##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.24-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.24-bioc/R/site-library --timings HPiP_1.19.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.24-bioc/meat/HPiP.Rcheck’
* using R version 4.6.0 RC (2026-04-17 r89917)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
    GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
* running under: Ubuntu 24.04.4 LTS
* using session charset: UTF-8
* current time: 2026-05-16 04:49:24 UTC
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.19.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... INFO
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
corr_plot     35.298  0.400  35.701
FSmethod      34.899  0.448  35.432
var_imp       34.368  0.564  34.933
pred_ensembel 12.780  0.220  11.713
enrichfindP    0.569  0.041  12.572
* 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: 2 NOTEs
See
  ‘/home/biocbuild/bbs-3.24-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.24-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.24-bioc/R/site-library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.19.0’
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R version 4.6.0 RC (2026-04-17 r89917) -- "Because it was There"
Copyright (C) 2026 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
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 100.784056 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.733065 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.036697 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.094694 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.483547 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.361728 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.178226 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.255987 
iter  10 value 93.565089
final  value 93.561853 
converged
Fitting Repeat 4 

# weights:  305
initial  value 116.535519 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.429780 
final  value 94.088889 
converged
Fitting Repeat 1 

# weights:  507
initial  value 114.091208 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 112.167002 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.618282 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 109.519832 
iter  10 value 94.228678
iter  10 value 94.228678
iter  10 value 94.228678
final  value 94.228678 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.705567 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.552141 
iter  10 value 94.458475
iter  20 value 87.985821
iter  30 value 86.427615
iter  40 value 86.015837
iter  50 value 84.961429
iter  60 value 84.747009
final  value 84.740023 
converged
Fitting Repeat 2 

# weights:  103
initial  value 111.881666 
iter  10 value 94.351514
iter  20 value 91.470695
iter  30 value 87.731770
iter  40 value 85.778673
iter  50 value 84.901709
iter  60 value 84.728136
iter  70 value 84.721830
final  value 84.721790 
converged
Fitting Repeat 3 

# weights:  103
initial  value 110.168654 
iter  10 value 94.439781
iter  20 value 86.455788
iter  30 value 85.471118
iter  40 value 85.447509
iter  50 value 84.860843
iter  60 value 84.767109
iter  70 value 84.740501
final  value 84.740023 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.417997 
iter  10 value 94.489813
iter  20 value 93.618305
iter  30 value 88.135124
iter  40 value 85.434901
iter  50 value 85.284577
iter  60 value 84.453198
iter  70 value 84.395727
final  value 84.395715 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.923728 
iter  10 value 94.325022
iter  20 value 93.690325
iter  30 value 91.308681
iter  40 value 85.636526
iter  50 value 83.881913
iter  60 value 82.944000
iter  70 value 82.319245
iter  80 value 82.237256
iter  90 value 82.190974
iter 100 value 82.188201
final  value 82.188201 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 114.166647 
iter  10 value 96.570544
iter  20 value 94.610542
iter  30 value 94.412520
iter  40 value 93.643808
iter  50 value 92.800677
iter  60 value 88.607309
iter  70 value 87.495246
iter  80 value 86.702996
iter  90 value 85.440749
iter 100 value 85.174448
final  value 85.174448 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.231668 
iter  10 value 93.853738
iter  20 value 90.047626
iter  30 value 87.979341
iter  40 value 84.430052
iter  50 value 83.315251
iter  60 value 82.709077
iter  70 value 82.245112
iter  80 value 81.661460
iter  90 value 81.585782
iter 100 value 81.506113
final  value 81.506113 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.251592 
iter  10 value 94.632045
iter  20 value 93.759442
iter  30 value 88.896150
iter  40 value 87.166286
iter  50 value 86.396091
iter  60 value 85.396363
iter  70 value 85.208482
iter  80 value 84.961094
iter  90 value 84.226864
iter 100 value 82.103964
final  value 82.103964 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.262710 
iter  10 value 94.494648
iter  20 value 93.393937
iter  30 value 90.384625
iter  40 value 88.703002
iter  50 value 88.266901
iter  60 value 86.898952
iter  70 value 86.006839
iter  80 value 83.590394
iter  90 value 81.640231
iter 100 value 81.170232
final  value 81.170232 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.709529 
iter  10 value 94.865983
iter  20 value 93.658062
iter  30 value 90.200797
iter  40 value 87.508615
iter  50 value 86.679510
iter  60 value 85.258944
iter  70 value 84.298786
iter  80 value 83.804256
iter  90 value 81.915493
iter 100 value 81.833358
final  value 81.833358 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.390458 
iter  10 value 96.390339
iter  20 value 92.470031
iter  30 value 91.624296
iter  40 value 89.010185
iter  50 value 85.827793
iter  60 value 84.948518
iter  70 value 83.332190
iter  80 value 81.630789
iter  90 value 81.325768
iter 100 value 81.239884
final  value 81.239884 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 122.596647 
iter  10 value 99.353271
iter  20 value 91.982674
iter  30 value 89.650225
iter  40 value 87.332230
iter  50 value 86.075130
iter  60 value 85.697711
iter  70 value 84.670203
iter  80 value 82.862908
iter  90 value 82.131138
iter 100 value 81.277684
final  value 81.277684 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.569212 
iter  10 value 95.181426
iter  20 value 93.534659
iter  30 value 86.567377
iter  40 value 85.795532
iter  50 value 83.669272
iter  60 value 81.486279
iter  70 value 81.341675
iter  80 value 81.010683
iter  90 value 80.682342
iter 100 value 80.382847
final  value 80.382847 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 128.945810 
iter  10 value 94.976416
iter  20 value 93.904470
iter  30 value 90.556566
iter  40 value 86.704142
iter  50 value 83.813261
iter  60 value 82.707521
iter  70 value 81.712311
iter  80 value 81.388741
iter  90 value 81.263323
iter 100 value 81.052633
final  value 81.052633 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.401676 
iter  10 value 92.730555
iter  20 value 85.654518
iter  30 value 85.223665
iter  40 value 84.427649
iter  50 value 83.153552
iter  60 value 81.922563
iter  70 value 81.596986
iter  80 value 81.085164
iter  90 value 80.704904
iter 100 value 80.547600
final  value 80.547600 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 116.277229 
final  value 94.486125 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.883501 
final  value 94.485612 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.350421 
final  value 94.485993 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.695275 
final  value 94.485814 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.224678 
final  value 94.486020 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.632708 
iter  10 value 94.489327
iter  20 value 94.484242
iter  30 value 93.585011
iter  40 value 93.457336
iter  50 value 93.456983
final  value 93.456823 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.068658 
iter  10 value 94.489480
iter  20 value 94.090308
iter  30 value 89.773250
iter  40 value 86.728234
iter  50 value 84.983037
iter  60 value 84.843911
iter  70 value 84.805300
iter  80 value 84.649737
iter  90 value 84.647689
iter 100 value 84.644753
final  value 84.644753 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 110.913705 
iter  10 value 94.489278
iter  20 value 94.460635
iter  30 value 93.547309
iter  40 value 90.695984
iter  50 value 90.599061
iter  60 value 90.440025
iter  70 value 90.192366
iter  70 value 90.192365
iter  70 value 90.192365
final  value 90.192365 
converged
Fitting Repeat 4 

