##############################################################################
##############################################################################
###
### 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_1.17.2.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2026-01-15 r89304)
* using platform: aarch64-apple-darwin20
* R was compiled by
    Apple clang version 16.0.0 (clang-1600.0.26.6)
    GNU Fortran (GCC) 14.2.0
* running under: macOS Ventura 13.7.8
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.17.2’
* 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
FSmethod      18.916  0.980  21.140
corr_plot     18.787  0.959  20.716
var_imp       18.662  1.056  21.728
pred_ensembel  6.704  0.141   6.897
enrichfindP    0.196  0.037  10.268
* 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-3.23-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/4.6-arm64/Resources/library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.17.2’
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R Under development (unstable) (2026-01-15 r89304) -- "Unsuffered Consequences"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: aarch64-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 119.181398 
final  value 93.109890 
converged
Fitting Repeat 2 

# weights:  103
initial  value 111.320909 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.936624 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.927862 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.440839 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.260830 
iter  10 value 93.772976
final  value 93.772973 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.162806 
iter  10 value 89.457557
iter  20 value 89.220710
final  value 89.220521 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.257957 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.797516 
iter  10 value 94.120733
iter  20 value 94.112586
final  value 94.112570 
converged
Fitting Repeat 5 

# weights:  305
initial  value 110.836546 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 114.571441 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.338774 
final  value 94.252920 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.929787 
iter  10 value 94.484142
iter  20 value 94.478027
final  value 94.466818 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.059559 
iter  10 value 93.876129
iter  20 value 93.014415
final  value 93.014368 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.749948 
iter  10 value 93.773561
final  value 93.621187 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.183593 
iter  10 value 94.486489
iter  20 value 94.121075
iter  30 value 93.596606
iter  40 value 92.673444
iter  50 value 84.001168
iter  60 value 82.436097
iter  70 value 81.682891
iter  80 value 79.696565
iter  90 value 79.306955
final  value 79.298725 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.862456 
iter  10 value 94.488784
iter  20 value 94.380300
iter  30 value 93.643143
iter  40 value 92.780920
iter  50 value 87.908738
iter  60 value 86.872682
iter  70 value 81.955191
iter  80 value 79.401994
iter  90 value 79.364497
iter 100 value 79.329940
final  value 79.329940 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.512301 
iter  10 value 88.006721
iter  20 value 87.577541
iter  30 value 84.200669
iter  40 value 83.881345
iter  50 value 83.864272
iter  60 value 83.861839
final  value 83.861796 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.823063 
iter  10 value 94.292219
iter  20 value 92.334539
iter  30 value 91.732623
iter  40 value 89.942148
iter  50 value 89.930751
iter  60 value 89.926593
final  value 89.926558 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.203426 
iter  10 value 94.502494
iter  20 value 94.453865
iter  30 value 88.990947
iter  40 value 80.594785
iter  50 value 80.242085
iter  60 value 79.945834
iter  70 value 79.768444
iter  80 value 79.510630
iter  90 value 79.332162
final  value 79.325968 
converged
Fitting Repeat 1 

# weights:  305
initial  value 111.273340 
iter  10 value 95.611962
iter  20 value 90.357173
iter  30 value 89.919668
iter  40 value 87.925659
iter  50 value 86.047974
iter  60 value 81.256826
iter  70 value 80.900286
iter  80 value 80.649745
iter  90 value 80.365248
iter 100 value 80.078227
final  value 80.078227 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 115.269279 
iter  10 value 94.457169
iter  20 value 93.696918
iter  30 value 93.571067
iter  40 value 91.692231
iter  50 value 89.053007
iter  60 value 85.587336
iter  70 value 83.876284
iter  80 value 82.717602
iter  90 value 80.635524
iter 100 value 79.619270
final  value 79.619270 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.620867 
iter  10 value 94.616302
iter  20 value 86.679339
iter  30 value 83.317891
iter  40 value 82.424874
iter  50 value 81.255921
iter  60 value 80.800470
iter  70 value 80.510280
iter  80 value 79.949230
iter  90 value 79.481023
iter 100 value 79.223395
final  value 79.223395 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.198758 
iter  10 value 94.462677
iter  20 value 87.519456
iter  30 value 85.137538
iter  40 value 84.042713
iter  50 value 83.833454
iter  60 value 83.755017
iter  70 value 83.591886
iter  80 value 82.439963
iter  90 value 81.333683
iter 100 value 80.994149
final  value 80.994149 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.443330 
iter  10 value 85.654772
iter  20 value 84.038514
iter  30 value 83.687826
iter  40 value 82.233338
iter  50 value 80.281345
iter  60 value 79.367036
iter  70 value 79.056662
iter  80 value 78.883999
iter  90 value 78.804358
iter 100 value 78.515070
final  value 78.515070 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.179038 
iter  10 value 94.542327
iter  20 value 85.630286
iter  30 value 84.054557
iter  40 value 82.974417
iter  50 value 82.507552
iter  60 value 81.685738
iter  70 value 80.478492
iter  80 value 79.802170
iter  90 value 79.724188
iter 100 value 79.643382
final  value 79.643382 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.826460 
iter  10 value 87.981178
iter  20 value 87.308931
iter  30 value 86.322403
iter  40 value 83.754876
iter  50 value 79.672459
iter  60 value 79.235886
iter  70 value 78.624442
iter  80 value 78.443502
iter  90 value 78.306490
iter 100 value 78.242934
final  value 78.242934 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 122.745251 
iter  10 value 96.127488
iter  20 value 92.768876
iter  30 value 85.587639
iter  40 value 84.277649
iter  50 value 83.507963
iter  60 value 83.304033
iter  70 value 83.062306
iter  80 value 79.801342
iter  90 value 78.285922
iter 100 value 78.175074
final  value 78.175074 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 126.232171 
iter  10 value 93.985024
iter  20 value 84.535071
iter  30 value 81.293930
iter  40 value 79.952052
iter  50 value 79.414865
iter  60 value 79.144967
iter  70 value 79.121283
iter  80 value 78.978306
iter  90 value 78.651821
iter 100 value 78.568188
final  value 78.568188 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.679155 
iter  10 value 93.759250
iter  20 value 84.161853
iter  30 value 83.621189
iter  40 value 81.547664
iter  50 value 81.199393
iter  60 value 81.103619
iter  70 value 80.795364
iter  80 value 80.296773
iter  90 value 79.973754
iter 100 value 78.676749
final  value 78.676749 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.322360 
final  value 94.356118 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.246761 
iter  10 value 85.701297
iter  20 value 82.894216
iter  30 value 82.888411
iter  40 value 82.886935
iter  40 value 82.886934
iter  40 value 82.886934
final  value 82.886934 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.215483 
iter  10 value 85.193961
iter  20 value 85.041705
iter  30 value 85.035424
iter  40 value 84.817291
final  value 84.817275 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.297825 
final  value 94.485797 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.500448 
final  value 94.485810 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.744108 
iter  10 value 94.489365
iter  20 value 90.220941
iter  30 value 82.639173
iter  40 value 82.590728
iter  50 value 82.590037
iter  60 value 81.495196
iter  70 value 79.149465
iter  80 value 79.110262
iter  90 value 79.110204
final  value 79.109915 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.632063 
iter  10 value 94.359530
iter  20 value 94.354955
iter  30 value 93.172833
iter  40 value 84.627944
iter  50 value 79.853273
iter  60 value 78.580710
iter  70 value 76.708975
iter  80 value 76.664258
iter  90 value 76.662321
final  value 76.662133 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.623155 
iter  10 value 93.019800
iter  20 value 88.993239
iter  30 value 86.484690
iter  40 value 86.477774
iter  50 value 86.418996
iter  60 value 86.303777
iter  70 value 86.278925
iter  80 value 86.278603
iter  90 value 86.277547
iter 100 value 86.277423
final  value 86.277423 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.605379 
iter  10 value 94.488438
iter  20 value 94.484233
final  value 94.484223 
converged
Fitting Repeat 5 

