##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings HPiP_1.15.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.22-bioc/meat/HPiP.Rcheck’
* using R version 4.5.1 (2025-06-13)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
    GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
* running under: Ubuntu 24.04.3 LTS
* using session charset: UTF-8
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.15.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... INFO
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
FSmethod      33.860  0.620  34.483
corr_plot     33.939  0.345  34.358
var_imp       32.792  0.575  33.408
pred_ensembel 13.305  0.153  12.093
enrichfindP    0.498  0.032   9.183
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE

Status: 2 NOTEs
See
  ‘/home/biocbuild/bbs-3.22-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.22-bioc/R/site-library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.15.0’
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R version 4.5.1 (2025-06-13) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

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

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

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

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

# weights:  103
initial  value 107.827996 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.035320 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.005030 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.117171 
final  value 94.466822 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.786250 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.566766 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.158994 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.155059 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.382887 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.948013 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 127.069125 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.016971 
iter  10 value 94.355279
iter  10 value 94.355279
iter  10 value 94.355279
final  value 94.355279 
converged
Fitting Repeat 3 

# weights:  507
initial  value 119.662994 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  507
initial  value 128.428562 
final  value 94.484137 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.834654 
iter  10 value 94.483784
iter  10 value 94.483784
iter  10 value 94.483784
final  value 94.483784 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.315279 
iter  10 value 94.488936
iter  20 value 93.118717
iter  30 value 85.573026
iter  40 value 85.029011
iter  50 value 84.613507
iter  60 value 84.245210
iter  70 value 82.924286
iter  80 value 82.761213
iter  90 value 82.753710
final  value 82.751756 
converged
Fitting Repeat 2 

# weights:  103
initial  value 117.725667 
iter  10 value 94.493849
iter  20 value 94.365180
iter  30 value 86.521135
iter  40 value 84.987366
iter  50 value 84.507019
iter  60 value 84.379661
iter  70 value 83.568590
iter  80 value 83.212940
final  value 83.209157 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.468847 
iter  10 value 94.498113
iter  20 value 88.191221
iter  30 value 84.849566
iter  40 value 84.559061
iter  50 value 83.533326
iter  60 value 82.285807
iter  70 value 82.203106
iter  80 value 81.823025
iter  90 value 81.626757
iter 100 value 81.358707
final  value 81.358707 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.133739 
iter  10 value 94.518538
iter  20 value 91.777789
iter  30 value 83.844076
iter  40 value 82.836431
iter  50 value 82.354429
iter  60 value 82.306106
final  value 82.306087 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.313871 
iter  10 value 94.488364
iter  20 value 94.302146
iter  30 value 94.136236
iter  40 value 92.866998
iter  50 value 92.259330
iter  60 value 84.163059
iter  70 value 83.798980
iter  80 value 83.531316
iter  90 value 83.492142
final  value 83.491948 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.395645 
iter  10 value 94.453565
iter  20 value 89.860961
iter  30 value 84.985805
iter  40 value 82.274075
iter  50 value 81.694870
iter  60 value 81.409424
iter  70 value 81.175551
iter  80 value 80.947414
iter  90 value 80.369724
iter 100 value 80.163649
final  value 80.163649 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.457127 
iter  10 value 94.644231
iter  20 value 92.985951
iter  30 value 92.175982
iter  40 value 91.959510
iter  50 value 91.444681
iter  60 value 91.349997
iter  70 value 90.647350
iter  80 value 88.586081
iter  90 value 85.184075
iter 100 value 84.959235
final  value 84.959235 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 114.799385 
iter  10 value 94.509370
iter  20 value 88.092500
iter  30 value 84.748443
iter  40 value 82.188602
iter  50 value 81.660281
iter  60 value 80.864509
iter  70 value 80.106708
iter  80 value 80.043047
iter  90 value 79.982389
iter 100 value 79.973752
final  value 79.973752 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 139.381331 
iter  10 value 95.123507
iter  20 value 89.225112
iter  30 value 84.856202
iter  40 value 82.942972
iter  50 value 82.096244
iter  60 value 81.884326
iter  70 value 81.567566
iter  80 value 81.422487
iter  90 value 81.250065
iter 100 value 80.773153
final  value 80.773153 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 115.568482 
iter  10 value 95.573701
iter  20 value 94.487930
iter  30 value 94.154373
iter  40 value 94.073537
iter  50 value 86.261549
iter  60 value 84.888694
iter  70 value 83.458081
iter  80 value 81.638374
iter  90 value 81.275283
iter 100 value 80.664714
final  value 80.664714 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.582012 
iter  10 value 95.171047
iter  20 value 94.559039
iter  30 value 93.486518
iter  40 value 89.429922
iter  50 value 87.304770
iter  60 value 82.970481
iter  70 value 81.075079
iter  80 value 80.603945
iter  90 value 79.972455
iter 100 value 79.778190
final  value 79.778190 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 118.730237 
iter  10 value 94.558277
iter  20 value 90.792484
iter  30 value 85.566793
iter  40 value 84.031565
iter  50 value 83.138368
iter  60 value 82.633894
iter  70 value 82.573790
iter  80 value 82.523691
iter  90 value 82.270085
iter 100 value 81.377348
final  value 81.377348 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.949664 
iter  10 value 94.544890
iter  20 value 92.295586
iter  30 value 85.495713
iter  40 value 84.418246
iter  50 value 83.860825
iter  60 value 83.521139
iter  70 value 83.344981
iter  80 value 83.136132
iter  90 value 80.844448
iter 100 value 80.172506
final  value 80.172506 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 136.695552 
iter  10 value 94.001994
iter  20 value 90.857759
iter  30 value 88.941259
iter  40 value 83.944210
iter  50 value 83.007971
iter  60 value 81.120427
iter  70 value 80.151348
iter  80 value 79.975442
iter  90 value 79.851009
iter 100 value 79.671276
final  value 79.671276 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.888085 
iter  10 value 94.847631
iter  20 value 86.476114
iter  30 value 83.846101
iter  40 value 83.629001
iter  50 value 81.981493
iter  60 value 80.700874
iter  70 value 79.984390
iter  80 value 79.649196
iter  90 value 79.573558
iter 100 value 79.526163
final  value 79.526163 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.370958 
final  value 94.485764 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.722729 
final  value 94.485759 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.793654 
iter  10 value 92.793794
iter  20 value 92.487689
iter  30 value 92.480296
iter  40 value 92.353064
iter  50 value 92.310822
final  value 92.310739 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.802649 
final  value 94.485769 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.576382 
final  value 94.486159 
converged
Fitting Repeat 1 

