20 value 86.645938
iter  30 value 86.641728
iter  40 value 86.639324
iter  50 value 85.164204
iter  60 value 84.972711
iter  70 value 84.619209
iter  80 value 84.558497
final  value 84.558037 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.336210 
iter  10 value 94.474854
iter  20 value 94.467874
final  value 94.467004 
converged
Fitting Repeat 2 

# weights:  507
initial  value 111.290706 
iter  10 value 93.440147
iter  20 value 88.392556
iter  30 value 85.725140
iter  40 value 82.943549
iter  50 value 81.988353
iter  60 value 81.459653
iter  70 value 81.451200
iter  80 value 81.404372
iter  90 value 81.384235
iter 100 value 81.383770
final  value 81.383770 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 97.959111 
iter  10 value 94.484868
iter  20 value 94.427912
iter  30 value 94.320940
iter  40 value 94.289397
iter  50 value 94.289176
iter  60 value 94.287767
final  value 94.287760 
converged
Fitting Repeat 4 

# weights:  507
initial  value 113.497699 
iter  10 value 94.474646
iter  20 value 94.466927
iter  30 value 94.438846
iter  40 value 87.944409
iter  50 value 87.776037
iter  60 value 85.643457
iter  70 value 82.740452
iter  80 value 82.713134
final  value 82.713101 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.959645 
iter  10 value 94.491470
iter  20 value 94.441039
iter  30 value 93.044474
iter  40 value 86.303651
iter  50 value 86.077798
iter  60 value 85.860314
iter  70 value 84.218189
iter  80 value 83.868418
iter  90 value 83.754388
iter 100 value 83.609904
final  value 83.609904 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.366412 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.767542 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.960213 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.601363 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.127606 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.704615 
iter  10 value 94.467391
iter  10 value 94.467391
iter  10 value 94.467391
final  value 94.467391 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.519194 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.360149 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 93.974401 
iter  10 value 84.167637
iter  20 value 83.583799
final  value 83.510375 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.846319 
final  value 93.300000 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.782767 
final  value 94.467391 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.259313 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.640386 
final  value 94.467391 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.536247 
iter  10 value 94.437537
final  value 94.423539 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.720917 
final  value 94.467391 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.312011 
iter  10 value 94.470350
iter  20 value 93.463080
iter  30 value 87.516611
iter  40 value 85.154308
iter  50 value 84.081519
iter  60 value 83.927779
iter  70 value 83.696686
iter  80 value 83.495026
iter  90 value 83.384062
iter 100 value 83.246047
final  value 83.246047 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 106.871684 
iter  10 value 94.452519
iter  20 value 91.303820
iter  30 value 88.110198
iter  40 value 87.045168
iter  50 value 86.530777
iter  60 value 85.279582
iter  70 value 84.861012
final  value 84.759943 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.969665 
iter  10 value 94.412124
iter  20 value 92.327733
iter  30 value 89.118293
iter  40 value 88.126014
iter  50 value 85.067457
iter  60 value 84.947209
iter  70 value 84.798641
iter  80 value 84.105265
iter  90 value 83.936506
iter 100 value 83.838211
final  value 83.838211 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.809855 
iter  10 value 94.510602
iter  20 value 93.835174
iter  30 value 87.763921
iter  40 value 85.843805
iter  50 value 85.079027
iter  60 value 84.734259
iter  70 value 84.245943
iter  80 value 83.810077
final  value 83.784413 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.326742 
iter  10 value 94.503624
iter  20 value 90.227931
iter  30 value 88.733545
iter  40 value 86.756178
iter  50 value 86.150811
iter  60 value 84.426612
iter  70 value 83.960209
iter  80 value 83.954134
final  value 83.954131 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.900045 
iter  10 value 94.354257
iter  20 value 88.817067
iter  30 value 87.196496
iter  40 value 86.929074
iter  50 value 86.448636
iter  60 value 85.323673
iter  70 value 83.783568
iter  80 value 82.194250