# weights:  305
initial  value 112.400749 
iter  10 value 94.489249
iter  20 value 94.430389
iter  30 value 86.635620
iter  40 value 85.155465
iter  50 value 84.407585
iter  60 value 84.407146
final  value 84.407139 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.213787 
iter  10 value 94.280348
iter  20 value 94.276121
final  value 94.275773 
converged
Fitting Repeat 1 

# weights:  507
initial  value 124.440407 
iter  10 value 93.100341
iter  20 value 93.051344
iter  30 value 93.045349
final  value 93.043503 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.091092 
iter  10 value 94.492140
iter  20 value 94.484283
final  value 94.484265 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.966299 
iter  10 value 94.237444
iter  20 value 94.234891
iter  30 value 93.087739
iter  40 value 84.380730
iter  50 value 82.115604
iter  60 value 82.089778
iter  70 value 81.576163
iter  80 value 81.228617
iter  90 value 81.095153
iter 100 value 81.082856
final  value 81.082856 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.558708 
iter  10 value 94.491381
iter  20 value 93.562943
final  value 93.502516 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.950629 
iter  10 value 93.896101
iter  20 value 93.857680
iter  30 value 93.849750
iter  40 value 93.620822
iter  50 value 93.574720
iter  60 value 93.562265
iter  70 value 93.484592
iter  80 value 88.635114
iter  90 value 86.014005
iter 100 value 85.415779
final  value 85.415779 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.430356 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.239899 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.130341 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.497025 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.886609 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.420651 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.104598 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.615860 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.168136 
iter  10 value 92.082583
iter  20 value 86.279018
iter  30 value 86.001492
iter  40 value 85.986137
final  value 85.986025 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.434709 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.834323 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 110.928847 
iter  10 value 91.384539
iter  20 value 90.843076
final  value 90.842390 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.346480 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.021374 
iter  10 value 90.790478
iter  20 value 84.332062
iter  30 value 83.325253
iter  40 value 82.914841
iter  50 value 82.688818
iter  60 value 82.688306
final  value 82.688277 
converged
Fitting Repeat 5 

