##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:HPiP.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings HPiP_1.15.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.22-bioc/meat/HPiP.Rcheck’
* using R version 4.5.1 Patched (2025-09-10 r88807)
* using platform: x86_64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 14.2.0
* running under: macOS Monterey 12.7.6
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.15.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... 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       35.148  1.714  37.245
FSmethod      33.350  1.612  35.222
corr_plot     33.106  1.597  34.946
pred_ensembel 14.084  0.421  12.531
enrichfindP    0.482  0.053   7.855
* 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
  ‘/Users/biocbuild/bbs-3.22-bioc/meat/HPiP.Rcheck/00check.log’
for details.

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


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.5-x86_64/Resources/library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.15.0’
** 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 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20

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

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

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

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

# weights:  103
initial  value 95.526039 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.738830 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.807547 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.427975 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 107.656061 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 122.344847 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.261376 
final  value 94.448052 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.781875 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.994052 
iter  10 value 94.468123
final  value 94.467391 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.055372 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.604964 
iter  10 value 93.470621
iter  20 value 93.362073
final  value 93.361960 
converged
Fitting Repeat 2 

# weights:  507
initial  value 124.937713 
final  value 94.467391 
converged
Fitting Repeat 3 

# weights:  507
initial  value 122.697404 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.243801 
final  value 94.467391 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.545960 
final  value 94.467391 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.787151 
iter  10 value 94.480458
iter  20 value 93.862111
iter  30 value 93.823851
iter  40 value 88.223578
iter  50 value 86.040828
iter  60 value 84.898830
iter  70 value 84.831114
iter  80 value 84.650710
iter  90 value 84.564448
final  value 84.558381 
converged
Fitting Repeat 2 

# weights:  103
initial  value 114.234618 
iter  10 value 94.286809
iter  20 value 91.263030
iter  30 value 88.120018
iter  40 value 87.355530
iter  50 value 84.724134
iter  60 value 84.218728
iter  70 value 84.063651
iter  80 value 83.307622
iter  90 value 83.274386
iter 100 value 83.269776
final  value 83.269776 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 104.176011 
iter  10 value 94.485106
iter  20 value 94.311049
iter  30 value 88.485495
iter  40 value 85.296292
iter  50 value 83.970329
iter  60 value 83.882590
iter  70 value 83.864088
final  value 83.859211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 110.221391 
iter  10 value 93.853413
iter  20 value 86.138440
iter  30 value 85.207383
iter  40 value 84.889622
iter  50 value 84.791313
iter  60 value 84.616959
iter  70 value 84.576749
iter  80 value 84.538671
final  value 84.538433 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.701528 
iter  10 value 94.529011
iter  20 value 94.489265
iter  30 value 94.026418
iter  40 value 92.752076
iter  50 value 85.349467
iter  60 value 84.826008
iter  70 value 84.432383
iter  80 value 84.020211
iter  90 value 83.164119
iter 100 value 83.073529
final  value 83.073529 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 107.025562 
iter  10 value 94.600031
iter  20 value 91.063826
iter  30 value 86.918273
iter  40 value 84.861860
iter  50 value 84.022691
iter  60 value 83.441125
iter  70 value 82.429702
iter  80 value 82.281169
iter  90 value 81.749855
iter 100 value 81.583564
final  value 81.583564 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 145.025351 
iter  10 value 94.541839
iter  20 value 89.910808
iter  30 value 88.460633
iter  40 value 87.848872
iter  50 value 84.911399
iter  60 value 84.215999
iter  70 value 83.703871
iter  80 value 83.583511
iter  90 value 83.255363
iter 100 value 83.130157
final  value 83.130157 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.328464 
iter  10 value 94.661766
iter  20 value 94.043496
iter  30 value 87.800669
iter  40 value 85.890274
iter  50 value 84.021013
iter  60 value 83.531804
iter  70 value 82.626640
iter  80 value 82.194484
iter  90 value 81.786544
iter 100 value 81.534638
final  value 81.534638 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.288514 
iter  10 value 92.714331
iter  20 value 91.997624
iter  30 value 88.441883
iter  40 value 85.250660
iter  50 value 83.914741
iter  60 value 83.782542
iter  70 value 83.676523
iter  80 value 83.566676
iter  90 value 83.481472
iter 100 value 83.400996
final  value 83.400996 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 124.065770 
iter  10 value 94.216186
iter  20 value 89.228314
iter  30 value 86.441487
iter  40 value 85.540186
iter  50 value 84.839250
iter  60 value 84.501955
iter  70 value 83.858586
iter  80 value 83.450285
iter  90 value 83.330515
iter 100 value 83.311601
final  value 83.311601 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.906704 
iter  10 value 96.502462
iter  20 value 90.573865
iter  30 value 86.658329
iter  40 value 85.292051
iter  50 value 84.635626
iter  60 value 84.505061
iter  70 value 84.454658
iter  80 value 84.172345
iter  90 value 83.297895
iter 100 value 82.107527
final  value 82.107527 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.552127 
iter  10 value 100.026360
iter  20 value 85.450252
iter  30 value 84.837327
iter  40 value 84.375291
iter  50 value 81.822891
iter  60 value 81.555231
iter  70 value 81.313220
iter  80 value 81.000011
iter  90 value 80.910766
iter 100 value 80.885593
final  value 80.885593 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 124.978599 
iter  10 value 94.455149
iter  20 value 88.463747
iter  30 value 85.969699
iter  40 value 85.634003
iter  50 value 83.124247
iter  60 value 82.354962
iter  70 value 81.915579
iter  80 value 81.714928
iter  90 value 81.295393
iter 100 value 81.089215
final  value 81.089215 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 114.541545 
iter  10 value 94.652303
iter  20 value 93.603274
iter  30 value 88.959480
iter  40 value 87.874246
iter  50 value 87.684588
iter  60 value 86.400237
iter  70 value 84.231743
iter  80 value 82.616988
iter  90 value 81.606463
iter 100 value 81.094662
final  value 81.094662 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.162799 
iter  10 value 94.603192
iter  20 value 89.465975
iter  30 value 85.210340
iter  40 value 83.966057
iter  50 value 83.335655
iter  60 value 82.274251
iter  70 value 82.029205
iter  80 value 81.252410
iter  90 value 81.097090
iter 100 value 80.940627
final  value 80.940627 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.171771 
final  value 94.485827 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.308446 
iter  10 value 94.485821
iter  20 value 94.484043
iter  30 value 93.406983
final  value 93.406974 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.020767 
final  value 94.485964 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.152793 
final  value 94.485706 
converged
Fitting Repeat 5 

