##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings HPiP_1.14.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2025-02-19 r87757)
* using platform: aarch64-unknown-linux-gnu
* R was compiled by
    aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0
    GNU Fortran (GCC) 14.2.0
* running under: openEuler 24.03 (LTS-SP1)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.14.0’
* 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
var_imp       38.529  0.347  38.930
corr_plot     36.835  0.259  37.140
FSmethod      36.533  0.272  36.905
pred_ensembel 17.698  0.407  16.939
enrichfindP    0.509  0.016  18.923
getFASTA       0.073  0.004   5.522
* 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: 2 NOTEs
See
  ‘/home/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/R/R-devel_2025-02-19/site-library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.14.0’
** 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 Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu

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

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

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

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

# weights:  103
initial  value 96.778486 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.451566 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.056106 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.242134 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.671625 
final  value 94.147186 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.774148 
final  value 94.252875 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.430417 
iter  10 value 93.940938
iter  20 value 92.652730
iter  30 value 86.799033
iter  40 value 85.722536
iter  50 value 85.657527
iter  60 value 85.573967
iter  70 value 84.948032
iter  80 value 84.837965
final  value 84.837726 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.296755 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.954460 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 110.229159 
iter  10 value 93.437567
iter  20 value 91.693799
iter  30 value 91.693351
final  value 91.693344 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.791354 
iter  10 value 93.126149
iter  20 value 90.966153
final  value 90.963961 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.021723 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.348111 
final  value 94.275363 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.843699 
final  value 94.455556 
converged
Fitting Repeat 5 

# weights:  507
initial  value 110.191595 
iter  10 value 94.466842
iter  20 value 94.231594
iter  30 value 94.231398
iter  30 value 94.231397
iter  30 value 94.231397
final  value 94.231397 
converged
Fitting Repeat 1 

# weights:  103
initial  value 107.627025 
iter  10 value 94.545687
iter  20 value 94.449028
iter  30 value 94.224457
iter  40 value 94.124987
iter  50 value 94.107618
iter  60 value 94.103419
iter  70 value 94.012939
iter  80 value 93.784178
iter  90 value 93.772240
iter 100 value 86.459349
final  value 86.459349 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 98.263383 
iter  10 value 94.038131
iter  20 value 88.452128
iter  30 value 87.409791
iter  40 value 87.289068
iter  50 value 84.740409
iter  60 value 84.440885
iter  70 value 84.315885
final  value 84.300447 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.614767 
iter  10 value 94.419824
iter  20 value 87.227113
iter  30 value 86.183461
iter  40 value 84.703156
iter  50 value 84.300578
final  value 84.300447 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.489465 
iter  10 value 94.413232
iter  20 value 94.120304
iter  30 value 87.446008
iter  40 value 85.108462
iter  50 value 84.893586
iter  60 value 84.577099
iter  70 value 84.282777
iter  80 value 83.695077
iter  90 value 82.765184
iter 100 value 82.688965
final  value 82.688965 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 112.930143 
iter  10 value 94.415532
iter  20 value 88.431799
iter  30 value 87.232346
iter  40 value 86.046520
iter  50 value 85.222884
iter  60 value 84.232641
iter  70 value 82.510850
iter  80 value 82.386511
iter  90 value 82.309841
final  value 82.302663 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.041813 
iter  10 value 94.337859
iter  20 value 88.745430
iter  30 value 86.140608
iter  40 value 84.952185
iter  50 value 83.154611
iter  60 value 82.649229
iter  70 value 82.414047
iter  80 value 82.306682
iter  90 value 82.132037
iter 100 value 82.093042
final  value 82.093042 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.061927 
iter  10 value 90.961258
iter  20 value 85.688882
iter  30 value 84.532918
iter  40 value 82.553705
iter  50 value 81.963379
iter  60 value 81.703251
iter  70 value 81.409586
iter  80 value 81.221834
iter  90 value 81.085219
iter 100 value 81.043669
final  value 81.043669 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 125.128471 
iter  10 value 91.853163
iter  20 value 87.324523
iter  30 value 85.990012
iter  40 value 85.001566
iter  50 value 82.672886
iter  60 value 82.401675
iter  70 value 81.805890
iter  80 value 80.969769
iter  90 value 80.665017
iter 100 value 80.621245
final  value 80.621245 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 111.286118 
iter  10 value 94.902250
iter  20 value 93.928947
iter  30 value 91.276547
iter  40 value 87.205882
iter  50 value 85.689226
iter  60 value 84.470366
iter  70 value 84.129999
iter  80 value 83.648519
iter  90 value 82.883879
iter 100 value 82.521172
final  value 82.521172 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.230833 
iter  10 value 94.725872
iter  20 value 93.521852
iter  30 value 85.131709
iter  40 value 83.791964
iter  50 value 83.012851
iter  60 value 82.247672
iter  70 value 81.860671
iter  80 value 81.473415
iter  90 value 81.118473
iter 100 value 80.746760
final  value 80.746760 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.018354 
iter  10 value 95.592854
iter  20 value 93.990677
iter  30 value 87.641341
iter  40 value 84.815700
iter  50 value 82.371366
iter  60 value 81.916099
iter  70 value 81.667206
iter  80 value 81.262976
iter  90 value 81.011384
iter 100 value 80.810983
final  value 80.810983 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 119.924839 
iter  10 value 92.501722
iter  20 value 86.859264
iter  30 value 85.584502
iter  40 value 84.833492
iter  50 value 84.435520
iter  60 value 84.121709
iter  70 value 83.995921
iter  80 value 82.860596
iter  90 value 81.724155
iter 100 value 81.588525
final  value 81.588525 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.215069 
iter  10 value 94.786085
iter  20 value 92.703585
iter  30 value 89.946725
iter  40 value 85.721813
iter  50 value 84.395210
iter  60 value 83.662784
iter  70 value 83.539049
iter  80 value 83.139567
iter  90 value 82.278140
iter 100 value 81.917652
final  value 81.917652 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.030067 
iter  10 value 93.250285
iter  20 value 87.392797
iter  30 value 84.584050
iter  40 value 81.962585
iter  50 value 80.855884
iter  60 value 80.615654
iter  70 value 80.542285
iter  80 value 80.501502
iter  90 value 80.486199
iter 100 value 80.422675
final  value 80.422675 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 112.528952 
iter  10 value 93.168891
iter  20 value 89.874397
iter  30 value 85.156756
iter  40 value 83.500008
iter  50 value 82.382174
iter  60 value 81.797587
iter  70 value 81.568048
iter  80 value 81.435163
iter  90 value 81.184354
iter 100 value 81.091512
final  value 81.091512 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 105.241481 
final  value 94.485672 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.615728 
iter  10 value 94.485742
iter  20 value 94.478614
iter  30 value 92.349658
iter  40 value 91.089868
final  value 91.089776 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.860515 
final  value 94.485838 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.137217 
final  value 94.486053 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.337689 
iter  10 value 94.277021
iter  20 value 94.268509
iter  30 value 88.197070
iter  40 value 85.264396
iter  50 value 85.169870
final  value 85.169824 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.434438 
iter  10 value 94.490908
iter  20 value 94.485839
iter  30 value 90.957020
iter  40 value 85.436450
iter  50 value 85.433940
iter  60 value 85.432141
iter  70 value 82.067282
iter  80 value 80.727971
iter  90 value 80.611884
iter 100 value 80.587226
final  value 80.587226 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 112.922927 
iter  10 value 94.280191
iter  20 value 94.278931
iter  30 value 94.136496
iter  40 value 87.030117
iter  50 value 85.985979
iter  60 value 82.866714
iter  70 value 82.763235
iter  80 value 82.136591
iter  90 value 82.072250
iter 100 value 82.071003
final  value 82.071003 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 107.235813 
iter  10 value 94.460315
iter  20 value 94.457379
iter  30 value 94.457178
iter  30 value 94.457178
iter  30 value 94.457177
final  value 94.457177 
converged
Fitting Repeat 4 

