##############################################################################
##############################################################################
###
### 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) (2026-03-01 r89506)
* using platform: aarch64-apple-darwin23
* R was compiled by
    Apple clang version 17.0.0 (clang-1700.3.19.1)
    GNU Fortran (GCC) 14.2.0
* running under: macOS Sonoma 14.8.3
* using session charset: UTF-8
* current time: 2026-03-11 23:07:05 UTC
* 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
corr_plot     18.244  0.981  20.392
var_imp       18.100  1.083  20.695
FSmethod      17.561  0.898  19.335
pred_ensembel  6.653  0.170   6.728
enrichfindP    0.203  0.038  10.930
* 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/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) (2026-03-01 r89506) -- "Unsuffered Consequences"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin23

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 97.002370 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.019246 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.647399 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.314343 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.951357 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.018930 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 110.000389 
final  value 94.354396 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.336177 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.604636 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.848057 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.618641 
final  value 94.353550 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.680968 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.663651 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.575933 
iter  10 value 93.924456
iter  20 value 88.101338
final  value 87.590733 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.675741 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.981783 
iter  10 value 94.488130
iter  20 value 89.639335
iter  30 value 87.363239
iter  40 value 86.688079
iter  50 value 86.230856
iter  60 value 86.227379
final  value 86.227313 
converged
Fitting Repeat 2 

# weights:  103
initial  value 114.539997 
iter  10 value 94.265727
iter  20 value 88.206773
iter  30 value 86.074731
iter  40 value 85.923739
iter  50 value 85.841975
iter  60 value 85.545265
iter  70 value 85.439847
iter  80 value 85.432210
final  value 85.432160 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.237600 
iter  10 value 92.401210
iter  20 value 88.293142
iter  30 value 86.940779
iter  40 value 85.735194
iter  50 value 85.490729
iter  60 value 85.339478
iter  70 value 85.267025
iter  80 value 85.163703
iter  90 value 85.094392
final  value 85.093447 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.943031 
iter  10 value 94.454042
iter  20 value 88.622171
iter  30 value 88.287004
iter  40 value 87.025001
iter  50 value 86.470239
iter  60 value 85.653504
iter  70 value 85.465464
iter  80 value 85.050948
iter  90 value 84.927248
final  value 84.927132 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.635891 
iter  10 value 94.503555
iter  20 value 93.548324
iter  30 value 88.900957
iter  40 value 87.415072
iter  50 value 87.207487
iter  60 value 86.085596
iter  70 value 86.037428
iter  80 value 85.875049
iter  90 value 85.617196
iter 100 value 85.482392
final  value 85.482392 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 103.309606 
iter  10 value 95.571162
iter  20 value 94.578085
iter  30 value 93.709421
iter  40 value 90.403727
iter  50 value 86.102304
iter  60 value 83.137746
iter  70 value 82.759274
iter  80 value 82.502176
iter  90 value 82.350373
iter 100 value 82.194250
final  value 82.194250 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 114.491815 
iter  10 value 94.427707
iter  20 value 88.833122
iter  30 value 88.068026
iter  40 value 87.120354
iter  50 value 86.963941
iter  60 value 85.616283
iter  70 value 85.493934
iter  80 value 85.311088
iter  90 value 85.231004
iter 100 value 85.181762
final  value 85.181762 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.986009 
iter  10 value 94.375101
iter  20 value 87.497371
iter  30 value 86.987880
iter  40 value 85.697070
iter  50 value 83.710736
iter  60 value 83.081812
iter  70 value 82.674289
iter  80 value 82.409241
iter  90 value 82.226004
iter 100 value 82.196349
final  value 82.196349 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 112.849003 
iter  10 value 94.525110
iter  20 value 94.402138
iter  30 value 94.382147
iter  40 value 90.457765
iter  50 value 86.868678
iter  60 value 84.413940
iter  70 value 83.039396
iter  80 value 82.377174
iter  90 value 82.272854
iter 100 value 82.241629
final  value 82.241629 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.834045 
iter  10 value 94.533799
iter  20 value 89.664074
iter  30 value 87.364426
iter  40 value 87.058447
iter  50 value 86.942202
iter  60 value 85.600178
iter  70 value 85.346031
iter  80 value 85.268190
iter  90 value 85.168176
iter 100 value 85.020758
final  value 85.020758 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.955814 
iter  10 value 92.413633
iter  20 value 86.414512
iter  30 value 86.081933
iter  40 value 84.971835
iter  50 value 84.293033
iter  60 value 83.932680
iter  70 value 83.133906
iter  80 value 82.739636
iter  90 value 82.277500
iter 100 value 82.166843
final  value 82.166843 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.938010 
iter  10 value 94.361719
iter  20 value 87.793987
iter  30 value 86.317669
iter  40 value 84.877555
iter  50 value 83.918684
iter  60 value 83.607618
iter  70 value 83.534769
iter  80 value 83.432194
iter  90 value 82.769104
iter 100 value 82.029935
final  value 82.029935 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 136.554157 
iter  10 value 95.108402
iter  20 value 94.702405
iter  30 value 91.136796
iter  40 value 85.965483
iter  50 value 84.140454
iter  60 value 83.235862
iter  70 value 82.554908
iter  80 value 82.422238
iter  90 value 82.163074
iter 100 value 81.879483
final  value 81.879483 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.770527 
iter  10 value 94.763420
iter  20 value 92.680763
iter  30 value 88.710422
iter  40 value 88.384164
iter  50 value 87.030763
iter  60 value 84.441124
iter  70 value 83.771793
iter  80 value 82.777577
iter  90 value 82.400374
iter 100 value 82.191137
final  value 82.191137 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 119.563519 
iter  10 value 94.188994
iter  20 value 88.196651
iter  30 value 86.958222
iter  40 value 84.411132
iter  50 value 83.305545
iter  60 value 82.897876
iter  70 value 82.454846
iter  80 value 82.121492
iter  90 value 82.057778
iter 100 value 81.857728
final  value 81.857728 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.951105 
iter  10 value 94.356092
iter  20 value 94.354459
iter  30 value 88.162173
final  value 87.592963 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.781939 
iter  10 value 94.485772
iter  20 value 94.484269
final  value 94.484214 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.115017 
final  value 94.485834 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.693012 
final  value 94.485666 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.636487 
iter  10 value 94.305661
iter  20 value 94.304834
iter  30 value 94.299194
iter  40 value 91.977240
final  value 91.977190 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.341945 
iter  10 value 94.359060
iter  20 value 94.354541
final  value 94.354535 
converged
Fitting Repeat 2 