# weights:  103
initial  value 109.863278 
final  value 94.468562 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.579956 
iter  10 value 94.329775
iter  20 value 94.315018
iter  30 value 94.183843
iter  40 value 94.142949
iter  50 value 93.102322
iter  60 value 93.047905
iter  70 value 93.038192
iter  80 value 92.838846
iter  90 value 92.838525
iter 100 value 92.838177
final  value 92.838177 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.710400 
iter  10 value 94.472643
iter  20 value 94.467574
final  value 94.467570 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.683642 
iter  10 value 94.472258
iter  20 value 94.448058
iter  30 value 92.493224
iter  40 value 91.520961
iter  50 value 90.586509
iter  60 value 83.781641
iter  70 value 83.054818
iter  80 value 82.980282
iter  90 value 82.979048
iter 100 value 82.793997
final  value 82.793997 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.744072 
iter  10 value 89.252285
iter  20 value 87.566804
iter  30 value 85.742789
iter  40 value 85.740984
iter  50 value 85.735103
iter  60 value 85.734991
final  value 85.734723 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.783239 
iter  10 value 94.472381
iter  20 value 94.468530
final  value 94.467800 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.810673 
iter  10 value 92.331385
iter  20 value 92.284180
iter  30 value 92.246487
iter  40 value 92.238971
iter  50 value 92.181788
iter  60 value 92.181353
iter  70 value 92.180428
final  value 92.180352 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.380145 
iter  10 value 93.881448
iter  20 value 88.318835
iter  30 value 87.033682
iter  40 value 87.031389
iter  50 value 87.030137
iter  60 value 86.674010
iter  70 value 86.612280
iter  80 value 86.611029
iter  90 value 85.047979
iter 100 value 83.591237
final  value 83.591237 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.670183 
iter  10 value 94.491560
iter  20 value 94.481761
iter  30 value 89.559889
iter  40 value 86.311919
iter  50 value 85.680523
iter  60 value 85.145808
iter  70 value 84.861942
iter  80 value 84.856776
final  value 84.854520 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.107540 
iter  10 value 93.353296
iter  20 value 86.840535
iter  30 value 86.693544
iter  40 value 86.688715
iter  50 value 86.662751
iter  60 value 85.979873
iter  70 value 82.419166
iter  80 value 81.048702
iter  90 value 80.613336
iter 100 value 80.429568
final  value 80.429568 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 95.133311 
iter  10 value 94.475414
iter  20 value 94.461341
iter  30 value 94.453584
iter  40 value 94.088495
iter  50 value 93.798581
iter  60 value 85.053698
iter  70 value 84.457668
iter  80 value 83.031470
iter  90 value 82.185772
iter 100 value 81.090704
final  value 81.090704 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.749435 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.308201 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.336806 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.093627 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.442447 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.723466 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.076898 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.287540 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 113.754290 
iter  10 value 93.773048
final  value 93.772973 
converged
Fitting Repeat 5 

# weights:  305
initial  value 111.755087 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.303471 
iter  10 value 92.316902
iter  20 value 92.218570
iter  30 value 92.216777
final  value 92.216767 
converged
Fitting Repeat 2 

# weights:  507
initial  value 112.253233 
iter  10 value 94.450867
final  value 94.450826 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.662361 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 124.715551 
iter  10 value 93.601364
final  value 93.567525 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.144541 
iter  10 value 89.932078
iter  20 value 88.919709
iter  30 value 87.310115
iter  40 value 86.747863
iter  50 value 86.416962
iter  60 value 86.416413
iter  70 value 85.873005
iter  80 value 85.813758
final  value 85.813113 
converged
Fitting Repeat 1 

# weights:  103
initial  value 119.591541 
iter  10 value 94.420791
iter  20 value 91.619246
iter  30 value 85.338026
iter  40 value 83.397022
iter  50 value 83.316117
iter  60 value 82.995778
iter  70 value 82.901414
iter  80 value 82.880134
final  value 82.880101 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.115905 
iter  10 value 94.473242
iter  20 value 90.065231
iter  30 value 84.425502
iter  40 value 83.896498
iter  50 value 83.279113
iter  60 value 82.933059
iter  70 value 82.897795
iter  80 value 82.880117
final  value 82.880101 
converged
Fitting Repeat 3 

