##############################################################################
##############################################################################
###
### Running command:
###
###   E:\biocbuild\bbs-3.19-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=E:\biocbuild\bbs-3.19-bioc\R\library --no-vignettes --timings HPiP_1.10.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory 'E:/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck'
* using R version 4.4.1 (2024-06-14 ucrt)
* using platform: x86_64-w64-mingw32
* R was compiled by
    gcc.exe (GCC) 13.2.0
    GNU Fortran (GCC) 13.2.0
* running under: Windows Server 2022 x64 (build 20348)
* using session charset: UTF-8
* using option '--no-vignettes'
* checking for file 'HPiP/DESCRIPTION' ... OK
* checking extension type ... Package
* this is package 'HPiP' version '1.10.0'
* 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 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
FSmethod      34.33   1.67   36.20
corr_plot     33.34   1.48   34.86
var_imp       32.26   1.17   33.59
pred_ensembel 15.12   0.61   11.35
enrichfindP    0.69   0.06   12.63
* 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
  'E:/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck/00check.log'
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   E:\biocbuild\bbs-3.19-bioc\R\bin\R.exe CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library 'E:/biocbuild/bbs-3.19-bioc/R/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 (2024-06-14 ucrt) -- "Race for Your Life"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64

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

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

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

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

# weights:  103
initial  value 96.573924 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.917712 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 116.250105 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.446622 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.256815 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.586495 
iter  10 value 91.106972
iter  20 value 90.322505
iter  30 value 89.930119
iter  40 value 89.927884
final  value 89.927851 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.774612 
iter  10 value 92.257263
final  value 92.243290 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.033868 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.363912 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 112.639947 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.723478 
final  value 93.836066 
converged
Fitting Repeat 2 

# weights:  507
initial  value 111.918275 
iter  10 value 92.033476
iter  20 value 92.029799
final  value 92.029796 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.751288 
final  value 93.836066 
converged
Fitting Repeat 4 

# weights:  507
initial  value 125.621708 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 113.785403 
iter  10 value 86.953381
iter  20 value 84.220256
iter  30 value 79.409167
iter  40 value 77.617218
iter  50 value 76.680969
iter  60 value 75.669995
iter  70 value 75.591695
iter  80 value 75.588357
iter  90 value 75.588084
iter 100 value 75.588018
final  value 75.588018 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.785741 
iter  10 value 93.908808
iter  20 value 93.081837
iter  30 value 87.530382
iter  40 value 83.580356
iter  50 value 83.403366
iter  60 value 82.791228
iter  70 value 82.454527
iter  80 value 82.313218
final  value 82.308846 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.416928 
iter  10 value 94.068062
iter  20 value 94.023844
iter  30 value 92.942749
iter  40 value 92.738818
iter  50 value 92.709899
iter  60 value 91.690658
iter  70 value 88.122200
iter  80 value 87.577820
iter  90 value 86.532122
iter 100 value 82.981652
final  value 82.981652 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 99.656688 
iter  10 value 94.028889
iter  20 value 92.719814
iter  30 value 92.536487
iter  40 value 90.553019
iter  50 value 84.088263
iter  60 value 83.085422
iter  70 value 82.453732
iter  80 value 82.360130
iter  90 value 82.323260
final  value 82.303200 
converged
Fitting Repeat 4 

# weights:  103
initial  value 108.285907 
iter  10 value 94.046296
iter  20 value 92.946320
iter  30 value 92.716041
iter  40 value 92.671315
iter  50 value 92.520143
iter  60 value 92.212821
iter  70 value 90.829926
iter  80 value 83.755204
iter  90 value 83.216056
iter 100 value 81.637073
final  value 81.637073 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 98.121194 
iter  10 value 94.142900
iter  20 value 94.032495
iter  30 value 92.677157
iter  40 value 92.393445
iter  50 value 91.612687
iter  60 value 90.949358
iter  70 value 87.592812
iter  80 value 85.553517
iter  90 value 85.405204
iter 100 value 84.954152
final  value 84.954152 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 109.037226 
iter  10 value 94.280929
iter  20 value 92.800347
iter  30 value 86.994260
iter  40 value 83.265174
iter  50 value 80.065947
iter  60 value 79.352676
iter  70 value 78.602365
iter  80 value 78.344404
iter  90 value 78.154117
iter 100 value 78.101281
final  value 78.101281 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.868443 
iter  10 value 94.680478
iter  20 value 92.796830
iter  30 value 91.826240
iter  40 value 86.850155
iter  50 value 83.000729
iter  60 value 82.315519
iter  70 value 82.086472
iter  80 value 82.014168
iter  90 value 81.973915
iter 100 value 81.753138
final  value 81.753138 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 116.639957 
iter  10 value 94.319560
iter  20 value 88.872371
iter  30 value 82.958490
iter  40 value 82.197613
iter  50 value 82.077538
iter  60 value 82.004344
iter  70 value 80.977716
iter  80 value 80.604495
iter  90 value 80.172717
iter 100 value 79.691360
final  value 79.691360 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.719018 
iter  10 value 93.853243
iter  20 value 93.042682
iter  30 value 92.904702
iter  40 value 90.603405
iter  50 value 82.536478
iter  60 value 80.388132
iter  70 value 78.507452
iter  80 value 77.647845
iter  90 value 77.402222
iter 100 value 77.335822
final  value 77.335822 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.363170 
iter  10 value 93.902483
iter  20 value 88.938782
iter  30 value 87.913726
iter  40 value 85.897430
iter  50 value 82.590994
iter  60 value 79.901477
iter  70 value 78.966736
iter  80 value 78.052787
iter  90 value 77.848973
iter 100 value 77.838696
final  value 77.838696 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.247775 
iter  10 value 94.170223
iter  20 value 93.769281
iter  30 value 92.811068
iter  40 value 87.090032
iter  50 value 83.682258
iter  60 value 80.290090
iter  70 value 79.457679
iter  80 value 78.869560
iter  90 value 78.176358
iter 100 value 78.101057
final  value 78.101057 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.651368 
iter  10 value 94.492761
iter  20 value 94.064775
iter  30 value 84.274128
iter  40 value 82.862895
iter  50 value 82.298183
iter  60 value 81.156212
iter  70 value 79.864178
iter  80 value 79.472091
iter  90 value 79.238642
iter 100 value 79.200444
final  value 79.200444 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.019863 
iter  10 value 94.046995
iter  20 value 92.756647
iter  30 value 89.961237
iter  40 value 84.119857
iter  50 value 82.562956
iter  60 value 80.211165
iter  70 value 78.663214
iter  80 value 78.185333
iter  90 value 78.141474
iter 100 value 77.709261
final  value 77.709261 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.476226 
iter  10 value 93.697216
iter  20 value 92.661548
iter  30 value 89.154810
iter  40 value 84.303867
iter  50 value 82.352572
iter  60 value 80.795503
iter  70 value 79.716205
iter  80 value 79.237453
iter  90 value 78.578785
iter 100 value 78.112370
final  value 78.112370 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.431517 
iter  10 value 93.915962
iter  20 value 90.209760
iter  30 value 86.680148
iter  40 value 85.946301
iter  50 value 85.242449
iter  60 value 82.369861
iter  70 value 82.083215
iter  80 value 81.821919
iter  90 value 80.798882
iter 100 value 78.519911
final  value 78.519911 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.166928 
final  value 94.054366 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.099671 
final  value 94.054777 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.623750 
final  value 94.054412 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.016910 
final  value 94.054536 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.619838 
iter  10 value 92.290422
iter  20 value 92.287677
iter  30 value 92.286534
iter  40 value 87.822141
iter  50 value 81.767190
iter  60 value 76.643659
iter  70 value 76.432853
iter  80 value 76.368835
iter  90 value 76.367418
final  value 76.367366 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.063657 
iter  10 value 94.057410
iter  20 value 94.053073
iter  30 value 92.605029
final  value 92.524160 
converged
Fitting Repeat 2 

