##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings HPiP_1.18.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck’
* using R version 4.6.0 RC (2026-04-17 r89917)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
    GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
* running under: Ubuntu 24.04.4 LTS
* using session charset: UTF-8
* current time: 2026-05-21 05:04:55 UTC
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.18.0’
* 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
FSmethod      33.959  0.548  34.608
corr_plot     33.983  0.474  34.521
var_imp       33.079  0.496  33.583
pred_ensembel 12.739  0.151  11.563
enrichfindP    0.544  0.043  11.299
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE

Status: 2 NOTEs
See
  ‘/home/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.23-bioc/R/site-library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.18.0’
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R version 4.6.0 RC (2026-04-17 r89917) -- "Because it was There"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

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

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

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

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

# weights:  103
initial  value 100.652408 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.122525 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.630894 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.222254 
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.940365 
final  value 94.275362 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.978525 
iter  10 value 89.475270
iter  20 value 88.899616
iter  30 value 88.899103
final  value 88.899102 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.437244 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.576980 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 120.438362 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.095603 
final  value 94.275362 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.041231 
iter  10 value 92.692946
iter  20 value 86.285826
final  value 86.144322 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.645098 
final  value 93.903448 
converged
Fitting Repeat 3 

# weights:  507
initial  value 116.941459 
final  value 94.275362 
converged
Fitting Repeat 4 

# weights:  507
initial  value 110.271039 
iter  10 value 89.857454
iter  20 value 82.914004
final  value 82.502128 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.278349 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 106.725015 
iter  10 value 94.367004
iter  20 value 89.741968
iter  30 value 87.744651
iter  40 value 84.895783
iter  50 value 84.484644
iter  60 value 82.637010
iter  70 value 82.131687
iter  80 value 81.547450
iter  90 value 81.474703
iter 100 value 81.344376
final  value 81.344376 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 105.027602 
iter  10 value 94.468652
iter  20 value 90.785601
iter  30 value 90.101562
iter  40 value 87.679504
iter  50 value 87.023731
iter  60 value 84.348388
iter  70 value 84.217812
iter  80 value 83.345884
iter  90 value 83.054560
iter 100 value 82.945756
final  value 82.945756 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.828704 
iter  10 value 94.335089
iter  20 value 86.356492
iter  30 value 84.128940
iter  40 value 83.793798
iter  50 value 83.709483
iter  60 value 83.702286
iter  70 value 83.701108
final  value 83.701107 
converged
Fitting Repeat 4 

# weights:  103
initial  value 109.988192 
iter  10 value 94.407380
iter  20 value 87.344848
iter  30 value 86.988177
iter  40 value 84.370622
iter  50 value 83.341038
iter  60 value 83.081320
iter  70 value 82.930847
iter  80 value 82.930347
final  value 82.930345 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.182113 
iter  10 value 94.995892
iter  20 value 94.485466
iter  30 value 94.035952
iter  40 value 84.479232
iter  50 value 83.468421
iter  60 value 83.204080
iter  70 value 83.029190
iter  80 value 82.931279
iter  90 value 82.930616
final  value 82.930346 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.282563 
iter  10 value 94.775734
iter  20 value 94.361115
iter  30 value 86.932949
iter  40 value 84.870242
iter  50 value 83.801798
iter  60 value 83.380254
iter  70 value 82.833103
iter  80 value 82.689783
iter  90 value 82.638917
iter 100 value 82.500143
final  value 82.500143 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 112.745032 
iter  10 value 94.198225
iter  20 value 85.342474
iter  30 value 83.780889
iter  40 value 82.807757
iter  50 value 82.209646
iter  60 value 81.155277
iter  70 value 80.546198
iter  80 value 80.206804
iter  90 value 80.082515
iter 100 value 79.955596
final  value 79.955596 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.326706 
iter  10 value 94.475033
iter  20 value 93.105330
iter  30 value 84.339387
iter  40 value 83.239096
iter  50 value 82.092883
iter  60 value 80.993016
iter  70 value 80.479665
iter  80 value 79.986154
iter  90 value 79.922077
iter 100 value 79.841959
final  value 79.841959 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.397481 
iter  10 value 94.170962
iter  20 value 88.776889
iter  30 value 84.260246
iter  40 value 82.002769
iter  50 value 80.886258
iter  60 value 80.614388
iter  70 value 80.158397
iter  80 value 80.031001
iter  90 value 79.975172
iter 100 value 79.884761
final  value 79.884761 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.329610 
iter  10 value 94.375145
iter  20 value 87.057242
iter  30 value 83.732513
iter  40 value 82.250573
iter  50 value 80.905604
iter  60 value 80.787306
iter  70 value 80.682368
iter  80 value 80.502278
iter  90 value 80.278464
iter 100 value 80.147211
final  value 80.147211 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.107968 
iter  10 value 94.516902
iter  20 value 85.110007
iter  30 value 82.918291
iter  40 value 81.666389
iter  50 value 80.474245
iter  60 value 80.231507
iter  70 value 80.215162
iter  80 value 80.000683
iter  90 value 79.832129
iter 100 value 79.736792
final  value 79.736792 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.182901 
iter  10 value 94.468530
iter  20 value 85.327372
iter  30 value 84.042036
iter  40 value 83.929523
iter  50 value 83.559022
iter  60 value 82.913659
iter  70 value 82.618089
iter  80 value 82.555101
iter  90 value 82.213106
iter 100 value 81.211346
final  value 81.211346 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.677071 
iter  10 value 97.542463
iter  20 value 92.979831
iter  30 value 85.841664
iter  40 value 82.908378
iter  50 value 82.202304
iter  60 value 82.046524
iter  70 value 81.298151
iter  80 value 80.429131
iter  90 value 80.209572
iter 100 value 80.127966
final  value 80.127966 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.258973 
iter  10 value 91.231482
iter  20 value 85.408359
iter  30 value 82.909836
iter  40 value 81.702739
iter  50 value 80.875980
iter  60 value 80.350396
iter  70 value 80.134151
iter  80 value 80.046270
iter  90 value 79.742541
iter 100 value 79.586387
final  value 79.586387 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 102.464867 
iter  10 value 94.463574
iter  20 value 92.817969
iter  30 value 89.433779
iter  40 value 83.963184
iter  50 value 83.666421
iter  60 value 83.366327
iter  70 value 82.560443
iter  80 value 81.038554
iter  90 value 80.604882
iter 100 value 80.086451
final  value 80.086451 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.770822 
final  value 94.485741 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.053092 
final  value 94.485791 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.443741 
iter  10 value 94.485184
iter  20 value 94.468259
iter  30 value 94.299370
final  value 94.276500 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.519014 
iter  10 value 94.485706
final  value 94.484216 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.319669 
final  value 94.485683 
converged
Fitting Repeat 1 