# weights:  305
initial  value 125.641425 
iter  10 value 94.488969
iter  20 value 94.412912
iter  30 value 94.149470
iter  40 value 92.496712
iter  50 value 92.265396
final  value 92.154273 
converged
Fitting Repeat 2 

# weights:  305
initial  value 113.790129 
iter  10 value 94.471607
iter  20 value 94.055357
iter  30 value 94.053618
iter  40 value 93.006839
iter  50 value 83.696621
iter  60 value 82.476678
iter  70 value 81.325431
iter  80 value 81.199222
final  value 81.199108 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.708690 
iter  10 value 94.259165
iter  20 value 94.211652
iter  30 value 87.202429
iter  40 value 85.464635
iter  50 value 81.963382
iter  60 value 80.096304
iter  70 value 78.703079
iter  80 value 78.494768
iter  90 value 78.429835
iter 100 value 78.424834
final  value 78.424834 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 97.277663 
iter  10 value 90.950118
iter  20 value 90.017363
iter  30 value 89.365857
iter  40 value 89.314201
iter  50 value 89.299421
iter  60 value 88.925138
iter  70 value 88.908593
final  value 88.908018 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.890567 
iter  10 value 94.471401
iter  20 value 94.467457
iter  30 value 94.466874
final  value 94.466700 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.703115 
iter  10 value 94.492575
iter  20 value 94.484938
iter  30 value 90.038892
iter  40 value 84.179973
iter  50 value 81.842349
iter  60 value 81.817215
iter  70 value 81.720428
iter  80 value 81.193542
iter  90 value 80.590348
iter 100 value 80.578965
final  value 80.578965 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 99.241601 
iter  10 value 92.986798
iter  20 value 85.169648
iter  30 value 83.084606
iter  40 value 83.077180
iter  50 value 83.072712
iter  60 value 82.867705
iter  70 value 82.867002
iter  80 value 82.724072
iter  90 value 82.469215
iter 100 value 82.024243
final  value 82.024243 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.918109 
iter  10 value 94.322430
iter  20 value 93.654643
iter  30 value 92.052765
final  value 91.995683 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.972793 
iter  10 value 94.492761
iter  20 value 94.469786
final  value 94.466874 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.867900 
iter  10 value 94.309547
iter  20 value 94.307568
iter  30 value 92.824942
iter  40 value 85.722456
iter  50 value 85.677079
iter  60 value 85.110399
iter  70 value 85.012908
iter  80 value 85.008338
iter  90 value 85.006475
final  value 85.006401 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.754372 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.094968 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.212933 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.101492 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.241566 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.988964 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.362089 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 113.986648 
final  value 94.032967 
converged
Fitting Repeat 4 

# weights:  305
initial  value 121.761664 
final  value 94.032967 
converged
Fitting Repeat 5 

# weights:  305
initial  value 116.228599 
iter  10 value 92.049936
iter  20 value 92.033161
final  value 92.031334 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.789841 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.339611 
iter  10 value 92.322715
iter  20 value 91.884506
iter  30 value 91.845591
iter  40 value 91.845369
final  value 91.845366 
converged
Fitting Repeat 3 

# weights:  507
initial  value 119.116468 
iter  10 value 93.725779
iter  20 value 93.484264
iter  30 value 93.479305
iter  40 value 93.472497
final  value 93.472464 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.071396 
iter  10 value 94.033147
final  value 94.032968 
converged
Fitting Repeat 5 

# weights:  507
initial  value 124.643885 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.357492 
iter  10 value 93.998665
iter  20 value 90.443972
iter  30 value 89.443017
iter  40 value 88.770620
iter  50 value 88.284837
iter  60 value 86.667345
iter  70 value 85.300577
iter  80 value 85.210607
iter  90 value 85.078326
iter 100 value 85.065719
final  value 85.065719 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.687883 
iter  10 value 94.053519
iter  20 value 88.631803
iter  30 value 86.030831
iter  40 value 85.847918
iter  50 value 85.335652
iter  60 value 84.619357
iter  70 value 84.407246
iter  80 value 84.227657
final  value 84.149285 
converged
Fitting Repeat 3 

# weights:  103
initial  value 108.680285 
iter  10 value 94.621733
iter  20 value 94.057084
iter  30 value 92.902796
iter  40 value 86.688879
iter  50 value 85.977869
iter  60 value 85.291912
iter  70 value 84.923475
iter  80 value 84.720171
iter  90 value 84.658509
iter 100 value 84.252018
final  value 84.252018 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 102.719439 
iter  10 value 92.956908
iter  20 value 87.530803
iter  30 value 86.626728
iter  40 value 86.294580
iter  50 value 85.796821
iter  60 value 85.579314
iter  70 value 84.892503
iter  80 value 84.379326
iter  90 value 84.151432
final  value 84.149285 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.774613 
iter  10 value 93.614387
iter  20 value 87.311627
iter  30 value 86.727573
iter  40 value 86.343660
iter  50 value 85.579550
iter  60 value 85.388781
iter  70 value 85.171189
final  value 85.170554 
converged
Fitting Repeat 1 