# weights:  103
initial  value 114.734989 
iter  10 value 94.486621
iter  20 value 93.686232
iter  30 value 93.422753
iter  40 value 84.389219
iter  50 value 84.010285
iter  60 value 83.143198
iter  70 value 81.478165
iter  80 value 81.007859
iter  90 value 80.333648
final  value 80.301166 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.306435 
iter  10 value 94.611907
iter  20 value 94.487687
iter  30 value 93.551039
iter  40 value 93.414974
iter  50 value 86.065586
iter  60 value 84.278295
iter  70 value 81.354582
iter  80 value 80.798238
iter  90 value 80.602869
iter 100 value 80.306831
final  value 80.306831 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 105.304651 
iter  10 value 94.488615
iter  20 value 93.818238
iter  30 value 92.546470
iter  40 value 88.332562
iter  50 value 87.055472
iter  60 value 86.783853
iter  70 value 86.704461
iter  80 value 86.690802
iter  90 value 86.651485
iter 100 value 86.515781
final  value 86.515781 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 100.017574 
iter  10 value 92.493947
iter  20 value 84.210389
iter  30 value 83.354210
iter  40 value 82.138509
iter  50 value 80.856227
iter  60 value 80.409653
iter  70 value 80.283327
iter  80 value 79.915539
iter  90 value 79.711791
iter 100 value 79.608918
final  value 79.608918 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.178555 
iter  10 value 94.492234
iter  20 value 86.788889
iter  30 value 84.604309
iter  40 value 84.242279
iter  50 value 82.193300
iter  60 value 81.841447
iter  70 value 81.726394
iter  80 value 81.606022
iter  90 value 80.632961
iter 100 value 80.010378
final  value 80.010378 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 115.958907 
iter  10 value 94.558282
iter  20 value 94.076445
iter  30 value 87.152254
iter  40 value 86.444934
iter  50 value 86.171944
iter  60 value 82.632984
iter  70 value 82.498135
iter  80 value 82.479020
iter  90 value 82.268445
iter 100 value 80.974491
final  value 80.974491 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.102761 
iter  10 value 94.494192
iter  20 value 93.326348
iter  30 value 88.493501
iter  40 value 86.923715
iter  50 value 86.439524
iter  60 value 85.412989
iter  70 value 82.184428
iter  80 value 80.281332
iter  90 value 79.293582
iter 100 value 78.944827
final  value 78.944827 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 136.714260 
iter  10 value 94.386989
iter  20 value 84.754195
iter  30 value 84.021968
iter  40 value 83.347998
iter  50 value 82.681464
iter  60 value 82.126660
iter  70 value 80.474392
iter  80 value 79.715200
iter  90 value 79.643660
iter 100 value 79.533863
final  value 79.533863 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.297533 
iter  10 value 94.719347
iter  20 value 92.595313
iter  30 value 87.690733
iter  40 value 81.651170
iter  50 value 80.849468
iter  60 value 79.688511
iter  70 value 79.241549
iter  80 value 79.156648
iter  90 value 79.098823
iter 100 value 78.919758
final  value 78.919758 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.747967 
iter  10 value 94.400534
iter  20 value 91.911100
iter  30 value 87.080098
iter  40 value 84.987332
iter  50 value 83.434095
iter  60 value 81.742657
iter  70 value 81.123807
iter  80 value 80.333071
iter  90 value 79.765659
iter 100 value 79.416062
final  value 79.416062 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 126.165326 
iter  10 value 97.875597
iter  20 value 87.276906
iter  30 value 83.325174
iter  40 value 83.069141
iter  50 value 80.728854
iter  60 value 79.708294
iter  70 value 79.613032
iter  80 value 79.474568
iter  90 value 79.261924
iter 100 value 78.882297
final  value 78.882297 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 114.553367 
iter  10 value 94.524516
iter  20 value 94.094937
iter  30 value 84.430992
iter  40 value 82.836453
iter  50 value 81.956255
iter  60 value 81.354563
iter  70 value 79.965394
iter  80 value 79.203458
iter  90 value 78.968495
iter 100 value 78.839463
final  value 78.839463 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 119.950125 
iter  10 value 86.018286
iter  20 value 83.438731
iter  30 value 82.770405
iter  40 value 82.497073
iter  50 value 82.308892
iter  60 value 81.634149
iter  70 value 81.409388
iter  80 value 80.141763
iter  90 value 79.493695
iter 100 value 78.926080
final  value 78.926080 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.531770 
final  value 94.486175 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.157922 
final  value 94.485928 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.109012 
final  value 94.485602 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.203644 
iter  10 value 93.774829
iter  20 value 93.726013
iter  30 value 93.320008
iter  40 value 93.192059
iter  50 value 93.191991
final  value 93.191985 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.564650 
final  value 94.485867 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.421365 
iter  10 value 94.488074
final  value 94.484364 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.211962 
iter  10 value 87.403765
iter  20 value 84.560159
iter  30 value 83.955812
iter  40 value 83.477958
iter  50 value 80.537305
iter  60 value 78.239869
iter  70 value 77.635149
iter  80 value 77.616121
final  value 77.606680 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.792440 
iter  10 value 93.778130
iter  20 value 93.774126
iter  30 value 85.105067
iter  40 value 82.758964
iter  50 value 81.161455
iter  60 value 79.139015
iter  70 value 78.029151
iter  80 value 78.024935
iter  90 value 78.023818
final  value 78.023773 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.459647 
iter  10 value 94.489682
iter  20 value 94.404539
iter  30 value 85.384521
iter  40 value 84.860651
iter  50 value 83.698526
iter  60 value 83.571485
iter  70 value 81.252052
iter  80 value 80.168568
iter  90 value 80.161779
iter 100 value 79.932769
final  value 79.932769 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.616556 
iter  10 value 93.392357
iter  20 value 93.389234
final  value 93.377140 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.106061 
iter  10 value 94.495127
iter  20 value 94.287758
iter  30 value 82.461466
iter  40 value 82.185427
iter  50 value 82.177523
iter  60 value 82.174712
iter  70 value 82.171604
iter  80 value 82.037798
iter  90 value 81.669781
iter 100 value 81.661198
final  value 81.661198 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.789318 
iter  10 value 90.079651
iter  20 value 88.636500
iter  30 value 88.635046
iter  40 value 82.982526
iter  50 value 82.152213
iter  60 value 81.994244
iter  70 value 81.993042
iter  80 value 81.988392
iter  90 value 81.943669
final  value 81.941646 
converged
Fitting Repeat 3 