# weights:  507
initial  value 115.331767 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 112.089952 
iter  10 value 94.011115
iter  20 value 91.536105
iter  30 value 91.302489
iter  40 value 91.038918
iter  50 value 90.477213
iter  60 value 90.037542
iter  70 value 89.874753
iter  80 value 89.786708
final  value 89.783271 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.309740 
iter  10 value 94.033225
iter  20 value 92.454140
iter  30 value 91.355185
iter  40 value 89.879567
iter  50 value 89.577959
final  value 89.574677 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.539138 
iter  10 value 94.040785
iter  20 value 93.851925
iter  30 value 89.792463
iter  40 value 84.619137
iter  50 value 84.397466
iter  60 value 83.804376
iter  70 value 83.481389
iter  80 value 82.602637
iter  90 value 82.556781
final  value 82.554091 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.558305 
iter  10 value 94.054797
iter  20 value 93.893401
iter  30 value 93.454915
iter  40 value 93.385055
iter  50 value 85.626399
iter  60 value 85.160308
iter  70 value 84.297572
iter  80 value 83.009708
iter  90 value 82.776269
iter 100 value 81.953029
final  value 81.953029 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.757838 
iter  10 value 94.078432
iter  20 value 94.056545
iter  30 value 94.054885
iter  40 value 91.053769
iter  50 value 84.118763
iter  60 value 83.918607
iter  70 value 83.661334
iter  80 value 83.268564
iter  90 value 82.643460
iter 100 value 82.267280
final  value 82.267280 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 102.721243 
iter  10 value 95.289663
iter  20 value 92.667453
iter  30 value 87.752453
iter  40 value 83.715090
iter  50 value 83.416491
iter  60 value 82.102326
iter  70 value 81.997656
iter  80 value 81.556824
iter  90 value 81.223811
iter 100 value 80.936423
final  value 80.936423 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.070441 
iter  10 value 93.951558
iter  20 value 93.445557
iter  30 value 92.781095
iter  40 value 90.308982
iter  50 value 87.860991
iter  60 value 83.897043
iter  70 value 81.275434
iter  80 value 81.065096
iter  90 value 80.818538
iter 100 value 79.897647
final  value 79.897647 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.769025 
iter  10 value 94.043703
iter  20 value 90.736386
iter  30 value 90.450359
iter  40 value 87.713484
iter  50 value 84.605764
iter  60 value 82.872634
iter  70 value 80.423234
iter  80 value 79.899022
iter  90 value 79.564200
iter 100 value 79.378220
final  value 79.378220 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.002358 
iter  10 value 94.110474
iter  20 value 91.431620
iter  30 value 89.223993
iter  40 value 87.973819
iter  50 value 83.489709
iter  60 value 81.665436
iter  70 value 81.011550
iter  80 value 80.554796
iter  90 value 80.032422
iter 100 value 79.626807
final  value 79.626807 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.111339 
iter  10 value 94.050686
iter  20 value 84.417516
iter  30 value 83.932736
iter  40 value 82.605556
iter  50 value 82.218859
iter  60 value 82.049403
iter  70 value 81.805758
iter  80 value 80.490565
iter  90 value 79.865999
iter 100 value 79.727429
final  value 79.727429 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.620045 
iter  10 value 94.990489
iter  20 value 93.957876
iter  30 value 91.970713
iter  40 value 83.881798
iter  50 value 83.445622
iter  60 value 82.173306
iter  70 value 81.222311
iter  80 value 80.575978
iter  90 value 79.824220
iter 100 value 79.492968
final  value 79.492968 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 119.047345 
iter  10 value 94.102269
iter  20 value 90.504431
iter  30 value 83.583159
iter  40 value 82.996080
iter  50 value 82.385455
iter  60 value 81.328548
iter  70 value 80.533599
iter  80 value 80.358406
iter  90 value 80.058839
iter 100 value 79.611186
final  value 79.611186 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.910273 
iter  10 value 93.421935
iter  20 value 85.402921
iter  30 value 84.381856
iter  40 value 83.327768
iter  50 value 82.999286
iter  60 value 82.822436
iter  70 value 82.166565
iter  80 value 81.517789
iter  90 value 81.268976
iter 100 value 81.048445
final  value 81.048445 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.294488 
iter  10 value 94.030328
iter  20 value 92.481701
iter  30 value 90.736036
iter  40 value 85.218121
iter  50 value 82.745989
iter  60 value 81.132264
iter  70 value 80.123496
iter  80 value 79.904187
iter  90 value 79.300492
iter 100 value 79.241853
final  value 79.241853 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.106334 
iter  10 value 95.315544
iter  20 value 88.826560
iter  30 value 87.781461
iter  40 value 83.312968
iter  50 value 82.402553
iter  60 value 81.074376
iter  70 value 80.673343
iter  80 value 79.818750
iter  90 value 79.226271
iter 100 value 79.007866
final  value 79.007866 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.297821 
iter  10 value 94.054474
iter  20 value 94.043430
iter  30 value 83.548764
iter  40 value 83.361601
iter  50 value 83.361109
final  value 83.361086 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.303046 
iter  10 value 93.630472
iter  20 value 93.629211
iter  30 value 91.986521
iter  40 value 88.845355
iter  50 value 88.836997
iter  60 value 86.154274
iter  70 value 84.887235
iter  80 value 84.882198
iter  90 value 84.881837
final  value 84.881792 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.923173 
final  value 93.917369 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.101316 
final  value 94.054651 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.830000 
final  value 94.054353 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.972019 
iter  10 value 94.058143
iter  20 value 93.914773
iter  30 value 93.074197
iter  40 value 93.068418
iter  50 value 93.018219
iter  60 value 93.016901
final  value 93.016896 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.885472 
iter  10 value 93.920371
iter  20 value 93.550642
iter  30 value 90.199347
iter  40 value 89.846566
iter  50 value 89.565716
iter  60 value 88.076685
final  value 87.731440 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.791783 
iter  10 value 94.046854
iter  20 value 93.989335
final  value 93.915948 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.527926 
iter  10 value 94.046727
iter  20 value 93.723414
iter  30 value 85.224453
iter  40 value 84.175485
final  value 84.164466 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.688440 
iter  10 value 84.411423
iter  20 value 83.546424
iter  30 value 83.545810
iter  40 value 83.542859
iter  50 value 83.405576
iter  60 value 83.404965
final  value 83.404939 
converged
Fitting Repeat 1 

# weights:  507
initial  value 113.156157 
iter  10 value 94.062216
iter  20 value 94.046660
iter  30 value 92.469262
iter  40 value 91.157763
iter  50 value 90.568449
iter  60 value 84.219412
iter  70 value 80.982996
iter  80 value 80.428873
iter  90 value 80.385778
iter 100 value 80.382761
final  value 80.382761 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 100.279312 
iter  10 value 93.365141
iter  20 value 93.329054
iter  30 value 92.966400
iter  40 value 92.959022
iter  50 value 92.125920
iter  60 value 90.609750
iter  70 value 90.608235
iter  80 value 90.565325
iter  90 value 90.535110
iter 100 value 89.705248
final  value 89.705248 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 115.708384 
iter  10 value 94.059322
iter  20 value 85.319071
iter  30 value 82.965755
iter  40 value 82.416963
iter  50 value 82.355443
iter  60 value 82.355288
iter  70 value 82.354543
final  value 82.354464 
converged
Fitting Repeat 4 