# weights:  305
initial  value 113.072815 
iter  10 value 94.488480
iter  20 value 94.290952
iter  30 value 86.267519
iter  40 value 83.905815
final  value 83.904196 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.838396 
iter  10 value 94.488637
iter  20 value 94.484325
iter  20 value 94.484325
final  value 94.484325 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.863379 
iter  10 value 84.269092
iter  20 value 83.115178
iter  30 value 82.987991
iter  40 value 82.986696
iter  50 value 82.985441
iter  60 value 82.935848
iter  70 value 81.004692
iter  80 value 79.916995
iter  90 value 79.856930
iter 100 value 79.646703
final  value 79.646703 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 97.154636 
iter  10 value 94.486881
iter  20 value 94.313292
iter  30 value 90.092315
iter  40 value 89.773940
iter  50 value 89.591566
final  value 89.591557 
converged
Fitting Repeat 3 

# weights:  507
initial  value 111.434872 
iter  10 value 94.283614
iter  20 value 94.023176
iter  30 value 92.464160
iter  40 value 85.988254
iter  50 value 84.346656
iter  60 value 82.203447
iter  70 value 81.847857
iter  80 value 81.826435
iter  90 value 81.826112
final  value 81.825944 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.886748 
iter  10 value 94.012701
iter  20 value 93.696674
iter  30 value 93.695081
iter  40 value 93.679427
iter  50 value 93.658733
iter  60 value 93.651629
iter  70 value 84.576677
iter  80 value 83.054180
iter  90 value 82.955856
final  value 82.955382 
converged
Fitting Repeat 5 

# weights:  507
initial  value 133.269558 
iter  10 value 94.494097
iter  20 value 94.486247
final  value 94.275892 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.857160 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.300831 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.818617 
final  value 94.484130 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.100194 
final  value 94.200000 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.479980 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 120.043437 
iter  10 value 94.484212
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.776560 
final  value 94.473119 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.840970 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.903014 
iter  10 value 87.803119
iter  20 value 83.910118
iter  30 value 83.171387
iter  40 value 83.141888
iter  50 value 83.141776
iter  50 value 83.141775
iter  50 value 83.141775
final  value 83.141775 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.056468 
iter  10 value 94.480244
final  value 94.473118 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.444248 
iter  10 value 94.371856
iter  20 value 94.364990
final  value 94.364984 
converged
Fitting Repeat 2 

# weights:  507
initial  value 114.213807 
iter  10 value 94.473190
iter  20 value 94.473138
iter  20 value 94.473138
final  value 94.473133 
converged
Fitting Repeat 3 

# weights:  507
initial  value 126.715860 
iter  10 value 94.485483
iter  20 value 94.482705
iter  30 value 94.473183
final  value 94.473118 
converged
Fitting Repeat 4 