# weights:  305
initial  value 121.270032 
iter  10 value 93.534532
iter  20 value 92.796795
iter  30 value 85.708647
iter  40 value 82.619125
iter  50 value 82.507086
iter  60 value 82.504089
iter  70 value 82.489477
iter  80 value 82.466804
iter  90 value 82.296142
iter 100 value 82.293213
final  value 82.293213 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.246306 
iter  10 value 94.493419
iter  20 value 94.470529
iter  30 value 83.782070
iter  40 value 82.916336
iter  50 value 82.898628
iter  60 value 79.506195
iter  70 value 79.488083
iter  80 value 79.356004
iter  90 value 79.313849
iter 100 value 79.312234
final  value 79.312234 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 119.288336 
iter  10 value 93.118387
iter  20 value 89.119160
iter  30 value 82.889766
iter  40 value 82.887192
iter  50 value 82.860687
iter  60 value 82.859645
final  value 82.859597 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.128847 
iter  10 value 94.491990
iter  20 value 94.122807
iter  30 value 83.094374
iter  40 value 82.942976
iter  50 value 82.908661
iter  60 value 82.896185
iter  70 value 82.786604
final  value 82.786472 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.599421 
iter  10 value 94.362462
iter  20 value 92.769091
iter  30 value 85.052044
iter  40 value 84.935929
final  value 84.930562 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.190857 
iter  10 value 94.157008
iter  20 value 94.147081
iter  30 value 93.369829
iter  40 value 90.099059
iter  50 value 90.098089
final  value 90.097621 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.253148 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.735367 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.723591 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.551964 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.314052 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.194749 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 106.257461 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 115.217689 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.544595 
iter  10 value 91.927587
iter  20 value 86.061029
final  value 86.059625 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.835542 
iter  10 value 94.527219
iter  20 value 94.434792
iter  30 value 94.422621
iter  30 value 94.422620
iter  30 value 94.422620
final  value 94.422620 
converged
Fitting Repeat 1 