# weights:  507
initial  value 116.718958 
iter  10 value 93.924380
iter  20 value 93.916323
iter  30 value 93.915986
final  value 93.915983 
converged
Fitting Repeat 5 

# weights:  507
initial  value 113.719717 
iter  10 value 93.953157
iter  20 value 89.519619
iter  30 value 84.727527
iter  40 value 83.322703
iter  50 value 82.409662
iter  60 value 82.406558
iter  70 value 81.893313
iter  80 value 81.845746
iter  90 value 81.707515
iter 100 value 80.948405
final  value 80.948405 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.199912 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.141136 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.220588 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.645185 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.084410 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.330287 
iter  10 value 93.551684
final  value 93.394928 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.340374 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.894756 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.246748 
iter  10 value 93.394929
final  value 93.394928 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.284770 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.291169 
iter  10 value 93.321243
final  value 93.320226 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.413301 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.330568 
iter  10 value 93.394930
iter  10 value 93.394929
iter  10 value 93.394929
final  value 93.394929 
converged
Fitting Repeat 4 

# weights:  507
initial  value 111.531782 
iter  10 value 93.362959
final  value 93.362784 
converged
Fitting Repeat 5 

# weights:  507
initial  value 123.801230 
final  value 94.449438 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.825982 
iter  10 value 93.718867
iter  20 value 93.444474
iter  30 value 91.840581
iter  40 value 90.908438
iter  50 value 90.438923
iter  60 value 86.852770
iter  70 value 86.033330
iter  80 value 83.251536
iter  90 value 81.702981
iter 100 value 81.416354
final  value 81.416354 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 110.275821 
iter  10 value 94.486646
iter  20 value 93.848051
iter  30 value 93.678296
iter  40 value 93.677013
iter  50 value 93.526514
iter  60 value 92.852184
iter  70 value 90.065273
iter  80 value 87.660287
iter  90 value 86.937823
iter 100 value 83.990963
final  value 83.990963 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 100.241885 
iter  10 value 94.490329
iter  20 value 87.008844
iter  30 value 85.432250
iter  40 value 85.394929
iter  50 value 85.191318
iter  60 value 83.628112
iter  70 value 83.117186
iter  80 value 83.110916
iter  80 value 83.110915
iter  80 value 83.110915
final  value 83.110915 
converged
Fitting Repeat 4 

# weights:  103
initial  value 109.253504 
iter  10 value 94.488543
iter  20 value 94.040073
iter  30 value 93.855785
iter  40 value 93.476825
iter  50 value 92.232651
iter  60 value 85.643303
iter  70 value 85.347658
iter  80 value 85.196702
iter  90 value 84.764903
iter 100 value 83.754139
final  value 83.754139 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 101.548008 
iter  10 value 94.444805
iter  20 value 91.869029
iter  30 value 90.074598
iter  40 value 88.644396
iter  50 value 85.480550
iter  60 value 84.997713
iter  70 value 83.693939
iter  80 value 81.506986
iter  90 value 81.331358
iter 100 value 81.327794
final  value 81.327794 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 104.606673 
iter  10 value 93.863062
iter  20 value 93.492996
iter  30 value 91.958220
iter  40 value 88.645447
iter  50 value 85.862022
iter  60 value 82.331087
iter  70 value 81.648007
iter  80 value 81.080285
iter  90 value 80.696422
iter 100 value 80.459560
final  value 80.459560 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 114.686094 
iter  10 value 90.366223
iter  20 value 84.598509
iter  30 value 82.123163
iter  40 value 80.451186
iter  50 value 79.875935
iter  60 value 79.820238
iter  70 value 79.795054
iter  80 value 79.695825
iter  90 value 79.601791
iter 100 value 79.436288
final  value 79.436288 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.198650 
iter  10 value 92.113932
iter  20 value 85.470266
iter  30 value 83.598031
iter  40 value 81.947269
iter  50 value 81.405543
iter  60 value 80.118282
iter  70 value 79.493348
iter  80 value 79.329082
iter  90 value 79.253717
iter 100 value 79.230589
final  value 79.230589 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.034979 
iter  10 value 94.473462
iter  20 value 89.727409
iter  30 value 86.117504
iter  40 value 84.426892
iter  50 value 84.038329
iter  60 value 83.909234
iter  70 value 83.865259
iter  80 value 83.456602
iter  90 value 81.954907
iter 100 value 80.536666
final  value 80.536666 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 112.338228 
iter  10 value 93.647680
iter  20 value 86.842728
iter  30 value 85.817541
iter  40 value 85.385570
iter  50 value 83.440473
iter  60 value 82.432707
iter  70 value 81.440102
iter  80 value 80.410552
iter  90 value 79.783310
iter 100 value 79.499190
final  value 79.499190 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 131.315256 
iter  10 value 93.627106
iter  20 value 86.974669
iter  30 value 85.523936
iter  40 value 85.013399
iter  50 value 84.768372
iter  60 value 84.138145
iter  70 value 83.914543
iter  80 value 83.808675
iter  90 value 83.399483
iter 100 value 83.062662
final  value 83.062662 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.237368 
iter  10 value 94.013741
iter  20 value 91.970117
iter  30 value 88.153971
iter  40 value 84.360985
iter  50 value 83.636169
iter  60 value 83.173476
iter  70 value 82.944331
iter  80 value 82.747890
iter  90 value 82.027887
iter 100 value 81.270124
final  value 81.270124 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.416344 
iter  10 value 93.836465
iter  20 value 87.022519
iter  30 value 86.281512
iter  40 value 82.762679
iter  50 value 80.852375
iter  60 value 80.447797
iter  70 value 80.059480
iter  80 value 79.846894
iter  90 value 79.586962
iter 100 value 79.385112
final  value 79.385112 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.212376 
iter  10 value 93.934546
iter  20 value 87.300390
iter  30 value 84.574584
iter  40 value 83.922244
iter  50 value 83.418529
iter  60 value 82.864302
iter  70 value 82.705921
iter  80 value 82.346783
iter  90 value 81.983730
iter 100 value 81.587474
final  value 81.587474 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 112.483181 
iter  10 value 88.810340
iter  20 value 86.231739
iter  30 value 84.643990
iter  40 value 83.509643
iter  50 value 82.787780
iter  60 value 82.243337
iter  70 value 80.735767
iter  80 value 80.283288
iter  90 value 80.010928
iter 100 value 79.812010
final  value 79.812010 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.542097 
final  value 94.485769 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.751470 
final  value 94.486058 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.521272 
final  value 94.485937 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.579743 
final  value 94.485577 
converged
Fitting Repeat 5 