iter  90 value 81.874169
iter 100 value 81.712862
final  value 81.712862 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 111.645187 
iter  10 value 94.940832
iter  20 value 94.581493
iter  30 value 93.835164
iter  40 value 85.414328
iter  50 value 85.008199
iter  60 value 84.221444
iter  70 value 82.597860
iter  80 value 82.139885
iter  90 value 82.108544
iter 100 value 81.994310
final  value 81.994310 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.328567 
iter  10 value 90.439515
iter  20 value 85.214488
iter  30 value 84.300967
iter  40 value 84.205988
iter  50 value 83.710321
iter  60 value 82.970246
iter  70 value 82.308599
iter  80 value 82.056907
iter  90 value 82.012242
iter 100 value 82.002414
final  value 82.002414 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.110772 
iter  10 value 94.454156
iter  20 value 88.572530
iter  30 value 85.290663
iter  40 value 83.434980
iter  50 value 83.092172
iter  60 value 82.796451
iter  70 value 82.741956
iter  80 value 82.680281
iter  90 value 82.538057
iter 100 value 82.370343
final  value 82.370343 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.940798 
iter  10 value 94.505017
iter  20 value 93.791488
iter  30 value 91.271427
iter  40 value 90.858262
iter  50 value 90.791596
iter  60 value 85.717572
iter  70 value 84.453780
iter  80 value 83.506394
iter  90 value 83.143892
iter 100 value 83.104898
final  value 83.104898 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 115.687931 
iter  10 value 94.546674
iter  20 value 94.276009
iter  30 value 93.763524
iter  40 value 87.151072
iter  50 value 84.175244
iter  60 value 83.381917
iter  70 value 82.913507
iter  80 value 82.620060
iter  90 value 82.389076
iter 100 value 82.314563
final  value 82.314563 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 149.102477 
iter  10 value 96.522675
iter  20 value 94.740766
iter  30 value 90.406488
iter  40 value 87.441966
iter  50 value 84.895418
iter  60 value 84.102669
iter  70 value 82.664052
iter  80 value 82.317445
iter  90 value 82.076073
iter 100 value 81.903708
final  value 81.903708 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.817925 
iter  10 value 95.007450
iter  20 value 87.585770
iter  30 value 85.534803
iter  40 value 85.250081
iter  50 value 84.998820
iter  60 value 84.145996
iter  70 value 83.913296
iter  80 value 82.420528
iter  90 value 81.867444
iter 100 value 81.775090
final  value 81.775090 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.262430 
iter  10 value 94.510189
iter  20 value 94.400567
iter  30 value 89.547657
iter  40 value 86.824916
iter  50 value 83.277472
iter  60 value 82.742577
iter  70 value 82.564441
iter  80 value 82.308620
iter  90 value 82.143915
iter 100 value 82.101389
final  value 82.101389 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.526487 
iter  10 value 94.521624
iter  20 value 93.472950
iter  30 value 86.911355
iter  40 value 85.936298
iter  50 value 83.322671
iter  60 value 82.844903
iter  70 value 82.787834
iter  80 value 82.637358
iter  90 value 82.568806
iter 100 value 82.238011
final  value 82.238011 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.989400 
iter  10 value 94.486136
iter  20 value 94.484308
iter  30 value 92.432732
iter  40 value 86.249809
iter  50 value 85.969815
iter  60 value 85.953027
final  value 85.952974 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.614639 
iter  10 value 94.488828
final  value 94.487113 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.865462 
final  value 94.486008 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.120055 
final  value 94.485727 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.760288 
final  value 94.485822 
converged
Fitting Repeat 1 

# weights:  305
initial  value 117.354561 
iter  10 value 86.202095
iter  20 value 84.430437
iter  30 value 84.425497
iter  40 value 84.347397
iter  50 value 84.324857
iter  60 value 84.320165
final  value 84.320074 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.312506 
iter  10 value 94.489381
iter  20 value 94.293532
iter  30 value 88.824496
iter  40 value 88.421936
iter  50 value 81.927755
iter  60 value 81.712646
iter  70 value 81.712235
iter  80 value 81.710444
iter  90 value 81.693264
iter 100 value 81.692524
final  value 81.692524 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 95.847265 
iter  10 value 94.448103
iter  20 value 90.411030
iter  30 value 88.016990
iter  40 value 87.773690
iter  50 value 86.131538
iter  60 value 86.084590
final  value 86.084250 
converged
Fitting Repeat 4 