# weights:  305
initial  value 117.171894 
iter  10 value 94.057987
iter  20 value 93.723346
iter  30 value 91.443847
iter  40 value 82.947377
iter  50 value 81.662996
iter  60 value 80.778960
iter  70 value 80.768063
iter  80 value 80.708414
iter  90 value 80.702331
final  value 80.702311 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.616582 
iter  10 value 93.841360
iter  20 value 93.593560
iter  30 value 92.374626
final  value 92.243738 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.313301 
iter  10 value 93.841430
iter  20 value 92.445313
iter  30 value 84.669830
iter  40 value 82.085908
iter  50 value 80.894491
iter  60 value 80.113447
iter  70 value 79.501088
iter  80 value 79.478001
iter  80 value 79.478001
iter  80 value 79.478001
final  value 79.478001 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.081814 
iter  10 value 93.815064
iter  20 value 93.614722
iter  30 value 90.183792
iter  40 value 90.176242
iter  50 value 90.147931
iter  60 value 90.068197
iter  70 value 83.282103
iter  80 value 82.216478
iter  90 value 82.150330
iter 100 value 82.132633
final  value 82.132633 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 100.512415 
iter  10 value 91.571118
iter  20 value 91.379517
iter  30 value 90.012469
iter  40 value 84.698989
iter  50 value 84.491060
iter  60 value 84.462553
iter  70 value 84.462305
iter  80 value 84.439624
iter  90 value 84.394727
iter 100 value 84.385975
final  value 84.385975 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 101.702416 
iter  10 value 89.905957
iter  20 value 82.062414
iter  30 value 82.004102
iter  40 value 81.989008
iter  40 value 81.989007
final  value 81.989007 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.109815 
iter  10 value 92.838749
iter  20 value 92.829484
iter  30 value 91.947511
iter  40 value 91.569124
iter  50 value 91.553777
iter  60 value 91.027272
iter  70 value 90.550698
iter  80 value 90.508933
iter  90 value 90.493088
iter 100 value 90.422966
final  value 90.422966 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 94.571293 
iter  10 value 94.057651
iter  20 value 92.983001
iter  30 value 92.014807
iter  40 value 86.018084
iter  50 value 81.098300
iter  60 value 80.354837
iter  70 value 79.108606
iter  80 value 77.498792
iter  90 value 77.498362
iter 100 value 76.656721
final  value 76.656721 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 97.307029 
iter  10 value 94.060167
iter  20 value 94.000473
iter  30 value 83.942002
iter  40 value 83.911862
iter  50 value 83.299709
iter  60 value 82.797004
iter  70 value 82.633777
final  value 82.633382 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.863401 
final  value 94.144481 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.566849 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.783817 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.795691 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.621639 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 123.596050 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.068512 
iter  10 value 94.326471
iter  10 value 94.326471
iter  10 value 94.326471
final  value 94.326471 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.184766 
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.507133 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.225849 
iter  10 value 94.300419
iter  20 value 94.283438
iter  30 value 94.283334
iter  30 value 94.283334
iter  30 value 94.283334
final  value 94.283334 
converged
Fitting Repeat 1 