# weights:  507
initial  value 113.413809 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.932932 
final  value 94.443243 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.753674 
iter  10 value 94.263158
final  value 94.263149 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.641849 
iter  10 value 86.950133
iter  20 value 85.541039
iter  30 value 83.616792
iter  40 value 83.608493
iter  50 value 83.587608
iter  60 value 83.536803
iter  70 value 83.536659
final  value 83.536646 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.553518 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.035516 
iter  10 value 94.431733
iter  20 value 93.301268
iter  30 value 87.243828
iter  40 value 84.421067
iter  50 value 84.266743
iter  60 value 82.612675
iter  70 value 82.432767
iter  80 value 82.430778
iter  80 value 82.430778
iter  80 value 82.430778
final  value 82.430778 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.910222 
iter  10 value 94.441814
iter  20 value 86.255925
iter  30 value 84.790806
iter  40 value 84.293928
iter  50 value 84.271567
final  value 84.271513 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.543998 
iter  10 value 94.473449
iter  20 value 94.296216
iter  30 value 94.289663
iter  40 value 89.588017
iter  50 value 87.857359
iter  60 value 87.060940
iter  70 value 86.286955
iter  80 value 84.712802
iter  90 value 83.993874
iter 100 value 83.580223
final  value 83.580223 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.282192 
iter  10 value 94.507254
iter  20 value 94.485343
iter  30 value 94.347845
iter  40 value 93.395179
iter  50 value 87.524726
iter  60 value 87.072836
iter  70 value 86.858300
final  value 86.846126 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.206278 
iter  10 value 94.219461
iter  20 value 91.241120
iter  30 value 87.443721
iter  40 value 86.306662
iter  50 value 85.877832
iter  60 value 85.579107
final  value 85.579010 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.507575 
iter  10 value 94.519983
iter  20 value 94.471003
iter  30 value 91.729738
iter  40 value 86.700760
iter  50 value 84.127311
iter  60 value 82.914391
iter  70 value 82.445908
iter  80 value 82.352741
iter  90 value 82.347458
iter 100 value 82.310936
final  value 82.310936 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 113.014690 
iter  10 value 94.487163
iter  20 value 92.990717
iter  30 value 89.752690
iter  40 value 87.403359
iter  50 value 87.268984
iter  60 value 86.861504
iter  70 value 86.833852
iter  80 value 84.122978
iter  90 value 81.773505
iter 100 value 81.455502
final  value 81.455502 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.269790 
iter  10 value 94.345693
iter  20 value 89.868346
iter  30 value 87.374386
iter  40 value 86.545704
iter  50 value 85.932677
iter  60 value 85.652254
iter  70 value 85.083506
iter  80 value 82.396796
iter  90 value 81.680040
iter 100 value 81.621940
final  value 81.621940 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.015762 
iter  10 value 94.621656
iter  20 value 91.094249
iter  30 value 87.685176
iter  40 value 85.628504
iter  50 value 83.476628
iter  60 value 82.693021
iter  70 value 81.981817
iter  80 value 81.385720
iter  90 value 80.792413
iter 100 value 80.731666
final  value 80.731666 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.727924 
iter  10 value 94.534295
iter  20 value 89.195559
iter  30 value 87.429447
iter  40 value 87.302953
iter  50 value 87.235892
iter  60 value 85.720119
iter  70 value 84.758615
iter  80 value 82.740558
iter  90 value 81.384084
iter 100 value 81.281097
final  value 81.281097 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.866735 
iter  10 value 95.581120
iter  20 value 94.882180
iter  30 value 93.581135
iter  40 value 89.078061
iter  50 value 86.281538
iter  60 value 85.746486
iter  70 value 84.499027
iter  80 value 82.108176
iter  90 value 81.611171
iter 100 value 81.064237
final  value 81.064237 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 114.784851 
iter  10 value 94.456556
iter  20 value 92.119983
iter  30 value 86.769575
iter  40 value 86.545593
iter  50 value 86.273586
iter  60 value 85.446181
iter  70 value 83.124494
iter  80 value 82.121509
iter  90 value 81.427102
iter 100 value 81.118317
final  value 81.118317 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.117488 
iter  10 value 94.219782
iter  20 value 90.866425
iter  30 value 86.095183
iter  40 value 84.591683
iter  50 value 83.169307
iter  60 value 82.336230
iter  70 value 81.245943
iter  80 value 81.015181
iter  90 value 80.953877
iter 100 value 80.750622
final  value 80.750622 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.169441 
iter  10 value 93.156668
iter  20 value 87.076201
iter  30 value 85.783056
iter  40 value 84.592632
iter  50 value 84.358635
iter  60 value 84.255365
iter  70 value 83.962585
iter  80 value 83.032923
iter  90 value 82.164076
iter 100 value 81.623526
final  value 81.623526 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 119.236363 
iter  10 value 94.383305
iter  20 value 87.159874
iter  30 value 85.790084
iter  40 value 84.659350
iter  50 value 83.115082
iter  60 value 81.277582
iter  70 value 80.742140
iter  80 value 80.651827
iter  90 value 80.578534
iter 100 value 80.376252
final  value 80.376252 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.724157 
iter  10 value 89.332790
iter  20 value 88.673974
iter  30 value 88.094239
iter  40 value 88.088619
iter  50 value 88.088469
iter  60 value 88.087479
final  value 88.087392 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.083580 
iter  10 value 93.218885
iter  20 value 93.218257
final  value 93.184128 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.844620 
final  value 94.485795 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.876832 
final  value 94.485693 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.384403 
iter  10 value 94.485883
final  value 94.484235 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.762098 
iter  10 value 91.981110
iter  20 value 91.683089
iter  30 value 91.497997
iter  40 value 91.496742
iter  50 value 91.495174
iter  60 value 91.493861
iter  60 value 91.493861
final  value 91.493861 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.098858 
iter  10 value 94.488804
iter  20 value 94.484218
iter  30 value 94.265574
iter  40 value 94.263179
iter  50 value 85.366651
iter  60 value 83.341637
iter  70 value 80.628401
iter  80 value 80.564011
iter  90 value 80.470555
iter 100 value 80.430151
final  value 80.430151 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.579663 
iter  10 value 94.488649
iter  20 value 93.218864
iter  30 value 88.277493
iter  40 value 85.977840
final  value 85.977715 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.642409 
iter  10 value 94.448215
iter  20 value 94.443914
iter  30 value 94.438318
iter  40 value 88.515430
iter  50 value 86.497693
iter  60 value 85.979900
final  value 85.978404 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.164434 
iter  10 value 94.489087
iter  20 value 94.343481
iter  30 value 94.278484
final  value 94.263390 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.386778 
iter  10 value 94.451276
iter  20 value 94.443657
iter  30 value 94.432869
iter  40 value 92.827274
iter  50 value 86.509788
iter  60 value 86.122011
iter  70 value 86.101312
iter  80 value 85.628127
iter  90 value 82.994106
iter 100 value 80.971839
final  value 80.971839 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.811472 
iter  10 value 94.492143
iter  20 value 94.471621
iter  30 value 86.788892
iter  40 value 84.712375
iter  50 value 83.459765
iter  60 value 83.176023
iter  70 value 83.068596
final  value 83.066528 
converged
Fitting Repeat 3 