# weights:  305
initial  value 111.038531 
iter  10 value 94.488957
iter  20 value 91.463743
iter  30 value 83.847908
iter  40 value 83.331386
final  value 83.321633 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.366140 
iter  10 value 94.472654
iter  20 value 91.649493
iter  30 value 86.806212
iter  40 value 86.364187
iter  50 value 86.036866
iter  60 value 85.664579
final  value 85.661421 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.716852 
iter  10 value 86.209545
iter  20 value 86.206413
iter  30 value 84.167329
iter  40 value 84.167189
iter  50 value 84.165723
final  value 84.165521 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.126819 
iter  10 value 94.491656
iter  20 value 94.491103
iter  30 value 94.460984
iter  40 value 86.272718
iter  50 value 85.877339
iter  60 value 85.608866
iter  70 value 82.273345
iter  80 value 81.823638
final  value 81.823026 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.184062 
iter  10 value 94.497681
iter  20 value 94.489578
iter  30 value 92.054468
iter  40 value 91.922899
iter  50 value 90.369776
iter  60 value 85.682165
iter  70 value 85.118599
iter  80 value 85.116205
iter  90 value 84.154857
iter 100 value 83.222844
final  value 83.222844 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 101.843751 
iter  10 value 94.491214
iter  20 value 94.224586
iter  30 value 89.693007
iter  40 value 86.698431
iter  50 value 86.312436
iter  60 value 86.086512
iter  70 value 86.083217
iter  80 value 86.082307
iter  90 value 85.667946
iter 100 value 84.635556
final  value 84.635556 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 99.133542 
iter  10 value 94.493763
iter  20 value 94.485005
iter  30 value 92.237126
iter  40 value 86.538178
iter  50 value 84.499253
iter  60 value 82.538556
iter  70 value 82.532016
iter  80 value 82.512702
iter  90 value 82.359721
iter 100 value 82.182740
final  value 82.182740 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.304169 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.703315 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.043263 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.268291 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.959691 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.576541 
iter  10 value 93.157475
final  value 93.157468 
converged
Fitting Repeat 2 

# weights:  305
initial  value 112.770959 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.922227 
final  value 93.567525 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.992669 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.401068 
iter  10 value 94.265055
final  value 94.263153 
converged
Fitting Repeat 1 

# weights:  507
initial  value 126.362604 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.060136 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 120.274398 
final  value 94.312038 
converged
Fitting Repeat 4 

# weights:  507
initial  value 107.810781 
iter  10 value 91.600500
iter  20 value 86.053801
final  value 86.053792 
converged
Fitting Repeat 5 