# weights:  305
initial  value 108.369498 
iter  10 value 94.359473
iter  20 value 94.354860
final  value 94.354544 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.797099 
iter  10 value 94.488738
iter  20 value 94.484345
iter  30 value 93.788891
final  value 93.784015 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.293106 
iter  10 value 94.359344
iter  20 value 94.354756
final  value 94.354518 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.560428 
iter  10 value 94.359084
iter  20 value 94.354986
final  value 94.354894 
converged
Fitting Repeat 1 

# weights:  507
initial  value 127.362480 
iter  10 value 94.492050
iter  20 value 94.477403
iter  30 value 94.206939
iter  40 value 86.396412
iter  50 value 86.343007
iter  60 value 86.223188
final  value 86.210926 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.009710 
iter  10 value 94.492261
iter  20 value 94.423235
iter  30 value 91.931158
final  value 91.916750 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.669992 
iter  10 value 94.362403
iter  20 value 92.993276
iter  30 value 90.003106
iter  40 value 89.996828
iter  50 value 89.995165
iter  60 value 89.985212
iter  70 value 89.918883
iter  80 value 89.686318
iter  90 value 89.675771
iter 100 value 89.070913
final  value 89.070913 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.696697 
iter  10 value 94.492336
iter  20 value 94.447047
iter  30 value 89.228122
iter  40 value 86.721491
iter  50 value 86.720037
iter  60 value 86.719668
iter  70 value 86.718537
iter  80 value 86.718347
iter  90 value 86.717606
iter 100 value 86.620525
final  value 86.620525 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 119.305547 
iter  10 value 94.492298
iter  20 value 94.368334
iter  30 value 88.183444
iter  40 value 88.179266
iter  50 value 88.094384
iter  60 value 86.628945
iter  70 value 86.627366
iter  80 value 86.580451
iter  90 value 84.955633
iter 100 value 83.620186
final  value 83.620186 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.189278 
iter  10 value 84.318918
final  value 84.318744 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.962645 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.520396 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.681319 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.062973 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.747520 
iter  10 value 92.321521
iter  20 value 92.051092
iter  30 value 92.050002
iter  30 value 92.050002
iter  30 value 92.050002
final  value 92.050002 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.308697 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 113.991151 
final  value 94.264858 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.077677 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.122708 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.401810 
iter  10 value 94.228680
final  value 94.228678 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.477079 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.280237 
final  value 94.443243 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.844088 
final  value 94.443243 
converged
Fitting Repeat 5 

