##############################################################################
##############################################################################
###
### 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_1.12.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck’
* using R version 4.4.1 (2024-06-14)
* using platform: aarch64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 12.2.0
* running under: macOS Ventura 13.6.7
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.12.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ...Warning: unable to access index for repository https://CRAN.R-project.org/src/contrib:
  cannot open URL 'https://CRAN.R-project.org/src/contrib/PACKAGES'
 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 ... NOTE
Unknown package ‘ftrCOOL’ in Rd xrefs
* 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    15.541  0.391  15.934
var_imp     15.414  0.452  15.865
corr_plot   15.106  0.393  15.508
enrichfindP  0.128  0.022  10.686
* 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: 3 NOTEs
See
  ‘/Users/biocbuild/bbs-3.20-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/4.4-arm64/Resources/library’
* installing *source* package ‘HPiP’ ...
** 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 4.4.1 (2024-06-14) -- "Race for Your Life"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20

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

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

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

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

# weights:  103
initial  value 96.549834 
final  value 94.477594 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.698007 
final  value 94.026542 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.864213 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.771719 
iter  10 value 94.480785
final  value 94.477626 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.360039 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.082743 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.148729 
final  value 94.428839 
converged
Fitting Repeat 3 

# weights:  305
initial  value 109.762878 
iter  10 value 93.792175
iter  20 value 93.788088
final  value 93.788077 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.885912 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 114.218863 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.080935 
final  value 94.026542 
converged
Fitting Repeat 2 

# weights:  507
initial  value 112.824974 
iter  10 value 94.428839
iter  10 value 94.428839
iter  10 value 94.428839
final  value 94.428839 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.850654 
iter  10 value 92.007986
iter  20 value 91.603929
final  value 91.603811 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.301683 
iter  10 value 93.668813
final  value 93.668704 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.024790 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.839443 
iter  10 value 93.961816
iter  20 value 84.666325
iter  30 value 84.027912
iter  40 value 83.896913
iter  50 value 81.139888
iter  60 value 80.023094
iter  70 value 79.766798
iter  80 value 79.756198
iter  90 value 79.386948
iter 100 value 79.303014
final  value 79.303014 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.503375 
iter  10 value 87.024007
iter  20 value 86.075383
iter  30 value 84.800531
iter  40 value 84.094198
iter  50 value 84.005075
iter  60 value 83.442116
iter  70 value 83.040078
iter  80 value 83.008085
final  value 83.008032 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.950812 
iter  10 value 94.129625
iter  20 value 88.885640
iter  30 value 83.709661
iter  40 value 83.196587
iter  50 value 82.301830
iter  60 value 80.364864
iter  70 value 79.413998
iter  80 value 79.349137
iter  90 value 79.308752
iter 100 value 79.299647
final  value 79.299647 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.017215 
iter  10 value 94.472926
iter  20 value 88.222466
iter  30 value 87.302250
iter  40 value 86.974660
iter  50 value 86.256075
iter  60 value 86.054366
iter  60 value 86.054366
final  value 86.054366 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.001363 
iter  10 value 94.501758
iter  20 value 84.620922
iter  30 value 82.816734
iter  40 value 82.031081
iter  50 value 81.855768
iter  60 value 80.461958
iter  70 value 79.365102
iter  80 value 79.306152
iter  90 value 79.289222
final  value 79.289219 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.380961 
iter  10 value 94.074638
iter  20 value 88.888619
iter  30 value 84.194045
iter  40 value 83.255441
iter  50 value 82.271413
iter  60 value 80.748019
iter  70 value 79.509302
iter  80 value 78.668325
iter  90 value 78.434228
iter 100 value 78.350328
final  value 78.350328 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.550448 
iter  10 value 95.135423
iter  20 value 83.510300
iter  30 value 82.271688
iter  40 value 81.648527
iter  50 value 80.105762
iter  60 value 79.581493
iter  70 value 79.401516
iter  80 value 79.148381
iter  90 value 79.089417
iter 100 value 79.070950
final  value 79.070950 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.292998 
iter  10 value 94.023409
iter  20 value 89.794775
iter  30 value 85.820953
iter  40 value 81.195214
iter  50 value 79.830467
iter  60 value 79.733151
iter  70 value 78.628742
iter  80 value 78.276313
iter  90 value 78.053406
iter 100 value 77.826091
final  value 77.826091 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.885065 
iter  10 value 88.135110
iter  20 value 83.534195
iter  30 value 83.110102
iter  40 value 82.992207
iter  50 value 82.612372
iter  60 value 80.751907
iter  70 value 79.354412
iter  80 value 79.077957
iter  90 value 78.959400
iter 100 value 78.878794
final  value 78.878794 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 113.975434 
iter  10 value 94.532011
iter  20 value 94.162176
iter  30 value 93.901298
iter  40 value 91.554448
iter  50 value 86.583169
iter  60 value 85.323301
iter  70 value 84.371611
iter  80 value 83.872479
iter  90 value 83.331549
iter 100 value 82.972384
final  value 82.972384 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 128.733612 
iter  10 value 93.663570
iter  20 value 92.456746
iter  30 value 89.698938
iter  40 value 85.513055
iter  50 value 83.392563
iter  60 value 80.301986
iter  70 value 79.724480
iter  80 value 79.675780
iter  90 value 79.498297
iter 100 value 79.066711
final  value 79.066711 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 118.215507 
iter  10 value 95.844079
iter  20 value 94.210679
iter  30 value 92.172856
iter  40 value 90.981781
iter  50 value 87.080337
iter  60 value 83.934985
iter  70 value 81.011723
iter  80 value 78.734485
iter  90 value 78.065771
iter 100 value 77.952238
final  value 77.952238 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.708773 
iter  10 value 94.582035
iter  20 value 93.402995
iter  30 value 87.214123
iter  40 value 82.654380
iter  50 value 80.063904
iter  60 value 79.376805
iter  70 value 78.810290
iter  80 value 78.377971
iter  90 value 78.331301
iter 100 value 78.196858
final  value 78.196858 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.147674 
iter  10 value 94.370065
iter  20 value 86.831347
iter  30 value 85.697116
iter  40 value 84.379096
iter  50 value 83.650559
iter  60 value 83.215226
iter  70 value 82.855272
iter  80 value 81.224752
iter  90 value 80.757143
iter 100 value 80.011363
final  value 80.011363 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.789038 
iter  10 value 94.958131
iter  20 value 89.954079
iter  30 value 84.593013
iter  40 value 83.457794
iter  50 value 81.943293
iter  60 value 79.172655
iter  70 value 78.514543
iter  80 value 78.310587
iter  90 value 77.815454
iter 100 value 77.718266
final  value 77.718266 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.630045 
final  value 94.485677 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.774871 
final  value 94.470631 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.329501 
final  value 94.486174 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.353018 
iter  10 value 94.028359
iter  20 value 94.026957
final  value 94.026704 
converged
Fitting Repeat 5 