# weights:  507
initial  value 122.408613 
iter  10 value 94.492112
iter  20 value 94.367314
iter  30 value 89.034876
iter  40 value 83.510875
iter  50 value 79.841401
iter  60 value 79.461908
iter  70 value 79.433767
iter  80 value 79.426813
iter  90 value 79.425537
iter 100 value 79.425254
final  value 79.425254 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 99.919733 
iter  10 value 94.492533
iter  20 value 94.426400
iter  30 value 87.418656
iter  40 value 85.926393
iter  50 value 85.427224
iter  60 value 82.249880
iter  70 value 80.736535
iter  80 value 80.656800
iter  90 value 80.367356
iter 100 value 79.698886
final  value 79.698886 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 102.987584 
iter  10 value 94.492636
iter  20 value 94.482578
iter  30 value 87.378808
iter  40 value 86.111061
iter  50 value 84.115196
iter  60 value 83.144496
iter  70 value 83.089381
iter  80 value 83.087915
iter  90 value 83.087828
iter 100 value 83.087642
final  value 83.087642 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.102930 
final  value 94.052911 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.985199 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.114785 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.630831 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.789321 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.258639 
iter  10 value 94.052053
iter  20 value 94.050161
final  value 94.050155 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.103158 
final  value 93.582418 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.116727 
final  value 93.193350 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.078489 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.512230 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.644389 
iter  10 value 94.053190
final  value 94.052911 
converged
Fitting Repeat 2 

# weights:  507
initial  value 154.555868 
iter  10 value 93.582493
final  value 93.582418 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.084931 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 129.180850 
final  value 94.052911 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.236928 
final  value 93.582418 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.414056 
iter  10 value 94.056314
iter  20 value 86.538497
iter  30 value 83.021535
iter  40 value 82.611791
iter  50 value 81.938303
iter  60 value 81.240877
iter  70 value 81.050046
iter  80 value 81.042990
final  value 81.042968 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.040012 
iter  10 value 94.054955
iter  20 value 93.880730
iter  30 value 87.619907
iter  40 value 83.500205
iter  50 value 83.008623
iter  60 value 82.826051
iter  70 value 82.481080
iter  80 value 82.307080
iter  90 value 82.306099
iter 100 value 82.240415
final  value 82.240415 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 94.365095 
iter  10 value 92.314871
iter  20 value 91.021587
iter  30 value 90.657137
iter  40 value 90.624980
final  value 90.624966 
converged
Fitting Repeat 4 

# weights:  103
initial  value 112.157775 
iter  10 value 93.656626
iter  20 value 83.511778
iter  30 value 82.911545
iter  40 value 82.382450
iter  50 value 81.857054
iter  60 value 81.783735
iter  70 value 81.698240
iter  80 value 81.695036
final  value 81.695034 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.702038 
iter  10 value 94.056697
iter  20 value 93.677068
iter  30 value 87.978667
iter  40 value 87.315638
iter  50 value 85.133428
iter  60 value 83.283217
iter  70 value 82.475266
iter  80 value 82.155981
iter  90 value 82.140557
final  value 82.140552 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.121017 
iter  10 value 93.777343
iter  20 value 93.686262
iter  30 value 88.880358
iter  40 value 86.407440
iter  50 value 84.655395
iter  60 value 82.824564
iter  70 value 82.197327
iter  80 value 81.632313
iter  90 value 81.440019
iter 100 value 81.274322
final  value 81.274322 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.176334 
iter  10 value 93.711471
iter  20 value 93.682144
iter  30 value 93.522502
iter  40 value 87.562012
iter  50 value 83.966498
iter  60 value 82.027444
iter  70 value 81.550842
iter  80 value 81.373309
iter  90 value 81.279942
iter 100 value 81.159877
final  value 81.159877 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 109.496299 
iter  10 value 93.255018
iter  20 value 92.091504
iter  30 value 86.784395
iter  40 value 84.487957
iter  50 value 83.892707
iter  60 value 82.512783
iter  70 value 82.452218
iter  80 value 82.296391
iter  90 value 81.427130
iter 100 value 81.302329
final  value 81.302329 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 123.875616 
iter  10 value 96.243419
iter  20 value 93.361258
iter  30 value 84.114204
iter  40 value 82.846561
iter  50 value 82.287028
iter  60 value 81.732217
iter  70 value 81.030902
iter  80 value 80.205708
iter  90 value 79.997917
iter 100 value 79.966902
final  value 79.966902 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.101837 
iter  10 value 94.007623
iter  20 value 93.685932
iter  30 value 93.641831
iter  40 value 93.168839
iter  50 value 88.818000
iter  60 value 82.922262
iter  70 value 82.348596
iter  80 value 81.868662
iter  90 value 80.927169
iter 100 value 80.346116
final  value 80.346116 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.167435 
iter  10 value 87.161772
iter  20 value 83.047890
iter  30 value 82.638344
iter  40 value 81.692822
iter  50 value 80.846513
iter  60 value 80.600807
iter  70 value 80.312362
iter  80 value 79.955871
iter  90 value 79.818006
iter 100 value 79.774366
final  value 79.774366 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.551517 
iter  10 value 94.203698
iter  20 value 93.767470
iter  30 value 93.488257
iter  40 value 87.630778
iter  50 value 84.895801
iter  60 value 84.117918
iter  70 value 83.802280
iter  80 value 81.700027
iter  90 value 80.965968
iter 100 value 80.551920
final  value 80.551920 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 116.387245 
iter  10 value 94.025044
iter  20 value 85.677826
iter  30 value 85.098411
iter  40 value 82.750750
iter  50 value 81.491987
iter  60 value 80.681684
iter  70 value 79.998839
iter  80 value 79.927375
iter  90 value 79.846171
iter 100 value 79.563153
final  value 79.563153 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 117.496373 
iter  10 value 94.159497
iter  20 value 93.566239
iter  30 value 88.771575
iter  40 value 83.315035
iter  50 value 81.725328
iter  60 value 80.755927
iter  70 value 80.305299
iter  80 value 80.124966
iter  90 value 80.046189
iter 100 value 79.981171
final  value 79.981171 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.248133 
iter  10 value 94.821924
iter  20 value 91.060800
iter  30 value 84.872575
iter  40 value 82.836465
iter  50 value 80.984082
iter  60 value 80.761136
iter  70 value 80.380339
iter  80 value 79.808059
iter  90 value 79.677367
iter 100 value 79.402858
final  value 79.402858 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.167044 
final  value 94.054393 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.113940 
final  value 94.054649 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.707440 
iter  10 value 93.584180
iter  20 value 93.583083
final  value 93.582813 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.409646 
final  value 94.054473 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.284241 
final  value 94.054813 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.029147 
iter  10 value 94.058197
iter  20 value 94.037981
iter  30 value 92.605472
iter  40 value 91.866462
iter  50 value 91.467185
iter  60 value 89.233791
iter  70 value 83.326627
iter  80 value 83.179638
iter  90 value 82.483727
iter 100 value 82.195758
final  value 82.195758 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 111.584815 
iter  10 value 93.887181
iter  20 value 93.857268
iter  30 value 93.855969
iter  40 value 92.061386
iter  50 value 92.017757
iter  60 value 91.975572
iter  70 value 91.974881
final  value 91.973495 
converged
Fitting Repeat 3 