# weights:  305
initial  value 125.349720 
iter  10 value 94.488829
iter  20 value 94.468325
iter  30 value 94.057530
iter  40 value 93.672618
iter  50 value 86.367903
iter  60 value 86.103062
iter  70 value 84.763073
iter  80 value 83.700748
iter  90 value 83.385954
iter 100 value 83.382835
final  value 83.382835 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.897845 
iter  10 value 94.488733
iter  20 value 94.427246
iter  30 value 88.252977
iter  40 value 86.361781
iter  50 value 86.273850
iter  60 value 86.093131
iter  70 value 83.118553
iter  80 value 82.560847
iter  90 value 82.541749
iter 100 value 81.695666
final  value 81.695666 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 97.081958 
iter  10 value 94.489087
iter  20 value 94.385311
final  value 93.864586 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.931999 
iter  10 value 94.489210
iter  20 value 94.484343
final  value 94.484292 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.604778 
iter  10 value 94.488998
iter  20 value 93.633366
iter  30 value 90.180586
iter  40 value 90.179708
iter  50 value 89.600561
iter  60 value 89.144967
final  value 89.144808 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.037473 
iter  10 value 94.491890
iter  20 value 85.342292
final  value 83.029068 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.955137 
iter  10 value 93.930272
iter  20 value 93.881520
iter  30 value 93.875261
iter  40 value 92.469319
iter  50 value 85.073405
iter  60 value 80.431389
iter  70 value 79.188948
iter  80 value 78.999070
iter  90 value 78.818183
iter  90 value 78.818183
final  value 78.818183 
converged
Fitting Repeat 3 