# weights:  103
initial  value 112.156003 
final  value 94.485977 
converged
Fitting Repeat 1 

# weights:  305
initial  value 121.315279 
iter  10 value 94.485948
iter  20 value 82.830481
iter  30 value 79.266560
iter  40 value 77.010851
iter  50 value 76.671937
iter  60 value 76.453382
iter  70 value 76.421384
iter  80 value 76.419470
iter  90 value 76.413488
iter 100 value 76.411420
final  value 76.411420 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 95.039013 
iter  10 value 94.093790
iter  20 value 91.783634
iter  30 value 83.833398
iter  40 value 83.646979
iter  50 value 83.628796
final  value 83.628629 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.591979 
iter  10 value 93.981956
iter  20 value 93.620741
iter  30 value 87.067709
iter  40 value 86.130584
iter  50 value 86.120966
iter  60 value 85.493435
iter  70 value 85.353191
iter  80 value 85.349515
iter  90 value 85.347055
iter 100 value 85.345785
final  value 85.345785 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.801275 
iter  10 value 91.988355
iter  20 value 84.980536
iter  30 value 83.667863
iter  40 value 83.484609
iter  50 value 82.343797
iter  60 value 80.289861
iter  70 value 79.690025
iter  80 value 79.689508
iter  90 value 79.451320
final  value 79.450188 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.981392 
iter  10 value 94.488812
iter  20 value 94.482921
iter  30 value 94.027647
iter  40 value 94.026958
iter  50 value 92.726128
iter  60 value 84.283063
iter  70 value 84.154541
iter  80 value 84.023464
iter  90 value 83.806626
iter 100 value 83.806104
final  value 83.806104 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 94.632182 
iter  10 value 93.629072
iter  20 value 93.558071
iter  30 value 93.553003
iter  40 value 93.262311
iter  50 value 90.116710
iter  60 value 84.015142
iter  70 value 78.625951
iter  80 value 78.044138
iter  90 value 78.014811
iter 100 value 77.969586
final  value 77.969586 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.046295 
iter  10 value 94.037436
iter  20 value 94.031987
iter  30 value 93.957612
iter  40 value 93.942569
iter  50 value 93.940970
final  value 93.939444 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.252733 
iter  10 value 94.035154
iter  20 value 93.744399
iter  30 value 90.663930
iter  40 value 90.337966
iter  50 value 90.336884
iter  60 value 87.305123
iter  70 value 87.256988
iter  80 value 87.255743
iter  90 value 87.138505
iter 100 value 87.133628
final  value 87.133628 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 99.020434 
iter  10 value 94.035112
iter  20 value 93.253779
iter  30 value 85.105724
iter  40 value 79.586560
iter  50 value 79.379804
iter  60 value 79.139333
iter  70 value 79.128457
iter  80 value 79.108281
final  value 79.108238 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.493408 
iter  10 value 94.491298
iter  20 value 94.313310
iter  30 value 85.279744
iter  40 value 85.211421
iter  50 value 84.871270
iter  60 value 84.669691
iter  70 value 84.668477
iter  80 value 84.665094
iter  90 value 83.604995
iter 100 value 81.491258
final  value 81.491258 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 105.763501 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.764704 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 109.185422 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.344867 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 107.318537 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.738700 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 110.197831 
final  value 94.275362 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.205082 
iter  10 value 94.322897
iter  10 value 94.322897
iter  10 value 94.322897
final  value 94.322897 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.324800 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.465502 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.582521 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.606436 
iter  10 value 93.159468
iter  20 value 87.082990
iter  30 value 86.451452
iter  40 value 85.752648
iter  50 value 85.524228
final  value 85.523080 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.110496 
iter  10 value 86.582496
iter  20 value 84.438048
iter  30 value 84.437367
iter  40 value 84.431557
iter  50 value 84.407264
final  value 84.407143 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.627779 
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  507
initial  value 120.553417 
iter  10 value 92.519179
iter  20 value 84.155620
iter  30 value 83.829712
iter  40 value 83.829353
iter  50 value 83.732876