# weights:  507
initial  value 112.495976 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 106.131669 
iter  10 value 94.476547
iter  20 value 84.538592
iter  30 value 83.577145
iter  40 value 82.848878
iter  50 value 81.383142
iter  60 value 81.094521
final  value 81.080871 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.767754 
iter  10 value 94.494472
iter  20 value 94.477718
iter  30 value 83.977957
iter  40 value 82.042922
iter  50 value 81.848663
iter  60 value 81.812759
iter  70 value 81.810695
iter  70 value 81.810695
iter  70 value 81.810695
final  value 81.810695 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.543448 
iter  10 value 94.263982
iter  20 value 88.984963
iter  30 value 87.823041
iter  40 value 86.338260
iter  50 value 85.607190
iter  60 value 81.482855
iter  70 value 79.061856
iter  80 value 78.620207
iter  90 value 78.599943
iter 100 value 78.599137
final  value 78.599137 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 114.205096 
iter  10 value 94.487910
iter  20 value 94.486012
iter  30 value 84.594604
iter  40 value 83.096064
iter  50 value 81.930897
iter  60 value 81.812333
iter  70 value 81.810701
final  value 81.810695 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.536321 
iter  10 value 92.417089
iter  20 value 83.531964
iter  30 value 82.310963
iter  40 value 81.871745
iter  50 value 81.810924
final  value 81.810695 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.125157 
iter  10 value 94.518565
iter  20 value 87.571634
iter  30 value 85.851142
iter  40 value 82.095808
iter  50 value 81.543284
iter  60 value 81.444852
iter  70 value 81.226695
iter  80 value 79.372790
iter  90 value 77.772288
iter 100 value 77.138345
final  value 77.138345 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.482175 
iter  10 value 94.587261
iter  20 value 91.348346
iter  30 value 89.832502
iter  40 value 89.430631
iter  50 value 80.261013
iter  60 value 79.713937
iter  70 value 79.375729
iter  80 value 78.965946
iter  90 value 78.425217
iter 100 value 77.491405
final  value 77.491405 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.958584 
iter  10 value 93.533386
iter  20 value 89.065647
iter  30 value 88.046400
iter  40 value 84.653453
iter  50 value 81.327367
iter  60 value 80.739576
iter  70 value 79.609679
iter  80 value 78.728200
iter  90 value 78.613511
iter 100 value 78.221458
final  value 78.221458 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.339346 
iter  10 value 92.863512
iter  20 value 88.306807
iter  30 value 84.985404
iter  40 value 82.398146
iter  50 value 80.874584
iter  60 value 80.643607
iter  70 value 80.404186
iter  80 value 79.413660
iter  90 value 77.403333
iter 100 value 77.127105
final  value 77.127105 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.946560 
iter  10 value 95.797308
iter  20 value 93.944570
iter  30 value 87.609394
iter  40 value 86.390729
iter  50 value 79.073694
iter  60 value 78.639550
iter  70 value 78.172957
iter  80 value 77.609454
iter  90 value 77.354225
iter 100 value 77.255072
final  value 77.255072 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 123.440853 
iter  10 value 94.553586
iter  20 value 94.408060
iter  30 value 93.828990
iter  40 value 88.973614
iter  50 value 87.615137
iter  60 value 85.460336
iter  70 value 81.911965
iter  80 value 78.829044
iter  90 value 77.660851
iter 100 value 77.085283
final  value 77.085283 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 116.315943 
iter  10 value 94.469036
iter  20 value 89.016130
iter  30 value 83.907347
iter  40 value 82.909708
iter  50 value 81.363462
iter  60 value 80.924470
iter  70 value 80.783718
iter  80 value 80.376222
iter  90 value 80.253675
iter 100 value 79.286022
final  value 79.286022 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.098788 
iter  10 value 94.449559
iter  20 value 93.177730
iter  30 value 85.900130
iter  40 value 83.403495
iter  50 value 81.821277
iter  60 value 81.430508
iter  70 value 80.265066
iter  80 value 79.899374
iter  90 value 79.567645
iter 100 value 79.131566
final  value 79.131566 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 117.156725 
iter  10 value 93.420344
iter  20 value 87.336649
iter  30 value 85.620604
iter  40 value 82.026558
iter  50 value 80.731691
iter  60 value 79.959602
iter  70 value 79.241072
iter  80 value 78.779095
iter  90 value 78.364652
iter 100 value 78.137669
final  value 78.137669 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.896211 
iter  10 value 89.257257
iter  20 value 83.800933
iter  30 value 81.635738
iter  40 value 80.468599
iter  50 value 79.507183
iter  60 value 78.303342
iter  70 value 77.819324
iter  80 value 77.410625
iter  90 value 77.292560
iter 100 value 77.200481
final  value 77.200481 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 107.947327 
final  value 94.485769 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.162577 
iter  10 value 94.485974
final  value 94.484304 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.195003 
final  value 94.485932 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.755021 
final  value 94.485634 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.960053 
final  value 94.485589 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.454786 
iter  10 value 94.031703
iter  20 value 93.970181
iter  30 value 92.802115
final  value 92.721668 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.415305 
iter  10 value 94.489344
iter  20 value 94.484442
iter  30 value 93.646665
iter  40 value 93.489946
final  value 93.489886 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.991445 
iter  10 value 94.489306
iter  20 value 94.469067
iter  30 value 90.010345
iter  40 value 87.777217
iter  50 value 87.667579
iter  60 value 85.171007
final  value 85.170332 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.571640 
iter  10 value 94.488830
iter  20 value 91.471089
iter  30 value 84.836629
iter  40 value 84.676484
iter  50 value 84.612701
iter  60 value 83.986481
iter  70 value 83.839866
iter  80 value 83.830846
iter  90 value 83.809930
iter 100 value 83.709012
final  value 83.709012 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.150574 
iter  10 value 94.031707
iter  20 value 93.864575
iter  30 value 80.158222
iter  40 value 77.272677
iter  50 value 77.267572
final  value 77.266924 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.419590 
iter  10 value 94.034493
iter  20 value 94.030833
iter  30 value 94.029207
iter  40 value 93.993141
iter  50 value 93.438615
iter  60 value 91.864604
iter  70 value 85.718024
iter  80 value 85.711839
iter  90 value 85.130261
final  value 85.126724 
converged
Fitting Repeat 2 