# weights:  507
initial  value 126.115636 
iter  10 value 94.493116
iter  20 value 93.568429
iter  30 value 82.441190
iter  40 value 82.387152
iter  50 value 82.378912
iter  60 value 82.378506
iter  70 value 82.377243
iter  70 value 82.377243
iter  70 value 82.377242
final  value 82.377242 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.776497 
iter  10 value 94.491774
iter  20 value 90.002366
iter  30 value 86.909264
iter  40 value 86.649511
iter  50 value 86.646736
iter  60 value 82.594178
iter  70 value 81.425838
iter  80 value 81.352195
iter  90 value 81.006141
iter 100 value 79.237826
final  value 79.237826 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.920058 
iter  10 value 94.271598
iter  20 value 94.262478
iter  30 value 94.043194
iter  40 value 90.395989
iter  50 value 86.646686
iter  60 value 86.643912
iter  70 value 86.642465
iter  80 value 85.586868
iter  90 value 84.618861
iter 100 value 82.448286
final  value 82.448286 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.572560 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.166677 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.504974 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.625821 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.787288 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.835105 
iter  10 value 94.498192
iter  20 value 94.484223
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.682917 
iter  10 value 93.366429
final  value 93.304242 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.648330 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.224640 
iter  10 value 92.867244
iter  20 value 90.487620
final  value 90.487501 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.686692 
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  507
initial  value 129.144846 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.764599 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.526792 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 109.981547 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.565318 
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.426276 
iter  10 value 94.488566
iter  20 value 93.793495
iter  30 value 93.424790
iter  40 value 93.407459
iter  50 value 93.396526
iter  60 value 93.335584
iter  70 value 91.967817
iter  80 value 85.516367
iter  90 value 84.934638
iter 100 value 82.237376
final  value 82.237376 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 100.665262 
iter  10 value 94.450271
iter  20 value 86.770059
iter  30 value 85.965117
iter  40 value 85.872199
iter  50 value 85.721405
iter  60 value 85.089933
iter  70 value 84.888198
iter  80 value 84.882553
final  value 84.882542 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.102053 
iter  10 value 94.285450
iter  20 value 90.602283
iter  30 value 88.266868
iter  40 value 87.888060
iter  50 value 87.655886
iter  60 value 83.247174
iter  70 value 82.449077
iter  80 value 81.508896
iter  90 value 81.272017
iter 100 value 81.172625
final  value 81.172625 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 104.547500 
iter  10 value 94.488862
iter  20 value 94.350288
iter  30 value 93.438970
iter  40 value 87.010291
iter  50 value 86.163533
iter  60 value 85.416778
iter  70 value 85.219143
final  value 85.218192 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.906720 
iter  10 value 94.538556
iter  20 value 94.486142
iter  30 value 93.420796
iter  40 value 93.354393
iter  50 value 93.329851
iter  60 value 91.238468
iter  70 value 85.767513
iter  80 value 83.875780
iter  90 value 83.649975
iter 100 value 83.309137
final  value 83.309137 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 101.999043 
iter  10 value 94.134204
iter  20 value 86.044208
iter  30 value 85.706243
iter  40 value 84.171631
iter  50 value 83.385541
iter  60 value 82.260603
iter  70 value 81.597668
iter  80 value 81.242085
iter  90 value 81.083010
iter 100 value 80.959218
final  value 80.959218 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 117.836924 
iter  10 value 94.182551
iter  20 value 93.518498
iter  30 value 93.374245
iter  40 value 93.301510
iter  50 value 92.545473
iter  60 value 87.453661
iter  70 value 84.141964
iter  80 value 83.272201
iter  90 value 82.888931
iter 100 value 81.450576
final  value 81.450576 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 111.068925 
iter  10 value 94.691986
iter  20 value 94.020948
iter  30 value 86.788775
iter  40 value 84.183738
iter  50 value 83.053532
iter  60 value 80.760118
iter  70 value 80.502127
iter  80 value 80.411874
iter  90 value 80.286716
iter 100 value 80.220691
final  value 80.220691 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.577363 
iter  10 value 93.780771
iter  20 value 85.095000
iter  30 value 82.681279
iter  40 value 82.571365
iter  50 value 81.865726
iter  60 value 81.685250
iter  70 value 80.866882
iter  80 value 80.166925
iter  90 value 80.075669
iter 100 value 80.031931
final  value 80.031931 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 112.444049 
iter  10 value 94.502970
iter  20 value 93.566329
iter  30 value 83.987690
iter  40 value 82.736549
iter  50 value 82.069886
iter  60 value 80.661992
iter  70 value 80.316266
iter  80 value 80.166223
iter  90 value 80.146997
iter 100 value 80.142457
final  value 80.142457 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 113.421947 
iter  10 value 94.072859
iter  20 value 86.248288
iter  30 value 83.223292
iter  40 value 82.474968
iter  50 value 80.932354
iter  60 value 80.277266
iter  70 value 80.117534
iter  80 value 80.091573
iter  90 value 79.922179
iter 100 value 79.787082
final  value 79.787082 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.879257 
iter  10 value 92.552114
iter  20 value 86.125084
iter  30 value 85.722238
iter  40 value 83.636399
iter  50 value 81.921833
iter  60 value 80.901149
iter  70 value 80.313261
iter  80 value 80.190548
iter  90 value 80.005812
iter 100 value 79.676545
final  value 79.676545 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.723169 
iter  10 value 94.170064
iter  20 value 88.878827
iter  30 value 83.431761
iter  40 value 82.683264
iter  50 value 81.291819
iter  60 value 80.870741
iter  70 value 80.285478
iter  80 value 80.140323
iter  90 value 79.884998
iter 100 value 79.835531
final  value 79.835531 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.556950 
iter  10 value 91.895326
iter  20 value 89.760184
iter  30 value 88.140686
iter  40 value 85.903801
iter  50 value 83.916295
iter  60 value 83.172618
iter  70 value 81.574293
iter  80 value 81.095981
iter  90 value 80.867127
iter 100 value 80.618891
final  value 80.618891 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 116.164966 
iter  10 value 94.434448
iter  20 value 92.774701
iter  30 value 83.053140
iter  40 value 82.109648
iter  50 value 81.326231
iter  60 value 81.087841
iter  70 value 80.921518
iter  80 value 80.741417
iter  90 value 80.618817
iter 100 value 80.457507
final  value 80.457507 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.866038 
final  value 94.485542 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.793884 
final  value 94.485878 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.964026 
final  value 94.485850 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.985478 
iter  10 value 94.526763
iter  20 value 94.520481
iter  30 value 94.497635
final  value 94.484216 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.812897 
final  value 94.485930 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.437839 
iter  10 value 91.443931
iter  20 value 86.089304
iter  30 value 86.081493
iter  40 value 85.838205
iter  50 value 82.848461
iter  60 value 80.468859
iter  70 value 80.228830
iter  80 value 80.189821
iter  90 value 79.820864
iter 100 value 79.036266
final  value 79.036266 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 98.708564 
iter  10 value 94.488747
iter  20 value 94.342391
iter  30 value 92.896256
iter  40 value 92.872661
iter  50 value 92.327590
iter  60 value 89.954987
iter  70 value 89.887127
iter  80 value 89.879073
iter  90 value 89.877673
iter 100 value 89.875770
final  value 89.875770 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 97.401048 
iter  10 value 94.488346
iter  20 value 94.484229
iter  30 value 94.005785
iter  40 value 90.145664
iter  50 value 83.314029
iter  60 value 83.254578
iter  70 value 81.796375
iter  80 value 80.941179
iter  90 value 80.875518
iter 100 value 80.845287
final  value 80.845287 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.577645 
iter  10 value 94.359475
iter  20 value 93.537505
iter  30 value 92.885668
iter  40 value 92.864734
iter  50 value 92.627847
iter  60 value 85.945663
iter  70 value 85.328780
iter  80 value 84.531691
iter  90 value 84.024995
iter 100 value 82.138982
final  value 82.138982 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.341719 
iter  10 value 94.489186
iter  20 value 94.484353
final  value 94.484224 
converged
Fitting Repeat 1 