# weights:  507
initial  value 108.743117 
iter  10 value 94.492437
iter  20 value 94.482947
iter  30 value 93.889481
iter  40 value 87.666367
iter  50 value 86.647715
iter  60 value 86.104555
iter  70 value 85.965732
iter  80 value 85.960277
final  value 85.959630 
converged
Fitting Repeat 4 

# weights:  507
initial  value 109.182379 
iter  10 value 94.492879
iter  20 value 94.478217
iter  30 value 89.758593
iter  40 value 88.602214
iter  50 value 88.449078
final  value 88.448544 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.739144 
iter  10 value 93.781023
iter  20 value 93.777929
iter  30 value 84.698564
iter  40 value 83.986370
iter  50 value 83.375704
iter  60 value 83.299400
iter  70 value 83.286540
iter  70 value 83.286539
final  value 83.286539 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.455890 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 93.161661 
iter  10 value 83.894585
iter  20 value 83.685550
iter  30 value 83.364760
final  value 83.364499 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.019138 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.947845 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.017796 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.666446 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 106.937571 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.291775 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.361447 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.106450 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.318663 
iter  10 value 94.309860
final  value 94.309797 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.774469 
iter  10 value 94.424304
final  value 94.424079 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.073415 
iter  10 value 93.175047
final  value 93.175041 
converged
Fitting Repeat 4 

# weights:  507
initial  value 113.798401 
iter  10 value 94.480520
iter  10 value 94.480519
iter  10 value 94.480519
final  value 94.480519 
converged
Fitting Repeat 5 

# weights:  507
initial  value 117.367627 
iter  10 value 94.466748
final  value 94.466667 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.469479 
iter  10 value 93.950092
iter  20 value 87.210550
iter  30 value 86.308049
iter  40 value 86.232378
iter  50 value 85.696444
iter  60 value 85.069009
iter  70 value 84.707055
iter  80 value 84.645506
final  value 84.645481 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.018840 
iter  10 value 94.547200
iter  20 value 94.487685
iter  30 value 93.945842
iter  40 value 93.275031
iter  50 value 89.738780
iter  60 value 88.753513
iter  70 value 86.308125
iter  80 value 86.097724
iter  90 value 85.992036
iter 100 value 85.935847
final  value 85.935847 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 118.882498 
iter  10 value 94.330881
iter  20 value 87.759561
iter  30 value 86.649746
iter  40 value 86.548182
iter  50 value 86.355894
iter  60 value 84.789282
iter  70 value 84.265329
final  value 84.265044 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.911279 
iter  10 value 94.486463
iter  20 value 89.822568
iter  30 value 86.746980
iter  40 value 85.977338
iter  50 value 84.740867
iter  60 value 82.984600
iter  70 value 82.542206
final  value 82.496234 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.750807 
iter  10 value 94.470185
iter  20 value 86.845952
iter  30 value 86.302879
iter  40 value 86.194914
iter  50 value 86.019706
iter  60 value 85.495936
iter  70 value 84.778382
iter  80 value 84.586287
iter  90 value 84.392533
iter 100 value 84.285147
final  value 84.285147 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 102.827003 
iter  10 value 94.011753
iter  20 value 87.041293
iter  30 value 85.210023
iter  40 value 82.903295
iter  50 value 81.313689
iter  60 value 80.813906
iter  70 value 80.728526
iter  80 value 80.682968
iter  90 value 80.657454
iter 100 value 80.580334
final  value 80.580334 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.806336 
iter  10 value 93.861141
iter  20 value 87.445989
iter  30 value 85.329800
iter  40 value 85.075248
iter  50 value 84.938982
iter  60 value 83.936210
iter  70 value 82.639566
iter  80 value 82.436658
iter  90 value 82.364493
iter 100 value 82.145541
final  value 82.145541 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.860135 
iter  10 value 94.784489
iter  20 value 94.493753
iter  30 value 94.379339
iter  40 value 92.930940
iter  50 value 87.388512
iter  60 value 86.648408
iter  70 value 86.211121
iter  80 value 85.085592
iter  90 value 83.332506
iter 100 value 81.893878
final  value 81.893878 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 131.393831 
iter  10 value 94.497780
iter  20 value 94.029037
iter  30 value 86.155567
iter  40 value 85.258117
iter  50 value 81.884037
iter  60 value 81.199915
iter  70 value 80.964147
iter  80 value 80.938365
iter  90 value 80.831825
iter 100 value 80.746283
final  value 80.746283 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.492635 
iter  10 value 94.486563
iter  20 value 89.770147
iter  30 value 85.771386
iter  40 value 85.081208
iter  50 value 83.807644
iter  60 value 83.160582
iter  70 value 81.391051
iter  80 value 81.044254
iter  90 value 80.996717
iter 100 value 80.972173
final  value 80.972173 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.764241 
iter  10 value 94.242383
iter  20 value 89.553664
iter  30 value 86.401573
iter  40 value 85.371749
iter  50 value 83.845884
iter  60 value 83.332817
iter  70 value 83.237467
iter  80 value 83.172840
iter  90 value 82.969999
iter 100 value 82.469080
final  value 82.469080 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.819263 
iter  10 value 95.574386
iter  20 value 86.476533
iter  30 value 85.984919
iter  40 value 85.174741
iter  50 value 83.735221
iter  60 value 82.944993
iter  70 value 82.717256
iter  80 value 82.390424
iter  90 value 82.290712
iter 100 value 82.255094
final  value 82.255094 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.908273 
iter  10 value 94.739323
iter  20 value 88.815017
iter  30 value 87.031185
iter  40 value 86.258238
iter  50 value 85.812347
iter  60 value 83.943795
iter  70 value 82.810537
iter  80 value 82.421696
iter  90 value 82.130554
iter 100 value 81.523672
final  value 81.523672 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.875301 
iter  10 value 94.355271
iter  20 value 86.405517
iter  30 value 85.381919
iter  40 value 84.815897
iter  50 value 82.900786
iter  60 value 82.006156
iter  70 value 81.760805
iter  80 value 81.240221
iter  90 value 81.012452
iter 100 value 80.879362
final  value 80.879362 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 118.828336 
iter  10 value 93.676452
iter  20 value 82.345942
iter  30 value 80.921601
iter  40 value 80.533236
iter  50 value 80.374653
iter  60 value 80.333897
iter  70 value 80.308451
iter  80 value 80.227377
iter  90 value 80.223999
iter 100 value 80.189497
final  value 80.189497 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.340547 
final  value 94.485644 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.835750 
final  value 94.482087 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.141949 
final  value 94.486692 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.621213 
final  value 94.486043 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.973791 
final  value 94.485894 
converged
Fitting Repeat 1 