# weights:  507
initial  value 117.702167 
iter  10 value 90.373053
iter  20 value 84.431934
iter  30 value 84.399078
iter  40 value 84.318334
iter  50 value 84.317369
final  value 84.317368 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.522592 
iter  10 value 94.488743
iter  20 value 94.404686
iter  30 value 93.601734
iter  40 value 93.583955
iter  50 value 92.424594
iter  60 value 87.309540
iter  70 value 87.232010
iter  80 value 86.218049
iter  90 value 84.945469
iter 100 value 84.063008
final  value 84.063008 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 106.166385 
iter  10 value 94.489347
iter  20 value 94.486520
iter  30 value 91.724024
iter  40 value 85.604499
iter  50 value 84.377202
iter  60 value 84.114707
iter  70 value 84.056159
iter  80 value 84.046628
iter  90 value 84.036896
final  value 84.034961 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.769909 
iter  10 value 93.962835
iter  20 value 87.652611
iter  30 value 86.700580
iter  40 value 86.456938
iter  50 value 86.184493
iter  60 value 84.706089
iter  70 value 84.073256
iter  80 value 84.041507
final  value 84.034961 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.670941 
iter  10 value 94.138855
iter  20 value 94.101901
iter  30 value 94.086927
iter  40 value 88.392106
iter  50 value 85.414079
iter  60 value 85.375482
iter  70 value 84.120103
iter  80 value 84.051899
final  value 84.046477 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.685862 
iter  10 value 94.441901
iter  20 value 92.877475
iter  30 value 91.778885
iter  40 value 91.765288
iter  50 value 91.761228
iter  60 value 91.759250
iter  70 value 86.035461
iter  80 value 85.289678
iter  90 value 84.635873
iter 100 value 84.278709
final  value 84.278709 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 126.646989 
iter  10 value 94.548437
iter  20 value 92.526349
iter  30 value 89.044866
iter  40 value 85.678696
iter  50 value 84.505665
iter  60 value 82.328504
iter  70 value 81.400950
iter  80 value 81.238079
iter  90 value 81.156189
iter 100 value 81.038273
final  value 81.038273 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.746214 
iter  10 value 94.475228
iter  20 value 88.136378
iter  30 value 87.071906
iter  40 value 85.128343
iter  50 value 84.619445
iter  60 value 83.585413
iter  70 value 82.440204
iter  80 value 80.998641
iter  90 value 80.721666
iter 100 value 80.658420
final  value 80.658420 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 117.080534 
iter  10 value 94.486705
iter  20 value 86.704136
iter  30 value 85.799326
iter  40 value 84.824468
iter  50 value 83.062916
iter  60 value 82.077250
iter  70 value 81.521394
iter  80 value 81.028956
iter  90 value 80.583384
iter 100 value 80.419746
final  value 80.419746 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.968423 
iter  10 value 94.150371
iter  20 value 85.935440
iter  30 value 84.527567
iter  40 value 83.971057
iter  50 value 83.922251
iter  60 value 83.878899
iter  70 value 82.335753
iter  80 value 81.542702
iter  90 value 81.250723
iter 100 value 80.572719
final  value 80.572719 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.171243 
iter  10 value 94.554095
iter  20 value 90.384825
iter  30 value 86.982741
iter  40 value 86.560082
iter  50 value 86.458041
iter  60 value 86.231234
iter  70 value 84.672494
iter  80 value 83.499337
iter  90 value 82.330436
iter 100 value 82.106935
final  value 82.106935 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.575842 
iter  10 value 93.673561
iter  20 value 87.841603
iter  30 value 86.894295
iter  40 value 82.215262
iter  50 value 81.692027
iter  60 value 81.227130
iter  70 value 80.732421
iter  80 value 80.116333
iter  90 value 79.685220
iter 100 value 79.604018
final  value 79.604018 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.580657 
iter  10 value 96.728422
iter  20 value 94.565145
iter  30 value 91.121209
iter  40 value 89.463218
iter  50 value 86.273895
iter  60 value 85.731959
iter  70 value 85.117012
iter  80 value 82.447704
iter  90 value 80.710698
iter 100 value 80.141078
final  value 80.141078 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.062480 
iter  10 value 93.883039
iter  20 value 93.192756
iter  30 value 85.916817
iter  40 value 84.592977
iter  50 value 82.668087
iter  60 value 82.064972
iter  70 value 81.761216
iter  80 value 81.536431
iter  90 value 81.170799
iter 100 value 80.784837
final  value 80.784837 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.567970 
iter  10 value 94.701057
iter  20 value 89.592970
iter  30 value 85.944939
iter  40 value 81.622639
iter  50 value 81.196854
iter  60 value 81.038886
iter  70 value 80.860625
iter  80 value 80.555744
iter  90 value 80.526062
iter 100 value 80.455626
final  value 80.455626 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.349197 
iter  10 value 96.168247
iter  20 value 94.274124
iter  30 value 89.900159
iter  40 value 89.325050
iter  50 value 88.029775
iter  60 value 85.124289
iter  70 value 82.624423
iter  80 value 81.591185
iter  90 value 81.169736
iter 100 value 80.637955
final  value 80.637955 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 108.330606 
iter  10 value 94.486022
iter  20 value 94.484222
final  value 94.484219 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.405836 
final  value 94.485867 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.087028 
final  value 94.486074 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.894566 
final  value 94.485743 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.883835 
final  value 94.485807 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.646746 
iter  10 value 92.313908
iter  20 value 92.306923
iter  30 value 92.303688
iter  40 value 91.591348
iter  50 value 91.590314
iter  60 value 91.590193
iter  70 value 91.589836
final  value 91.589570 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.421603 
iter  10 value 94.448529
iter  20 value 94.437675
iter  30 value 91.489331
iter  40 value 86.735924
iter  50 value 86.123358
iter  60 value 86.121721
final  value 86.121696 
converged
Fitting Repeat 3 

# weights:  305
initial  value 109.009876 
iter  10 value 94.489100
iter  20 value 94.229660
iter  30 value 87.853434
iter  40 value 86.261134
iter  50 value 86.259973
iter  60 value 86.258395
iter  70 value 86.257818
iter  80 value 86.255480
iter  90 value 86.250771
iter 100 value 86.250231
final  value 86.250231 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.528169 
iter  10 value 87.386889
iter  20 value 86.107980
iter  30 value 86.053012
final  value 86.052612 
converged
Fitting Repeat 5 

# weights:  305
initial  value 113.290136 
iter  10 value 94.489130
iter  20 value 94.483160
iter  30 value 94.052387
iter  40 value 93.998117
final  value 93.998013 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.196774 
iter  10 value 94.492727
iter  20 value 94.218567
iter  30 value 93.300956
iter  40 value 88.077766
iter  50 value 82.541727
iter  60 value 82.397337
iter  70 value 82.392568
final  value 82.392531 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.759271 
iter  10 value 94.451881
iter  20 value 94.444731
iter  30 value 94.361163
iter  40 value 91.589530
iter  50 value 84.817814
iter  60 value 84.684011
iter  70 value 84.680501
iter  80 value 84.680286
iter  90 value 84.678477
iter 100 value 84.596444
final  value 84.596444 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 127.856680 
iter  10 value 94.491752
iter  20 value 94.465220
iter  30 value 92.920501
iter  40 value 82.749207
iter  50 value 82.298399
iter  60 value 82.264756
iter  70 value 82.264435
iter  80 value 82.257728
iter  90 value 82.153550
iter 100 value 81.122689
final  value 81.122689 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 130.673348 
iter  10 value 94.492625
iter  20 value 94.427914
iter  30 value 85.639003
iter  40 value 84.684520
iter  50 value 84.683892
final  value 84.683674 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.670794 
iter  10 value 90.510824
iter  20 value 88.721943
iter  30 value 88.701742
iter  40 value 88.699827
iter  50 value 88.698545
iter  60 value 88.697913
iter  70 value 88.695630
iter  80 value 88.541871
iter  90 value 87.767595
iter 100 value 85.511482
final  value 85.511482 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.460521 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.323899 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.026761 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.803576 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.394474 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.152352 
iter  10 value 93.891983
iter  20 value 93.883904
final  value 93.883852 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.896033 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.408870 
final  value 94.032967 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.671446 
final  value 94.032967 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.642288 
iter  10 value 93.261231
final  value 93.153846 
converged
Fitting Repeat 1 