# weights:  507
initial  value 111.953038 
final  value 94.088890 
converged
Fitting Repeat 2 

# weights:  507
initial  value 112.029179 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 110.342446 
iter  10 value 94.326471
iter  10 value 94.326471
iter  10 value 94.326471
final  value 94.326471 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.764877 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 110.200960 
iter  10 value 93.665315
iter  20 value 93.621813
final  value 93.621797 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.332824 
iter  10 value 94.489249
iter  20 value 90.677630
iter  30 value 89.187494
iter  40 value 88.918048
iter  50 value 88.635489
iter  60 value 88.306604
iter  70 value 88.261972
final  value 88.261876 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.235311 
iter  10 value 94.256529
iter  20 value 89.407059
iter  30 value 88.529335
iter  40 value 87.733768
iter  50 value 87.398151
iter  60 value 87.050931
iter  70 value 86.299102
iter  80 value 86.274432
final  value 86.274393 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.376713 
iter  10 value 94.458763
iter  20 value 92.043306
iter  30 value 90.775516
iter  40 value 90.410192
iter  50 value 90.025021
iter  60 value 88.858407
iter  70 value 87.218935
iter  80 value 86.713298
iter  90 value 86.662391
iter 100 value 86.457066
final  value 86.457066 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.905222 
iter  10 value 94.492659
iter  20 value 94.441516
iter  30 value 92.360044
iter  40 value 91.345953
iter  50 value 89.737693
iter  60 value 89.227488
iter  70 value 89.120026
iter  80 value 88.601604
iter  90 value 88.412165
iter 100 value 88.267608
final  value 88.267608 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.237956 
iter  10 value 94.475352
iter  20 value 93.704482
iter  30 value 91.218071
iter  40 value 90.691645
iter  50 value 88.139844
iter  60 value 87.942973
iter  70 value 87.862399
iter  80 value 87.002628
iter  90 value 86.187812
iter 100 value 86.118288
final  value 86.118288 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 105.656393 
iter  10 value 94.481327
iter  20 value 91.686784
iter  30 value 89.441035
iter  40 value 88.302272
iter  50 value 88.104429
iter  60 value 87.653947
iter  70 value 87.520408
iter  80 value 87.478853
iter  90 value 87.326751
iter 100 value 86.416925
final  value 86.416925 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 118.592083 
iter  10 value 94.324558
iter  20 value 90.663684
iter  30 value 89.354692
iter  40 value 89.150631
iter  50 value 88.781369
iter  60 value 87.287330
iter  70 value 86.268407
iter  80 value 86.035208
iter  90 value 85.819254
iter 100 value 85.792881
final  value 85.792881 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.655303 
iter  10 value 95.181196
iter  20 value 94.733021
iter  30 value 93.556883
iter  40 value 93.092379
iter  50 value 92.324127
iter  60 value 91.558191
iter  70 value 89.787600
iter  80 value 88.431371
iter  90 value 87.789624
iter 100 value 87.464440
final  value 87.464440 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 113.650610 
iter  10 value 94.567127
iter  20 value 93.819049
iter  30 value 88.838758
iter  40 value 88.597053
iter  50 value 88.089929
iter  60 value 86.466782
iter  70 value 86.014530
iter  80 value 85.704406
iter  90 value 85.554877
iter 100 value 85.552543
final  value 85.552543 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.083924 
iter  10 value 94.454802
iter  20 value 94.175964
iter  30 value 90.757226
iter  40 value 88.705706
iter  50 value 87.115168
iter  60 value 86.529133
iter  70 value 86.105902
iter  80 value 85.329121
iter  90 value 85.294256
iter 100 value 85.219602
final  value 85.219602 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 111.850174 
iter  10 value 94.353699
iter  20 value 91.795615
iter  30 value 90.006731
iter  40 value 87.648215
iter  50 value 86.985609
iter  60 value 85.909328
iter  70 value 85.547214
iter  80 value 85.313557
iter  90 value 85.242131
iter 100 value 85.051904
final  value 85.051904 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.737587 
iter  10 value 92.323272
iter  20 value 89.222300
iter  30 value 88.212092
iter  40 value 87.341318
iter  50 value 86.721922
iter  60 value 86.519183
iter  70 value 86.062753
iter  80 value 86.030418
iter  90 value 85.627220
iter 100 value 85.279967
final  value 85.279967 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 119.367704 
iter  10 value 94.430928
iter  20 value 88.994385
iter  30 value 88.778232
iter  40 value 88.723342
iter  50 value 88.196473
iter  60 value 87.672378
iter  70 value 87.280830
iter  80 value 86.059769
iter  90 value 85.459124
iter 100 value 85.351832
final  value 85.351832 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.081088 
iter  10 value 94.348541
iter  20 value 93.624254
iter  30 value 88.564466
iter  40 value 88.072498
iter  50 value 87.754277
iter  60 value 87.489946
iter  70 value 87.170412
iter  80 value 86.392698
iter  90 value 85.551668
iter 100 value 85.372062
final  value 85.372062 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.912513 
iter  10 value 94.716467
iter  20 value 89.083236
iter  30 value 88.053906
iter  40 value 87.130352
iter  50 value 85.618995
iter  60 value 85.268547
iter  70 value 84.860487
iter  80 value 84.627912
iter  90 value 84.495798
iter 100 value 84.442811
final  value 84.442811 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.523823 
final  value 94.146159 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.870182 
final  value 94.485712 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.304765 
final  value 94.485930 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.629225 
final  value 94.485843 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.403263 
final  value 94.454789 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.461445 
iter  10 value 94.486800
final  value 94.484870 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.103608 
iter  10 value 94.489167
iter  20 value 94.475188
iter  30 value 93.408600
iter  40 value 90.989074
iter  50 value 88.873264
iter  60 value 88.513992
iter  70 value 88.197913
final  value 88.197123 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.566606 
iter  10 value 94.359157
iter  20 value 94.322126
iter  30 value 91.616453
iter  40 value 88.052510
iter  50 value 87.700643
iter  60 value 86.800043
final  value 86.798844 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.972883 
iter  10 value 94.359543
iter  20 value 94.355601
final  value 94.354926 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.066206 
iter  10 value 93.796780
iter  20 value 88.467495
iter  30 value 88.275548
iter  40 value 87.903952
iter  50 value 87.899541
iter  60 value 87.760009
iter  70 value 87.055379
iter  80 value 87.051971
final  value 87.051919 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.249559 
iter  10 value 94.491963
iter  20 value 94.484079
iter  30 value 90.627162
iter  40 value 90.610892
iter  50 value 88.919213
iter  60 value 88.917770
iter  70 value 88.917120
iter  80 value 88.917033
iter  90 value 88.513671
iter 100 value 88.352607
final  value 88.352607 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 99.126657 
iter  10 value 94.396359
iter  20 value 94.389992
iter  30 value 93.933457
iter  40 value 89.154949
iter  50 value 88.709602
iter  60 value 88.707978
iter  70 value 88.381985
iter  80 value 87.825565
iter  90 value 87.819590
iter 100 value 87.818564
final  value 87.818564 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.603494 
iter  10 value 94.152458
iter  20 value 93.998713
iter  30 value 89.809050
iter  40 value 89.519189
iter  50 value 86.784778
iter  60 value 85.503921
iter  70 value 85.051138
iter  80 value 84.862459
final  value 84.827641 
converged
Fitting Repeat 4 