# weights:  305
initial  value 137.664716 
iter  10 value 94.064569
iter  20 value 90.873319
iter  30 value 87.050596
iter  40 value 85.544004
iter  50 value 84.458427
iter  60 value 83.488271
iter  70 value 83.396981
iter  80 value 82.765768
iter  90 value 82.012272
iter 100 value 81.577785
final  value 81.577785 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.774091 
iter  10 value 94.258722
iter  20 value 93.996044
iter  30 value 90.314009
iter  40 value 88.635604
iter  50 value 87.777307
iter  60 value 84.995749
iter  70 value 84.710785
iter  80 value 84.660407
iter  90 value 83.650432
iter 100 value 83.519695
final  value 83.519695 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.755122 
iter  10 value 94.130004
iter  20 value 90.006263
iter  30 value 86.602757
iter  40 value 86.331680
iter  50 value 85.863082
iter  60 value 84.944978
iter  70 value 84.084976
iter  80 value 81.826032
iter  90 value 81.771666
iter 100 value 81.533627
final  value 81.533627 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 112.428843 
iter  10 value 94.203080
iter  20 value 86.033964
iter  30 value 83.616235
iter  40 value 83.453335
iter  50 value 82.894958
iter  60 value 82.538001
iter  70 value 82.130779
iter  80 value 82.102011
iter  90 value 82.052084
iter 100 value 81.992404
final  value 81.992404 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.977518 
iter  10 value 94.394032
iter  20 value 93.992796
iter  30 value 88.011662
iter  40 value 84.679679
iter  50 value 82.961927
iter  60 value 82.483636
iter  70 value 82.087018
iter  80 value 82.031948
iter  90 value 81.984711
iter 100 value 81.953737
final  value 81.953737 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.413626 
iter  10 value 94.256503
iter  20 value 93.368110
iter  30 value 92.054604
iter  40 value 86.816970
iter  50 value 83.030304
iter  60 value 82.299211
iter  70 value 81.857315
iter  80 value 81.724411
iter  90 value 81.664641
iter 100 value 81.638417
final  value 81.638417 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.438616 
iter  10 value 94.037940
iter  20 value 90.282073
iter  30 value 89.105068
iter  40 value 85.267281
iter  50 value 84.377631
iter  60 value 83.031069
iter  70 value 82.040648
iter  80 value 81.853458
iter  90 value 81.799110
iter 100 value 81.754337
final  value 81.754337 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.465015 
iter  10 value 98.259919
iter  20 value 91.892896
iter  30 value 88.453029
iter  40 value 84.742258
iter  50 value 83.854087
iter  60 value 82.657051
iter  70 value 82.322120
iter  80 value 82.188045
iter  90 value 82.089842
iter 100 value 81.985978
final  value 81.985978 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.768715 
iter  10 value 94.439286
iter  20 value 93.796096
iter  30 value 90.214810
iter  40 value 85.623452
iter  50 value 83.544346
iter  60 value 82.586069
iter  70 value 81.978287
iter  80 value 81.867483
iter  90 value 81.749656
iter 100 value 81.570512
final  value 81.570512 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 119.790382 
iter  10 value 94.114915
iter  20 value 93.884142
iter  30 value 92.028115
iter  40 value 86.402444
iter  50 value 85.972971
iter  60 value 85.203556
iter  70 value 83.976775
iter  80 value 83.717781
iter  90 value 83.386363
iter 100 value 82.261185
final  value 82.261185 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 108.170138 
final  value 94.054619 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.698123 
final  value 94.054792 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.487794 
iter  10 value 94.054434
iter  20 value 94.050446
iter  30 value 93.032624
iter  40 value 91.882488
iter  50 value 91.877990
iter  60 value 91.569967
iter  70 value 91.559034
final  value 91.558920 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.306335 
iter  10 value 94.054793
iter  20 value 93.988660
iter  30 value 90.838951
iter  40 value 90.727130
iter  50 value 90.364209
iter  60 value 90.258651
final  value 90.258567 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.759574 
iter  10 value 85.964983
iter  20 value 85.578361
final  value 85.574542 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.758255 
iter  10 value 94.057526
iter  20 value 92.273992
iter  30 value 91.599712
final  value 91.598422 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.214209 
iter  10 value 94.057057
iter  20 value 93.971148
iter  30 value 91.752320
iter  40 value 91.227089
iter  50 value 91.161622
iter  60 value 91.123210
iter  70 value 91.085405
iter  80 value 91.084819
iter  90 value 90.802673
iter 100 value 90.369436
final  value 90.369436 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.186511 
iter  10 value 94.054885
iter  20 value 94.033862
iter  30 value 94.016705
iter  40 value 85.254996
iter  50 value 84.813061
iter  60 value 83.429035
iter  70 value 82.556634
iter  80 value 82.392054
final  value 82.392049 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.350657 
iter  10 value 94.058047
iter  20 value 94.052905
iter  30 value 93.870904
iter  40 value 89.059026
iter  50 value 88.878245
iter  60 value 88.824199
iter  70 value 88.823769
final  value 88.823742 
converged
Fitting Repeat 5 

# weights:  305
initial  value 113.554579 
iter  10 value 93.905368
iter  20 value 92.148061
iter  30 value 85.538695
iter  40 value 83.269924
iter  50 value 82.210874
iter  60 value 81.361388
iter  70 value 81.332669
iter  80 value 81.328770
iter  90 value 80.416869
iter 100 value 80.338093
final  value 80.338093 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 95.586531 
iter  10 value 87.860607
iter  20 value 87.386566
iter  30 value 87.386134
iter  40 value 86.623592
iter  50 value 86.173763
iter  60 value 86.159133
final  value 86.158591 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.050638 
iter  10 value 94.061241
iter  20 value 94.001767
iter  30 value 91.380190
iter  40 value 90.266660
iter  50 value 90.205232
final  value 90.204706 
converged
Fitting Repeat 3 