# weights:  507
initial  value 113.316253 
final  value 94.477594 
converged
Fitting Repeat 5 

# weights:  507
initial  value 123.569272 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.526939 
iter  10 value 93.926551
iter  20 value 88.076817
iter  30 value 87.159327
iter  40 value 87.090977
iter  50 value 86.058741
iter  60 value 85.205950
iter  70 value 85.097033
final  value 85.095737 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.894736 
iter  10 value 94.601010
iter  20 value 94.488398
iter  30 value 94.159102
iter  40 value 91.815039
iter  50 value 91.438094
iter  60 value 88.177234
iter  70 value 85.344989
iter  80 value 85.243727
iter  90 value 85.207483
iter 100 value 85.191785
final  value 85.191785 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 101.485821 
iter  10 value 94.487277
iter  20 value 94.192294
iter  30 value 94.100509
iter  40 value 93.103467
iter  50 value 85.297289
iter  60 value 84.397143
iter  70 value 84.057580
iter  80 value 83.907165
iter  90 value 83.747627
iter 100 value 83.329356
final  value 83.329356 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 109.283606 
iter  10 value 94.486611
iter  20 value 94.162617
iter  30 value 89.780116
iter  40 value 88.806721
iter  50 value 88.414738
iter  60 value 87.466618
iter  70 value 87.391658
final  value 87.388602 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.416580 
iter  10 value 94.418988
iter  20 value 88.467074
iter  30 value 88.174638
iter  40 value 87.847292
iter  50 value 87.019697
iter  60 value 85.912800
iter  70 value 85.857885
iter  80 value 85.097895
iter  90 value 85.095740
final  value 85.095737 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.675728 
iter  10 value 91.698222
iter  20 value 87.892213
iter  30 value 86.193513
iter  40 value 84.485466
iter  50 value 84.074435
iter  60 value 83.749886
iter  70 value 83.035711
iter  80 value 82.743050
iter  90 value 82.691493
iter 100 value 82.618889
final  value 82.618889 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.183486 
iter  10 value 94.999159
iter  20 value 94.640101
iter  30 value 94.347933
iter  40 value 94.167587
iter  50 value 94.147468
iter  60 value 94.007969
iter  70 value 88.253804
iter  80 value 85.887492
iter  90 value 84.139561
iter 100 value 83.018677
final  value 83.018677 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.736020 
iter  10 value 94.370477
iter  20 value 88.869993
iter  30 value 86.142293
iter  40 value 84.167950
iter  50 value 82.925108
iter  60 value 82.785830
iter  70 value 82.571011
iter  80 value 82.228118
iter  90 value 82.143287
iter 100 value 81.982464
final  value 81.982464 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.591635 
iter  10 value 94.495442
iter  20 value 89.917186
iter  30 value 85.578686
iter  40 value 83.765339
iter  50 value 83.386967
iter  60 value 83.196723
iter  70 value 83.080115
iter  80 value 82.614682
iter  90 value 82.329989
iter 100 value 82.144309
final  value 82.144309 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 118.897144 
iter  10 value 94.433968
iter  20 value 92.093240
iter  30 value 88.496017
iter  40 value 87.089928
iter  50 value 86.906040
iter  60 value 86.847860
iter  70 value 86.778563
iter  80 value 85.664759
iter  90 value 83.812847
iter 100 value 82.780439
final  value 82.780439 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.165409 
iter  10 value 88.093603
iter  20 value 87.583220
iter  30 value 86.146338
iter  40 value 84.214669
iter  50 value 83.864942
iter  60 value 83.706424
iter  70 value 83.397919
iter  80 value 83.137325
iter  90 value 82.937659
iter 100 value 82.658401
final  value 82.658401 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 123.616073 
iter  10 value 92.198549
iter  20 value 87.848740
iter  30 value 87.235675
iter  40 value 86.810388
iter  50 value 85.237979
iter  60 value 84.671661
iter  70 value 83.998650
iter  80 value 83.965989
iter  90 value 83.753558
iter 100 value 83.382342
final  value 83.382342 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 122.905450 
iter  10 value 93.479134
iter  20 value 89.794600
iter  30 value 84.384558
iter  40 value 82.663657
iter  50 value 82.114676
iter  60 value 82.072278
iter  70 value 81.997681
iter  80 value 81.855366
iter  90 value 81.818672
iter 100 value 81.670517
final  value 81.670517 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.235095 
iter  10 value 94.853231
iter  20 value 93.466879
iter  30 value 91.143510
iter  40 value 89.750962
iter  50 value 85.148392
iter  60 value 84.473958
iter  70 value 83.991807
iter  80 value 82.859726
iter  90 value 82.410527
iter 100 value 82.013591
final  value 82.013591 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 114.845903 
iter  10 value 94.499256
iter  20 value 93.668592
iter  30 value 90.794739
iter  40 value 88.036947
iter  50 value 85.505077
iter  60 value 84.377555
iter  70 value 83.813922
iter  80 value 82.477090
iter  90 value 82.098759
iter 100 value 81.921452
final  value 81.921452 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.199881 
final  value 94.485889 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.661833 
iter  10 value 94.485922
final  value 94.485917 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.597216 
final  value 94.485940 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.644808 
final  value 94.485617 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.686684 
iter  10 value 94.485913
iter  20 value 94.384720
iter  30 value 88.685692
iter  40 value 87.603205
iter  50 value 87.600256
final  value 87.600178 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.636357 
iter  10 value 94.496943
iter  20 value 94.441463
iter  30 value 94.180863
iter  40 value 87.296299
iter  50 value 85.598512
iter  60 value 85.008678
final  value 85.008623 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.616685 
iter  10 value 94.489208
iter  20 value 94.481075
iter  30 value 94.473150
final  value 94.473134 
converged
Fitting Repeat 3 