# weights:  507
initial  value 115.067286 
iter  10 value 94.494071
iter  20 value 94.467408
iter  30 value 87.665920
iter  40 value 87.384078
iter  50 value 87.380854
iter  60 value 86.944793
iter  70 value 83.356452
iter  80 value 81.540100
iter  90 value 81.172100
iter 100 value 80.394252
final  value 80.394252 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 123.430261 
iter  10 value 94.127293
iter  20 value 93.641895
iter  30 value 93.640249
iter  40 value 93.639663
iter  50 value 93.418188
iter  60 value 90.718449
iter  70 value 90.168450
iter  80 value 90.165637
iter  90 value 90.152445
iter 100 value 88.194045
final  value 88.194045 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.920698 
iter  10 value 94.061090
iter  20 value 94.055021
iter  30 value 94.054275
iter  40 value 94.053671
iter  50 value 93.369471
iter  60 value 93.305929
iter  70 value 93.301357
final  value 93.297455 
converged
Fitting Repeat 4 

# weights:  507
initial  value 114.032264 
iter  10 value 94.361996
iter  20 value 93.634458
iter  30 value 82.605613
iter  40 value 82.410049
iter  50 value 82.408378
final  value 82.408101 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.140542 
iter  10 value 91.806693
iter  20 value 88.252710
iter  30 value 88.249306
iter  40 value 86.755793
iter  50 value 86.700346
iter  60 value 85.641118
iter  70 value 85.384720
iter  80 value 84.375669
iter  90 value 84.136652
iter 100 value 83.990474
final  value 83.990474 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.109548 
final  value 94.032967 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.317777 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.844839 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.138434 
final  value 94.032967 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.414544 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 128.933524 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.605628 
iter  10 value 94.032976
final  value 94.032967 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.085340 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.778735 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.668541 
iter  10 value 94.033405
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.932171 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.498298 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.790585 
iter  10 value 92.111119
iter  20 value 91.407909
iter  30 value 91.282399
iter  40 value 91.280006
final  value 91.280001 
converged
Fitting Repeat 4 

# weights:  507
initial  value 132.713209 
iter  10 value 91.254120
iter  20 value 88.667619
final  value 88.219780 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.600472 
final  value 94.005042 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.311526 
iter  10 value 94.014064
iter  20 value 87.233448
iter  30 value 83.195030
iter  40 value 82.733996
iter  50 value 82.263148
iter  60 value 82.178561
iter  70 value 81.938848
iter  80 value 81.493614
iter  90 value 81.476313
final  value 81.476303 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.956397 
iter  10 value 94.041961
iter  20 value 93.477988
iter  30 value 90.610198
iter  40 value 87.671510
iter  50 value 84.305565
iter  60 value 82.733895
iter  70 value 82.522379
iter  80 value 82.308063
iter  90 value 82.287106
iter 100 value 82.202129
final  value 82.202129 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.801347 
iter  10 value 93.333448
iter  20 value 85.511511
iter  30 value 84.241395
iter  40 value 83.640314
iter  50 value 83.207537
iter  60 value 83.034438
iter  70 value 82.993165
iter  80 value 82.376357
iter  90 value 81.795910
iter 100 value 81.684758
final  value 81.684758 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 95.793646 
iter  10 value 94.057830
iter  20 value 93.967050
iter  30 value 91.002223
iter  40 value 90.561182
iter  50 value 86.886269
iter  60 value 84.727013
iter  70 value 84.300146
iter  80 value 83.627105
iter  90 value 81.111531
iter 100 value 80.363488
final  value 80.363488 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.328327 
iter  10 value 93.722368
iter  20 value 86.118298
iter  30 value 83.924275
iter  40 value 83.422383
iter  50 value 82.975165
iter  60 value 82.521449
iter  70 value 82.147802
final  value 82.142896 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.274864 
iter  10 value 85.201753
iter  20 value 83.669020
iter  30 value 82.527392
iter  40 value 82.242727
iter  50 value 81.971444
iter  60 value 81.750934
iter  70 value 81.507472
iter  80 value 80.636549
iter  90 value 80.190711
iter 100 value 79.462132
final  value 79.462132 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.161901 
iter  10 value 94.499847
iter  20 value 85.693256
iter  30 value 82.941200
iter  40 value 82.516618
iter  50 value 82.026335
iter  60 value 81.763557
iter  70 value 81.757783
iter  80 value 80.969401
iter  90 value 80.697984
iter 100 value 80.079060
final  value 80.079060 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.119273 
iter  10 value 94.020525
iter  20 value 92.979740
iter  30 value 92.357675
iter  40 value 86.323849
iter  50 value 85.192590
iter  60 value 83.847703
iter  70 value 80.399585
iter  80 value 80.045858
iter  90 value 79.276378
iter 100 value 78.656767
final  value 78.656767 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.918772 
iter  10 value 94.025766
iter  20 value 89.658524
iter  30 value 85.545509
iter  40 value 84.737550
iter  50 value 83.743479
iter  60 value 80.664349
iter  70 value 78.695077
iter  80 value 78.457115
iter  90 value 78.351831
iter 100 value 78.329337
final  value 78.329337 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.076752 
iter  10 value 94.005227
iter  20 value 88.319334
iter  30 value 84.221442
iter  40 value 83.411045
iter  50 value 83.201234
iter  60 value 81.428958
iter  70 value 80.931427
iter  80 value 80.872807
iter  90 value 80.807258
iter 100 value 80.771625
final  value 80.771625 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.044082 
iter  10 value 94.243902
iter  20 value 87.693539
iter  30 value 83.940332
iter  40 value 81.916437
iter  50 value 81.433957
iter  60 value 80.824595
iter  70 value 80.146769
iter  80 value 78.895314
iter  90 value 78.639217
iter 100 value 78.270496
final  value 78.270496 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.363848 
iter  10 value 94.092784
iter  20 value 85.116040
iter  30 value 83.836018
iter  40 value 82.641490
iter  50 value 82.407231
iter  60 value 80.614992
iter  70 value 79.283239
iter  80 value 78.447370
iter  90 value 78.025568
iter 100 value 77.912328
final  value 77.912328 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.178884 
iter  10 value 94.032716
iter  20 value 83.967322
iter  30 value 82.839494
iter  40 value 82.602938
iter  50 value 82.317539
iter  60 value 82.146365
iter  70 value 81.160546
iter  80 value 79.624566
iter  90 value 78.920114
iter 100 value 78.700863
final  value 78.700863 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.574782 
iter  10 value 92.680814
iter  20 value 84.897754
iter  30 value 83.413422
iter  40 value 81.510290
iter  50 value 81.367015
iter  60 value 80.957687
iter  70 value 80.088007
iter  80 value 79.124631
iter  90 value 78.690651
iter 100 value 78.566489
final  value 78.566489 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.953520 
iter  10 value 97.633814
iter  20 value 92.615701
iter  30 value 92.134791
iter  40 value 91.774241
iter  50 value 91.084491
iter  60 value 81.513016
iter  70 value 79.932329
iter  80 value 79.573664
iter  90 value 79.244607
iter 100 value 79.099553
final  value 79.099553 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.781842 
final  value 94.055120 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.728156 
final  value 94.054508 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.334278 
final  value 94.054714 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.184614 
iter  10 value 94.054322
iter  20 value 94.052994
iter  30 value 92.548142
iter  40 value 90.641138
iter  50 value 90.413717
final  value 90.410316 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.266452 
final  value 94.054544 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.378432 
iter  10 value 94.030453
iter  20 value 93.515713
iter  30 value 92.807682
iter  40 value 92.791833
iter  50 value 92.537604
iter  60 value 92.533215
iter  70 value 92.532868
iter  80 value 92.532369
iter  90 value 92.531359
final  value 92.531316 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.745846 
iter  10 value 93.148566
iter  20 value 93.119339
iter  30 value 93.097034
final  value 93.097016 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.919895 
iter  10 value 94.054186
iter  20 value 94.031579
iter  30 value 93.259759
iter  40 value 93.100749
iter  50 value 93.100103
final  value 93.100083 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.592733 
iter  10 value 94.055437
iter  20 value 94.048706
iter  30 value 94.024616
iter  40 value 84.811469
iter  50 value 82.588996
final  value 82.588042 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.086078 
iter  10 value 94.026955
iter  20 value 89.823550
iter  30 value 86.550546
iter  40 value 86.537036
iter  50 value 86.536066
iter  60 value 83.670330
iter  70 value 81.628092
iter  80 value 81.553714
iter  90 value 81.202292
iter 100 value 81.088347
final  value 81.088347 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 102.059873 
iter  10 value 94.066432
iter  20 value 94.028963
iter  30 value 89.442320
iter  40 value 85.680474
iter  50 value 84.026199
iter  60 value 84.000986
iter  70 value 83.995562
iter  80 value 83.896457
final  value 83.731512 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.891527 
iter  10 value 93.718934
iter  20 value 87.956264
iter  30 value 86.424914
final  value 86.424118 
converged
Fitting Repeat 3 