# weights:  507
initial  value 114.386273 
iter  10 value 94.033002
final  value 94.032967 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.688997 
final  value 93.991525 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.877599 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 122.637666 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 114.625465 
final  value 93.991526 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.888367 
iter  10 value 93.969308
iter  20 value 91.373725
iter  30 value 91.085795
iter  40 value 91.023246
iter  50 value 90.252473
iter  60 value 90.207878
final  value 90.207848 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.114915 
iter  10 value 94.056868
iter  20 value 93.838436
iter  30 value 88.199190
iter  40 value 83.496541
iter  50 value 83.095980
iter  60 value 82.852623
iter  70 value 81.669807
iter  80 value 80.979544
iter  90 value 80.932619
iter  90 value 80.932619
iter  90 value 80.932619
final  value 80.932619 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.261135 
iter  10 value 88.823692
iter  20 value 85.995569
iter  30 value 84.711793
iter  40 value 84.360775
iter  50 value 84.319729
iter  60 value 84.297773
iter  70 value 84.279748
iter  80 value 82.367768
iter  90 value 81.399214
iter 100 value 80.376121
final  value 80.376121 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 100.541209 
iter  10 value 93.848289
iter  20 value 85.985773
iter  30 value 85.049479
iter  40 value 84.568971
iter  50 value 84.530312
iter  60 value 83.715118
iter  70 value 80.584937
iter  80 value 80.042181
iter  90 value 79.962681
iter 100 value 79.895322
final  value 79.895322 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 106.567920 
iter  10 value 93.986109
iter  20 value 87.292317
iter  30 value 86.366419
iter  40 value 84.913924
iter  50 value 84.449971
iter  60 value 84.309727
iter  70 value 84.278820
iter  80 value 79.958490
iter  90 value 79.859936
iter 100 value 79.859749
final  value 79.859749 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 109.457672 
iter  10 value 94.046854
iter  20 value 88.417992
iter  30 value 84.323398
iter  40 value 82.589607
iter  50 value 81.188925
iter  60 value 80.222898
iter  70 value 79.749599
iter  80 value 79.392114
iter  90 value 78.992643
iter 100 value 78.663933
final  value 78.663933 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 114.045325 
iter  10 value 89.281515
iter  20 value 82.223447
iter  30 value 79.626116
iter  40 value 78.875346
iter  50 value 77.678472
iter  60 value 76.699545
iter  70 value 76.575345
iter  80 value 76.329222
iter  90 value 76.171489
iter 100 value 76.126139
final  value 76.126139 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 111.024494 
iter  10 value 94.078382
iter  20 value 92.809171
iter  30 value 89.580039
iter  40 value 82.561919
iter  50 value 81.099087
iter  60 value 80.240403
iter  70 value 79.710774
iter  80 value 79.159702
iter  90 value 78.825213
iter 100 value 78.713395
final  value 78.713395 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 114.716655 
iter  10 value 95.250756
iter  20 value 94.077533
iter  30 value 89.738154
iter  40 value 80.226525
iter  50 value 79.697131
iter  60 value 79.572095
iter  70 value 78.849874
iter  80 value 78.077373
iter  90 value 77.649513
iter 100 value 77.589018
final  value 77.589018 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 112.541420 
iter  10 value 94.063250
iter  20 value 94.040624
iter  30 value 93.465192
iter  40 value 93.327359
iter  50 value 89.641567
iter  60 value 80.019327
iter  70 value 79.703969
iter  80 value 79.582549
iter  90 value 79.464786
iter 100 value 79.381769
final  value 79.381769 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.376396 
iter  10 value 93.145079
iter  20 value 83.521468
iter  30 value 81.886253
iter  40 value 78.501338
iter  50 value 76.831073
iter  60 value 76.563891
iter  70 value 76.391631
iter  80 value 76.236988
iter  90 value 76.191626
iter 100 value 76.133985
final  value 76.133985 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 144.563799 
iter  10 value 94.160214
iter  20 value 88.053289
iter  30 value 83.459937
iter  40 value 78.950500
iter  50 value 77.844814
iter  60 value 77.581952
iter  70 value 77.366831
iter  80 value 77.197674
iter  90 value 76.926431
iter 100 value 76.824839
final  value 76.824839 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.094930 
iter  10 value 87.129899
iter  20 value 84.116334
iter  30 value 80.068064
iter  40 value 79.028017
iter  50 value 78.337319
iter  60 value 77.194395
iter  70 value 76.905916
iter  80 value 76.237878
iter  90 value 75.989649
iter 100 value 75.726506
final  value 75.726506 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 117.429906 
iter  10 value 94.011030
iter  20 value 84.268913
iter  30 value 81.462916
iter  40 value 80.823311
iter  50 value 80.210540
iter  60 value 79.425533
iter  70 value 78.923687
iter  80 value 78.683093
iter  90 value 78.229579
iter 100 value 78.099452
final  value 78.099452 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 114.972598 
iter  10 value 94.502897
iter  20 value 83.755232
iter  30 value 82.954379
iter  40 value 80.579370
iter  50 value 78.880230
iter  60 value 78.358106
iter  70 value 77.791691
iter  80 value 77.553715
iter  90 value 77.290448
iter 100 value 77.117284
final  value 77.117284 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.057187 
iter  10 value 94.034540
iter  20 value 93.998169
iter  30 value 85.031986
iter  40 value 84.116055
iter  50 value 81.721024
final  value 81.216814 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.339192 
iter  10 value 94.054577
final  value 94.052915 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.113803 
final  value 94.054695 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.918636 
final  value 94.054882 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.134798 
final  value 94.054448 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.994713 
iter  10 value 94.058079
iter  20 value 94.052855
iter  30 value 92.992506
iter  40 value 91.859153
final  value 91.823402 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.053872 
iter  10 value 94.053162
iter  20 value 92.580064
iter  30 value 91.954221
iter  40 value 91.848161
iter  50 value 91.847652
iter  60 value 87.964584
iter  70 value 81.556932
iter  80 value 81.051238
final  value 80.981387 
converged
Fitting Repeat 3 