# weights:  507
initial  value 111.474662 
iter  10 value 94.494087
iter  20 value 94.466535
iter  30 value 89.319406
iter  40 value 88.653990
iter  50 value 88.233111
iter  60 value 88.229192
final  value 88.229105 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.327497 
iter  10 value 94.490873
iter  20 value 94.350738
iter  30 value 92.116251
iter  40 value 90.240178
iter  50 value 90.236306
iter  60 value 90.236134
iter  70 value 90.235848
iter  80 value 90.235623
iter  90 value 90.235339
iter 100 value 90.088527
final  value 90.088527 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.140294 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.657018 
iter  10 value 94.112907
final  value 94.112903 
converged
Fitting Repeat 3 

# weights:  103
initial  value 114.193918 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.253713 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.856624 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.753948 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.306197 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.509824 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.438470 
final  value 94.448052 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.032120 
final  value 94.427726 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.903768 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.175816 
final  value 94.478286 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.687298 
iter  10 value 85.092890
iter  20 value 84.745702
iter  30 value 84.650065
iter  40 value 84.649952
final  value 84.649951 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.431465 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 120.372687 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.252842 
iter  10 value 94.488687
iter  20 value 91.275749
iter  30 value 88.900981
iter  40 value 86.140383
iter  50 value 85.698931
iter  60 value 84.807172
iter  70 value 84.201613
iter  80 value 83.789825
iter  90 value 83.725670
final  value 83.725640 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.636376 
iter  10 value 93.396780
iter  20 value 87.070906
iter  30 value 86.303396
iter  40 value 85.013332
iter  50 value 84.690616
iter  60 value 84.236378
iter  70 value 83.997428
iter  80 value 83.949402
iter  90 value 83.947580
final  value 83.947554 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.863254 
iter  10 value 94.478260
iter  20 value 94.319090
iter  30 value 94.316922
iter  40 value 93.038370
iter  50 value 86.936325
iter  60 value 86.518503
iter  70 value 85.584298
iter  80 value 84.451135
iter  90 value 84.161361
iter 100 value 84.117689
final  value 84.117689 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 98.873400 
iter  10 value 94.500545
iter  20 value 94.289074
iter  30 value 90.368268
iter  40 value 87.516396
iter  50 value 84.864792
iter  60 value 83.856673
iter  70 value 83.763536
iter  80 value 83.725442
final  value 83.724939 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.888218 
iter  10 value 94.288582
iter  20 value 94.190244
iter  30 value 86.390525
iter  40 value 85.158509
iter  50 value 84.874597
iter  60 value 84.588625
iter  70 value 84.064685
iter  80 value 83.955675
iter  90 value 83.947634
final  value 83.947554 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.956293 
iter  10 value 94.492241
iter  20 value 91.544401
iter  30 value 89.416903
iter  40 value 86.306760
iter  50 value 85.545456
iter  60 value 83.556955
iter  70 value 82.856444
iter  80 value 81.547451
iter  90 value 81.306959
iter 100 value 81.284043
final  value 81.284043 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.647805 
iter  10 value 90.826023
iter  20 value 87.443432
iter  30 value 86.089317
iter  40 value 85.819944
iter  50 value 85.749283
iter  60 value 85.467991
iter  70 value 83.835645
iter  80 value 81.900346
iter  90 value 81.380812
iter 100 value 81.340783
final  value 81.340783 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 120.870468 
iter  10 value 94.690221
iter  20 value 94.219044
iter  30 value 91.156364
iter  40 value 85.509901
iter  50 value 84.585574
iter  60 value 84.333394
iter  70 value 82.514843
iter  80 value 81.843363
iter  90 value 81.399990
iter 100 value 80.898185
final  value 80.898185 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.805893 
iter  10 value 91.990139
iter  20 value 88.577347
iter  30 value 88.062532
iter  40 value 84.303337
iter  50 value 82.691046
iter  60 value 82.535990
iter  70 value 82.430640
iter  80 value 81.759591
iter  90 value 81.188778
iter 100 value 80.851014
final  value 80.851014 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 110.633189 
iter  10 value 100.133633
iter  20 value 94.589973
iter  30 value 94.281083
iter  40 value 89.479986
iter  50 value 88.283912
iter  60 value 86.462598
iter  70 value 86.149603
iter  80 value 85.450929
iter  90 value 84.726719
iter 100 value 82.409757
final  value 82.409757 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 113.092276 
iter  10 value 94.534821
iter  20 value 94.488940
iter  30 value 88.910679
iter  40 value 84.635988
iter  50 value 84.391407
iter  60 value 84.043956
iter  70 value 83.518926
iter  80 value 82.321892
iter  90 value 81.590761
iter 100 value 81.231769
final  value 81.231769 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.964485 
iter  10 value 94.445241
iter  20 value 87.295852
iter  30 value 86.376903
iter  40 value 86.091461
iter  50 value 85.301377
iter  60 value 83.525805
iter  70 value 83.086290
iter  80 value 82.869333
iter  90 value 82.388224
iter 100 value 82.232524
final  value 82.232524 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 115.989371 
iter  10 value 94.443703
iter  20 value 89.490627
iter  30 value 88.186841
iter  40 value 85.135636
iter  50 value 83.891670
iter  60 value 83.783970
iter  70 value 83.570386
iter  80 value 83.444306
iter  90 value 83.059985
iter 100 value 82.604866
final  value 82.604866 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 116.177160 
iter  10 value 94.862889
iter  20 value 93.185347
iter  30 value 86.117466
iter  40 value 82.648940
iter  50 value 81.448525
iter  60 value 81.168480
iter  70 value 81.026207
iter  80 value 80.614765
iter  90 value 79.835634
iter 100 value 79.613994
final  value 79.613994 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 114.387787 
iter  10 value 94.792066
iter  20 value 94.215112
iter  30 value 86.263382
iter  40 value 84.813887
iter  50 value 84.396634
iter  60 value 84.164444
iter  70 value 83.796674
iter  80 value 82.079075
iter  90 value 81.132633
iter 100 value 80.565902
final  value 80.565902 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.212004 
final  value 94.485947 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.895562 
final  value 94.486189 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.256309 
final  value 94.485913 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.109770 
iter  10 value 94.114936
iter  20 value 94.114420
iter  30 value 94.113369
final  value 94.113336 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.821984 
final  value 94.485960 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.523885 
iter  10 value 93.877242
iter  20 value 93.838543
iter  30 value 93.837603
iter  40 value 93.833266
iter  50 value 93.832776
iter  60 value 93.758236
iter  70 value 92.139240
iter  80 value 85.068758
iter  90 value 82.769923
iter 100 value 79.838672
final  value 79.838672 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 122.477726 
iter  10 value 94.488935
iter  20 value 94.484491
iter  30 value 94.411426
iter  40 value 93.206545
iter  50 value 88.717450
iter  60 value 86.852850
iter  70 value 86.850709
iter  70 value 86.850708
iter  70 value 86.850708
final  value 86.850708 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.532420 
iter  10 value 94.488461
iter  20 value 93.887075
iter  30 value 86.076352
iter  40 value 85.845915
iter  50 value 85.808229
iter  60 value 85.654427
iter  70 value 85.644024
iter  80 value 83.390391
final  value 83.390379 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.092649 
iter  10 value 94.452842
iter  20 value 94.448722
iter  30 value 94.266495
iter  40 value 94.264941
final  value 94.264939 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.587661 
iter  10 value 94.489315
iter  20 value 94.397653
iter  30 value 92.334451
iter  40 value 91.991499
iter  50 value 91.910033
final  value 91.909614 
converged
Fitting Repeat 1 