final  value 83.674441 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.523968 
iter  10 value 94.487297
iter  20 value 94.486662
iter  30 value 92.803527
iter  40 value 87.007663
iter  50 value 85.597591
iter  60 value 85.343124
iter  70 value 84.917389
iter  80 value 84.706998
iter  90 value 84.684198
final  value 84.680077 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.628899 
iter  10 value 94.465163
iter  20 value 92.341870
iter  30 value 90.891264
iter  40 value 88.279255
iter  50 value 84.719000
iter  60 value 82.901026
iter  70 value 82.248285
iter  80 value 82.145921
iter  90 value 82.009405
final  value 82.008704 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.726389 
iter  10 value 94.488676
iter  20 value 92.007730
iter  30 value 89.971137
iter  40 value 87.343346
iter  50 value 83.838104
iter  60 value 82.569353
iter  70 value 82.168217
iter  80 value 82.105955
iter  90 value 81.937920
iter 100 value 81.904607
final  value 81.904607 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 101.753474 
iter  10 value 94.494658
iter  20 value 94.410003
iter  30 value 90.757683
iter  40 value 89.302181
iter  50 value 87.512777
iter  60 value 85.864417
iter  70 value 84.442940
iter  80 value 84.373542
iter  90 value 84.324885
iter 100 value 84.318032
final  value 84.318032 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 98.680604 
iter  10 value 94.486695
iter  10 value 94.486694
iter  20 value 94.377485
iter  30 value 91.782088
iter  40 value 88.853140
iter  50 value 86.396895
iter  60 value 83.575808
iter  70 value 82.939572
iter  80 value 82.580026
iter  90 value 82.318380
iter 100 value 82.021093
final  value 82.021093 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 109.717881 
iter  10 value 94.464129
iter  20 value 88.953435
iter  30 value 85.166022
iter  40 value 84.194239
iter  50 value 83.391135
iter  60 value 82.675197
iter  70 value 82.564300
iter  80 value 81.403743
iter  90 value 81.212461
iter 100 value 80.985747
final  value 80.985747 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 111.921605 
iter  10 value 94.471090
iter  20 value 94.328308
iter  30 value 94.306877
iter  40 value 86.894593
iter  50 value 85.254077
iter  60 value 83.996555
iter  70 value 83.083615
iter  80 value 82.812308
iter  90 value 82.251299
iter 100 value 81.276907
final  value 81.276907 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.175804 
iter  10 value 94.139607
iter  20 value 86.391908
iter  30 value 85.591497
iter  40 value 85.071215
iter  50 value 82.366858
iter  60 value 81.430945
iter  70 value 81.203983
iter  80 value 80.774899
iter  90 value 80.618579
iter 100 value 80.500720
final  value 80.500720 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.228980 
iter  10 value 94.443348
iter  20 value 93.679118
iter  30 value 91.671379
iter  40 value 90.897971
iter  50 value 90.616773
iter  60 value 83.781470
iter  70 value 82.432963
iter  80 value 82.217279
iter  90 value 82.060992
iter 100 value 81.443710
final  value 81.443710 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.715786 
iter  10 value 91.694859
iter  20 value 89.281456
iter  30 value 87.157151
iter  40 value 85.408539
iter  50 value 84.804200
iter  60 value 83.372838
iter  70 value 82.729091
iter  80 value 82.514915
iter  90 value 82.056511
iter 100 value 81.550601
final  value 81.550601 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.734742 
iter  10 value 94.534632
iter  20 value 92.286795
iter  30 value 91.628157
iter  40 value 91.240826
iter  50 value 90.796754
iter  60 value 90.616894
iter  70 value 90.463677
iter  80 value 89.913159
iter  90 value 85.543399
iter 100 value 84.362472
final  value 84.362472 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 136.073525 
iter  10 value 94.510468
iter  20 value 94.318741
iter  30 value 93.319751
iter  40 value 88.527029
iter  50 value 85.956425
iter  60 value 82.285874
iter  70 value 81.717570
iter  80 value 81.339116
iter  90 value 80.921013
iter 100 value 80.685403
final  value 80.685403 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.763316 
iter  10 value 96.636560
iter  20 value 92.058670
iter  30 value 90.068113
iter  40 value 83.819520
iter  50 value 81.510350
iter  60 value 81.264594
iter  70 value 81.095357
iter  80 value 80.852495
iter  90 value 80.709637
iter 100 value 80.662111
final  value 80.662111 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.391901 
iter  10 value 92.764927
iter  20 value 85.550436
iter  30 value 85.153261
iter  40 value 84.487259
iter  50 value 82.948005
iter  60 value 81.870042
iter  70 value 81.156532