# weights:  305
initial  value 127.859450 
iter  10 value 94.491832
iter  20 value 94.485211
iter  30 value 94.046880
iter  40 value 86.612510
iter  50 value 84.949695
iter  60 value 84.941524
iter  70 value 84.940886
iter  80 value 84.939620
iter  90 value 84.939183
iter 100 value 84.920226
final  value 84.920226 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.564325 
iter  10 value 94.315066
iter  20 value 94.311796
iter  30 value 93.132594
iter  40 value 92.899787
final  value 92.898381 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.383116 
iter  10 value 94.433599
iter  20 value 94.416435
iter  30 value 86.936145
iter  40 value 86.874315
iter  50 value 86.873411
iter  60 value 86.872864
iter  70 value 86.786673
iter  80 value 86.746155
iter  90 value 86.745403
final  value 86.745185 
converged
Fitting Repeat 4 

# weights:  305
initial  value 118.216792 
iter  10 value 94.431299
iter  20 value 94.427832
iter  30 value 92.752034
iter  40 value 83.760974
iter  50 value 83.153880
iter  60 value 83.153667
final  value 83.153629 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.924845 
iter  10 value 94.485814
iter  20 value 94.245988
iter  30 value 90.541821
iter  40 value 87.724621
iter  50 value 83.286712
iter  60 value 82.551981
iter  70 value 82.546295
iter  80 value 82.399635
iter  90 value 82.393891
final  value 82.393870 
converged
Fitting Repeat 1 

# weights:  507
initial  value 119.814442 
iter  10 value 94.488451
iter  20 value 94.474189
iter  30 value 94.470843
iter  40 value 93.600385
iter  50 value 82.760820
iter  60 value 81.968736
iter  70 value 81.441831
iter  80 value 80.754719
iter  90 value 80.364539
iter 100 value 80.005306
final  value 80.005306 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 97.826532 
iter  10 value 92.503223
iter  20 value 86.625130
iter  30 value 86.579053
iter  40 value 86.576373
iter  50 value 84.545310
iter  60 value 84.430812
iter  70 value 83.890693
iter  80 value 82.034909
iter  90 value 81.251599
iter 100 value 81.013799
final  value 81.013799 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.514853 
iter  10 value 94.475222
iter  20 value 94.467278
iter  30 value 94.196932
iter  40 value 87.848730
iter  50 value 87.826511
iter  60 value 87.778887
iter  70 value 87.774499
iter  80 value 87.187846
iter  90 value 86.505254
iter 100 value 84.670207
final  value 84.670207 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 122.571108 
iter  10 value 91.772960
iter  20 value 83.780234
iter  30 value 83.776921
iter  40 value 83.593804
iter  50 value 83.217696
iter  60 value 83.215409
iter  70 value 83.201767
iter  80 value 82.866737
iter  90 value 82.795705
iter 100 value 82.792677
final  value 82.792677 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 101.585888 
iter  10 value 86.737230
iter  20 value 86.708195
iter  30 value 86.702127
iter  40 value 86.681987
iter  50 value 86.592824
iter  60 value 86.588516
iter  70 value 86.578209
iter  80 value 85.246290
iter  90 value 84.765567
final  value 84.765316 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.136039 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.042088 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.094056 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.354840 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.369708 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 122.720220 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.435610 
final  value 94.025290 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.220866 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.586449 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.224739 
iter  10 value 93.582418
iter  10 value 93.582418
iter  10 value 93.582418
final  value 93.582418 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.628185 
iter  10 value 93.430672
final  value 93.430422 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.289600 
iter  10 value 94.052912
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.706480 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.729802 
final  value 93.582418 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.039938 
iter  10 value 93.529068
final  value 93.528329 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.777595 
iter  10 value 94.032649
iter  20 value 93.614012
iter  30 value 93.415690
iter  40 value 92.700848
iter  50 value 85.989809
iter  60 value 85.744154
iter  70 value 85.378207
iter  80 value 85.306116
iter  90 value 84.994263
iter 100 value 84.633605
final  value 84.633605 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 102.654826 
iter  10 value 96.329124
iter  20 value 94.049396
iter  30 value 89.152266
iter  40 value 87.103182
iter  50 value 86.074878
iter  60 value 84.575871
iter  70 value 82.532404
iter  80 value 81.952883
iter  90 value 81.918029
final  value 81.916407 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.844543 
iter  10 value 94.056724
iter  20 value 87.213760
iter  30 value 85.491168
iter  40 value 84.405890
iter  50 value 83.571735
iter  60 value 83.155068
iter  70 value 82.575223
iter  80 value 82.132484
iter  90 value 82.103927
final  value 82.102331 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.312347 
iter  10 value 94.065541
iter  20 value 94.059309
iter  30 value 88.847694
iter  40 value 87.196580
iter  50 value 86.951959
iter  60 value 86.898583
iter  70 value 86.516558
iter  80 value 86.359221
iter  90 value 83.523766
iter 100 value 83.459009
final  value 83.459009 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 100.040224 
iter  10 value 93.888889
iter  20 value 85.816842
iter  30 value 85.156275
iter  40 value 84.871404
iter  50 value 83.800427
iter  60 value 83.470134
iter  70 value 83.457873
final  value 83.457841 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.436349 
iter  10 value 94.495724
iter  20 value 94.097540
iter  30 value 88.064720
iter  40 value 84.821816
iter  50 value 84.022370
iter  60 value 83.536324
iter  70 value 83.442563
iter  80 value 83.431853
iter  90 value 83.211952
iter 100 value 83.125680
final  value 83.125680 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.492323 
iter  10 value 93.764955
iter  20 value 86.995435
iter  30 value 85.589248
iter  40 value 85.407934
iter  50 value 84.851701
iter  60 value 84.623669
iter  70 value 83.929377
iter  80 value 83.627857
iter  90 value 82.277593
iter 100 value 81.517524
final  value 81.517524 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.335704 
iter  10 value 92.928497
iter  20 value 91.219815
iter  30 value 86.769803
iter  40 value 86.423128
iter  50 value 83.873762
iter  60 value 82.077149
iter  70 value 81.323345
iter  80 value 81.141019
iter  90 value 81.056368
iter 100 value 81.000251
final  value 81.000251 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.202022 
iter  10 value 95.354777
iter  20 value 91.936854
iter  30 value 87.149124
iter  40 value 85.475974
iter  50 value 84.939186
iter  60 value 84.325340
iter  70 value 83.970450
iter  80 value 83.520069
final  value 83.482547 
converged
Fitting Repeat 5 