# weights:  507
initial  value 112.476199 
iter  10 value 94.274506
iter  20 value 94.267026
iter  30 value 94.072689
iter  40 value 94.068258
iter  50 value 94.066872
final  value 94.066769 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.833563 
iter  10 value 94.492039
iter  20 value 88.056777
iter  30 value 86.629372
iter  40 value 86.628523
iter  50 value 85.262815
iter  60 value 83.821096
iter  70 value 83.237656
iter  80 value 83.213475
iter  90 value 83.212651
iter 100 value 83.212353
final  value 83.212353 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.317818 
iter  10 value 94.491799
iter  20 value 94.476437
iter  30 value 86.706854
iter  40 value 85.744700
iter  50 value 85.434327
iter  60 value 85.410328
iter  70 value 85.385934
iter  80 value 83.776959
iter  90 value 83.635901
iter 100 value 83.618900
final  value 83.618900 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 116.458578 
iter  10 value 94.492904
iter  20 value 94.305464
iter  30 value 86.125607
iter  40 value 85.755940
iter  50 value 85.610969
iter  60 value 85.176093
iter  70 value 85.056658
iter  80 value 85.055695
final  value 85.055600 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.562424 
iter  10 value 85.514633
iter  20 value 83.018195
iter  30 value 82.751337
iter  40 value 82.749766
iter  50 value 81.582981
iter  60 value 80.557369
iter  70 value 80.106208
iter  80 value 80.095822
iter  90 value 79.850613
iter 100 value 79.689780
final  value 79.689780 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.134171 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.860177 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.331728 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.853780 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 111.349853 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.903592 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.783215 
final  value 94.461538 
converged
Fitting Repeat 3 

# weights:  305
initial  value 113.269968 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.524748 
final  value 94.483334 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.685829 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.244478 
iter  10 value 94.467027
iter  20 value 94.466825
iter  20 value 94.466824
iter  20 value 94.466824
final  value 94.466824 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.124246 
final  value 94.427726 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.500833 
iter  10 value 93.963334
iter  20 value 92.061894
iter  30 value 91.345657
iter  40 value 90.309887
iter  50 value 90.227548
iter  60 value 90.215934
iter  70 value 90.215604
final  value 90.215602 
converged
Fitting Repeat 4 

# weights:  507
initial  value 114.302622 
iter  10 value 88.107443
iter  20 value 87.464043
final  value 87.464042 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.973546 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.849435 
iter  10 value 94.112776
iter  20 value 90.939970
iter  30 value 90.046830
iter  40 value 84.756220
iter  50 value 83.933270
iter  60 value 83.051880
iter  70 value 80.625907
iter  80 value 79.942021
iter  90 value 79.856817
final  value 79.856105 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.647445 
iter  10 value 94.367280
iter  20 value 87.080658
iter  30 value 84.212438
iter  40 value 82.507853
iter  50 value 82.343153
iter  60 value 82.184198
iter  70 value 82.129856
final  value 82.129666 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.389663 
iter  10 value 94.428475
iter  20 value 88.485692
iter  30 value 88.074667
iter  40 value 85.806900
iter  50 value 85.214287
iter  60 value 84.948577
iter  70 value 83.298319
iter  80 value 80.619367
iter  90 value 79.353227
iter 100 value 79.263663
final  value 79.263663 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.795889 
iter  10 value 94.491071
iter  20 value 93.198711
iter  30 value 87.490704
iter  40 value 87.119085
iter  50 value 82.852641
iter  60 value 82.363686
iter  70 value 82.341243
iter  80 value 82.135678
final  value 82.129666 
converged
Fitting Repeat 5 