# weights:  507
initial  value 108.800103 
iter  10 value 94.042352
iter  20 value 93.755757
iter  30 value 89.536022
iter  40 value 83.919927
iter  50 value 82.054900
iter  60 value 81.611717
iter  70 value 81.601782
iter  80 value 81.466199
iter  90 value 81.416863
final  value 81.416839 
converged
Fitting Repeat 4 

# weights:  507
initial  value 107.060749 
iter  10 value 93.722535
iter  20 value 93.715061
iter  30 value 85.486086
iter  40 value 83.982203
iter  50 value 83.863562
iter  60 value 83.772114
final  value 83.771809 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.143581 
iter  10 value 94.061662
iter  20 value 94.052947
iter  30 value 84.674476
iter  40 value 82.424882
iter  50 value 82.369973
iter  60 value 82.361979
iter  70 value 82.239578
iter  80 value 82.065727
iter  90 value 81.660239
iter 100 value 81.469377
final  value 81.469377 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.063908 
iter  10 value 84.316178
iter  20 value 84.080000
final  value 84.079991 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.308995 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.874081 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.302159 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.707518 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.999967 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 109.806646 
iter  10 value 93.946240
final  value 93.946237 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.071209 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.646262 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.209896 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.425345 
iter  10 value 93.367030
iter  20 value 92.211247
iter  30 value 92.159106
final  value 92.158190 
converged
Fitting Repeat 2 

# weights:  507
initial  value 129.594541 
final  value 94.032967 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.909249 
final  value 92.892737 
converged
Fitting Repeat 4 

# weights:  507
initial  value 114.396686 
iter  10 value 86.726734
iter  20 value 82.928871
iter  30 value 82.080764
iter  40 value 81.891366
iter  50 value 81.890806
final  value 81.890758 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.013613 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 109.095284 
iter  10 value 94.031025
iter  20 value 91.725314
iter  30 value 86.378880
iter  40 value 85.426851
iter  50 value 83.813881
iter  60 value 83.250780
iter  70 value 83.075840
iter  80 value 83.055389
iter  90 value 83.054998
final  value 83.054947 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.507948 
iter  10 value 94.052168
iter  20 value 92.695952
iter  30 value 92.153969
iter  40 value 91.044053
iter  50 value 89.974056
iter  60 value 86.875819
iter  70 value 85.841128
iter  80 value 85.683089
iter  90 value 85.635796
iter 100 value 85.485873
final  value 85.485873 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.502599 
iter  10 value 94.021512
iter  20 value 92.015646
iter  30 value 89.645344
iter  40 value 84.013335
iter  50 value 83.579861
iter  60 value 83.416780
iter  70 value 83.389736
final  value 83.385335 
converged
Fitting Repeat 4 