# weights:  305
initial  value 119.470441 
iter  10 value 94.008102
iter  20 value 93.973483
iter  30 value 93.702945
final  value 93.583192 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.666838 
iter  10 value 94.057632
iter  20 value 94.055644
iter  30 value 93.950620
iter  40 value 93.156161
iter  50 value 90.699413
iter  60 value 90.646031
iter  70 value 90.645317
iter  80 value 90.641996
iter  80 value 90.641996
final  value 90.641996 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.501113 
iter  10 value 94.057828
iter  20 value 94.052930
iter  30 value 93.659784
final  value 93.582583 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.678798 
iter  10 value 85.828340
iter  20 value 85.824353
iter  30 value 85.817771
iter  40 value 85.709307
final  value 85.708802 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.996425 
iter  10 value 94.060984
iter  20 value 93.940330
iter  30 value 92.751889
iter  40 value 89.068074
iter  50 value 86.964272
iter  60 value 85.472789
iter  70 value 85.344260
final  value 85.344247 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.306937 
iter  10 value 94.067087
iter  20 value 93.756762
iter  30 value 85.764604
iter  40 value 85.755048
iter  50 value 84.236059
iter  60 value 83.459966
iter  70 value 82.247029
iter  80 value 82.070354
iter  90 value 81.983103
iter 100 value 81.978518
final  value 81.978518 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 117.468988 
iter  10 value 92.065417
iter  20 value 90.201107
iter  30 value 90.077844
final  value 90.077138 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.294461 
iter  10 value 91.121891
iter  20 value 90.690715
iter  30 value 90.683766
iter  40 value 90.552437
iter  50 value 90.549999
iter  60 value 90.544309
iter  70 value 90.543888
iter  80 value 90.367094
iter  90 value 90.359650
iter 100 value 89.556789
final  value 89.556789 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.461087 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.518996 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.324941 
iter  10 value 94.036366
final  value 94.032968 
converged
Fitting Repeat 4 