# weights:  103
initial  value 113.603189 
iter  10 value 93.397525
iter  20 value 93.397241
iter  30 value 93.205718
iter  40 value 93.154971
iter  50 value 93.154617
final  value 93.154609 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.867600 
iter  10 value 93.399870
iter  20 value 93.396278
final  value 93.395542 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.502457 
iter  10 value 94.488680
iter  20 value 93.399273
final  value 93.321078 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.886560 
iter  10 value 94.490264
iter  20 value 94.453953
iter  30 value 92.207293
iter  40 value 87.298189
iter  50 value 87.040904
iter  60 value 85.979993
iter  70 value 85.976580
iter  80 value 85.975729
final  value 85.975510 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.673638 
iter  10 value 94.485643
iter  20 value 94.042588
iter  30 value 92.168153
iter  40 value 84.343805
iter  50 value 84.339750
iter  60 value 84.338609
iter  70 value 84.335016
iter  80 value 84.226933
iter  90 value 84.226613
iter  90 value 84.226612
final  value 84.226612 
converged
Fitting Repeat 5 

# weights:  305
initial  value 113.596388 
iter  10 value 94.489051
iter  20 value 94.453144
iter  30 value 93.530934
iter  40 value 93.403970
iter  50 value 93.395630
iter  60 value 91.995587
iter  70 value 86.055681
final  value 86.055614 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.084991 
iter  10 value 94.453558
iter  20 value 94.450808
iter  30 value 94.055139
iter  40 value 93.643864
iter  50 value 93.515269
iter  60 value 93.201482
iter  70 value 84.689663
iter  80 value 83.154000
iter  90 value 83.028170
iter 100 value 83.027868
final  value 83.027868 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 97.794749 
iter  10 value 93.404839
iter  20 value 93.399297
iter  30 value 93.396567
iter  40 value 93.285680
final  value 93.154720 
converged
Fitting Repeat 3 

# weights:  507
initial  value 120.391907 
iter  10 value 94.492073
iter  20 value 94.484442
iter  30 value 93.321077
final  value 93.321067 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.443937 
iter  10 value 93.385367
iter  20 value 92.584051
iter  30 value 83.638739
iter  40 value 82.178721
iter  50 value 82.151096
iter  60 value 81.827862
iter  70 value 81.455674
iter  80 value 81.454028
iter  90 value 81.452686
iter 100 value 81.452019
final  value 81.452019 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 95.564432 
iter  10 value 94.491878
iter  20 value 93.091825
iter  30 value 93.071055
iter  40 value 93.056434
iter  50 value 88.910707
iter  60 value 87.128795
iter  70 value 87.128468
iter  80 value 87.126745
iter  90 value 87.044375
iter 100 value 83.850537
final  value 83.850537 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.384779 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.468568 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 115.037674 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.823233 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.998126 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.292431 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.326468 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.576302 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.225519 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 118.646313 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.212731 
final  value 94.038251 
converged
Fitting Repeat 2 