# weights:  103
initial  value 111.711816 
iter  10 value 94.056252
iter  20 value 94.055332
iter  30 value 92.048694
iter  40 value 88.521382
iter  50 value 88.347772
iter  60 value 87.407391
iter  70 value 85.984755
iter  80 value 83.771202
iter  90 value 83.209891
iter 100 value 82.848099
final  value 82.848099 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.416893 
iter  10 value 92.893750
iter  20 value 90.259619
iter  30 value 83.735526
iter  40 value 83.150123
iter  50 value 83.105340
final  value 83.102271 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.820244 
iter  10 value 94.055475
iter  20 value 93.908813
iter  30 value 85.619753
iter  40 value 83.237924
iter  50 value 82.754529
iter  60 value 82.582414
iter  70 value 82.372232
iter  80 value 82.327491
iter  90 value 82.284420
iter 100 value 82.052275
final  value 82.052275 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.021586 
iter  10 value 95.737181
iter  20 value 84.695904
iter  30 value 83.794717
iter  40 value 83.359562
iter  50 value 83.134913
iter  60 value 83.045350
iter  70 value 82.942326
iter  80 value 82.829775
iter  90 value 82.392160
iter 100 value 80.393021
final  value 80.393021 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.113468 
iter  10 value 93.886409
iter  20 value 88.732449
iter  30 value 84.659406
iter  40 value 84.011166
iter  50 value 82.580690
iter  60 value 81.755431
iter  70 value 81.214203
iter  80 value 80.757925
iter  90 value 80.031899
iter 100 value 79.915241
final  value 79.915241 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.888674 
iter  10 value 93.598004
iter  20 value 87.821583
iter  30 value 85.210956
iter  40 value 84.994476
iter  50 value 84.280944
iter  60 value 83.977963
iter  70 value 82.722891
iter  80 value 81.539752
iter  90 value 80.758657
iter 100 value 80.205559
final  value 80.205559 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.508789 
iter  10 value 94.162188
iter  20 value 94.028830
iter  30 value 85.621737
iter  40 value 83.379096
iter  50 value 83.149097
iter  60 value 83.080081
iter  70 value 83.001063
iter  80 value 82.653924
iter  90 value 81.631219
iter 100 value 80.725002
final  value 80.725002 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 102.494382 
iter  10 value 94.152816
iter  20 value 89.884558
iter  30 value 86.280078
iter  40 value 83.926903
iter  50 value 83.335857
iter  60 value 83.147316
iter  70 value 82.997936
iter  80 value 82.102519
iter  90 value 81.179870
iter 100 value 80.080901
final  value 80.080901 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 116.946390 
iter  10 value 94.008381
iter  20 value 92.885032
iter  30 value 86.994323
iter  40 value 86.246491
iter  50 value 84.561408
iter  60 value 83.209932
iter  70 value 82.879358
iter  80 value 81.768265
iter  90 value 80.244897
iter 100 value 80.126322
final  value 80.126322 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.391446 
iter  10 value 94.192547
iter  20 value 93.890630
iter  30 value 86.639791
iter  40 value 85.560260
iter  50 value 83.391177
iter  60 value 83.083480
iter  70 value 82.975949
iter  80 value 82.420074
iter  90 value 81.422745
iter 100 value 80.869407
final  value 80.869407 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.273130 
iter  10 value 94.216760
iter  20 value 89.251339
iter  30 value 86.062104
iter  40 value 84.763369
iter  50 value 83.811121
iter  60 value 82.963852
iter  70 value 81.187749
iter  80 value 80.774008
iter  90 value 80.681432
iter 100 value 80.395149
final  value 80.395149 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 122.818523 
iter  10 value 94.248305
iter  20 value 84.941489
iter  30 value 83.475180
iter  40 value 82.485784
iter  50 value 81.934665
iter  60 value 81.795402
iter  70 value 81.715023
iter  80 value 81.359373
iter  90 value 80.792224
iter 100 value 80.657034
final  value 80.657034 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.612148 
iter  10 value 93.658097
final  value 93.636160 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.949209 
final  value 94.054510 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.134469 
iter  10 value 94.054544
iter  20 value 94.052922
iter  30 value 88.986438
final  value 88.916412 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.156043 
iter  10 value 93.731742
iter  20 value 93.493027
iter  30 value 93.416224
iter  40 value 93.411584
final  value 93.411492 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.191270 
final  value 94.054539 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.871578 
iter  10 value 94.054985
iter  20 value 94.042342
iter  30 value 92.961316
iter  40 value 85.460306
iter  50 value 84.454249
iter  60 value 84.347190
iter  70 value 83.856782
iter  80 value 83.605885
iter  90 value 83.602880
final  value 83.602782 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.199131 
iter  10 value 94.037785
iter  20 value 93.997357
final  value 93.947001 
converged
Fitting Repeat 3 

# weights:  305
initial  value 92.431164 
iter  10 value 91.913755
iter  20 value 91.739880
iter  30 value 91.735897
iter  40 value 91.731940
final  value 91.730998 
converged
Fitting Repeat 4 