# weights:  305
initial  value 109.166793 
iter  10 value 94.496708
iter  20 value 94.491418
iter  30 value 94.480307
iter  40 value 94.466251
iter  50 value 89.459925
iter  60 value 88.704648
iter  70 value 88.637953
final  value 88.637717 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.504150 
final  value 94.489107 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.635141 
iter  10 value 94.478520
iter  20 value 94.473369
iter  30 value 94.466119
iter  40 value 86.963427
iter  50 value 86.957527
iter  60 value 86.957191
iter  70 value 86.865689
iter  80 value 86.539328
iter  90 value 84.979506
iter 100 value 84.884741
final  value 84.884741 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 102.880896 
iter  10 value 94.480856
iter  20 value 94.440871
iter  30 value 85.766591
iter  40 value 84.125246
iter  50 value 83.971129
final  value 83.970560 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.805411 
iter  10 value 94.494782
iter  20 value 94.451210
iter  30 value 94.108267
iter  40 value 94.096444
iter  50 value 94.086196
iter  60 value 88.975683
iter  70 value 83.091949
iter  80 value 82.465581
iter  90 value 82.191379
iter 100 value 82.166296
final  value 82.166296 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 136.248824 
iter  10 value 94.506074
iter  20 value 94.493926
iter  30 value 87.531460
iter  40 value 87.488369
iter  50 value 87.481699
iter  60 value 87.477803
final  value 87.477732 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.231707 
iter  10 value 94.481458
iter  20 value 94.481207
iter  30 value 94.029226
iter  40 value 89.008962
iter  50 value 89.007600
iter  60 value 88.984135
iter  70 value 87.876137
iter  80 value 86.837665
iter  90 value 86.815483
iter 100 value 86.381667
final  value 86.381667 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 95.264115 
iter  10 value 94.222375
iter  20 value 88.435733
iter  30 value 85.337957
iter  40 value 83.451748
iter  50 value 83.116154
iter  60 value 82.194993
iter  70 value 82.049075
iter  80 value 81.305358
iter  90 value 81.134335
iter 100 value 81.007840
final  value 81.007840 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 106.225729 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.012194 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.552876 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.491791 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.866897 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.975939 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.152385 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.533222 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.776382 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.337597 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.723398 
iter  10 value 93.455694
iter  20 value 89.224715
iter  30 value 88.887136
iter  40 value 88.679982
iter  50 value 88.676782
final  value 88.676778 
converged
Fitting Repeat 2 

# weights:  507
initial  value 114.751064 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.620294 
iter  10 value 93.806511
iter  20 value 91.050656
iter  30 value 87.287598
final  value 87.283810 
converged
Fitting Repeat 4 

# weights:  507
initial  value 109.651986 
iter  10 value 88.396871
iter  20 value 87.134583
iter  30 value 87.122692
final  value 87.122677 
converged
Fitting Repeat 5 

# weights:  507
initial  value 112.534019 
iter  10 value 94.354409
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.773170 
iter  10 value 94.425455
iter  20 value 90.935989
iter  30 value 88.264350
iter  40 value 87.659300
iter  50 value 87.570689
final  value 87.568186 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.473153 
iter  10 value 94.520893
iter  20 value 94.477109
iter  30 value 90.914148
iter  40 value 84.194572
iter  50 value 82.708652
iter  60 value 79.328442
iter  70 value 78.342432
iter  80 value 78.151813
iter  90 value 77.764783
iter 100 value 77.634452
final  value 77.634452 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.055556 
iter  10 value 94.395343
iter  20 value 90.590741
iter  30 value 88.867109
iter  40 value 88.384937
iter  50 value 87.575391
iter  60 value 87.568337
final  value 87.568186 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.823731 
iter  10 value 94.437222
iter  20 value 82.156077
iter  30 value 79.312416
iter  40 value 78.290097
iter  50 value 77.574323
iter  60 value 77.320143
iter  70 value 77.272234
iter  80 value 77.236386
iter  90 value 77.186652
final  value 77.186275 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.869788 
iter  10 value 94.491176
iter  20 value 94.428704
iter  30 value 94.412757
iter  40 value 93.561843
iter  50 value 89.758562
iter  60 value 87.415467
iter  70 value 87.201385
iter  80 value 87.197520
final  value 87.197358 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.822069 
iter  10 value 94.506215
iter  20 value 94.274646
iter  30 value 85.222717
iter  40 value 82.396054
iter  50 value 81.114033
iter  60 value 80.224734
iter  70 value 79.304865
iter  80 value 77.950458
iter  90 value 77.609921
iter 100 value 77.333117
final  value 77.333117 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.884697 
iter  10 value 94.559567
iter  20 value 85.454245
iter  30 value 81.666882
iter  40 value 78.988950
iter  50 value 78.672919
iter  60 value 77.485137
iter  70 value 76.844110
iter  80 value 76.406247
iter  90 value 76.175344
iter 100 value 76.102502
final  value 76.102502 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 98.136711 
iter  10 value 91.578988
iter  20 value 83.378923
iter  30 value 82.230090
iter  40 value 81.565431
iter  50 value 78.209478
iter  60 value 77.751153
iter  70 value 77.376320
iter  80 value 77.172109
iter  90 value 76.178934
iter 100 value 75.957890
final  value 75.957890 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.096352 
iter  10 value 94.635125
iter  20 value 94.530208
iter  30 value 94.314375
iter  40 value 89.577516
iter  50 value 87.628987
iter  60 value 85.686832
iter  70 value 85.185027
iter  80 value 82.048991
iter  90 value 80.718357
iter 100 value 80.113236
final  value 80.113236 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.664691 
iter  10 value 95.100606
iter  20 value 94.620354
iter  30 value 94.311460
iter  40 value 89.549640
iter  50 value 88.085139
iter  60 value 87.961288
iter  70 value 85.328718
iter  80 value 82.428389
iter  90 value 82.051024
iter 100 value 81.567592
final  value 81.567592 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 118.500179 
iter  10 value 94.922424
iter  20 value 89.057855
iter  30 value 84.459987
iter  40 value 79.207845
iter  50 value 77.595340
iter  60 value 77.230258
iter  70 value 76.901888
iter  80 value 76.611159
iter  90 value 76.412574
iter 100 value 76.299081
final  value 76.299081 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.346845 
iter  10 value 101.435192
iter  20 value 89.777968
iter  30 value 83.051069
iter  40 value 82.576024
iter  50 value 81.229413
iter  60 value 80.873649
iter  70 value 80.356546
iter  80 value 78.722460
iter  90 value 77.526124
iter 100 value 76.187365
final  value 76.187365 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.483998 
iter  10 value 94.064706
iter  20 value 90.776253
iter  30 value 87.591601
iter  40 value 87.366573
iter  50 value 85.768808
iter  60 value 81.738991
iter  70 value 80.695519
iter  80 value 80.576773
iter  90 value 80.402613
iter 100 value 79.346005
final  value 79.346005 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.025054 
iter  10 value 95.088305
iter  20 value 89.413705
iter  30 value 85.048435
iter  40 value 83.997220
iter  50 value 82.004486
iter  60 value 79.557172
iter  70 value 78.218725
iter  80 value 77.832315
iter  90 value 77.760177
iter 100 value 77.619656
final  value 77.619656 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.451571 
iter  10 value 94.703752
iter  20 value 94.050713
iter  30 value 89.429066
iter  40 value 85.521254
iter  50 value 82.095513
iter  60 value 79.748196
iter  70 value 79.300583
iter  80 value 79.209061
iter  90 value 79.154945
iter 100 value 79.080310
final  value 79.080310 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.123925 
final  value 94.485564 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.958418 
iter  10 value 94.356051
iter  20 value 94.354489
iter  30 value 94.188349
iter  40 value 81.765786
iter  50 value 81.759158
iter  60 value 81.748673
iter  70 value 79.563063
iter  80 value 79.175202
iter  90 value 78.930396
iter 100 value 78.929598
final  value 78.929598 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.149828 
iter  10 value 86.003295
iter  20 value 84.609925
iter  30 value 84.210382
iter  40 value 84.208302
iter  50 value 84.204395
iter  60 value 81.858400
iter  70 value 81.724555
iter  80 value 81.435406
iter  90 value 81.309211
iter 100 value 81.308974
final  value 81.308974 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.073112 
iter  10 value 93.026171
iter  20 value 92.610893
iter  30 value 92.155343
iter  40 value 92.133707
iter  50 value 92.132836
iter  60 value 92.132602
final  value 92.132563 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.450950 
final  value 94.327760 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.861834 
iter  10 value 94.317475
iter  20 value 94.310724
iter  30 value 94.309576
iter  40 value 93.635436
iter  50 value 90.204938
iter  60 value 90.199734
iter  70 value 90.196837
iter  80 value 89.831991
iter  90 value 89.772819
iter 100 value 89.771910
final  value 89.771910 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.319730 
iter  10 value 94.489980
final  value 94.489121 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.890890 
iter  10 value 94.330303
iter  20 value 89.730789
iter  30 value 81.304142
iter  40 value 81.275391
iter  50 value 80.996916
iter  60 value 80.977791
final  value 80.976358 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.834644 
iter  10 value 94.488912
iter  20 value 94.483856
iter  30 value 90.621217
iter  40 value 86.710184
iter  50 value 86.703519
iter  60 value 86.702840
iter  70 value 86.640288
iter  80 value 86.089507
iter  90 value 83.048549
iter 100 value 78.083821
final  value 78.083821 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.211034 
iter  10 value 94.488866
iter  20 value 94.484228
iter  30 value 94.435641
final  value 94.354484 
converged
Fitting Repeat 1 