# weights:  305
initial  value 115.373792 
iter  10 value 94.059158
final  value 94.054859 
converged
Fitting Repeat 4 

# weights:  305
initial  value 115.900466 
iter  10 value 94.058083
iter  20 value 93.936705
iter  30 value 86.065157
iter  40 value 84.939104
iter  50 value 84.802014
iter  60 value 84.796483
iter  70 value 84.402044
iter  80 value 84.222836
iter  90 value 84.219575
iter 100 value 84.091402
final  value 84.091402 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 94.123859 
iter  10 value 94.037478
iter  20 value 94.033022
iter  30 value 89.098860
iter  40 value 88.406954
final  value 88.405734 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.500140 
iter  10 value 94.059306
iter  20 value 93.860555
iter  30 value 84.907064
iter  40 value 84.411398
iter  50 value 84.406919
iter  60 value 84.151750
iter  70 value 83.117699
iter  80 value 83.036910
iter  90 value 81.204107
iter 100 value 81.078147
final  value 81.078147 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 96.337156 
iter  10 value 93.977326
iter  20 value 93.706793
iter  30 value 86.781709
iter  40 value 86.473294
iter  50 value 86.187535
iter  60 value 80.071280
iter  70 value 76.523409
iter  80 value 76.451274
final  value 76.446695 
converged
Fitting Repeat 3 

# weights:  507
initial  value 111.221229 
iter  10 value 93.976033
iter  20 value 93.969767
iter  30 value 88.691058
iter  40 value 81.081394
iter  50 value 79.136485
iter  60 value 77.260716
iter  70 value 76.896541
iter  80 value 76.750853
iter  90 value 76.724260
final  value 76.718600 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.417053 
iter  10 value 94.061075
iter  20 value 93.996233
iter  30 value 84.112493
iter  40 value 84.019029
iter  50 value 81.335970
iter  60 value 80.017303
iter  70 value 78.428360
iter  80 value 78.427847
iter  90 value 78.390326
iter 100 value 78.075797
final  value 78.075797 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 97.808268 
iter  10 value 94.058566
iter  20 value 91.926809
iter  30 value 90.182146
iter  40 value 89.406813
iter  50 value 88.936177
iter  60 value 88.857494
iter  70 value 88.825786
final  value 88.821363 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.392740 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.107756 
final  value 94.483333 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.904772 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.520870 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.945873 
iter  10 value 93.670246
final  value 93.572293 
converged
Fitting Repeat 1 

# weights:  305
initial  value 124.174567 
iter  10 value 94.484211
iter  10 value 94.484211
iter  10 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.701719 
final  value 94.088889 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.447722 
final  value 94.448052 
converged
Fitting Repeat 4 

# weights:  305
initial  value 109.039138 
final  value 94.461538 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.265404 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.354852 
iter  10 value 90.328108
iter  20 value 86.263984
iter  30 value 86.187907
iter  40 value 86.174219
final  value 86.157328 
converged
Fitting Repeat 2 

# weights:  507
initial  value 117.124337 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.889796 
iter  10 value 87.074426
iter  20 value 86.525711
iter  30 value 86.464533
final  value 86.464479 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.729026 
iter  10 value 94.134496
final  value 94.055814 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.232748 
iter  10 value 93.553953
iter  20 value 93.161760
final  value 93.161539 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.477244 
iter  10 value 94.406969
iter  20 value 93.766301
iter  30 value 86.743664
iter  40 value 83.971803
iter  50 value 83.458257
iter  60 value 83.080341
iter  70 value 82.767320
iter  80 value 82.459380
iter  90 value 82.286594
final  value 82.286570 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.042991 
iter  10 value 94.663002
iter  20 value 94.383977
iter  30 value 91.814058
iter  40 value 85.312860
iter  50 value 84.571774
iter  60 value 82.566946
iter  70 value 82.208319
final  value 82.136930 
converged
Fitting Repeat 3 

# weights:  103
initial  value 110.400656 
iter  10 value 94.013315
iter  20 value 89.413110
iter  30 value 88.913460
iter  40 value 88.836237
iter  50 value 88.095538
iter  60 value 86.741837
iter  70 value 85.975776
iter  80 value 85.961669
final  value 85.961609 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.287240 
iter  10 value 94.490738
iter  20 value 94.281365
iter  30 value 93.978850
iter  40 value 92.725708
iter  50 value 88.187345
iter  60 value 87.088323
iter  70 value 86.808871
iter  80 value 86.200977
iter  90 value 86.033660
iter 100 value 85.961905
final  value 85.961905 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 96.988547 
iter  10 value 91.946354
iter  20 value 88.855823
iter  30 value 87.857768
iter  40 value 85.704169
iter  50 value 85.604784
iter  60 value 85.569612
final  value 85.561261 
converged
Fitting Repeat 1 