iter  80 value 80.935803
iter  90 value 80.777838
iter 100 value 80.651191
final  value 80.651191 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.796744 
iter  10 value 93.507805
iter  20 value 85.831743
iter  30 value 85.464038
iter  40 value 84.495118
iter  50 value 84.023229
iter  60 value 83.902544
iter  70 value 83.385730
iter  80 value 82.633656
iter  90 value 81.671891
iter 100 value 80.697710
final  value 80.697710 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.097254 
final  value 94.485738 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.786747 
final  value 94.485731 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.404005 
final  value 94.485858 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.546495 
final  value 94.485761 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.970011 
final  value 94.485892 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.994813 
iter  10 value 94.489221
iter  20 value 94.444504
iter  30 value 92.168210
iter  40 value 90.673004
iter  50 value 90.400567
iter  60 value 90.395924
iter  70 value 90.395794
final  value 90.395177 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.763365 
iter  10 value 94.488682
iter  20 value 94.414899
final  value 94.275469 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.050612 
iter  10 value 94.489044
iter  20 value 93.018794
iter  30 value 90.177508
iter  40 value 89.712712
iter  50 value 89.591195
iter  60 value 89.591054
iter  60 value 89.591054
iter  60 value 89.591054
final  value 89.591054 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.765622 
iter  10 value 94.487394
iter  20 value 92.888654
iter  30 value 92.503002
iter  40 value 91.668734
iter  50 value 91.640353
final  value 91.640293 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.756044 
iter  10 value 94.488056
iter  20 value 94.420070
iter  30 value 91.515050
iter  40 value 91.381679
iter  50 value 91.381335
iter  60 value 91.380564
iter  70 value 91.380379
iter  80 value 91.374840
iter  90 value 90.218535
iter 100 value 89.994078
final  value 89.994078 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.984816 
iter  10 value 94.283734
iter  20 value 94.281493
iter  30 value 94.279837
iter  40 value 94.002175
iter  50 value 88.112512
iter  60 value 87.291965
iter  70 value 87.224780
iter  80 value 84.018342
iter  90 value 81.460536
iter 100 value 79.703042
final  value 79.703042 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.016033 
iter  10 value 94.492070
iter  20 value 94.484356
iter  30 value 92.127272
iter  40 value 85.101821
iter  50 value 85.039765
iter  60 value 82.439937
iter  70 value 80.974294
iter  80 value 80.867133
iter  90 value 80.850870
final  value 80.850118 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.202438 
iter  10 value 94.451060
iter  20 value 93.769358
iter  30 value 90.761675
iter  40 value 89.055303
iter  50 value 89.054579
iter  60 value 88.864324
iter  70 value 88.714483
final  value 88.714475 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.107129 
iter  10 value 94.194871
iter  20 value 94.088012
iter  30 value 94.081250
iter  40 value 94.080546
iter  50 value 94.077389
iter  60 value 94.077074
iter  70 value 94.057321
iter  80 value 90.468234
iter  90 value 87.568706
iter 100 value 83.473187
final  value 83.473187 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 99.116057 
iter  10 value 94.493094
iter  20 value 94.475783
iter  30 value 93.886097
iter  40 value 90.167492
iter  50 value 89.991917
iter  60 value 89.988998
iter  70 value 86.186569
iter  80 value 83.341458
iter  90 value 82.773371
iter 100 value 82.468333
final  value 82.468333 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.512643 
final  value 93.943841 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.700284 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.563032 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.262641 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.382067 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.256778 
final  value 94.032967 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.697475 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.542716 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.942273 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.745072 
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.551712 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.276650 
final  value 94.032967 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.754983 
iter  10 value 93.808316
final  value 93.808310 
converged
Fitting Repeat 4 