# weights:  103
initial  value 110.581185 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.107364 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.214881 
iter  10 value 93.288889
iter  10 value 93.288889
iter  10 value 93.288889
final  value 93.288889 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.950336 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.707892 
final  value 94.032967 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.975494 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.555571 
iter  10 value 94.032963
iter  10 value 94.032963
iter  10 value 94.032963
final  value 94.032963 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.809998 
iter  10 value 93.863618
final  value 93.863615 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.246540 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.195674 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 111.042884 
iter  10 value 93.735645
iter  20 value 93.288917
iter  20 value 93.288917
final  value 93.288889 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.021194 
iter  10 value 93.879282
iter  20 value 90.895309
iter  30 value 84.227234
iter  40 value 83.915008
iter  50 value 83.914943
iter  60 value 83.763640
final  value 83.763577 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.705746 
iter  10 value 93.947487
iter  20 value 90.455616
iter  30 value 89.172935
iter  40 value 86.121361
iter  50 value 85.778815
iter  60 value 85.367077
iter  70 value 85.231190
final  value 85.230727 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.513735 
iter  10 value 94.108681
iter  20 value 92.801760
iter  30 value 92.671034
iter  40 value 91.539111
iter  50 value 90.863471
iter  60 value 90.813976
iter  70 value 90.813382
iter  70 value 90.813382
iter  70 value 90.813382
final  value 90.813382 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.698370 
iter  10 value 94.125109
iter  20 value 94.056639
iter  30 value 93.650021
iter  40 value 87.614359
iter  50 value 87.334402
iter  60 value 86.328935
iter  70 value 85.585126
iter  80 value 85.077898
iter  90 value 85.042086
final  value 85.042049 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.326806 
iter  10 value 93.550835
iter  20 value 86.065978
iter  30 value 84.315045
iter  40 value 83.004392
iter  50 value 82.905017
iter  60 value 82.801924
iter  70 value 82.744292
iter  80 value 82.388783
iter  90 value 82.231295
iter 100 value 82.173201
final  value 82.173201 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 96.527539 
iter  10 value 94.070715
iter  20 value 91.714075
iter  30 value 87.880134
iter  40 value 87.284612
iter  50 value 85.762512
iter  60 value 85.282601
final  value 85.281041 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.659992 
iter  10 value 93.748870
iter  20 value 87.335099
iter  30 value 85.231484
iter  40 value 84.764661
iter  50 value 84.661579
iter  60 value 83.989079
iter  70 value 82.855072
iter  80 value 82.460712
iter  90 value 82.183585
iter 100 value 81.922391
final  value 81.922391 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.889142 
iter  10 value 94.077188
iter  20 value 92.592358
iter  30 value 87.242415
iter  40 value 85.820583
iter  50 value 85.616761
iter  60 value 84.341323
iter  70 value 82.707565
iter  80 value 81.656370
iter  90 value 81.283452
iter 100 value 81.056629
final  value 81.056629 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.078497 
iter  10 value 94.253759
iter  20 value 92.547538
iter  30 value 88.480973
iter  40 value 87.891805
iter  50 value 86.587320
iter  60 value 82.773879
iter  70 value 81.543697
iter  80 value 81.137148
iter  90 value 80.934489
iter 100 value 80.844851
final  value 80.844851 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 114.096160 
iter  10 value 93.869643
iter  20 value 85.920318
iter  30 value 85.657187
iter  40 value 85.523681
iter  50 value 84.749216
iter  60 value 82.797836
iter  70 value 81.470513
iter  80 value 81.257842
iter  90 value 80.945542
iter 100 value 80.931359
final  value 80.931359 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.949612 
iter  10 value 94.831101
iter  20 value 89.484258
iter  30 value 88.315056
iter  40 value 86.575839
iter  50 value 86.463731
iter  60 value 85.358590
iter  70 value 84.696171
iter  80 value 83.364315
iter  90 value 83.098440
iter 100 value 82.901667
final  value 82.901667 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 115.372158 
iter  10 value 98.251689
iter  20 value 91.493860
iter  30 value 85.587680
iter  40 value 83.406706
iter  50 value 82.884276
iter  60 value 82.389521
iter  70 value 81.558940
iter  80 value 81.392749
iter  90 value 81.308600
iter 100 value 81.250453
final  value 81.250453 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 129.739219 
iter  10 value 94.102994
iter  20 value 93.546392
iter  30 value 88.056697
iter  40 value 84.022797
iter  50 value 82.303089
iter  60 value 81.822767
iter  70 value 81.718388
iter  80 value 81.073682
iter  90 value 80.839594
iter 100 value 80.745700
final  value 80.745700 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 117.220819 
iter  10 value 94.081516
iter  20 value 87.512293
iter  30 value 86.970553
iter  40 value 85.054377
iter  50 value 83.861090
iter  60 value 81.788504
iter  70 value 81.266488
iter  80 value 81.193935
iter  90 value 81.111924
iter 100 value 81.107664
final  value 81.107664 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 119.868527 
iter  10 value 102.600295
iter  20 value 95.281505
iter  30 value 90.022064
iter  40 value 85.494324
iter  50 value 85.239477
iter  60 value 84.225213
iter  70 value 83.238490
iter  80 value 82.783905
iter  90 value 81.960259
iter 100 value 81.886133
final  value 81.886133 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.730542 
iter  10 value 87.852338
iter  20 value 87.468319
iter  30 value 87.279771
iter  40 value 85.434511
iter  50 value 85.056408
iter  60 value 84.474028
iter  70 value 83.287110
iter  80 value 81.976217
iter  90 value 81.834337
iter 100 value 81.678208
final  value 81.678208 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 109.029834 
iter  10 value 94.054395
iter  20 value 93.936737
iter  30 value 88.486316
iter  40 value 88.148301
iter  50 value 87.591149
iter  60 value 87.589747
final  value 87.589686 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.600522 
final  value 94.054369 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.241740 
final  value 94.054791 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.405878 
final  value 94.054514 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.316980 
final  value 94.054609 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.926433 
iter  10 value 89.034682
iter  20 value 86.621089
iter  30 value 86.616550
iter  40 value 86.415417
iter  50 value 86.412298
iter  60 value 86.411902
iter  70 value 86.411709
final  value 86.411678 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.104427 
iter  10 value 94.057058
iter  20 value 93.793662
iter  30 value 89.811185
iter  40 value 86.230080
iter  50 value 86.226745
iter  60 value 86.224598
iter  70 value 86.221678
iter  80 value 86.218759
iter  90 value 86.218305
iter 100 value 86.217752
final  value 86.217752 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 110.385240 
iter  10 value 94.058016
iter  20 value 94.032713
iter  30 value 88.132050
iter  40 value 86.298315
iter  50 value 86.208488
iter  60 value 86.201737
iter  70 value 86.200066
final  value 86.200020 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.609054 
iter  10 value 94.037423
iter  20 value 93.649902
iter  30 value 93.289931
final  value 93.289244 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.158869 
final  value 94.057963 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.934697 
iter  10 value 94.061057
iter  20 value 94.048799
iter  30 value 91.408942
iter  40 value 84.874551
iter  50 value 84.840790
iter  60 value 84.791567
iter  70 value 84.612772
iter  80 value 84.587650
iter  90 value 84.583372
iter 100 value 84.581500
final  value 84.581500 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 96.991859 
iter  10 value 94.063459
iter  20 value 93.700683
iter  30 value 87.025658
iter  40 value 87.022155
iter  50 value 87.020953
iter  60 value 86.969396
iter  70 value 84.386647
iter  80 value 84.170743
iter  90 value 83.709866
iter 100 value 82.392693
final  value 82.392693 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.115896 
iter  10 value 94.061659
iter  20 value 94.054957
iter  30 value 94.006786
iter  40 value 86.861541
iter  50 value 85.294731
iter  60 value 85.291411
final  value 85.291368 
converged
Fitting Repeat 4 