# weights:  507
initial  value 116.489348 
iter  10 value 94.061340
iter  20 value 94.047249
iter  30 value 90.303759
iter  40 value 86.265333
iter  50 value 85.691885
iter  60 value 85.507383
iter  70 value 85.104765
iter  80 value 81.642079
iter  90 value 81.172822
iter 100 value 81.160320
final  value 81.160320 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 96.161680 
iter  10 value 94.060539
iter  20 value 93.961846
iter  30 value 91.980694
iter  40 value 91.858411
iter  50 value 91.846932
final  value 91.846803 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.751564 
iter  10 value 94.041121
iter  20 value 94.033911
iter  30 value 93.014594
iter  40 value 87.420384
iter  50 value 87.053095
iter  60 value 87.046050
final  value 87.046003 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.717155 
final  value 94.026542 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.565255 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 108.546339 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.818032 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.994105 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.751133 
final  value 94.448052 
converged
Fitting Repeat 2 

# weights:  305
initial  value 111.208014 
iter  10 value 93.974684
final  value 93.974641 
converged
Fitting Repeat 3 

# weights:  305
initial  value 108.268289 
iter  10 value 94.026542
iter  10 value 94.026542
iter  10 value 94.026542
final  value 94.026542 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.451577 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.574514 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.452197 
final  value 94.026542 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.625111 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 115.456762 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.416694 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.912936 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 106.643007 
iter  10 value 93.947362
iter  20 value 85.905821
iter  30 value 84.045563
iter  40 value 81.143057
iter  50 value 79.598032
iter  60 value 79.595052
final  value 79.594848 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.391178 
iter  10 value 94.487635
iter  20 value 86.155764
iter  30 value 80.255549
iter  40 value 79.801004
iter  50 value 79.614327
iter  60 value 79.594848
iter  60 value 79.594848
iter  60 value 79.594848
final  value 79.594848 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.670616 
iter  10 value 94.736963
iter  20 value 93.866868
iter  30 value 93.621646
iter  40 value 92.576319
iter  50 value 87.448452
iter  60 value 86.731228
iter  70 value 86.167539
iter  80 value 81.645294
iter  90 value 79.729957
iter 100 value 76.826516
final  value 76.826516 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 100.187277 
iter  10 value 94.492784
iter  20 value 94.463108
iter  30 value 94.240723
iter  40 value 93.308781
iter  50 value 80.488051
iter  60 value 79.482298
iter  70 value 79.242374
iter  80 value 79.078549
final  value 79.073808 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.262992 
iter  10 value 95.023315
iter  20 value 94.490015
iter  30 value 93.514332
iter  40 value 90.580433
iter  50 value 83.560720
iter  60 value 80.412763
iter  70 value 80.284255
iter  80 value 79.855221
iter  90 value 79.600917
iter 100 value 79.595761
final  value 79.595761 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 99.902802 
iter  10 value 93.567092
iter  20 value 85.379946
iter  30 value 79.976045
iter  40 value 79.620521
iter  50 value 78.563550
iter  60 value 78.225744
iter  70 value 77.728980
iter  80 value 76.863092
iter  90 value 76.165352
iter 100 value 75.830119
final  value 75.830119 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.425247 
iter  10 value 94.324606
iter  20 value 93.756917
iter  30 value 93.050624
iter  40 value 88.159201
iter  50 value 85.974136
iter  60 value 79.662420
iter  70 value 79.018116
iter  80 value 78.010727
iter  90 value 76.733402
iter 100 value 76.684643
final  value 76.684643 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.651529 
iter  10 value 94.078276
iter  20 value 93.435013
iter  30 value 90.457700
iter  40 value 87.656228
iter  50 value 86.679287
iter  60 value 84.845481
iter  70 value 83.859752
iter  80 value 81.114493
iter  90 value 79.271004
iter 100 value 77.881507
final  value 77.881507 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.208194 
iter  10 value 86.646629
iter  20 value 83.931338
iter  30 value 83.645095
iter  40 value 80.079717
iter  50 value 79.683006
iter  60 value 79.320348
iter  70 value 78.113599
iter  80 value 76.159714
iter  90 value 75.805953
iter 100 value 75.780097
final  value 75.780097 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 110.030868 
iter  10 value 94.547497
iter  20 value 94.352126
iter  30 value 89.475076
iter  40 value 80.981330
iter  50 value 80.091551
iter  60 value 79.757341
iter  70 value 78.101214
iter  80 value 77.364936
iter  90 value 76.995350
iter 100 value 76.718805
final  value 76.718805 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 140.543857 
iter  10 value 94.491652
iter  20 value 90.473519
iter  30 value 82.181178
iter  40 value 80.162308
iter  50 value 78.070236
iter  60 value 76.912410
iter  70 value 76.033290
iter  80 value 75.698866
iter  90 value 75.361225
iter 100 value 75.187256
final  value 75.187256 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.051141 
iter  10 value 94.350400
iter  20 value 93.329320
iter  30 value 86.377024
iter  40 value 85.384693
iter  50 value 78.845806
iter  60 value 77.098126
iter  70 value 76.918895
iter  80 value 76.236965
iter  90 value 75.955109
iter 100 value 75.935267
final  value 75.935267 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.137633 
iter  10 value 94.265383
iter  20 value 84.261017
iter  30 value 83.022760
iter  40 value 82.436335
iter  50 value 80.770789
iter  60 value 80.350959
iter  70 value 78.557489
iter  80 value 77.381520
iter  90 value 76.858608
iter 100 value 76.142656
final  value 76.142656 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.655916 
iter  10 value 94.480217
iter  20 value 93.372134
iter  30 value 91.606811
iter  40 value 87.960853
iter  50 value 87.236093
iter  60 value 84.931369
iter  70 value 81.992219
iter  80 value 77.592546
iter  90 value 76.842417
iter 100 value 75.959824
final  value 75.959824 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.216815 
iter  10 value 93.341829
iter  20 value 85.230474
iter  30 value 82.116666
iter  40 value 80.420080
iter  50 value 77.343587
iter  60 value 76.572585
iter  70 value 76.060157
iter  80 value 75.605295
iter  90 value 75.550323
iter 100 value 75.504015
final  value 75.504015 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.751729 
final  value 94.485594 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.945104 
iter  10 value 94.028417
iter  20 value 94.026739
iter  30 value 90.124240
iter  40 value 89.083219
iter  50 value 89.081370
iter  60 value 88.806436
final  value 88.613859 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.259549 
iter  10 value 94.485991
iter  20 value 94.453790
iter  30 value 87.632612
iter  40 value 81.294333
iter  50 value 78.614244
iter  60 value 78.611942
iter  70 value 78.604294
iter  80 value 78.600633
iter  90 value 78.595328
final  value 78.595274 
converged
Fitting Repeat 4 