# weights:  305
initial  value 110.060564 
iter  10 value 94.036839
iter  20 value 87.868228
iter  30 value 86.382117
iter  40 value 83.810187
iter  50 value 82.690778
iter  60 value 82.378157
iter  70 value 81.978703
iter  80 value 81.201322
iter  90 value 80.968170
iter 100 value 80.944273
final  value 80.944273 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 117.460926 
iter  10 value 93.908965
iter  20 value 87.816693
iter  30 value 85.977839
iter  40 value 84.758494
iter  50 value 84.449183
iter  60 value 84.069372
iter  70 value 83.490126
iter  80 value 82.282211
iter  90 value 80.830736
iter 100 value 80.312121
final  value 80.312121 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.668546 
iter  10 value 92.294214
iter  20 value 89.650443
iter  30 value 87.662310
iter  40 value 87.262228
iter  50 value 85.942705
iter  60 value 83.870901
iter  70 value 82.487447
iter  80 value 81.401863
iter  90 value 81.159011
iter 100 value 80.907005
final  value 80.907005 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.621547 
iter  10 value 94.288630
iter  20 value 90.880811
iter  30 value 85.202027
iter  40 value 84.026604
iter  50 value 82.005534
iter  60 value 80.935398
iter  70 value 80.715841
iter  80 value 80.632647
iter  90 value 80.610675
iter 100 value 80.604674
final  value 80.604674 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 115.781728 
iter  10 value 93.916182
iter  20 value 89.503857
iter  30 value 85.112525
iter  40 value 83.311117
iter  50 value 82.211291
iter  60 value 81.640779
iter  70 value 81.152653
iter  80 value 80.590992
iter  90 value 80.452892
iter 100 value 80.390849
final  value 80.390849 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.913823 
iter  10 value 93.819487
iter  20 value 90.739547
iter  30 value 83.695814
iter  40 value 82.666218
iter  50 value 82.407057
iter  60 value 81.754938
iter  70 value 80.968095
iter  80 value 80.700890
iter  90 value 80.515270
iter 100 value 80.349573
final  value 80.349573 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.779872 
iter  10 value 94.043801
iter  20 value 94.029681
iter  30 value 94.028309
iter  40 value 92.832151
iter  50 value 89.008426
iter  60 value 88.999298
iter  70 value 86.517745
iter  80 value 86.491811
iter  90 value 86.463355
iter 100 value 86.224650
final  value 86.224650 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 100.410478 
final  value 94.054713 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.714896 
final  value 94.054414 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.720004 
final  value 94.054785 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.474582 
iter  10 value 93.584085
iter  20 value 93.582874
final  value 93.528532 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.663075 
iter  10 value 94.057955
iter  20 value 93.629891
iter  30 value 92.014737
iter  40 value 89.836650
iter  50 value 89.659452
final  value 89.656488 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.591000 
iter  10 value 93.609614
iter  20 value 93.535119
iter  30 value 93.102450
iter  40 value 87.319014
iter  50 value 86.460071
iter  60 value 86.445349
iter  70 value 85.247427
iter  80 value 85.090587
iter  90 value 85.068513
iter 100 value 84.847937
final  value 84.847937 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.160874 
iter  10 value 94.057688
iter  20 value 94.051442
iter  30 value 93.585338
iter  40 value 93.361498
iter  50 value 91.067983
iter  60 value 91.019530
iter  70 value 91.018699
iter  80 value 91.018493
final  value 91.018491 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.093726 
iter  10 value 94.057895
iter  20 value 93.806827
iter  30 value 93.604743
final  value 93.604723 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.484275 
iter  10 value 93.587534
iter  20 value 93.584950
iter  30 value 93.448303
iter  40 value 86.609499
iter  50 value 84.640227
iter  60 value 84.185859
iter  70 value 84.176189
iter  80 value 84.174893
iter  90 value 84.167084
iter 100 value 82.718883
final  value 82.718883 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 98.362052 
iter  10 value 93.590208
iter  20 value 93.584469
iter  30 value 93.528637
final  value 93.528634 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.772486 
iter  10 value 92.240191
iter  20 value 91.964594
iter  30 value 91.603011
iter  40 value 91.364150
iter  50 value 91.361843
iter  60 value 91.349624
iter  70 value 90.813639
iter  80 value 90.812722
iter  90 value 90.812483
iter 100 value 90.812312
final  value 90.812312 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.568062 
iter  10 value 94.067023
iter  20 value 94.058103
iter  30 value 92.936191
iter  40 value 87.616452
iter  50 value 87.590321
iter  60 value 84.247975
iter  70 value 83.521018
iter  80 value 82.699626
iter  90 value 82.065500
iter 100 value 81.479944
final  value 81.479944 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 101.198952 
iter  10 value 94.060651
iter  20 value 94.053265
iter  30 value 93.585829
final  value 93.582602 
converged
Fitting Repeat 5 