# weights:  305
initial  value 111.322211 
iter  10 value 96.444686
iter  20 value 93.470511
iter  30 value 88.361016
iter  40 value 84.197878
iter  50 value 83.017410
iter  60 value 82.864272
iter  70 value 82.530676
iter  80 value 82.257135
iter  90 value 82.132028
iter 100 value 81.640897
final  value 81.640897 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.745394 
iter  10 value 94.349645
iter  20 value 93.692218
iter  30 value 93.653504
iter  40 value 89.536247
iter  50 value 88.576916
iter  60 value 88.151745
iter  70 value 85.971921
iter  80 value 83.544072
iter  90 value 82.201001
iter 100 value 81.458861
final  value 81.458861 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.167889 
iter  10 value 92.957107
iter  20 value 87.334486
iter  30 value 86.341549
iter  40 value 83.831619
iter  50 value 83.238248
iter  60 value 82.781558
iter  70 value 81.933011
iter  80 value 81.876156
iter  90 value 81.753027
iter 100 value 81.289240
final  value 81.289240 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.835951 
iter  10 value 94.432005
iter  20 value 93.732390
iter  30 value 93.701632
iter  40 value 93.383262
iter  50 value 92.177075
iter  60 value 89.798654
iter  70 value 88.018400
iter  80 value 85.673286
iter  90 value 84.229124
iter 100 value 83.644809
final  value 83.644809 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.311665 
iter  10 value 89.716938
iter  20 value 87.656889
iter  30 value 85.753447
iter  40 value 85.503911
iter  50 value 85.402116
iter  60 value 85.362707
iter  70 value 85.060256
iter  80 value 83.139753
iter  90 value 82.520054
iter 100 value 81.266684
final  value 81.266684 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.225293 
iter  10 value 95.121117
iter  20 value 85.754068
iter  30 value 84.226441
iter  40 value 83.450218
iter  50 value 82.136465
iter  60 value 81.560904
iter  70 value 81.293081
iter  80 value 81.164523
iter  90 value 81.113645
iter 100 value 81.027232
final  value 81.027232 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 116.471911 
iter  10 value 94.753277
iter  20 value 87.575656
iter  30 value 85.677154
iter  40 value 82.492542
iter  50 value 81.964541
iter  60 value 81.591646
iter  70 value 81.257712
iter  80 value 81.175500
iter  90 value 81.081905
iter 100 value 80.804353
final  value 80.804353 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.259352 
iter  10 value 93.702941
iter  20 value 92.844539
iter  30 value 89.659526
iter  40 value 85.862528
iter  50 value 83.749866
iter  60 value 82.188448
iter  70 value 81.518409
iter  80 value 80.946710
iter  90 value 80.611995
iter 100 value 80.504500
final  value 80.504500 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.563743 
iter  10 value 94.758985
iter  20 value 94.302516
iter  30 value 91.887940
iter  40 value 88.798610
iter  50 value 85.923279
iter  60 value 85.336215
iter  70 value 84.020262
iter  80 value 83.299305
iter  90 value 82.729020
iter 100 value 82.514499
final  value 82.514499 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.056044 
iter  10 value 92.517067
iter  20 value 91.304016
iter  30 value 90.939953
iter  40 value 87.014689
iter  50 value 83.680685
iter  60 value 83.065890
iter  70 value 82.873685
iter  80 value 82.182415
iter  90 value 82.047259
iter 100 value 81.847779
final  value 81.847779 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.201948 
final  value 94.485567 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.090761 
final  value 94.485773 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.723518 
final  value 94.485989 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.153650 
iter  10 value 94.486029
iter  20 value 94.277141
iter  30 value 88.021675
iter  40 value 87.968189
iter  50 value 87.967882
iter  60 value 86.896206
final  value 86.896196 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.643262 
iter  10 value 93.102103
iter  20 value 88.920740
iter  30 value 88.604045
iter  40 value 86.636564
iter  50 value 86.623889
iter  60 value 86.618887
iter  70 value 86.617683
final  value 86.617675 
converged
Fitting Repeat 1 

# weights:  305
initial  value 122.273847 
iter  10 value 87.946398
iter  20 value 83.428018
iter  30 value 83.424567
final  value 83.424157 
converged
Fitting Repeat 2 

# weights:  305
initial  value 106.856996 
iter  10 value 93.778156
iter  20 value 93.774510
iter  30 value 93.498286
iter  40 value 83.490945
iter  50 value 83.369882
final  value 83.369459 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.838160 
iter  10 value 92.028406
iter  20 value 91.818889
iter  30 value 91.818274
iter  30 value 91.818273
final  value 91.818270 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.652422 
iter  10 value 93.778492
iter  20 value 93.777886
iter  30 value 93.773564
iter  40 value 93.773495
final  value 93.773491 
converged
Fitting Repeat 5 

# weights:  305
initial  value 109.107400 
iter  10 value 94.489152
iter  20 value 93.984406
iter  30 value 93.595155
final  value 93.540875 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.499903 
iter  10 value 94.105448
iter  20 value 94.064121
iter  30 value 92.416963
iter  40 value 92.185821
iter  50 value 92.162750
iter  60 value 92.160461
iter  70 value 92.156356
iter  80 value 87.169124
iter  90 value 86.374886
final  value 86.372393 
converged
Fitting Repeat 2 

# weights:  507
initial  value 111.713549 
iter  10 value 93.863005
iter  20 value 93.854199
iter  30 value 93.565464
iter  40 value 93.540270
iter  50 value 93.414742
iter  60 value 85.551457
iter  70 value 85.155769
iter  80 value 84.913787
iter  90 value 84.885011
iter 100 value 84.690121
final  value 84.690121 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 94.813887 
iter  10 value 91.358843
iter  20 value 91.324777
iter  30 value 90.788979
iter  40 value 90.728888
iter  50 value 90.724240
final  value 90.724108 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.170115 
iter  10 value 94.492185
iter  20 value 94.483571
iter  30 value 88.112878
iter  40 value 88.012540
iter  50 value 87.946252
iter  60 value 85.671004
iter  70 value 83.795674
iter  80 value 82.916862
final  value 82.916858 
converged
Fitting Repeat 5 