# weights:  103
initial  value 112.888556 
final  value 94.485663 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.095314 
final  value 94.485912 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.876658 
iter  10 value 91.878384
iter  20 value 83.045414
iter  30 value 83.041989
iter  40 value 83.039048
iter  50 value 78.213480
iter  60 value 78.088313
iter  70 value 78.078763
iter  80 value 78.074886
iter  90 value 78.071908
iter 100 value 78.071576
final  value 78.071576 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 115.228845 
iter  10 value 94.489191
iter  20 value 94.468269
iter  30 value 93.709342
iter  40 value 93.141993
iter  50 value 93.138478
iter  50 value 93.138478
final  value 93.138471 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.677779 
iter  10 value 94.031846
iter  20 value 94.028110
final  value 94.027805 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.658781 
iter  10 value 92.340621
iter  20 value 92.302685
iter  30 value 92.302408
iter  40 value 92.298280
iter  50 value 92.257813
iter  60 value 88.851774
iter  70 value 86.158654
iter  80 value 79.107260
iter  90 value 75.704330
iter 100 value 75.304318
final  value 75.304318 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.025047 
iter  10 value 94.489062
iter  20 value 94.484374
iter  30 value 93.561658
iter  40 value 91.175639
iter  50 value 78.599206
iter  60 value 78.586563
iter  70 value 78.575802
iter  80 value 78.028068
iter  90 value 78.022075
iter 100 value 78.020874
final  value 78.020874 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.695485 
iter  10 value 94.492624
iter  20 value 94.484597
iter  30 value 94.484236
iter  40 value 85.595853
iter  50 value 77.413339
iter  60 value 76.203162
iter  70 value 76.191640
iter  80 value 76.167510
iter  90 value 75.630056
iter 100 value 74.201221
final  value 74.201221 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 97.397659 
iter  10 value 84.285846
iter  20 value 83.935840
iter  30 value 83.931882
iter  40 value 83.927050
iter  50 value 83.926507
iter  60 value 80.733046
iter  70 value 80.701477
iter  80 value 80.323572
final  value 80.309112 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.209042 
iter  10 value 94.492512
iter  20 value 94.484551
iter  30 value 94.167876
iter  40 value 93.321784
iter  50 value 93.320958
final  value 93.320935 
converged
Fitting Repeat 4 

# weights:  507
initial  value 109.360574 
iter  10 value 94.492745
iter  20 value 94.191616
iter  30 value 81.580130
iter  40 value 81.017608
iter  50 value 81.015449
iter  60 value 80.762671
iter  70 value 80.694560
iter  80 value 80.693224
iter  90 value 80.692568
iter  90 value 80.692568
final  value 80.692568 
converged
Fitting Repeat 5 

# weights:  507
initial  value 114.895074 
iter  10 value 94.173588
iter  20 value 93.613032
iter  30 value 83.744195
iter  40 value 76.607968
iter  50 value 76.214300
iter  60 value 76.212198
iter  70 value 76.203724
iter  80 value 75.152298
iter  90 value 75.106487
final  value 75.105638 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.846267 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.305113 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.075182 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.055422 
iter  10 value 94.008696
iter  10 value 94.008696
iter  10 value 94.008696
final  value 94.008696 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.765985 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.189136 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.227981 
final  value 94.008696 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.739226 
iter  10 value 94.052910
iter  10 value 94.052910
iter  10 value 94.052910
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 108.007773 
iter  10 value 94.052978
final  value 94.052911 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.485885 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.081739 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.608037 
final  value 94.008696 
converged
Fitting Repeat 3 