# weights:  507
initial  value 94.211320 
iter  10 value 91.816910
iter  20 value 83.450638
iter  30 value 79.479062
iter  40 value 79.290975
iter  50 value 79.285082
final  value 79.280186 
converged
Fitting Repeat 3 

# weights:  507
initial  value 112.220416 
iter  10 value 91.182444
iter  20 value 84.387770
iter  30 value 84.374305
iter  40 value 84.370936
iter  50 value 84.370494
iter  60 value 84.366817
iter  70 value 83.693862
iter  80 value 80.571439
iter  90 value 79.118784
iter 100 value 79.112232
final  value 79.112232 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.182488 
iter  10 value 93.698814
iter  20 value 81.279245
iter  30 value 80.326957
iter  40 value 80.313339
iter  50 value 80.307775
iter  60 value 80.305423
iter  70 value 80.304497
iter  80 value 80.296242
iter  90 value 78.862729
iter 100 value 77.646969
final  value 77.646969 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 98.550807 
iter  10 value 94.492022
iter  20 value 94.480568
iter  30 value 82.165399
iter  40 value 81.735600
iter  50 value 81.688391
iter  60 value 81.644833
iter  70 value 80.536033
iter  80 value 79.933278
iter  90 value 79.763590
iter 100 value 79.695450
final  value 79.695450 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 148.447372 
iter  10 value 119.268203
iter  20 value 117.843267
iter  30 value 117.024999
iter  40 value 110.813039
iter  50 value 107.958077
iter  60 value 107.246605
iter  70 value 106.588795
iter  80 value 105.653895
iter  90 value 105.185629
iter 100 value 104.293516
final  value 104.293516 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 131.340035 
iter  10 value 117.912328
iter  20 value 115.417361
iter  30 value 107.580412
iter  40 value 104.964036
iter  50 value 104.176702
iter  60 value 103.791452
iter  70 value 103.700382
iter  80 value 103.564426
iter  90 value 103.309009
iter 100 value 102.875150
final  value 102.875150 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 133.776550 
iter  10 value 117.991096
iter  20 value 116.679158
iter  30 value 112.078970
iter  40 value 104.137550
iter  50 value 103.439202
iter  60 value 102.751112
iter  70 value 101.889350
iter  80 value 101.107593
iter  90 value 100.646994
iter 100 value 100.550587
final  value 100.550587 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 136.813946 
iter  10 value 119.764758
iter  20 value 116.677771
iter  30 value 108.206943
iter  40 value 103.216272
iter  50 value 102.680723
iter  60 value 102.353261
iter  70 value 101.590541
iter  80 value 101.442909
iter  90 value 101.369858
iter 100 value 101.200979
final  value 101.200979 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 139.776466 
iter  10 value 118.363098
iter  20 value 108.423533
iter  30 value 107.441982
iter  40 value 106.241982
iter  50 value 103.715930
iter  60 value 102.973111
iter  70 value 102.835014
iter  80 value 102.280502
iter  90 value 102.000706
iter 100 value 101.879462
final  value 101.879462 
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 -- Thu Jun 27 20:56:03 2024 
*********************************************** 
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 
Warning messages:
1: `repeats` has no meaning for this resampling method. 
2: executing %dopar% sequentially: no parallel backend registered 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
 42.063   1.957  43.591