# weights:  507
initial  value 115.937305 
iter  10 value 94.334349
iter  20 value 93.426076
iter  30 value 88.156122
iter  40 value 87.515959
iter  50 value 87.514509
iter  60 value 87.514186
final  value 87.514167 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.953520 
iter  10 value 94.510553
iter  20 value 94.500299
iter  30 value 94.371184
iter  40 value 94.326084
iter  50 value 91.554688
iter  60 value 90.780783
iter  70 value 87.589109
iter  80 value 87.265853
iter  90 value 87.262664
iter 100 value 87.255745
final  value 87.255745 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 145.184415 
iter  10 value 88.053454
iter  20 value 82.355033
iter  30 value 81.990590
iter  40 value 81.819581
iter  50 value 81.811489
final  value 81.811032 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.703735 
iter  10 value 94.319552
iter  20 value 94.219025
iter  30 value 94.215242
iter  40 value 94.212542
iter  40 value 94.212541
iter  40 value 94.212541
final  value 94.212541 
converged
Fitting Repeat 5 

# weights:  507
initial  value 109.480533 
iter  10 value 94.432187
iter  20 value 94.428568
iter  30 value 94.371781
iter  40 value 94.342102
iter  50 value 94.341261
iter  60 value 94.339983
iter  70 value 94.225617
iter  80 value 94.017241
iter  90 value 93.688947
iter 100 value 93.389935
final  value 93.389935 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.891654 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.670883 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.883832 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.239899 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 115.263422 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 117.436344 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.338183 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.462262 
iter  10 value 92.881235
iter  20 value 92.561993
final  value 92.561934 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.469710 
iter  10 value 92.171035
iter  20 value 92.083834
final  value 92.083334 
converged
Fitting Repeat 5 

# weights:  305
initial  value 117.131248 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.700737 
final  value 93.582418 
converged
Fitting Repeat 2 

# weights:  507
initial  value 94.513095 
iter  10 value 88.851665
iter  20 value 83.338709
iter  30 value 83.220660
iter  40 value 83.057396
iter  50 value 82.521741
iter  60 value 81.799584
iter  70 value 80.991070
iter  80 value 80.797231
iter  90 value 80.764450
iter 100 value 80.756429
final  value 80.756429 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 99.327345 
final  value 93.582418 
converged
Fitting Repeat 4 