# weights:  507
initial  value 111.069450 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 112.175460 
iter  10 value 93.946272
final  value 93.946242 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.734641 
final  value 94.038251 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.269628 
final  value 94.038251 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.534774 
iter  10 value 93.960784
iter  20 value 88.600335
iter  30 value 84.861925
iter  40 value 84.466135
iter  50 value 84.166779
iter  60 value 84.132655
iter  70 value 84.120777
final  value 84.120272 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.415080 
iter  10 value 94.056704
iter  20 value 87.527054
iter  30 value 85.283477
iter  40 value 84.519315
iter  50 value 83.968426
iter  60 value 83.870724
iter  70 value 83.753994
iter  80 value 83.726490
final  value 83.726373 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.314505 
iter  10 value 94.002072
iter  20 value 87.517524
iter  30 value 86.369814
iter  40 value 84.627817
iter  50 value 84.326359
iter  60 value 84.146869
iter  70 value 84.120795
final  value 84.120272 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.161489 
iter  10 value 94.034764
iter  20 value 87.338181
iter  30 value 84.347443
iter  40 value 82.991452
iter  50 value 81.556817
iter  60 value 80.677887
iter  70 value 80.436006
iter  80 value 80.196555
iter  90 value 80.180992
iter  90 value 80.180991
iter  90 value 80.180991
final  value 80.180991 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.474907 
iter  10 value 94.207473
iter  20 value 94.058207
iter  30 value 93.040096
iter  40 value 87.638201
iter  50 value 83.517666
iter  60 value 82.669711
iter  70 value 81.822140
iter  80 value 81.324832
iter  90 value 80.521472
iter 100 value 80.215889
final  value 80.215889 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 120.124250 
iter  10 value 93.939283
iter  20 value 88.108661
iter  30 value 86.911839
iter  40 value 85.072022
iter  50 value 82.581061
iter  60 value 82.131635
iter  70 value 80.276333
iter  80 value 79.259737
iter  90 value 78.934746
iter 100 value 78.876839
final  value 78.876839 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.433369 
iter  10 value 94.062727
iter  20 value 90.826280
iter  30 value 86.612368
iter  40 value 84.664629
iter  50 value 84.545659
iter  60 value 84.444178
iter  70 value 84.237032
iter  80 value 82.423512
iter  90 value 80.408690
iter 100 value 80.073391
final  value 80.073391 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.028938 
iter  10 value 94.065471
iter  20 value 90.233466
iter  30 value 84.808177
iter  40 value 83.766245
iter  50 value 80.690453
iter  60 value 79.833326
iter  70 value 79.642776
iter  80 value 79.471081
iter  90 value 79.436072
iter 100 value 79.414384
final  value 79.414384 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 124.288608 
iter  10 value 93.685767
iter  20 value 84.989864
iter  30 value 83.169765
iter  40 value 82.926930
iter  50 value 82.379726
iter  60 value 81.885186
iter  70 value 81.585166
iter  80 value 81.524786
iter  90 value 81.361166
iter 100 value 81.007463
final  value 81.007463 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.110266 
iter  10 value 94.097081
iter  20 value 94.037851
iter  30 value 93.935069
iter  40 value 85.556075
iter  50 value 82.335400
iter  60 value 80.575940
iter  70 value 79.973387
iter  80 value 79.466266
iter  90 value 79.334825
iter 100 value 79.213193
final  value 79.213193 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 116.364600 
iter  10 value 95.428726
iter  20 value 84.347217
iter  30 value 81.857860
iter  40 value 81.339580
iter  50 value 80.412670
iter  60 value 79.798348
iter  70 value 79.463399
iter  80 value 79.265230
iter  90 value 78.965109
iter 100 value 78.822653
final  value 78.822653 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.144887 
iter  10 value 91.397319
iter  20 value 90.972911
iter  30 value 85.104713
iter  40 value 82.724196
iter  50 value 81.610230
iter  60 value 80.299065
iter  70 value 79.452615
iter  80 value 79.331506
iter  90 value 79.286565
iter 100 value 79.248079
final  value 79.248079 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.343478 
iter  10 value 93.936016
iter  20 value 84.209975
iter  30 value 81.178410
iter  40 value 80.036368
iter  50 value 79.812936
iter  60 value 79.673793
iter  70 value 79.510463
iter  80 value 79.225427
iter  90 value 79.186762
iter 100 value 79.057076
final  value 79.057076 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.916826 
iter  10 value 94.058971
iter  20 value 89.300098
iter  30 value 83.874425
iter  40 value 82.650881
iter  50 value 81.563070
iter  60 value 80.830835
iter  70 value 80.279403
iter  80 value 79.570178
iter  90 value 79.064231
iter 100 value 78.771081
final  value 78.771081 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 112.576553 
iter  10 value 95.120604
iter  20 value 93.104754
iter  30 value 87.913574
iter  40 value 82.671375
iter  50 value 81.431078
iter  60 value 80.587475
iter  70 value 79.732590
iter  80 value 79.404453
iter  90 value 79.008293
iter 100 value 78.851741
final  value 78.851741 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 107.162653 
final  value 94.054823 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.423397 
final  value 94.056445 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.667115 
final  value 94.054977 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.102103 
final  value 94.054838 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.813645 
final  value 93.877916 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.525671 
iter  10 value 94.043216
iter  20 value 93.827046
iter  30 value 84.601033
iter  40 value 84.545167
iter  50 value 82.964217
iter  60 value 81.238039
iter  70 value 81.192018
iter  80 value 81.191797
iter  90 value 81.190410
iter 100 value 81.183709
final  value 81.183709 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 98.283270 
iter  10 value 94.057805
iter  20 value 93.967118
iter  30 value 86.422869
iter  40 value 86.355288
iter  50 value 86.354526
iter  60 value 83.956306
iter  70 value 83.953815
iter  80 value 83.953751
iter  90 value 83.953522
final  value 83.953516 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.670598 
iter  10 value 93.974135
iter  20 value 93.671825
iter  30 value 92.524778
final  value 92.502055 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.970686 
iter  10 value 94.057199
iter  20 value 93.898519
iter  30 value 85.321512
iter  40 value 84.638362
iter  50 value 80.177754
iter  60 value 78.588307
iter  70 value 78.265136
iter  80 value 78.256564
iter  90 value 78.255565
iter 100 value 77.555991
final  value 77.555991 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.593843 
iter  10 value 94.043319
iter  20 value 93.496660
iter  30 value 93.297227
iter  40 value 92.369848
iter  50 value 92.126475
iter  60 value 92.126119
iter  60 value 92.126119
iter  60 value 92.126119
final  value 92.126119 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.201333 
iter  10 value 93.877738
iter  20 value 93.871412
iter  30 value 84.574057
iter  40 value 84.398140
iter  50 value 84.395995
iter  60 value 83.097295
iter  70 value 82.641996
final  value 82.479562 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.329269 
iter  10 value 94.064895
iter  20 value 94.057365
iter  30 value 93.988712
iter  40 value 86.967878
iter  50 value 85.318635
iter  60 value 83.793984
iter  70 value 83.788225
iter  80 value 83.774894
iter  90 value 83.758902
iter 100 value 83.580492
final  value 83.580492 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.968840 
iter  10 value 92.401029
iter  20 value 91.266747
iter  30 value 90.790634
iter  40 value 90.789852
iter  50 value 88.970163
iter  60 value 81.728736
iter  70 value 80.415999
iter  80 value 79.848411
iter  90 value 79.451327
iter 100 value 79.172312
final  value 79.172312 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 128.118534 
iter  10 value 93.892981
iter  20 value 93.832022
iter  30 value 93.723105
iter  40 value 82.524775
iter  50 value 82.148051
iter  60 value 82.128174
final  value 82.121880 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.178633 
iter  10 value 94.060024
iter  20 value 93.946087
iter  30 value 83.520129
iter  40 value 83.445202
iter  50 value 83.444841
iter  50 value 83.444840
final  value 83.444840 
converged
Fitting Repeat 1 