# weights:  507
initial  value 109.551229 
iter  10 value 94.059896
iter  20 value 94.044328
iter  30 value 93.649799
iter  40 value 93.605350
iter  50 value 93.604959
final  value 93.604940 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.691718 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.749875 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.230884 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.077996 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 107.152491 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.466202 
final  value 94.032967 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.916444 
final  value 94.032967 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.679008 
final  value 94.032967 
converged
Fitting Repeat 4 

# weights:  305
initial  value 112.565612 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.218432 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.461493 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 110.033478 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 126.707259 
iter  10 value 94.052910
iter  10 value 94.052910
iter  10 value 94.052910
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.884273 
final  value 94.032967 
converged
Fitting Repeat 5 

# weights:  507
initial  value 134.343961 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.573815 
iter  10 value 94.047709
iter  20 value 92.474061
iter  30 value 92.337309
iter  40 value 85.327406
iter  50 value 83.118560
iter  60 value 82.683115
iter  70 value 82.582179
iter  80 value 81.951751
iter  90 value 81.903979
iter 100 value 81.889229
final  value 81.889229 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.743214 
iter  10 value 92.902591
iter  20 value 84.776366
iter  30 value 84.301645
iter  40 value 84.119615
iter  50 value 83.963521
iter  60 value 83.904647
iter  70 value 83.867996
iter  80 value 83.866481
final  value 83.865560 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.361445 
iter  10 value 94.020187
iter  20 value 93.639446
iter  30 value 92.632804
iter  40 value 84.075736
iter  50 value 82.857806
iter  60 value 82.627253
iter  70 value 82.155536
iter  80 value 81.914401
iter  90 value 81.909527
iter 100 value 81.907588
final  value 81.907588 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 102.032942 
iter  10 value 94.522178
iter  20 value 93.986598
iter  30 value 87.219130
iter  40 value 85.824850
iter  50 value 83.763689
iter  60 value 83.596855
iter  70 value 83.495817
iter  80 value 83.483241
iter  80 value 83.483241
iter  80 value 83.483241
final  value 83.483241 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.414658 
iter  10 value 94.057137
iter  20 value 93.199084
iter  30 value 92.537633
iter  40 value 90.047322
iter  50 value 82.113423
iter  60 value 80.405740
iter  70 value 80.004206
iter  80 value 79.897674
iter  90 value 79.580915
iter 100 value 79.523289
final  value 79.523289 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 108.964985 
iter  10 value 93.820787
iter  20 value 87.839686
iter  30 value 87.524143
iter  40 value 87.353053
iter  50 value 85.597903
iter  60 value 83.615305
iter  70 value 81.714181
iter  80 value 81.243742
iter  90 value 79.613405
iter 100 value 79.031880
final  value 79.031880 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.978408 
iter  10 value 94.058721
iter  20 value 91.714647
iter  30 value 89.008036
iter  40 value 87.100851
iter  50 value 83.333280
iter  60 value 80.823064
iter  70 value 79.897897
iter  80 value 79.859603
iter  90 value 79.773748
iter 100 value 79.311786
final  value 79.311786 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.371660 
iter  10 value 91.294930
iter  20 value 84.196723
iter  30 value 83.931238
iter  40 value 83.835246
iter  50 value 83.654934
iter  60 value 83.605634
iter  70 value 83.575550
iter  80 value 83.516464
iter  90 value 83.237200
iter 100 value 82.846684
final  value 82.846684 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.953371 
iter  10 value 94.034995
iter  20 value 88.128929
iter  30 value 86.952679
iter  40 value 85.647856
iter  50 value 82.692073
iter  60 value 80.728300
iter  70 value 79.932650
iter  80 value 79.438203
iter  90 value 78.715212
iter 100 value 78.278234
final  value 78.278234 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.210450 
iter  10 value 94.144823
iter  20 value 93.719446
iter  30 value 88.160346
iter  40 value 82.605396
iter  50 value 81.007849
iter  60 value 80.341276
iter  70 value 79.990806
iter  80 value 78.847029
iter  90 value 78.197938
iter 100 value 78.065960
final  value 78.065960 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.242479 
iter  10 value 93.073312
iter  20 value 86.921366
iter  30 value 83.502142
iter  40 value 81.148624
iter  50 value 80.386472
iter  60 value 79.773986
iter  70 value 79.639166
iter  80 value 79.044833
iter  90 value 78.809177
iter 100 value 78.775176
final  value 78.775176 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.696094 
iter  10 value 94.052001
iter  20 value 92.088798
iter  30 value 90.804199
iter  40 value 90.415945
iter  50 value 87.682605
iter  60 value 84.649938
iter  70 value 80.227320
iter  80 value 79.648306
iter  90 value 79.160823
iter 100 value 78.892631
final  value 78.892631 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 112.630484 
iter  10 value 94.090503
iter  20 value 86.304170
iter  30 value 82.427535
iter  40 value 82.109646
iter  50 value 80.443325
iter  60 value 80.037009
iter  70 value 78.854355
iter  80 value 78.577629
iter  90 value 78.531690
iter 100 value 78.450739
final  value 78.450739 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 118.574747 
iter  10 value 94.320965
iter  20 value 92.020259
iter  30 value 84.014225
iter  40 value 82.746815
iter  50 value 82.416708
iter  60 value 81.966068