# weights:  507
initial  value 110.053433 
final  value 93.582418 
converged
Fitting Repeat 5 

# weights:  507
initial  value 110.496796 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.182391 
iter  10 value 94.057856
iter  20 value 93.708410
iter  30 value 91.523819
iter  40 value 84.862312
iter  50 value 84.675384
iter  60 value 84.438796
iter  70 value 83.479287
iter  80 value 82.851824
iter  90 value 81.938214
iter 100 value 81.784868
final  value 81.784868 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.973768 
iter  10 value 94.020735
iter  20 value 93.062571
iter  30 value 92.910355
iter  40 value 89.617008
iter  50 value 85.694716
iter  60 value 84.584118
iter  70 value 83.603048
iter  80 value 82.051991
iter  90 value 81.771106
final  value 81.659384 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.281712 
iter  10 value 94.055483
iter  20 value 93.068215
iter  30 value 92.934574
iter  40 value 92.862304
iter  50 value 92.627265
iter  60 value 87.169277
iter  70 value 86.249379
iter  80 value 85.271351
iter  90 value 84.383233
iter 100 value 83.829170
final  value 83.829170 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.035952 
iter  10 value 94.063323
iter  20 value 93.455389
iter  30 value 89.936932
iter  40 value 89.268936
iter  50 value 86.641860
iter  60 value 85.351735
iter  70 value 84.438958
iter  80 value 83.077255
iter  90 value 81.902029
iter 100 value 81.787256
final  value 81.787256 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 102.175848 
iter  10 value 95.450381
iter  20 value 94.045761
iter  30 value 93.696284
iter  40 value 93.687750
iter  50 value 88.314645
iter  60 value 86.356049
iter  70 value 85.217565
iter  80 value 83.313165
iter  90 value 82.622780
iter 100 value 82.172739
final  value 82.172739 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 105.218277 
iter  10 value 93.999950
iter  20 value 92.859967
iter  30 value 92.554296
iter  40 value 86.393874
iter  50 value 84.803916
iter  60 value 84.110119
iter  70 value 83.614175
iter  80 value 83.070529
iter  90 value 82.285513
iter 100 value 81.510211
final  value 81.510211 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 112.854075 
iter  10 value 93.943044
iter  20 value 91.754394
iter  30 value 90.466945
iter  40 value 90.123487
iter  50 value 89.688336
iter  60 value 85.692050
iter  70 value 84.870197
iter  80 value 82.588179
iter  90 value 82.207918
iter 100 value 81.703090
final  value 81.703090 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.842054 
iter  10 value 94.724886
iter  20 value 93.886502
iter  30 value 85.767148
iter  40 value 84.663240
iter  50 value 84.295230
iter  60 value 83.930697
iter  70 value 83.026040
iter  80 value 80.994288
iter  90 value 80.654932
iter 100 value 80.525337
final  value 80.525337 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.435173 
iter  10 value 93.260918
iter  20 value 91.306427
iter  30 value 89.151959
iter  40 value 87.756455
iter  50 value 86.850937
iter  60 value 86.391198
iter  70 value 85.556337
iter  80 value 85.274115
iter  90 value 85.191180
iter 100 value 84.799602
final  value 84.799602 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 110.422457 
iter  10 value 94.511980
iter  20 value 89.223969
iter  30 value 85.853763
iter  40 value 84.480599
iter  50 value 84.226919
iter  60 value 83.774594
iter  70 value 83.376439
iter  80 value 83.164714
iter  90 value 82.288305
iter 100 value 81.729547
final  value 81.729547 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.412692 
iter  10 value 93.919404
iter  20 value 87.624400
iter  30 value 86.736671
iter  40 value 86.169062
iter  50 value 83.376564
iter  60 value 82.711618
iter  70 value 82.559994
iter  80 value 82.451942
iter  90 value 82.140080
iter 100 value 81.288523
final  value 81.288523 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.116715 
iter  10 value 94.072470
iter  20 value 92.916039
iter  30 value 92.676419
iter  40 value 92.475225
iter  50 value 90.975596
iter  60 value 87.851834
iter  70 value 86.481828
iter  80 value 84.873677
iter  90 value 81.580870
iter 100 value 81.200260
final  value 81.200260 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 128.619437 
iter  10 value 94.671209
iter  20 value 89.052880
iter  30 value 87.248995
iter  40 value 84.478317
iter  50 value 82.790986
iter  60 value 81.845865
iter  70 value 80.518071
iter  80 value 80.326458
iter  90 value 80.016630
iter 100 value 79.903030
final  value 79.903030 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.541643 
iter  10 value 94.369310
iter  20 value 92.706913
iter  30 value 92.472905
iter  40 value 90.597131
iter  50 value 83.918078
iter  60 value 82.304607
iter  70 value 80.945152
iter  80 value 80.400087
iter  90 value 80.060622
iter 100 value 80.028094
final  value 80.028094 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.462281 
iter  10 value 90.261728
iter  20 value 86.360983
iter  30 value 85.105418
iter  40 value 83.865490
iter  50 value 82.654888
iter  60 value 82.103471
iter  70 value 81.863820
iter  80 value 81.337824
iter  90 value 81.256850
iter 100 value 81.236367
final  value 81.236367 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.239714 
final  value 94.054684 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.707507 
final  value 94.054592 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.551402 
final  value 94.054326 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.763960 
final  value 94.054714 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.057273 
final  value 94.054812 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.781453 
iter  10 value 94.057943
iter  20 value 93.610288
final  value 93.582895 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.607272 
iter  10 value 93.999201
iter  20 value 93.810930
iter  30 value 91.979621
iter  40 value 91.805242
iter  50 value 86.688287
iter  60 value 86.103306
iter  70 value 85.921597
iter  80 value 85.835463
iter  90 value 85.834975
final  value 85.834954 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.135703 
iter  10 value 94.057722
iter  20 value 93.186087
iter  30 value 92.832805
iter  40 value 92.832252
iter  50 value 92.831958
final  value 92.831856 
converged
Fitting Repeat 4 