# weights:  103
initial  value 111.861288 
iter  10 value 94.485648
iter  20 value 87.500071
iter  30 value 85.840257
iter  40 value 85.192672
iter  50 value 84.130393
iter  60 value 83.974439
iter  70 value 80.372220
iter  80 value 79.900208
iter  90 value 79.877016
iter 100 value 79.858376
final  value 79.858376 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 100.900378 
iter  10 value 94.512832
iter  20 value 94.469457
iter  30 value 86.175138
iter  40 value 84.876297
iter  50 value 83.565373
iter  60 value 81.416903
iter  70 value 79.947659
iter  80 value 79.793150
iter  90 value 79.559506
iter 100 value 79.459230
final  value 79.459230 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.623729 
iter  10 value 94.709355
iter  20 value 91.984074
iter  30 value 90.730968
iter  40 value 90.527972
iter  50 value 87.780295
iter  60 value 82.454187
iter  70 value 81.713623
iter  80 value 79.628102
iter  90 value 78.623258
iter 100 value 78.163595
final  value 78.163595 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.387437 
iter  10 value 94.268109
iter  20 value 86.568374
iter  30 value 84.093252
iter  40 value 83.421589
iter  50 value 80.977594
iter  60 value 79.558537
iter  70 value 79.536416
iter  80 value 79.532677
iter  90 value 79.531385
iter 100 value 79.527618
final  value 79.527618 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.933223 
iter  10 value 94.580960
iter  20 value 91.193393
iter  30 value 86.865927
iter  40 value 85.598310
iter  50 value 83.257885
iter  60 value 81.957286
iter  70 value 81.766887
iter  80 value 81.725299
iter  90 value 81.553168
iter 100 value 80.220117
final  value 80.220117 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.086772 
iter  10 value 94.533010
iter  20 value 93.278215
iter  30 value 88.211183
iter  40 value 82.328688
iter  50 value 81.332697
iter  60 value 80.462038
iter  70 value 79.585129
iter  80 value 79.415674
iter  90 value 79.268697
iter 100 value 79.164115
final  value 79.164115 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.182996 
iter  10 value 94.614622
iter  20 value 94.492584
iter  30 value 93.223394
iter  40 value 84.209619
iter  50 value 83.606411
iter  60 value 81.254798
iter  70 value 80.213153
iter  80 value 79.826586
iter  90 value 79.388229
iter 100 value 79.112864
final  value 79.112864 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 127.450901 
iter  10 value 95.054748
iter  20 value 87.455785
iter  30 value 84.628602
iter  40 value 80.641274
iter  50 value 79.595272
iter  60 value 79.261099
iter  70 value 78.660918
iter  80 value 78.526981
iter  90 value 78.488974
iter 100 value 78.277815
final  value 78.277815 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 121.844468 
iter  10 value 94.389879
iter  20 value 88.668543
iter  30 value 82.664400
iter  40 value 80.645845
iter  50 value 79.762390
iter  60 value 79.598892
iter  70 value 79.397619
iter  80 value 79.270346
iter  90 value 79.093990
iter 100 value 78.831086
final  value 78.831086 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 116.577163 
iter  10 value 94.557197
iter  20 value 93.501372
iter  30 value 84.830546
iter  40 value 83.601579
iter  50 value 82.577487
iter  60 value 80.946649
iter  70 value 79.106317
iter  80 value 78.742240
iter  90 value 78.571625
iter 100 value 78.494181
final  value 78.494181 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.721613 
iter  10 value 93.437300
iter  20 value 85.160889
iter  30 value 81.677816
iter  40 value 80.887644
iter  50 value 80.606808
iter  60 value 80.449098
iter  70 value 80.310885
iter  80 value 79.825930
iter  90 value 78.778089
iter 100 value 78.613913
final  value 78.613913 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.909085 
final  value 94.485869 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.096777 
final  value 94.486016 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.443407 
final  value 94.485748 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.498651 
iter  10 value 94.485606
iter  20 value 90.845375
iter  30 value 89.864890
iter  40 value 89.092800
iter  50 value 89.092043
iter  60 value 89.087494
iter  70 value 88.998749
iter  80 value 88.998431
iter  90 value 88.998317
final  value 88.998310 
converged
Fitting Repeat 5 

# weights:  103
initial  value 113.612781 
iter  10 value 94.485859
iter  20 value 94.456498
iter  30 value 88.980732
iter  40 value 88.894514
iter  50 value 88.890631
iter  60 value 88.884147
iter  70 value 88.883815
iter  80 value 88.883726
iter  90 value 88.883638
final  value 88.883539 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.443528 
iter  10 value 94.454095
iter  20 value 94.419247
final  value 94.254256 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.849838 
iter  10 value 94.471634
iter  20 value 94.369521
iter  30 value 94.167342
iter  40 value 94.165964
iter  50 value 94.165860
final  value 94.165826 
converged
Fitting Repeat 3 