# weights:  103
initial  value 118.797152 
final  value 94.467391 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.826325 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.773457 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.190745 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.387297 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.585466 
final  value 94.467391 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.589722 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.635889 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.465277 
final  value 94.467391 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.095210 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 124.510123 
iter  10 value 89.696795
iter  20 value 87.289619
iter  30 value 85.463416
iter  40 value 84.771900
final  value 84.767548 
converged
Fitting Repeat 2 

# weights:  507
initial  value 135.232514 
iter  10 value 94.484213
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.420822 
final  value 94.484210 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.054176 
iter  10 value 94.374384
iter  20 value 87.595699
iter  30 value 87.584840
final  value 87.584678 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.428785 
final  value 94.482478 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.941658 
iter  10 value 94.488550
iter  20 value 94.424845
iter  30 value 93.744068
iter  40 value 86.618033
iter  50 value 85.917642
iter  60 value 85.462866
iter  70 value 85.274448
iter  80 value 84.900262
iter  90 value 83.519357
iter 100 value 82.601887
final  value 82.601887 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 113.467006 
iter  10 value 94.340733
iter  20 value 87.939038
iter  30 value 87.279384
iter  40 value 87.119805
iter  50 value 86.665400
iter  60 value 86.425920
iter  70 value 86.375068
final  value 86.371522 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.044729 
iter  10 value 94.481946
iter  20 value 87.303936
iter  30 value 86.239036
iter  40 value 85.882511
iter  50 value 83.177911
iter  60 value 82.795373
final  value 82.776302 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.505537 
iter  10 value 94.492866
iter  20 value 94.488258
iter  30 value 87.294906
iter  40 value 86.881379
final  value 86.808030 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.808485 
iter  10 value 94.494527
iter  20 value 94.486390
iter  30 value 94.146180
iter  40 value 93.184899
iter  50 value 88.197671
iter  60 value 86.102794
iter  70 value 83.868031
iter  80 value 83.785317
iter  90 value 83.733964
iter 100 value 83.508249
final  value 83.508249 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 118.009221 
iter  10 value 94.564252
iter  20 value 90.011043
iter  30 value 88.204962
iter  40 value 87.365660
iter  50 value 84.807903
iter  60 value 82.279491
iter  70 value 81.602116
iter  80 value 81.217363
iter  90 value 80.878751
iter 100 value 80.844328
final  value 80.844328 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 125.921208 
iter  10 value 94.350057
iter  20 value 87.940792
iter  30 value 86.439027
iter  40 value 85.518378
iter  50 value 84.101208
iter  60 value 83.547918
iter  70 value 83.127820
iter  80 value 82.623327
iter  90 value 82.436835
iter 100 value 82.295022
final  value 82.295022 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.229504 
iter  10 value 94.443412
iter  20 value 92.002161
iter  30 value 84.931940
iter  40 value 84.233749
iter  50 value 83.995851
iter  60 value 83.619174
iter  70 value 83.391709
iter  80 value 83.206944
iter  90 value 82.966111
iter 100 value 82.936168
final  value 82.936168 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.589844 
iter  10 value 94.901705
iter  20 value 94.547277
iter  30 value 88.248456
iter  40 value 86.519301
iter  50 value 84.619800
iter  60 value 83.504972
iter  70 value 82.989106
iter  80 value 82.953871
iter  90 value 82.866902
iter 100 value 81.779052
final  value 81.779052 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.410742 
iter  10 value 94.070027
iter  20 value 88.318266
iter  30 value 87.574714
iter  40 value 84.352287
iter  50 value 83.694866
iter  60 value 82.933169
iter  70 value 82.453641
iter  80 value 81.396100
iter  90 value 80.964356
iter 100 value 80.886227
final  value 80.886227 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 127.421371 
iter  10 value 94.451296
iter  20 value 89.065052
iter  30 value 86.585519
iter  40 value 86.173044
iter  50 value 85.924083
iter  60 value 85.894842
iter  70 value 85.723316
iter  80 value 83.609587
iter  90 value 82.774322
iter 100 value 82.079799
final  value 82.079799 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 114.350756 
iter  10 value 94.648965
iter  20 value 92.961573
iter  30 value 89.714875
iter  40 value 88.411724
iter  50 value 87.282587
iter  60 value 86.737361
iter  70 value 86.395506
iter  80 value 86.278378
iter  90 value 85.995406
iter 100 value 84.506439
final  value 84.506439 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.009354 
iter  10 value 93.735443
iter  20 value 87.638144
iter  30 value 83.668193
iter  40 value 82.788882
iter  50 value 82.165178
iter  60 value 81.425267
iter  70 value 81.111218
iter  80 value 81.017917
iter  90 value 80.882360
iter 100 value 80.790180
final  value 80.790180 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 118.077914 
iter  10 value 94.468099
iter  20 value 87.268479
iter  30 value 86.853611
iter  40 value 85.799073
iter  50 value 83.119160
iter  60 value 81.494174
iter  70 value 80.935200
iter  80 value 80.843484
iter  90 value 80.808597
iter 100 value 80.801708
final  value 80.801708 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.645222 
iter  10 value 94.602324
iter  20 value 87.068433
iter  30 value 86.224274
iter  40 value 85.565101
iter  50 value 83.785111
iter  60 value 82.151002
iter  70 value 81.537896
iter  80 value 80.853889
iter  90 value 80.605414
iter 100 value 80.525109
final  value 80.525109 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.125499 
final  value 94.485825 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.983209 
final  value 94.468806 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.521903 
final  value 94.485711 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.553611 
final  value 94.485619 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.511902 
final  value 94.485807 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.261072 
iter  10 value 94.488882
iter  20 value 94.442472
iter  30 value 90.294188
iter  40 value 90.278797
iter  50 value 89.964887
iter  60 value 89.257294
iter  70 value 88.641542
iter  80 value 82.367890
iter  90 value 82.021304
iter 100 value 81.951556
final  value 81.951556 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.758104 
iter  10 value 94.472234
iter  20 value 86.915042
iter  30 value 85.942555
iter  40 value 85.344482
iter  50 value 85.049066
iter  60 value 85.015446
iter  70 value 85.010436
iter  80 value 85.007995
iter  90 value 85.006759
iter 100 value 85.006142
final  value 85.006142 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 98.138044 
iter  10 value 94.444303
iter  20 value 94.428337
iter  30 value 94.258872
iter  40 value 94.241703
iter  50 value 94.241090
final  value 94.239773 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.803431 
iter  10 value 92.195879
iter  20 value 90.783092
iter  30 value 85.992959
iter  40 value 85.989406
iter  50 value 85.959480
iter  60 value 85.772172
iter  70 value 85.741890
iter  80 value 85.263714
iter  90 value 85.263593
iter 100 value 85.263519
final  value 85.263519 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.966895 
iter  10 value 94.489387
iter  20 value 94.483044
iter  30 value 87.874935
iter  40 value 87.344013
iter  50 value 86.936611
iter  60 value 86.929620
iter  60 value 86.929619
final  value 86.929619 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.846068 
iter  10 value 94.475014
iter  20 value 93.295497
iter  30 value 82.879156
iter  40 value 81.858558
iter  50 value 80.491794
iter  60 value 80.437911
iter  70 value 80.275164
iter  80 value 80.269184
iter  90 value 80.269025
iter 100 value 80.268554
final  value 80.268554 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 134.140507 
iter  10 value 86.337968
iter  20 value 86.208293
iter  30 value 86.149769
iter  40 value 86.047161
iter  50 value 86.045362
iter  60 value 86.043080
iter  70 value 85.304947
iter  80 value 84.956795
iter  90 value 84.956137
iter 100 value 84.953667
final  value 84.953667 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.933277 
iter  10 value 94.493952
iter  20 value 94.483553
iter  30 value 87.358577
iter  40 value 86.179898
iter  50 value 82.233368
iter  60 value 82.079495
iter  70 value 82.079278
iter  80 value 82.078738
iter  90 value 82.078588
iter 100 value 82.069898
final  value 82.069898 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 95.902501 
iter  10 value 94.491956
iter  20 value 94.343268
iter  30 value 85.258727
final  value 85.240573 
converged
Fitting Repeat 5 