# weights:  305
initial  value 118.821090 
iter  10 value 94.057919
iter  20 value 93.914329
iter  30 value 92.564024
iter  40 value 91.116146
iter  50 value 84.104647
iter  60 value 82.481885
iter  70 value 82.183885
iter  80 value 81.323621
iter  90 value 81.316940
final  value 81.316933 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.663916 
iter  10 value 94.057280
iter  20 value 93.982566
iter  30 value 93.582849
iter  30 value 93.582849
iter  30 value 93.582849
final  value 93.582849 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.221405 
iter  10 value 94.058823
iter  20 value 93.601159
iter  30 value 86.393139
iter  40 value 84.407493
iter  50 value 83.006906
iter  60 value 82.889955
iter  70 value 82.887683
iter  80 value 82.887587
iter  90 value 82.871176
final  value 82.870782 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.267344 
iter  10 value 93.420041
iter  20 value 92.824685
iter  30 value 92.815538
iter  40 value 92.809040
iter  50 value 91.790576
iter  60 value 90.374440
iter  70 value 89.855936
iter  80 value 89.847445
iter  80 value 89.847445
final  value 89.847412 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.873745 
iter  10 value 93.590710
iter  20 value 93.505243
iter  30 value 86.124990
iter  40 value 84.209849
iter  50 value 83.814841
iter  60 value 83.401817
iter  70 value 83.385543
iter  80 value 83.244288
iter  90 value 83.146955
final  value 83.143275 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.248137 
iter  10 value 94.060479
iter  20 value 94.048859
iter  30 value 89.595979
iter  40 value 86.260313
iter  50 value 86.073189
iter  60 value 86.046897
iter  70 value 86.040183
iter  80 value 85.744974
iter  90 value 85.094011
iter 100 value 85.035625
final  value 85.035625 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.929599 
iter  10 value 94.060812
iter  20 value 93.964236
iter  30 value 93.582892
iter  30 value 93.582892
iter  30 value 93.582892
final  value 93.582892 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.552073 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.715796 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.595896 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.626558 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.500068 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.800411 
iter  10 value 88.036294
iter  20 value 84.797529
iter  30 value 84.783604
final  value 84.783350 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.226407 
iter  10 value 93.921518
final  value 93.921213 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.790793 
final  value 93.967787 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.388988 
iter  10 value 94.034198
final  value 94.032967 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.172185 
final  value 93.991525 
converged
Fitting Repeat 1 

# weights:  507
initial  value 114.188405 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.730712 
iter  10 value 94.052441
iter  20 value 94.008784
final  value 94.008697 
converged
Fitting Repeat 3 

# weights:  507
initial  value 110.267304 
final  value 93.991525 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.886230 
iter  10 value 85.556598
iter  20 value 82.709267
final  value 82.709265 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.238412 
iter  10 value 93.671796
final  value 93.671508 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.045735 
iter  10 value 94.056960
iter  20 value 94.007280
iter  30 value 93.091004
iter  40 value 89.157834
iter  50 value 88.918579
iter  60 value 84.362051
iter  70 value 84.015923
iter  80 value 83.839842
iter  90 value 83.783908
iter 100 value 83.710979
final  value 83.710979 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 102.342035 
iter  10 value 94.052645
iter  20 value 89.864661
iter  30 value 88.129075
iter  40 value 84.737311
iter  50 value 84.197113
iter  60 value 84.030899
iter  70 value 83.989595
iter  80 value 80.883564
iter  90 value 80.708277
iter 100 value 80.698384
final  value 80.698384 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.599082 
iter  10 value 94.060125
iter  20 value 94.010500
iter  30 value 85.483009
iter  40 value 85.341644
iter  50 value 83.162501
iter  60 value 82.608380
iter  70 value 82.342304
iter  80 value 82.260590
iter  90 value 82.206702
final  value 82.206700 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.986817 
iter  10 value 94.055514
iter  20 value 93.279002
iter  30 value 87.598089
iter  40 value 84.716509
iter  50 value 84.509508
iter  60 value 83.534379
iter  70 value 83.057769
iter  80 value 82.994464
iter  90 value 82.972550
iter 100 value 82.948934
final  value 82.948934 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 101.140571 
iter  10 value 92.117210
iter  20 value 86.424076
iter  30 value 85.700566
iter  40 value 85.466090
iter  50 value 84.844971
iter  60 value 84.622957
final  value 84.622909 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.821987 
iter  10 value 94.420770
iter  20 value 94.069246
iter  30 value 92.947026
iter  40 value 86.410978
iter  50 value 85.130009
iter  60 value 82.959848
iter  70 value 81.090076
iter  80 value 80.698950
iter  90 value 80.633831
iter 100 value 80.531789
final  value 80.531789 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.717447 
iter  10 value 94.039167
iter  20 value 92.685700
iter  30 value 90.497168
iter  40 value 87.771812
iter  50 value 84.641180
iter  60 value 82.152886
iter  70 value 80.868334
iter  80 value 80.344826
iter  90 value 80.110671
iter 100 value 79.917465
final  value 79.917465 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.956167 
iter  10 value 94.048715
iter  20 value 92.778098
iter  30 value 88.448815
iter  40 value 85.745048
iter  50 value 85.495927
iter  60 value 83.386091
iter  70 value 82.593600
iter  80 value 82.086782
iter  90 value 81.974416
iter 100 value 81.090610
final  value 81.090610 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.520627 
iter  10 value 94.005504
iter  20 value 88.791058
iter  30 value 85.736378
iter  40 value 83.852139
iter  50 value 82.114158
iter  60 value 81.053578
iter  70 value 80.835123
iter  80 value 80.188622
iter  90 value 79.814454
iter 100 value 79.523812
final  value 79.523812 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.512728 
iter  10 value 94.031194
iter  20 value 92.606009
iter  30 value 86.361164
iter  40 value 84.286256
iter  50 value 82.702966
iter  60 value 80.656967
iter  70 value 80.135462
iter  80 value 79.697078
iter  90 value 79.600677
iter 100 value 79.517729
final  value 79.517729 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.951644 
iter  10 value 93.958712
iter  20 value 85.072630
iter  30 value 83.670447
iter  40 value 80.922150
iter  50 value 80.359033
iter  60 value 79.559922
iter  70 value 79.260709
iter  80 value 79.042650
iter  90 value 78.832781
iter 100 value 78.775724
final  value 78.775724 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 128.839511 
iter  10 value 93.832229
iter  20 value 84.167635
iter  30 value 83.578525
iter  40 value 82.714846
iter  50 value 80.903676
iter  60 value 80.554239
iter  70 value 80.163500
iter  80 value 79.789778
iter  90 value 79.659051
iter 100 value 79.609924
final  value 79.609924 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.238220 
iter  10 value 92.453709
iter  20 value 85.482796
iter  30 value 82.204271
iter  40 value 81.188512
iter  50 value 80.752407
iter  60 value 80.312344
iter  70 value 79.655221
iter  80 value 79.398167
iter  90 value 79.128625
iter 100 value 79.038365
final  value 79.038365 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.337779 
iter  10 value 94.024688
iter  20 value 90.136745
iter  30 value 86.487030
iter  40 value 84.847726
iter  50 value 83.001708
iter  60 value 80.605681
iter  70 value 80.179484
iter  80 value 79.345691
iter  90 value 79.104209
iter 100 value 78.991706
final  value 78.991706 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 117.436361 
iter  10 value 94.014845
iter  20 value 87.262911
iter  30 value 84.931025
iter  40 value 84.679598
iter  50 value 83.638462
iter  60 value 80.961750
iter  70 value 79.661853
iter  80 value 79.339825
iter  90 value 79.322563
iter 100 value 79.253158
final  value 79.253158 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 106.605438 
final  value 94.034307 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.184862 
final  value 94.054663 
converged
Fitting Repeat 3 