# weights:  305
initial  value 124.656321 
iter  10 value 94.473306
iter  20 value 94.415075
iter  30 value 94.410111
iter  40 value 94.258748
final  value 94.253911 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.945892 
iter  10 value 94.488673
iter  20 value 94.021461
iter  30 value 85.128704
iter  40 value 85.104682
final  value 85.104662 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.973695 
iter  10 value 94.489261
iter  20 value 94.480117
iter  30 value 93.894467
iter  40 value 92.843896
iter  50 value 92.843592
iter  60 value 91.648239
iter  70 value 91.639523
iter  80 value 91.639395
final  value 91.639297 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.812984 
iter  10 value 94.492091
iter  20 value 89.760831
iter  30 value 80.191629
iter  40 value 80.157601
iter  50 value 80.157277
iter  60 value 79.710086
iter  70 value 78.854105
iter  80 value 78.706063
iter  90 value 78.666469
iter 100 value 78.663260
final  value 78.663260 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 99.057027 
iter  10 value 94.492403
iter  20 value 93.447935
iter  30 value 87.818547
iter  40 value 87.792819
iter  50 value 87.545293
iter  60 value 87.535075
iter  70 value 87.527390
iter  80 value 87.105200
iter  90 value 85.004366
iter 100 value 84.975149
final  value 84.975149 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.047785 
iter  10 value 94.492257
iter  20 value 94.484179
iter  30 value 94.387334
iter  40 value 91.803764
iter  50 value 91.637322
final  value 91.637228 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.265026 
iter  10 value 94.414148
iter  20 value 94.408107
iter  30 value 85.002211
iter  40 value 83.213427
iter  50 value 83.137874
iter  60 value 82.827107
iter  70 value 82.352159
iter  80 value 82.249939
iter  90 value 81.671000
iter 100 value 81.659652
final  value 81.659652 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 95.611449 
iter  10 value 88.696126
iter  20 value 86.571091
iter  30 value 86.551464
iter  40 value 86.384065
iter  50 value 86.168541
iter  60 value 86.118516
iter  70 value 86.109932
iter  80 value 85.584534
iter  90 value 85.532836
iter 100 value 85.529617
final  value 85.529617 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.520898 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 115.437463 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.115175 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.332462 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.888023 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.422910 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.810375 
iter  10 value 93.969040
iter  10 value 93.969040
iter  10 value 93.969040
final  value 93.969040 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.373191 
iter  10 value 85.435132
iter  20 value 80.823829
iter  30 value 80.822275
iter  40 value 80.819218
iter  50 value 80.704696
final  value 80.669264 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.863198 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.913276 
iter  10 value 91.815948
iter  20 value 90.790709
iter  30 value 90.783409
final  value 90.782946 
converged
Fitting Repeat 1 