# weights:  507
initial  value 112.628475 
iter  10 value 90.120158
iter  20 value 86.981996
iter  30 value 85.987152
iter  40 value 84.628424
iter  50 value 84.596125
iter  60 value 84.595808
iter  70 value 84.587828
iter  80 value 84.583360
iter  90 value 84.582708
final  value 84.582206 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.112208 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 120.406733 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.535022 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.489793 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.905164 
iter  10 value 94.031390
final  value 94.022599 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.942329 
final  value 94.032967 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.118861 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.589109 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.106226 
final  value 94.032967 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.993017 
iter  10 value 92.567210
final  value 92.567155 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.893727 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.322882 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.785469 
iter  10 value 92.703908
iter  10 value 92.703907
iter  10 value 92.703907
final  value 92.703907 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.637982 
iter  10 value 94.052883
iter  20 value 94.052268
iter  30 value 89.322352
iter  40 value 87.216768
iter  50 value 87.142238
iter  60 value 84.834660
iter  70 value 84.628871
final  value 84.628815 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.588141 
final  value 94.044528 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.476622 
iter  10 value 94.057889
iter  20 value 94.056744
iter  30 value 93.546695
iter  40 value 92.693941
iter  50 value 92.485812
iter  60 value 92.275342
iter  70 value 86.640190
iter  80 value 83.547016
iter  90 value 82.840131
iter 100 value 82.472065
final  value 82.472065 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.053491 
iter  10 value 93.932759
iter  20 value 86.148443
iter  30 value 84.830035
iter  40 value 84.276220
iter  50 value 84.113013
iter  60 value 84.071431
iter  70 value 84.063824
iter  80 value 84.048500
final  value 84.048450 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.664180 
iter  10 value 89.014816
iter  20 value 87.667390
iter  30 value 87.367720
iter  40 value 85.237604
iter  50 value 84.936037
iter  60 value 84.850895
iter  70 value 84.821765
final  value 84.821753 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.626549 
iter  10 value 94.061080
iter  20 value 92.693694
iter  30 value 85.949143
iter  40 value 85.056872
iter  50 value 84.479099
iter  60 value 84.354934
iter  70 value 83.561864
iter  80 value 83.259786
iter  90 value 81.646046
final  value 81.641131 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.402482 
iter  10 value 94.058619
iter  20 value 94.015126
iter  30 value 93.624719
iter  40 value 92.703054
iter  50 value 88.238782
iter  60 value 86.930630
iter  70 value 86.520520
iter  80 value 85.029771
iter  90 value 84.821799
final  value 84.821754 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.923352 
iter  10 value 94.214010
iter  20 value 93.461435
iter  30 value 91.775859
iter  40 value 90.186980
iter  50 value 87.876416
iter  60 value 83.317704
iter  70 value 82.151685
iter  80 value 81.981861
iter  90 value 81.884843
iter 100 value 81.744399
final  value 81.744399 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.904783 
iter  10 value 94.078626
iter  20 value 94.047519
iter  30 value 93.286355
iter  40 value 93.068545
iter  50 value 91.369518
iter  60 value 86.041022
iter  70 value 84.216821
iter  80 value 81.877420
iter  90 value 81.584636
iter 100 value 81.313793
final  value 81.313793 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 117.024617 
iter  10 value 94.066948
iter  20 value 88.724512
iter  30 value 85.642471
iter  40 value 85.438024
iter  50 value 85.146169
iter  60 value 84.989361
iter  70 value 84.670655
iter  80 value 83.625917
iter  90 value 82.469482
iter 100 value 81.749058
final  value 81.749058 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.555541 
iter  10 value 94.244429
iter  20 value 94.039575
iter  30 value 93.530633
iter  40 value 92.014233
iter  50 value 88.352698
iter  60 value 85.471863
iter  70 value 85.323282
iter  80 value 83.465327
iter  90 value 83.276883
iter 100 value 83.229706
final  value 83.229706 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.054854 
iter  10 value 94.063532
iter  20 value 90.300990
iter  30 value 88.543217
iter  40 value 85.073660
iter  50 value 84.361181
iter  60 value 82.376002
iter  70 value 81.608896
iter  80 value 81.511241
iter  90 value 81.174368
iter 100 value 80.687611
final  value 80.687611 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 113.365610 
iter  10 value 94.287479
iter  20 value 93.422544
iter  30 value 86.560997
iter  40 value 85.863351
iter  50 value 83.580944
iter  60 value 81.664197
iter  70 value 80.588112
iter  80 value 80.274633
iter  90 value 80.163896
iter 100 value 79.770939
final  value 79.770939 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.064123 
iter  10 value 95.482046
iter  20 value 88.186132
iter  30 value 87.243306
iter  40 value 83.317603
iter  50 value 81.635977
iter  60 value 81.216969
iter  70 value 80.288899
iter  80 value 79.999414
iter  90 value 79.840048
iter 100 value 79.734787
final  value 79.734787 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.018193 
iter  10 value 88.297880
iter  20 value 84.048740
iter  30 value 81.861890
iter  40 value 81.141644
iter  50 value 80.888058
iter  60 value 80.716854
iter  70 value 80.394820
iter  80 value 80.226750
iter  90 value 79.933567
iter 100 value 79.714535
final  value 79.714535 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 117.581068 
iter  10 value 94.063901
iter  20 value 93.534689
iter  30 value 93.104366
iter  40 value 93.055683
iter  50 value 92.991409
iter  60 value 85.567979