# weights:  103
initial  value 114.858484 
iter  10 value 94.054455
iter  20 value 93.724243
iter  30 value 92.170126
iter  40 value 91.956180
iter  50 value 91.931238
final  value 91.931210 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.812820 
final  value 94.054335 
converged
Fitting Repeat 5 

# weights:  103
initial  value 115.916561 
final  value 94.054941 
converged
Fitting Repeat 1 

# weights:  305
initial  value 120.709029 
iter  10 value 94.058229
final  value 94.052942 
converged
Fitting Repeat 2 

# weights:  305
initial  value 110.154846 
iter  10 value 94.058131
iter  20 value 92.764094
iter  30 value 85.769178
final  value 85.763809 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.863704 
iter  10 value 83.991702
iter  20 value 83.787360
iter  30 value 83.750306
iter  40 value 83.538678
iter  50 value 83.536445
iter  60 value 83.533450
iter  70 value 83.499932
iter  80 value 83.477428
iter  90 value 83.477040
final  value 83.477014 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.580848 
iter  10 value 94.057931
iter  20 value 94.052579
iter  30 value 91.174993
iter  40 value 87.085115
iter  50 value 86.819761
iter  60 value 85.963867
iter  70 value 85.957527
iter  80 value 85.956795
iter  90 value 85.955963
final  value 85.955932 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.058917 
iter  10 value 94.057182
iter  20 value 93.914403
iter  30 value 89.781735
iter  40 value 88.627685
iter  50 value 85.636990
iter  60 value 85.332529
iter  70 value 85.317065
iter  80 value 84.964657
iter  90 value 81.959367
iter 100 value 81.943081
final  value 81.943081 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.262915 
iter  10 value 94.040872
iter  20 value 93.936671
iter  30 value 84.320790
final  value 84.225026 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.034654 
iter  10 value 94.061290
iter  20 value 94.049826
iter  30 value 93.889812
iter  40 value 93.869428
iter  50 value 93.867711
final  value 93.865343 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.359430 
iter  10 value 93.679907
iter  20 value 93.671287
iter  30 value 91.797286
iter  40 value 87.924677
iter  50 value 86.884728
iter  60 value 83.176285
iter  70 value 83.037761
iter  80 value 82.301184
iter  90 value 79.653565
iter 100 value 77.819307
final  value 77.819307 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.594262 
iter  10 value 94.061053
iter  20 value 93.989091
iter  30 value 84.996376
final  value 84.992810 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.529428 
iter  10 value 94.030854
iter  20 value 93.631590
iter  30 value 93.592695
iter  40 value 93.591765
iter  50 value 93.591029
iter  60 value 93.590545
iter  70 value 93.586738
iter  80 value 86.181041
iter  90 value 86.176151
iter 100 value 85.313764
final  value 85.313764 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 165.052354 
iter  10 value 117.932547
iter  20 value 117.616116
iter  30 value 117.613160
iter  40 value 117.490908
iter  50 value 109.411479
iter  60 value 107.522616
iter  70 value 104.029955
iter  80 value 103.534889
iter  90 value 103.356106
iter 100 value 101.858718
final  value 101.858718 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 129.696806 
iter  10 value 117.897985
iter  20 value 117.273109
iter  30 value 115.616927
final  value 115.616775 
converged
Fitting Repeat 3 

# weights:  507
initial  value 120.452789 
iter  10 value 117.739521
iter  20 value 117.735854
iter  30 value 112.635419
iter  40 value 109.530078
iter  50 value 109.476844
iter  60 value 109.165409
iter  70 value 108.966827
final  value 108.966704 
converged
Fitting Repeat 4 

# weights:  507
initial  value 119.232469 
iter  10 value 117.898413
iter  20 value 117.829786
iter  30 value 117.540479
iter  40 value 116.980451
iter  50 value 113.581615
iter  60 value 107.258133
iter  70 value 107.119823
iter  80 value 106.801321
iter  90 value 106.793016
iter 100 value 106.228539
final  value 106.228539 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 139.026978 
iter  10 value 117.766808
iter  20 value 117.744362
iter  30 value 116.173699
iter  40 value 107.129694
iter  50 value 106.755561
iter  60 value 106.755072
iter  70 value 106.754603
iter  80 value 106.752569
final  value 106.751967 
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 -- Tue Apr 22 10:07:36 2025 
*********************************************** 
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 
Warning messages:
1: `repeats` has no meaning for this resampling method. 
2: executing %dopar% sequentially: no parallel backend registered 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
 56.814   1.306 154.536