# weights:  507
initial  value 118.082271 
final  value 93.288889 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.552202 
final  value 94.032967 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.046168 
final  value 93.967787 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.703635 
final  value 94.032967 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.697361 
iter  10 value 87.239587
iter  20 value 84.193867
iter  30 value 84.124042
final  value 84.123737 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.439531 
iter  10 value 94.071551
iter  20 value 94.012903
iter  30 value 93.560755
iter  40 value 91.295001
iter  50 value 88.398991
iter  60 value 84.547704
iter  70 value 83.006600
iter  80 value 82.974878
iter  90 value 82.970797
final  value 82.970582 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.770732 
iter  10 value 91.948440
iter  20 value 83.025086
iter  30 value 82.008600
iter  40 value 81.717643
iter  50 value 81.485014
iter  60 value 81.449059
iter  70 value 81.431516
final  value 81.431497 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.416395 
iter  10 value 94.023998
iter  20 value 92.914832
iter  30 value 89.346154
iter  40 value 87.662107
iter  50 value 86.956765
iter  60 value 82.176120
iter  70 value 81.910416
iter  80 value 81.870762
iter  90 value 81.823993
iter 100 value 81.803040
final  value 81.803040 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.209866 
iter  10 value 94.063735
iter  20 value 87.268576
iter  30 value 86.099154
iter  40 value 85.464922
iter  50 value 83.180542
iter  60 value 82.658649
iter  70 value 81.683205
iter  80 value 79.646670
iter  90 value 79.213524
final  value 79.208389 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.270072 
iter  10 value 93.874969
iter  20 value 90.857478
iter  30 value 85.065957
iter  40 value 83.664201
iter  50 value 81.563158
iter  60 value 81.057224
iter  70 value 80.963543
final  value 80.962730 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.701596 
iter  10 value 93.966555
iter  20 value 90.311424
iter  30 value 84.365704
iter  40 value 81.485135
iter  50 value 80.901325
iter  60 value 80.246218
iter  70 value 79.740860
iter  80 value 78.845654
iter  90 value 78.273904
iter 100 value 78.206651
final  value 78.206651 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.920634 
iter  10 value 89.023243
iter  20 value 83.585743
iter  30 value 82.028971
iter  40 value 81.571742
iter  50 value 81.193120
iter  60 value 80.191528
iter  70 value 79.762976
iter  80 value 79.618396
iter  90 value 79.443744
iter 100 value 79.411962
final  value 79.411962 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.736580 
iter  10 value 93.789327
iter  20 value 86.877075
iter  30 value 83.932325
iter  40 value 82.354198
iter  50 value 80.524122
iter  60 value 79.938738
iter  70 value 79.768204
iter  80 value 79.491874
iter  90 value 79.229359
iter 100 value 79.218113
final  value 79.218113 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 111.262309 
iter  10 value 94.055385
iter  20 value 82.681569
iter  30 value 82.065961
iter  40 value 81.981427
iter  50 value 81.850248
iter  60 value 81.602518
iter  70 value 79.870662
iter  80 value 79.021680
iter  90 value 78.431979
iter 100 value 78.269375
final  value 78.269375 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 113.018212 
iter  10 value 94.061052
iter  20 value 94.049396
iter  30 value 81.774721
iter  40 value 79.745995
iter  50 value 79.156944
iter  60 value 78.701689
iter  70 value 78.567015
iter  80 value 78.474673
iter  90 value 78.138782
iter 100 value 77.817561
final  value 77.817561 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 111.531139 
iter  10 value 87.072972
iter  20 value 82.985682
iter  30 value 82.230547
iter  40 value 81.726177
iter  50 value 81.583038
iter  60 value 80.733648
iter  70 value 79.795336
iter  80 value 78.900351
iter  90 value 78.202745
iter 100 value 77.620198
final  value 77.620198 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 135.241316 
iter  10 value 94.137725
iter  20 value 93.402930
iter  30 value 87.848080
iter  40 value 82.090058
iter  50 value 80.501184
iter  60 value 79.030182
iter  70 value 78.573375
iter  80 value 78.413009
iter  90 value 78.065349
iter 100 value 77.647158
final  value 77.647158 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 115.395301 
iter  10 value 93.981345
iter  20 value 92.051326
iter  30 value 86.654225
iter  40 value 83.329837
iter  50 value 81.040359
iter  60 value 79.243245
iter  70 value 78.344075
iter  80 value 77.908723
iter  90 value 77.872496
iter 100 value 77.834368
final  value 77.834368 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 114.375029 
iter  10 value 93.571121
iter  20 value 84.213995
iter  30 value 80.836690
iter  40 value 79.606695
iter  50 value 78.116060
iter  60 value 77.613379
iter  70 value 77.500866
iter  80 value 77.259036
iter  90 value 77.178120
iter 100 value 77.143776
final  value 77.143776 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 112.952290 
iter  10 value 94.034527
iter  20 value 93.391489
iter  30 value 92.458522
iter  40 value 82.100932
iter  50 value 79.752961
iter  60 value 79.285310
iter  70 value 78.325932
iter  80 value 77.979588
iter  90 value 77.900085
iter 100 value 77.717980
final  value 77.717980 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.925215 
final  value 94.054337 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.308921 
final  value 94.054575 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.834827 
final  value 94.054649 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.876381 
final  value 94.054625 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.593056 
iter  10 value 85.607695
iter  20 value 85.606440
final  value 85.605031 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.932439 
iter  10 value 94.057033
final  value 94.053261 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.617198 
iter  10 value 94.057072
iter  20 value 89.381428
iter  30 value 85.110534
iter  40 value 84.979269
iter  50 value 83.639801
iter  60 value 83.628112
iter  70 value 83.627707
iter  80 value 80.376209
iter  90 value 80.101307
iter 100 value 80.091622
final  value 80.091622 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.678922 
iter  10 value 93.821683
iter  20 value 88.926096
iter  30 value 87.626982
iter  40 value 82.659111
iter  50 value 82.448218
iter  60 value 81.802354
final  value 81.769486 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.554189 
iter  10 value 93.198884
iter  20 value 92.827111
iter  30 value 92.823291
iter  40 value 91.912737
iter  40 value 91.912737
iter  50 value 79.717819
iter  60 value 79.244218
final  value 79.235883 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.938653 
iter  10 value 94.058558
iter  20 value 93.725251
iter  30 value 91.584350
iter  40 value 90.399410
iter  50 value 90.342460
iter  60 value 90.342109
final  value 90.342050 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.271888 
iter  10 value 93.999797
iter  20 value 93.925075
iter  30 value 89.436272
iter  40 value 89.286542
iter  50 value 89.267225
iter  60 value 89.223164
final  value 89.223144 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.439765 
iter  10 value 94.059795
iter  20 value 94.043231
iter  30 value 93.295040
iter  40 value 92.771334
iter  50 value 90.747867
final  value 90.747722 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.523115 
iter  10 value 94.061146
iter  20 value 87.031419
iter  30 value 82.596386
iter  40 value 82.002989
iter  50 value 81.009762
iter  60 value 81.004170
iter  70 value 80.998725
final  value 80.998179 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.122814 
iter  10 value 85.183229
iter  20 value 81.514273
iter  30 value 81.302407
iter  40 value 80.943783
iter  50 value 80.939045
iter  60 value 80.909687
iter  70 value 80.897660
iter  80 value 80.896100
final  value 80.895119 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.461160 
iter  10 value 94.041262
iter  20 value 93.596077
iter  30 value 84.107400
iter  40 value 83.649889
iter  50 value 83.618891
iter  60 value 83.616491
iter  70 value 83.609818
iter  80 value 82.079402
iter  90 value 77.946573
iter 100 value 77.319174
final  value 77.319174 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 137.274677 
iter  10 value 117.766912
iter  20 value 117.759418
iter  30 value 117.232197
iter  40 value 104.469587
iter  50 value 104.287270
iter  60 value 104.278981
iter  70 value 103.952004
iter  80 value 103.770910
iter  90 value 103.711606
final  value 103.710634 
converged
Fitting Repeat 2 

# weights:  507
initial  value 125.207208 
iter  10 value 117.899359
iter  20 value 117.890939
iter  30 value 117.885119
iter  40 value 117.759049
iter  40 value 117.759048
iter  40 value 117.759048
final  value 117.759048 
converged
Fitting Repeat 3 

# weights:  507
initial  value 134.175492 
iter  10 value 117.615806
iter  20 value 117.577089
iter  30 value 117.513453
iter  40 value 117.512625
iter  50 value 117.511799
iter  50 value 117.511799
final  value 117.511799 
converged
Fitting Repeat 4 

# weights:  507
initial  value 119.048407 
iter  10 value 117.766109
iter  20 value 117.726913
iter  30 value 117.201608
iter  40 value 109.307450
iter  50 value 107.054590
iter  60 value 106.910895
iter  70 value 106.899735
iter  80 value 106.545458
iter  90 value 102.958938
iter 100 value 100.798420
final  value 100.798420 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 126.928445 
iter  10 value 117.547200
iter  20 value 117.545299
iter  30 value 117.538360
final  value 117.538080 
converged
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Mon Sep 23 01:44:05 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 
  47.01    2.12   51.50