# weights:  507
initial  value 108.936547 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.589768 
final  value 93.897214 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.090452 
final  value 94.008696 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.207876 
iter  10 value 94.065041
iter  20 value 94.031977
iter  30 value 93.488452
iter  40 value 92.289513
iter  50 value 89.097932
iter  60 value 86.814489
iter  70 value 85.658979
iter  80 value 84.759401
iter  90 value 84.412174
iter 100 value 84.221477
final  value 84.221477 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 103.099942 
iter  10 value 94.054172
iter  20 value 93.854515
iter  30 value 93.846027
iter  40 value 93.843985
iter  50 value 93.757400
iter  60 value 90.033106
iter  70 value 87.427069
iter  80 value 86.878431
iter  90 value 86.396152
iter 100 value 86.172522
final  value 86.172522 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 101.606217 
iter  10 value 94.043662
iter  20 value 87.638160
iter  30 value 87.351817
iter  40 value 86.459232
iter  50 value 85.636111
iter  60 value 85.506239
iter  70 value 85.463505
final  value 85.449343 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.954441 
iter  10 value 94.055368
iter  20 value 93.921871
iter  30 value 89.346273
iter  40 value 88.419763
iter  50 value 87.385796
iter  60 value 86.830492
iter  70 value 86.448687
iter  80 value 85.939617
iter  90 value 85.879313
iter 100 value 84.266819
final  value 84.266819 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.034095 
iter  10 value 94.033794
iter  20 value 86.514057
iter  30 value 85.401606
iter  40 value 85.106917
iter  50 value 84.522494
iter  60 value 84.335519
iter  70 value 84.304005
iter  80 value 84.284934
final  value 84.284872 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.578053 
iter  10 value 94.376995
iter  20 value 90.258914
iter  30 value 86.391894
iter  40 value 84.345598
iter  50 value 83.137299
iter  60 value 82.366305
iter  70 value 82.265831
iter  80 value 82.151520
iter  90 value 81.967755
iter 100 value 81.663130
final  value 81.663130 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.495802 
iter  10 value 94.124619
iter  20 value 94.058608
iter  30 value 93.906138
iter  40 value 93.041236
iter  50 value 87.315232
iter  60 value 84.479590
iter  70 value 83.582187
iter  80 value 82.891070
iter  90 value 82.109164
iter 100 value 81.624951
final  value 81.624951 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 119.528637 
iter  10 value 93.756908
iter  20 value 88.237175
iter  30 value 86.474091
iter  40 value 86.056522
iter  50 value 85.865278
iter  60 value 85.700962
iter  70 value 85.551941
iter  80 value 85.419178
iter  90 value 84.241938
iter 100 value 83.748988
final  value 83.748988 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.122049 
iter  10 value 94.414179
iter  20 value 94.039852
iter  30 value 88.799785
iter  40 value 87.741881
iter  50 value 87.293135
iter  60 value 85.498131
iter  70 value 83.949557
iter  80 value 83.198528
iter  90 value 82.090048
iter 100 value 81.980396
final  value 81.980396 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.621376 
iter  10 value 93.904349
iter  20 value 88.823396
iter  30 value 87.059970
iter  40 value 86.671677
iter  50 value 86.159316
iter  60 value 85.770909
iter  70 value 85.562915
iter  80 value 85.431020
iter  90 value 84.288540
iter 100 value 82.838765
final  value 82.838765 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.100282 
iter  10 value 93.853534
iter  20 value 90.243815
iter  30 value 87.289936
iter  40 value 86.995277
iter  50 value 85.929773
iter  60 value 85.559113
iter  70 value 85.540441
iter  80 value 85.351705
iter  90 value 84.854888
iter 100 value 82.250187
final  value 82.250187 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.001253 
iter  10 value 98.196783
iter  20 value 97.122666
iter  30 value 88.469116
iter  40 value 87.186450
iter  50 value 84.620870
iter  60 value 83.911480
iter  70 value 83.404077
iter  80 value 83.213596
iter  90 value 82.527336
iter 100 value 82.167542
final  value 82.167542 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.652575 
iter  10 value 96.425285
iter  20 value 94.721632
iter  30 value 92.859642
iter  40 value 85.362027
iter  50 value 83.458744
iter  60 value 83.204686
iter  70 value 82.717841
iter  80 value 82.429695
iter  90 value 82.163950
iter 100 value 82.041442
final  value 82.041442 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 115.511336 
iter  10 value 94.218370
iter  20 value 92.236191
iter  30 value 87.667043
iter  40 value 84.743227
iter  50 value 84.286767
iter  60 value 84.004718
iter  70 value 83.921977
iter  80 value 83.742575
iter  90 value 83.459646
iter 100 value 82.743676
final  value 82.743676 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.268139 
iter  10 value 94.021828
iter  20 value 90.420939
iter  30 value 84.994658
iter  40 value 84.023197
iter  50 value 83.851922
iter  60 value 83.447979
iter  70 value 82.823379
iter  80 value 82.494892
iter  90 value 82.309543
iter 100 value 82.066260
final  value 82.066260 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.979385 
iter  10 value 94.054364
iter  20 value 94.035364
iter  30 value 87.084234
iter  40 value 87.072155
iter  50 value 87.027666
iter  60 value 86.849571
iter  70 value 86.772109
iter  80 value 86.023317
iter  90 value 85.837406
iter 100 value 85.836057
final  value 85.836057 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.020582 
iter  10 value 93.871302
iter  20 value 93.869890
final  value 93.869794 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.000470 
final  value 94.054414 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.504255 
final  value 94.054476 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.076936 
final  value 94.054639 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.233634 
iter  10 value 94.013921
iter  20 value 94.010066
iter  30 value 93.958760
iter  40 value 88.020418
iter  50 value 87.569476
iter  60 value 87.525373
iter  70 value 85.584846
iter  80 value 84.676155
iter  90 value 84.317920
iter 100 value 84.313245
final  value 84.313245 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.543220 
iter  10 value 93.898740
iter  20 value 93.894598
iter  30 value 93.772602
iter  40 value 87.337626
iter  50 value 85.190330
iter  60 value 84.854692
iter  70 value 84.431911
iter  80 value 84.415407
iter  90 value 84.415247
final  value 84.411898 
converged
Fitting Repeat 3 

# weights:  305
initial  value 125.274990 
iter  10 value 94.058042
iter  20 value 93.976600
iter  30 value 91.105434
iter  40 value 90.747883
iter  50 value 87.548271
iter  60 value 85.529618
iter  70 value 81.751103
iter  80 value 81.222077
iter  90 value 80.713348
iter 100 value 80.710800
final  value 80.710800 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.279210 
iter  10 value 94.057731
final  value 94.052920 
converged
Fitting Repeat 5 