# weights:  305
initial  value 128.920254 
iter  10 value 93.993918
iter  20 value 90.452197
iter  30 value 88.626899
iter  40 value 87.507066
iter  50 value 85.467430
final  value 85.466825 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.213985 
iter  10 value 94.037799
iter  20 value 93.949873
iter  30 value 93.947208
iter  40 value 84.143411
iter  50 value 83.914914
final  value 83.912886 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.625078 
iter  10 value 94.058604
iter  20 value 93.953954
iter  30 value 93.947253
iter  40 value 88.489458
iter  50 value 85.353777
iter  60 value 85.331528
iter  70 value 85.324500
iter  80 value 85.324137
iter  90 value 85.318415
iter 100 value 85.315270
final  value 85.315270 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 118.558525 
iter  10 value 94.061094
iter  20 value 94.053216
final  value 94.052900 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.734934 
iter  10 value 94.057739
iter  20 value 94.050034
iter  30 value 84.325013
iter  40 value 83.967947
iter  50 value 83.965235
iter  60 value 83.945861
iter  70 value 83.913092
final  value 83.913091 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.977265 
iter  10 value 94.059765
iter  20 value 93.818111
iter  30 value 91.584505
iter  40 value 91.580479
iter  50 value 91.029654
iter  60 value 90.756935
iter  70 value 85.488722
iter  80 value 85.340402
iter  90 value 85.330005
iter 100 value 84.984036
final  value 84.984036 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 98.090716 
iter  10 value 93.954526
iter  20 value 93.948498
iter  30 value 93.943328
iter  40 value 84.110807
iter  50 value 84.009349
iter  60 value 83.367077
iter  70 value 81.981157
iter  80 value 81.831236
iter  90 value 81.223010
iter 100 value 80.266222
final  value 80.266222 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.643690 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.553420 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.183098 
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.801381 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.511947 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.364044 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.517342 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.735208 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.034717 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.620399 
iter  10 value 91.905120
iter  20 value 91.030618
final  value 88.555221 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.836905 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 117.029479 
iter  10 value 94.442073
iter  10 value 94.442072
iter  10 value 94.442072
final  value 94.442072 
converged
Fitting Repeat 3 

# weights:  507
initial  value 144.366004 
iter  10 value 94.243664
iter  20 value 94.144345
iter  30 value 94.143760
final  value 94.143685 
converged
Fitting Repeat 4 

# weights:  507
initial  value 110.416891 
final  value 94.354396 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.479772 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 109.623222 
iter  10 value 94.496740
iter  20 value 91.694311
iter  30 value 87.156816
iter  40 value 84.578245
iter  50 value 84.089175
iter  60 value 83.764121
iter  70 value 83.529595
iter  80 value 83.448458
iter  90 value 83.386154
final  value 83.383561 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.505779 
iter  10 value 94.456262
iter  20 value 89.459803
iter  30 value 88.279831
iter  40 value 87.656044
iter  50 value 87.588702
iter  60 value 86.234342
iter  70 value 86.038291
iter  80 value 85.972995
final  value 85.972152 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.557797 
iter  10 value 94.542022
iter  20 value 94.482656
iter  30 value 87.225404
iter  40 value 86.546773
iter  50 value 86.383847
iter  60 value 85.911143
iter  70 value 85.457562
iter  80 value 85.358293
final  value 85.357404 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.140734 
iter  10 value 94.480614
iter  20 value 88.250312
iter  30 value 87.448321
iter  40 value 86.127222
iter  50 value 85.999465
iter  60 value 85.930391
iter  70 value 85.603231
final  value 85.552770 
converged
Fitting Repeat 5 