# weights:  507
initial  value 113.500554 
iter  10 value 93.733127
iter  20 value 92.435797
iter  30 value 87.385558
iter  40 value 86.615963
final  value 86.615953 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.419330 
iter  10 value 94.059140
iter  20 value 86.795137
iter  30 value 84.504947
iter  40 value 84.497165
iter  50 value 84.262812
iter  60 value 82.071701
iter  70 value 81.436505
iter  80 value 80.807469
iter  90 value 80.097042
iter 100 value 79.912176
final  value 79.912176 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.017945 
final  value 94.443243 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.840260 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.351148 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.318121 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 113.829868 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.565727 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.964884 
iter  10 value 89.137749
iter  20 value 86.106627
iter  30 value 85.795246
iter  40 value 85.793711
iter  40 value 85.793710
iter  40 value 85.793710
final  value 85.793710 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.101570 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.076146 
final  value 94.443243 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.906415 
final  value 93.783647 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.937876 
final  value 94.484137 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.638113 
iter  10 value 93.946860
iter  20 value 93.886755
iter  30 value 93.842070
final  value 93.842068 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.889672 
iter  10 value 93.605666
iter  20 value 93.452464
iter  30 value 93.450026
final  value 93.450014 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.735903 
iter  10 value 93.722397
final  value 93.722222 
converged
Fitting Repeat 5 

# weights:  507
initial  value 114.603039 
iter  10 value 89.216948
iter  20 value 87.316703
final  value 87.316697 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.188977 
iter  10 value 93.692233
iter  20 value 86.670101
iter  30 value 86.460065
iter  40 value 86.327724
iter  50 value 85.574197
iter  60 value 84.533652
iter  70 value 83.831532
iter  80 value 83.383804
iter  90 value 83.228994
final  value 83.228194 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.937689 
iter  10 value 94.547163
iter  20 value 88.889761
iter  30 value 85.753139
iter  40 value 85.106453
iter  50 value 84.567993
iter  60 value 84.404079
final  value 84.403426 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.335187 
iter  10 value 89.861666
iter  20 value 86.422236
iter  30 value 85.976282
iter  40 value 85.297932
iter  50 value 83.707283
iter  60 value 83.445596
iter  70 value 83.290207
iter  80 value 83.271670
iter  90 value 83.228873
final  value 83.228786 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.411599 
iter  10 value 94.005995
iter  20 value 93.894536
iter  30 value 88.824242
iter  40 value 88.644990
iter  50 value 88.503888
iter  60 value 87.634272
iter  70 value 86.849081
iter  80 value 86.739842
iter  90 value 84.137576
iter 100 value 84.049064
final  value 84.049064 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 98.166550 
iter  10 value 94.411740
iter  20 value 87.900846
iter  30 value 85.627162
iter  40 value 85.368673
iter  50 value 85.098746
iter  60 value 84.951437
iter  70 value 83.916547
iter  80 value 83.551622
iter  90 value 82.730658
iter 100 value 82.708829
final  value 82.708829 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 116.753551 
iter  10 value 94.542046
iter  20 value 94.025923
iter  30 value 93.721481
iter  40 value 88.141144
iter  50 value 87.285158
iter  60 value 86.838653
iter  70 value 86.105182
iter  80 value 84.197565
iter  90 value 82.173840
iter 100 value 81.623359
final  value 81.623359 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.797555 
iter  10 value 95.221078
iter  20 value 92.923854
iter  30 value 89.530814
iter  40 value 87.705263
iter  50 value 85.333465
iter  60 value 82.260941
iter  70 value 82.014606
iter  80 value 81.599897
iter  90 value 81.338300
iter 100 value 81.262292
final  value 81.262292 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.580147 
iter  10 value 94.488679
iter  20 value 93.958776
iter  30 value 90.304787
iter  40 value 88.248357
iter  50 value 85.295829
iter  60 value 83.912402
iter  70 value 82.630792
iter  80 value 82.363475
iter  90 value 82.174967
iter 100 value 82.019024
final  value 82.019024 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.425414 
iter  10 value 94.382936
iter  20 value 86.551296
iter  30 value 86.048062
iter  40 value 84.932009
iter  50 value 83.889731
iter  60 value 83.328845
iter  70 value 82.951619
iter  80 value 82.469591
iter  90 value 82.015053
iter 100 value 81.692084
final  value 81.692084 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.224663 
iter  10 value 94.481850
iter  20 value 93.716296
iter  30 value 87.750034
iter  40 value 85.014584
iter  50 value 84.494832
iter  60 value 83.711021
iter  70 value 82.996466
iter  80 value 81.929719
iter  90 value 81.230635
iter 100 value 81.027050
final  value 81.027050 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 116.026632 
iter  10 value 94.295576
iter  20 value 93.987830
iter  30 value 93.694101
iter  40 value 88.291716
iter  50 value 86.920920
iter  60 value 83.767080
iter  70 value 83.475975
iter  80 value 82.923428
iter  90 value 82.249608
iter 100 value 81.636469
final  value 81.636469 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.547464 
iter  10 value 94.583752
iter  20 value 91.917860
iter  30 value 88.040677
iter  40 value 83.760906
iter  50 value 83.000054
iter  60 value 81.940783
iter  70 value 81.504855
iter  80 value 81.477520
iter  90 value 81.342462
iter 100 value 81.276913
final  value 81.276913 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.726293 
iter  10 value 94.459388
iter  20 value 93.509341
iter  30 value 93.071646
iter  40 value 90.168881
iter  50 value 89.693778
iter  60 value 87.198469
iter  70 value 84.699549
iter  80 value 83.883743
iter  90 value 83.161168
iter 100 value 82.973692
final  value 82.973692 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 137.377213 
iter  10 value 94.926268
iter  20 value 90.762214
iter  30 value 85.507788
iter  40 value 83.723648
iter  50 value 82.503915
iter  60 value 81.819718
iter  70 value 81.682423
iter  80 value 81.217377
iter  90 value 80.932100
iter 100 value 80.804763
final  value 80.804763 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 124.781154 
iter  10 value 91.201127
iter  20 value 87.016313
iter  30 value 85.237381
iter  40 value 83.662004
iter  50 value 83.129196
iter  60 value 82.872649
iter  70 value 81.879249
iter  80 value 81.391701
iter  90 value 81.270820
iter 100 value 81.237284
final  value 81.237284 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.323398 
iter  10 value 85.641844
iter  20 value 84.769920
iter  30 value 84.759096
final  value 84.758903 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.172747 
final  value 94.486029 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.010278 
final  value 94.486223 
converged
Fitting Repeat 4 