# weights:  305
initial  value 109.354959 
iter  10 value 94.057791
iter  20 value 94.052918
iter  30 value 91.854748
iter  40 value 88.085252
final  value 88.085238 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.772898 
iter  10 value 94.061356
iter  20 value 94.031430
iter  30 value 93.818939
final  value 93.818934 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.828210 
iter  10 value 92.878257
iter  20 value 92.671813
final  value 92.669978 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.314804 
iter  10 value 94.060982
iter  20 value 93.054254
iter  30 value 86.348193
iter  40 value 85.766205
iter  50 value 85.736823
final  value 85.736786 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.518573 
iter  10 value 93.649970
iter  20 value 93.643222
iter  30 value 90.912040
iter  40 value 86.317265
iter  50 value 84.981520
iter  60 value 84.743591
iter  70 value 84.604252
final  value 84.603524 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.671905 
iter  10 value 93.827295
iter  20 value 93.819041
iter  30 value 93.817437
iter  40 value 93.605818
iter  50 value 87.677469
iter  60 value 85.621291
iter  70 value 84.846036
iter  80 value 84.507270
iter  90 value 83.605717
iter 100 value 82.774782
final  value 82.774782 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.716934 
iter  10 value 94.053030
final  value 94.052435 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.881684 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 112.539036 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.903095 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.945822 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.669562 
final  value 94.275362 
converged
Fitting Repeat 2 

# weights:  305
initial  value 120.318505 
iter  10 value 91.762716
iter  20 value 88.248767
iter  30 value 87.144826
iter  40 value 85.409680
final  value 85.131031 
converged
Fitting Repeat 3 

# weights:  305
initial  value 119.944873 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.302817 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 120.763290 
iter  10 value 94.275378
final  value 94.275362 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.347637 
iter  10 value 86.167015
iter  20 value 86.156239
iter  30 value 85.083635
iter  40 value 85.074852
final  value 85.074782 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.454748 
final  value 94.052427 
converged
Fitting Repeat 3 

# weights:  507
initial  value 118.576148 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 107.338948 
iter  10 value 94.484211
iter  10 value 94.484211
iter  10 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.831307 
final  value 94.275362 
converged
Fitting Repeat 1 

# weights:  103
initial  value 116.802484 
iter  10 value 94.411968
iter  20 value 91.954642
iter  30 value 87.596392
iter  40 value 86.409290
iter  50 value 86.340983
iter  60 value 86.053957
iter  70 value 85.860438
iter  80 value 85.771864
iter  90 value 85.663342
iter 100 value 85.654723
final  value 85.654723 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 108.101059 
iter  10 value 93.183142
iter  20 value 90.347155
iter  30 value 90.184706
iter  40 value 89.853300
final  value 89.853004 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.648987 
iter  10 value 94.497753
iter  20 value 94.486775
iter  30 value 94.317322
iter  40 value 90.970269
iter  50 value 86.860224
iter  60 value 86.541862
iter  70 value 85.384065
iter  80 value 85.040836
iter  90 value 84.090608
iter 100 value 84.036053
final  value 84.036053 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 112.804868 
iter  10 value 94.416454
iter  20 value 92.118012
iter  30 value 91.030084
iter  40 value 90.478040
iter  50 value 89.219646
iter  60 value 88.051859
iter  70 value 85.736461
iter  80 value 84.755333
iter  90 value 84.274050
iter 100 value 84.046793
final  value 84.046793 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.729392 
iter  10 value 94.489239
iter  20 value 87.641054
iter  30 value 85.812499
iter  40 value 85.024470
iter  50 value 84.951875
iter  60 value 84.613165
iter  70 value 84.473140
iter  80 value 84.341781
final  value 84.337328 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.358920 
iter  10 value 94.378505
iter  20 value 87.904724
iter  30 value 86.746841
iter  40 value 86.654799
iter  50 value 86.281297
iter  60 value 86.064316
iter  70 value 85.692211
iter  80 value 85.441676
iter  90 value 85.241277
iter 100 value 82.843854
final  value 82.843854 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.180064 
iter  10 value 94.467832
iter  20 value 92.277493
iter  30 value 90.136131
iter  40 value 84.645629
iter  50 value 84.121863
iter  60 value 83.675175
iter  70 value 82.843064
iter  80 value 82.012691
iter  90 value 81.961448
iter 100 value 81.901539
final  value 81.901539 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 113.829793 
iter  10 value 95.459059
iter  20 value 90.839890
iter  30 value 90.206179
iter  40 value 89.798774
iter  50 value 89.758336
iter  60 value 85.082898
iter  70 value 83.742249
iter  80 value 83.356585
iter  90 value 82.673543
iter 100 value 82.585888
final  value 82.585888 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.142825 
iter  10 value 94.510965
iter  20 value 88.881220
iter  30 value 87.217749
iter  40 value 86.171785
iter  50 value 85.276959
iter  60 value 83.716170
iter  70 value 83.210665
iter  80 value 82.457577
iter  90 value 81.935866
iter 100 value 81.275906
final  value 81.275906 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 113.414096 
iter  10 value 95.292172
iter  20 value 86.192647
iter  30 value 85.566139
iter  40 value 83.856000
iter  50 value 81.715349
iter  60 value 81.495972
iter  70 value 81.248632
iter  80 value 80.970040
iter  90 value 80.771395
iter 100 value 80.714100
final  value 80.714100 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 111.068808 
iter  10 value 96.026662
iter  20 value 87.836388
iter  30 value 86.968931
iter  40 value 86.031763
iter  50 value 83.844752
iter  60 value 83.589536
iter  70 value 83.426410
iter  80 value 82.728249
iter  90 value 81.466638
iter 100 value 81.039337
final  value 81.039337 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.629951 
iter  10 value 94.514263
iter  20 value 93.773880
iter  30 value 87.420536
iter  40 value 86.271176
iter  50 value 85.279604
iter  60 value 85.176144
iter  70 value 85.097998
iter  80 value 85.039804
iter  90 value 84.950459
iter 100 value 84.477904
final  value 84.477904 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.693281 
iter  10 value 95.127831
iter  20 value 94.677364
iter  30 value 92.793399
iter  40 value 88.817746
iter  50 value 86.756097
iter  60 value 85.219359
iter  70 value 83.064914
iter  80 value 81.471879
iter  90 value 81.122423
iter 100 value 80.806419
final  value 80.806419 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.017505 
iter  10 value 93.771408
iter  20 value 86.604094
iter  30 value 84.828452
iter  40 value 83.445877
iter  50 value 81.688147
iter  60 value 81.048885
iter  70 value 80.613204
iter  80 value 80.525323
iter  90 value 80.495822
iter 100 value 80.448629
final  value 80.448629 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.725522 
iter  10 value 94.799578
iter  20 value 91.794287
iter  30 value 85.361797
iter  40 value 83.113373
iter  50 value 82.430780
iter  60 value 81.138910
iter  70 value 80.179231
iter  80 value 80.102984
iter  90 value 80.030043
iter 100 value 79.883098
final  value 79.883098 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 113.833721 
final  value 94.485978 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.982547 
iter  10 value 94.485873
iter  20 value 94.484219
final  value 94.484215 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.526137 
final  value 94.449583 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.023483 
final  value 94.486072 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.757228 
final  value 94.485841 
converged
Fitting Repeat 1 