# weights:  103
initial  value 112.042645 
iter  10 value 94.487582
iter  20 value 94.424955
iter  30 value 92.649818
iter  40 value 89.377704
iter  50 value 88.298018
iter  60 value 87.757333
iter  70 value 86.964611
iter  80 value 86.476833
iter  90 value 86.019769
iter 100 value 85.972411
final  value 85.972411 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 101.803839 
iter  10 value 96.892121
iter  20 value 94.217973
iter  30 value 88.587708
iter  40 value 85.078882
iter  50 value 84.420657
iter  60 value 83.772294
iter  70 value 83.494784
iter  80 value 83.406335
iter  90 value 83.202343
iter 100 value 82.763374
final  value 82.763374 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.500240 
iter  10 value 94.580053
iter  20 value 93.224644
iter  30 value 87.810755
iter  40 value 85.810800
iter  50 value 84.135027
iter  60 value 82.649468
iter  70 value 82.521102
iter  80 value 82.444735
iter  90 value 82.189775
iter 100 value 82.049393
final  value 82.049393 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 111.137528 
iter  10 value 93.732126
iter  20 value 90.076495
iter  30 value 87.055542
iter  40 value 86.714210
iter  50 value 86.437916
iter  60 value 86.287338
iter  70 value 86.058509
iter  80 value 85.465353
iter  90 value 85.272188
iter 100 value 84.521101
final  value 84.521101 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.687684 
iter  10 value 94.413307
iter  20 value 91.491495
iter  30 value 87.117828
iter  40 value 86.600394
iter  50 value 83.653113
iter  60 value 83.054937
iter  70 value 82.803326
iter  80 value 82.447779
iter  90 value 82.288060
iter 100 value 82.149981
final  value 82.149981 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.709932 
iter  10 value 94.663113
iter  20 value 94.500626
iter  30 value 92.620253
iter  40 value 87.074841
iter  50 value 84.967622
iter  60 value 84.121364
iter  70 value 83.454104
iter  80 value 82.924950
iter  90 value 82.878772
iter 100 value 82.803036
final  value 82.803036 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.247410 
iter  10 value 94.699304
iter  20 value 89.688553
iter  30 value 87.055611
iter  40 value 86.519490
iter  50 value 85.932514
iter  60 value 84.747321
iter  70 value 83.618268
iter  80 value 83.554182
iter  90 value 83.419641
iter 100 value 83.363715
final  value 83.363715 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.570321 
iter  10 value 94.889015
iter  20 value 88.698240
iter  30 value 87.240019
iter  40 value 86.990283
iter  50 value 85.295991
iter  60 value 84.090625
iter  70 value 83.111149
iter  80 value 82.945851
iter  90 value 82.633694
iter 100 value 82.425993
final  value 82.425993 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 130.074920 
iter  10 value 94.681775
iter  20 value 94.306800
iter  30 value 93.987314
iter  40 value 87.307179
iter  50 value 86.699569
iter  60 value 84.477472
iter  70 value 82.851857
iter  80 value 82.530711
iter  90 value 82.070233
iter 100 value 81.804474
final  value 81.804474 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.884721 
iter  10 value 94.517183
iter  20 value 93.232790
iter  30 value 91.758862
iter  40 value 88.648202
iter  50 value 87.062869
iter  60 value 84.824832
iter  70 value 84.039363
iter  80 value 83.054741
iter  90 value 82.206016
iter 100 value 81.996135
final  value 81.996135 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 117.842312 
iter  10 value 94.918264
iter  20 value 94.406943
iter  30 value 94.064426
iter  40 value 91.426887
iter  50 value 88.701755
iter  60 value 86.963611
iter  70 value 86.147751
iter  80 value 85.286684
iter  90 value 83.968295
iter 100 value 82.767958
final  value 82.767958 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.417515 
final  value 94.485850 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.506187 
final  value 94.485729 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.025227 
final  value 94.485787 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.375459 
final  value 94.486071 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.326035 
final  value 94.485589 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.309566 
iter  10 value 94.488782
iter  20 value 94.472041
iter  30 value 94.147681
iter  40 value 94.145934
iter  50 value 94.134117
iter  50 value 94.134116
iter  50 value 94.134116
final  value 94.134116 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.101544 
iter  10 value 94.488406
iter  20 value 94.424505
iter  30 value 90.708190
iter  40 value 88.609596
iter  50 value 87.174552
iter  60 value 87.173964
final  value 87.173951 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.597537 
iter  10 value 94.488417
iter  20 value 94.237481
iter  30 value 87.706922
iter  40 value 87.680707
iter  50 value 84.333567
iter  60 value 82.563072
iter  70 value 82.541355
iter  80 value 82.465689
iter  90 value 82.293519
iter 100 value 82.163324
final  value 82.163324 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.977369 
iter  10 value 94.359283
iter  20 value 94.357054
iter  30 value 94.356861
iter  40 value 94.354552
iter  50 value 94.287396
iter  60 value 93.305118
iter  70 value 91.591825
iter  80 value 85.107511
final  value 85.080668 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.363960 
iter  10 value 93.736473
iter  20 value 93.671471
iter  30 value 93.670844
final  value 93.669965 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.753355 
iter  10 value 94.492655
iter  20 value 94.484649
iter  30 value 94.368545
iter  40 value 93.801030
iter  50 value 88.855413
iter  60 value 88.575972
iter  70 value 86.466979
iter  80 value 82.319477
iter  90 value 81.535117
iter 100 value 81.348599
final  value 81.348599 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 96.264438 
iter  10 value 94.492868
iter  20 value 94.478106
iter  30 value 94.145293
final  value 94.144544 
converged
Fitting Repeat 3 

# weights:  507
initial  value 108.166739 
iter  10 value 93.739986
iter  20 value 93.732783
iter  30 value 93.030524
iter  40 value 92.567118
iter  50 value 90.619647
iter  60 value 90.524889
iter  70 value 90.522204
iter  80 value 90.507192
iter  90 value 90.444577
iter 100 value 90.392443
final  value 90.392443 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 99.900573 
iter  10 value 94.491404
iter  20 value 89.067992
iter  30 value 86.517715
final  value 86.517514 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.000733 
iter  10 value 94.492341
iter  20 value 94.469356
iter  30 value 90.254997
iter  40 value 87.897595
iter  50 value 87.863973
iter  60 value 87.718656
iter  70 value 87.709524
final  value 87.709002 
converged
Fitting Repeat 1 

# weights:  305
initial  value 125.747487 
iter  10 value 117.895149
iter  20 value 117.784223
final  value 111.877295 
converged
Fitting Repeat 2 

# weights:  305
initial  value 127.276004 
iter  10 value 117.895075
iter  20 value 117.816322
iter  30 value 116.756522
iter  40 value 108.383250
iter  50 value 108.302973
iter  60 value 108.271582
iter  70 value 108.244276
iter  80 value 108.232295
iter  90 value 107.099455
iter 100 value 106.122167
final  value 106.122167 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 142.993325 
iter  10 value 116.220683
iter  20 value 116.145825
iter  30 value 115.469924
iter  40 value 115.242847
iter  50 value 115.242687
iter  60 value 115.242418
iter  70 value 114.647314
final  value 114.642957 
converged
Fitting Repeat 4 

# weights:  305
initial  value 140.834171 
iter  10 value 117.892730
iter  20 value 117.607098
iter  30 value 117.513894
iter  40 value 117.511356
iter  50 value 113.021549
iter  60 value 110.437494
iter  70 value 110.436449
final  value 110.435695 
converged
Fitting Repeat 5 

# weights:  305
initial  value 129.500780 
iter  10 value 117.743879
iter  20 value 115.079528
iter  30 value 115.040285
iter  40 value 114.946332
iter  50 value 114.943951
iter  60 value 114.432152
iter  70 value 113.721414
final  value 113.719875 
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 -- Thu May 21 01:10:22 2026 
*********************************************** 
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 
Warning messages:
1: `repeats` has no meaning for this resampling method. 
2: executing %dopar% sequentially: no parallel backend registered 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
 41.775   1.291 103.642