# weights:  103
initial  value 110.427097 
iter  10 value 94.215842
iter  20 value 93.924257
iter  30 value 86.276356
iter  40 value 85.955707
iter  50 value 85.917904
iter  60 value 85.917033
iter  70 value 85.878125
iter  80 value 85.493057
iter  90 value 84.525267
iter 100 value 84.048914
final  value 84.048914 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 110.913391 
iter  10 value 94.444987
iter  20 value 94.443622
final  value 94.443549 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.958518 
iter  10 value 94.489142
iter  20 value 94.484526
iter  30 value 94.144130
iter  40 value 91.061151
iter  50 value 90.907165
final  value 90.906704 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.006535 
iter  10 value 94.489101
iter  20 value 94.484255
iter  20 value 94.484255
final  value 94.484255 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.230709 
iter  10 value 94.489198
iter  20 value 94.484140
iter  20 value 94.484140
iter  30 value 92.092785
iter  40 value 86.157246
iter  50 value 86.148115
final  value 86.141414 
converged
Fitting Repeat 4 

# weights:  305
initial  value 108.685473 
iter  10 value 94.488867
iter  20 value 94.290080
iter  30 value 86.705972
iter  40 value 86.334238
iter  50 value 86.265566
iter  60 value 86.262489
final  value 86.262435 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.390777 
iter  10 value 94.489358
iter  20 value 94.484503
iter  30 value 88.584503
iter  40 value 88.263056
iter  50 value 88.260053
iter  60 value 88.259832
iter  70 value 88.241839
iter  80 value 88.237524
final  value 88.237498 
converged
Fitting Repeat 1 

# weights:  507
initial  value 118.949520 
iter  10 value 94.452051
iter  20 value 94.445928
iter  30 value 94.037895
iter  40 value 87.838686
iter  50 value 86.055086
final  value 86.045959 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.256483 
iter  10 value 94.486134
iter  20 value 89.176535
iter  30 value 85.832354
iter  40 value 85.829306
iter  50 value 85.759699
iter  60 value 85.756499
final  value 85.756456 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.405317 
iter  10 value 94.486003
iter  20 value 89.256158
iter  30 value 86.289489
iter  40 value 84.832000
iter  50 value 84.820599
iter  60 value 84.668313
iter  70 value 84.074347
iter  80 value 83.936333
iter  90 value 83.777665
iter 100 value 83.751663
final  value 83.751663 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.529035 
iter  10 value 94.492751
iter  20 value 94.484367
final  value 94.484252 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.445454 
iter  10 value 94.492869
iter  20 value 94.486751
iter  30 value 94.324660
iter  40 value 93.439051
iter  50 value 85.619739
iter  60 value 85.033367
iter  70 value 84.832578
iter  80 value 84.829969
final  value 84.829963 
converged
Fitting Repeat 1 

# weights:  507
initial  value 126.023863 
iter  10 value 117.898409
iter  20 value 117.618410
iter  30 value 117.557482
iter  40 value 117.512076
final  value 117.512016 
converged
Fitting Repeat 2 

# weights:  507
initial  value 119.264225 
iter  10 value 117.439837
iter  20 value 117.438666
iter  30 value 117.069687
iter  40 value 116.817682
iter  50 value 116.808889
final  value 116.808743 
converged
Fitting Repeat 3 

# weights:  507
initial  value 122.592108 
iter  10 value 117.751076
iter  20 value 117.618755
iter  30 value 117.534964
final  value 117.512382 
converged
Fitting Repeat 4 

# weights:  507
initial  value 120.423517 
iter  10 value 117.897973
iter  20 value 117.889751
iter  30 value 115.804945
iter  40 value 112.218042
iter  50 value 107.191093
iter  60 value 107.158067
iter  70 value 105.616038
iter  80 value 105.613940
iter  90 value 104.676886
iter 100 value 104.032826
final  value 104.032826 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 122.753233 
iter  10 value 117.897907
iter  20 value 117.088363
iter  30 value 113.098632
iter  40 value 112.227055
iter  50 value 111.766070
iter  60 value 111.492708
iter  70 value 111.436976
iter  80 value 110.112506
iter  90 value 105.009994
iter 100 value 102.205800
final  value 102.205800 
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 -- Fri Jan 23 20:32:17 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 
 20.735   0.496  71.897