# weights:  507
initial  value 117.200271 
iter  10 value 94.431386
iter  20 value 93.061667
iter  30 value 83.726607
iter  40 value 83.183252
iter  50 value 83.178907
iter  60 value 82.746527
iter  70 value 82.744464
iter  80 value 82.743247
iter  80 value 82.743247
final  value 82.743247 
converged
Fitting Repeat 1 

# weights:  305
initial  value 148.633279 
iter  10 value 117.912275
iter  20 value 112.639143
iter  30 value 108.692641
iter  40 value 106.591878
iter  50 value 105.556985
iter  60 value 103.152171
iter  70 value 102.291029
iter  80 value 101.423825
iter  90 value 101.373625
iter 100 value 101.353104
final  value 101.353104 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 129.233220 
iter  10 value 117.801896
iter  20 value 114.074372
iter  30 value 112.795182
iter  40 value 110.877434
iter  50 value 105.910446
iter  60 value 103.589846
iter  70 value 102.147877
iter  80 value 101.714555
iter  90 value 101.316971
iter 100 value 101.129365
final  value 101.129365 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 126.842884 
iter  10 value 118.043611
iter  20 value 117.871653
iter  30 value 109.015382
iter  40 value 106.561263
iter  50 value 105.051021
iter  60 value 102.050738
iter  70 value 101.223911
iter  80 value 101.062548
iter  90 value 100.928909
iter 100 value 100.805565
final  value 100.805565 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 144.500413 
iter  10 value 115.067794
iter  20 value 107.705880
iter  30 value 106.627341
iter  40 value 106.174731
iter  50 value 105.335844
iter  60 value 103.466350
iter  70 value 102.297329
iter  80 value 102.017184
iter  90 value 101.593697
iter 100 value 101.300742
final  value 101.300742 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 124.183630 
iter  10 value 111.309674
iter  20 value 106.121460
iter  30 value 104.985210
iter  40 value 103.654594
iter  50 value 101.706912
iter  60 value 101.225992
iter  70 value 101.028376
iter  80 value 100.943817
iter  90 value 100.899585
iter 100 value 100.693963
final  value 100.693963 
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 -- Sat May 16 00:54:40 2026 
*********************************************** 
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 
 40.546   1.235  83.601