iter  70 value 81.695149
iter  80 value 81.223322
iter  90 value 79.692722
iter 100 value 79.235178
final  value 79.235178 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.018027 
iter  10 value 94.007165
iter  20 value 92.034748
iter  30 value 89.325973
iter  40 value 87.601129
iter  50 value 87.518296
iter  60 value 87.453716
iter  70 value 87.271082
iter  80 value 85.789577
iter  90 value 83.298251
iter 100 value 78.947399
final  value 78.947399 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.649411 
final  value 94.054692 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.138044 
final  value 94.054564 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.875061 
iter  10 value 94.053210
iter  20 value 94.011249
iter  30 value 92.043397
iter  40 value 89.944977
iter  50 value 89.781012
iter  60 value 89.705346
iter  70 value 83.018109
iter  80 value 83.016143
iter  90 value 83.015605
final  value 83.015298 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.954869 
iter  10 value 94.034688
iter  20 value 93.870905
iter  30 value 89.821601
iter  40 value 85.707742
iter  50 value 85.644147
iter  60 value 85.639876
iter  70 value 85.638066
iter  80 value 85.636362
iter  90 value 85.632582
iter 100 value 85.630462
final  value 85.630462 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 96.245914 
iter  10 value 94.054509
iter  20 value 94.052280
iter  30 value 92.894850
iter  40 value 92.893986
final  value 92.893973 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.281073 
iter  10 value 94.058608
iter  20 value 93.804418
iter  30 value 93.524502
iter  40 value 90.253197
iter  50 value 90.243965
iter  60 value 90.208411
iter  70 value 90.185487
iter  80 value 90.153947
iter  90 value 86.418816
iter 100 value 80.836910
final  value 80.836910 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 95.122668 
iter  10 value 94.056590
iter  20 value 93.608177
iter  30 value 93.536017
final  value 93.535525 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.664022 
iter  10 value 91.172156
iter  20 value 91.161054
iter  30 value 90.544455
iter  40 value 90.540674
iter  50 value 90.537773
iter  60 value 88.852016
iter  60 value 88.852016
iter  60 value 88.852016
final  value 88.852016 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.679628 
iter  10 value 94.037549
iter  20 value 94.012657
iter  30 value 93.945105
iter  40 value 93.560796
iter  50 value 93.535501
iter  50 value 93.535500
iter  50 value 93.535500
final  value 93.535500 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.311367 
iter  10 value 94.061787
iter  20 value 93.886807
iter  30 value 84.770756
iter  40 value 84.446163
iter  50 value 84.416841
iter  60 value 80.712471
final  value 80.693017 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.301537 
iter  10 value 94.061054
iter  20 value 94.033510
final  value 94.033507 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.424028 
iter  10 value 94.041209
iter  20 value 94.029402
iter  30 value 84.163927
iter  40 value 83.399832
iter  50 value 81.710112
iter  60 value 80.269353
iter  70 value 79.222180
iter  80 value 79.213728
iter  90 value 78.520193
iter 100 value 78.216279
final  value 78.216279 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 97.335070 
iter  10 value 94.041173
iter  20 value 91.080552
iter  30 value 85.657414
iter  40 value 83.869097
iter  50 value 83.221437
iter  60 value 83.219383
iter  70 value 82.544804
iter  80 value 82.529188
iter  90 value 82.314784
final  value 82.297387 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.232313 
iter  10 value 94.061312
iter  20 value 94.000651
iter  30 value 87.251742
iter  40 value 87.250844
iter  50 value 86.932000
iter  60 value 86.309457
iter  70 value 86.083760
iter  80 value 84.053864
iter  90 value 82.701813
iter 100 value 82.668901
final  value 82.668901 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.549019 
iter  10 value 93.851315
iter  20 value 93.542874
iter  30 value 93.205432
iter  40 value 83.352183
iter  50 value 82.154849
iter  60 value 81.734757
iter  70 value 78.363939
iter  80 value 77.186843
iter  90 value 76.814032
iter 100 value 76.738024
final  value 76.738024 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 122.318114 
iter  10 value 117.878635
iter  20 value 117.762103
iter  30 value 117.544607
iter  40 value 113.205514
iter  50 value 103.842548
iter  60 value 103.716600
iter  70 value 103.711592
iter  80 value 103.710737
iter  90 value 103.689837
iter 100 value 103.484417
final  value 103.484417 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 150.822363 
iter  10 value 117.897873
iter  20 value 117.811432
iter  30 value 106.982130
final  value 106.779112 
converged
Fitting Repeat 3 

# weights:  507
initial  value 118.597423 
iter  10 value 117.895479
iter  20 value 112.184576
iter  30 value 106.795274
iter  40 value 106.783140
iter  50 value 106.781544
iter  50 value 106.781544
final  value 106.781544 
converged
Fitting Repeat 4 

# weights:  507
initial  value 139.457278 
iter  10 value 107.236452
iter  20 value 105.362195
iter  30 value 105.356672
iter  40 value 104.547684
iter  50 value 103.643385
iter  60 value 100.627038
iter  70 value 99.635582
iter  80 value 98.884725
iter  90 value 98.786390
iter 100 value 98.762620
final  value 98.762620 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 131.135292 
iter  10 value 117.766336
iter  20 value 117.749378
iter  30 value 117.018506
iter  40 value 106.831095
iter  50 value 104.096832
iter  60 value 104.085500
iter  70 value 104.085271
iter  80 value 104.081316
iter  90 value 101.998912
iter 100 value 101.875555
final  value 101.875555 
stopped after 100 iterations
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Wed Sep 10 22:40:45 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 
 42.542   1.647 119.482