# weights:  305
initial  value 116.724384 
iter  10 value 94.489854
iter  20 value 94.470529
iter  30 value 94.006534
iter  40 value 89.575726
iter  50 value 88.792494
iter  60 value 88.782459
iter  70 value 88.696352
final  value 88.680419 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.924510 
iter  10 value 94.297598
iter  20 value 94.234583
iter  30 value 94.082439
iter  40 value 85.543885
final  value 85.536542 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.542736 
iter  10 value 94.489463
iter  20 value 94.376946
iter  30 value 87.884169
iter  40 value 87.840303
iter  50 value 87.839648
final  value 87.839621 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.279707 
iter  10 value 94.045928
iter  20 value 89.723531
iter  30 value 86.143636
iter  40 value 86.067919
iter  50 value 85.584915
iter  60 value 85.572601
iter  70 value 85.571353
iter  80 value 85.570767
iter  90 value 85.570504
iter  90 value 85.570504
iter  90 value 85.570504
final  value 85.570504 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.162371 
iter  10 value 90.915591
iter  20 value 85.394185
iter  30 value 85.372638
iter  40 value 85.245329
iter  50 value 85.086924
iter  60 value 85.085980
iter  70 value 85.084906
iter  80 value 85.082526
iter  90 value 85.082373
iter 100 value 85.082283
final  value 85.082283 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.490654 
iter  10 value 94.283783
iter  20 value 94.281516
iter  30 value 94.279329
iter  40 value 94.239451
iter  50 value 93.999449
iter  60 value 93.919287
iter  70 value 87.765024
iter  80 value 85.527766
iter  90 value 85.203379
final  value 85.203064 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.701940 
iter  10 value 94.491071
iter  20 value 93.997581
iter  30 value 93.942102
iter  40 value 93.940223
final  value 93.940014 
converged
Fitting Repeat 3 

# weights:  507
initial  value 108.321382 
iter  10 value 94.458654
iter  20 value 94.453864
iter  30 value 94.411732
iter  40 value 85.869303
iter  50 value 85.467744
iter  60 value 84.802804
final  value 84.801532 
converged
Fitting Repeat 4 

# weights:  507
initial  value 113.717583 
iter  10 value 94.096942
final  value 94.096508 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.338545 
iter  10 value 94.492348
iter  20 value 94.464665
iter  30 value 91.169605
iter  40 value 87.073330
iter  50 value 84.481004
iter  60 value 82.163039
iter  70 value 80.501754
iter  80 value 79.477671
iter  90 value 79.432568
iter 100 value 79.390374
final  value 79.390374 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 134.118818 
iter  10 value 114.035182
iter  20 value 107.898011
iter  30 value 107.307643
iter  40 value 104.936582
iter  50 value 103.019495
iter  60 value 102.654344
iter  70 value 102.299111
iter  80 value 101.865156
iter  90 value 101.631678
iter 100 value 101.433622
final  value 101.433622 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 137.277493 
iter  10 value 117.140028
iter  20 value 111.056887
iter  30 value 107.694276
iter  40 value 106.583549
iter  50 value 105.751610
iter  60 value 105.084609
iter  70 value 104.706597
iter  80 value 104.624995
iter  90 value 104.441576
iter 100 value 104.265919
final  value 104.265919 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 148.317346 
iter  10 value 117.721672
iter  20 value 110.850536
iter  30 value 110.324293
iter  40 value 109.773367
iter  50 value 104.048839
iter  60 value 102.638463
iter  70 value 102.313462
iter  80 value 102.072481
iter  90 value 101.403750
iter 100 value 101.112601
final  value 101.112601 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 124.730731 
iter  10 value 110.433241
iter  20 value 106.389106
iter  30 value 103.476630
iter  40 value 102.576683
iter  50 value 101.929401
iter  60 value 101.461040
iter  70 value 101.137423
iter  80 value 101.051364
iter  90 value 101.032637
iter 100 value 100.748151
final  value 100.748151 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 140.119293 
iter  10 value 117.914089
iter  20 value 117.787749
iter  30 value 113.681229
iter  40 value 111.437512
iter  50 value 107.047159
iter  60 value 105.922218
iter  70 value 105.680107
iter  80 value 104.512281
iter  90 value 103.071010
iter 100 value 102.384159
final  value 102.384159 
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 -- Sun Aug 31 23:43:08 2025 
*********************************************** 
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 
Warning messages:
1: `repeats` has no meaning for this resampling method. 
2: executing %dopar% sequentially: no parallel backend registered 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
 39.968   1.481 102.823