iter  70 value 82.914684
iter  80 value 81.124659
iter  90 value 80.222762
iter 100 value 79.964033
final  value 79.964033 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 124.369094 
iter  10 value 94.202176
iter  20 value 85.817306
iter  30 value 85.498661
iter  40 value 84.761379
iter  50 value 82.157482
iter  60 value 80.587450
iter  70 value 80.472860
iter  80 value 80.339011
iter  90 value 80.114247
iter 100 value 80.043712
final  value 80.043712 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.889989 
final  value 94.034575 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.389765 
iter  10 value 94.054799
final  value 94.052927 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.549518 
iter  10 value 94.054738
iter  20 value 94.052968
iter  30 value 89.228176
iter  40 value 86.333879
iter  50 value 86.162768
iter  60 value 86.144890
iter  60 value 86.144890
iter  60 value 86.144890
final  value 86.144890 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.520764 
final  value 94.054484 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.286311 
final  value 94.054523 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.930814 
iter  10 value 92.343548
iter  20 value 92.305212
iter  30 value 92.267036
iter  40 value 92.265742
iter  50 value 89.470749
iter  60 value 85.207624
iter  70 value 83.961825
iter  80 value 83.347480
iter  90 value 83.099333
iter 100 value 82.848973
final  value 82.848973 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.863800 
iter  10 value 94.057739
iter  20 value 91.169257
iter  30 value 84.977511
iter  40 value 84.699898
iter  50 value 84.699293
iter  50 value 84.699293
final  value 84.699293 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.744945 
iter  10 value 94.057319
iter  20 value 93.722433
iter  30 value 93.175797
iter  40 value 92.264148
iter  50 value 92.261632
iter  60 value 92.187098
iter  70 value 90.997615
iter  80 value 85.274843
iter  90 value 85.181739
iter 100 value 85.179005
final  value 85.179005 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 111.172680 
iter  10 value 94.055016
iter  20 value 94.033525
iter  30 value 94.005666
final  value 94.005606 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.126908 
iter  10 value 94.058281
iter  20 value 94.052835
iter  30 value 93.934939
iter  40 value 92.090873
iter  50 value 86.411938
iter  60 value 85.905308
iter  70 value 85.632565
iter  80 value 83.536904
iter  90 value 83.269605
iter 100 value 83.245430
final  value 83.245430 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 101.468553 
iter  10 value 87.249867
iter  20 value 86.069484
iter  30 value 86.056460
iter  40 value 86.052473
iter  50 value 86.023533
iter  60 value 83.924299
iter  70 value 82.921552
iter  80 value 82.384917
iter  90 value 82.363491
iter 100 value 82.361205
final  value 82.361205 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 99.769914 
iter  10 value 94.060792
iter  20 value 93.734718
iter  30 value 85.428742
iter  40 value 81.875126
iter  50 value 81.161144
iter  60 value 78.509113
iter  70 value 78.156342
iter  80 value 77.804683
iter  90 value 77.793447
final  value 77.792971 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.914526 
iter  10 value 92.736363
iter  20 value 92.263814
iter  30 value 92.260340
iter  40 value 92.258035
iter  50 value 92.102282
iter  60 value 89.525326
iter  70 value 85.345893
iter  80 value 83.668111
iter  90 value 82.579611
iter 100 value 81.510629
final  value 81.510629 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 100.795879 
iter  10 value 94.059352
iter  20 value 93.590098
iter  30 value 88.464478
iter  40 value 85.735941
iter  50 value 83.296494
iter  60 value 82.440603
iter  70 value 81.300339
iter  80 value 80.632715
iter  90 value 79.458122
iter 100 value 79.430018
final  value 79.430018 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 99.369975 
iter  10 value 94.060847
iter  20 value 93.995622
iter  30 value 92.573145
iter  40 value 92.241602
iter  50 value 91.434801
iter  60 value 88.336063
iter  70 value 88.286044
iter  80 value 88.285030
iter  90 value 88.283712
iter 100 value 87.762135
final  value 87.762135 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 134.005453 
iter  10 value 117.952846
iter  20 value 106.301274
iter  30 value 105.926334
iter  40 value 105.468659
iter  50 value 105.153793
iter  60 value 103.771911
iter  70 value 102.786537
iter  80 value 102.598588
iter  90 value 102.174113
iter 100 value 101.642740
final  value 101.642740 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 152.757589 
iter  10 value 118.080741
iter  20 value 114.782778
iter  30 value 108.024307
iter  40 value 106.817343
iter  50 value 104.601279
iter  60 value 103.385178
iter  70 value 101.644562
iter  80 value 100.377638
iter  90 value 100.202751
iter 100 value 100.147014
final  value 100.147014 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 131.349426 
iter  10 value 119.008823
iter  20 value 110.409491
iter  30 value 109.005613
iter  40 value 108.365760
iter  50 value 107.594110
iter  60 value 107.151816
iter  70 value 103.867639
iter  80 value 103.110389
iter  90 value 102.059736
iter 100 value 101.563575
final  value 101.563575 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 147.471658 
iter  10 value 116.563063
iter  20 value 107.977013
iter  30 value 106.198854
iter  40 value 105.318544
iter  50 value 103.730287
iter  60 value 102.797376
iter  70 value 102.381523
iter  80 value 102.239411
iter  90 value 102.004626
iter 100 value 101.616517
final  value 101.616517 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 126.080465 
iter  10 value 114.483939
iter  20 value 111.017562
iter  30 value 106.924117
iter  40 value 104.900083
iter  50 value 102.966202
iter  60 value 102.458132
iter  70 value 101.873329
iter  80 value 101.296496
iter  90 value 101.031827
iter 100 value 100.994958
final  value 100.994958 
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 Mar 11 19:10:29 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 
 20.128   0.502  77.562