# weights:  507
initial  value 109.120980 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.413848 
iter  10 value 92.909260
iter  20 value 92.274256
final  value 92.274075 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.177091 
iter  10 value 94.258936
iter  20 value 94.038842
iter  30 value 93.460491
iter  40 value 93.151781
iter  50 value 90.534067
iter  60 value 88.804750
iter  70 value 86.320779
iter  80 value 86.021506
iter  90 value 85.618774
iter 100 value 85.588015
final  value 85.588015 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.158587 
iter  10 value 93.891385
iter  20 value 91.839983
iter  30 value 86.400555
iter  40 value 85.811537
iter  50 value 85.682686
iter  60 value 85.633731
iter  70 value 85.589808
final  value 85.588011 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.725756 
iter  10 value 94.054849
iter  20 value 90.987855
iter  30 value 88.246389
iter  40 value 88.172580
iter  50 value 86.304602
iter  60 value 85.851861
iter  70 value 85.779896
iter  80 value 85.683710
iter  90 value 85.633112
iter 100 value 85.588016
final  value 85.588016 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 100.420920 
iter  10 value 94.371676
iter  20 value 94.042955
iter  30 value 93.866352
iter  40 value 92.242407
iter  50 value 91.143862
iter  60 value 87.185142
iter  70 value 86.137049
iter  80 value 85.728288
iter  90 value 85.569209
iter 100 value 85.522540
final  value 85.522540 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 104.500999 
iter  10 value 94.028247
iter  20 value 90.302833
iter  30 value 89.702022
iter  40 value 89.425678
iter  50 value 89.396407
iter  60 value 87.181604
iter  70 value 85.510600
iter  80 value 85.262035
iter  90 value 85.237733
final  value 85.237717 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.860198 
iter  10 value 94.062188
iter  20 value 93.274935
iter  30 value 87.299230
iter  40 value 86.291273
iter  50 value 86.162918
iter  60 value 84.970012
iter  70 value 82.388617
iter  80 value 81.795224
iter  90 value 81.695429
iter 100 value 81.674622
final  value 81.674622 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 119.128451 
iter  10 value 94.049029
iter  20 value 90.222366
iter  30 value 87.879947
iter  40 value 86.984536
iter  50 value 86.017870
iter  60 value 84.094120
iter  70 value 82.622397
iter  80 value 82.427698
iter  90 value 82.058113
iter 100 value 81.869113
final  value 81.869113 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.321940 
iter  10 value 93.849003
iter  20 value 89.203389
iter  30 value 87.445292
iter  40 value 86.310120
iter  50 value 83.969876
iter  60 value 82.973927
iter  70 value 82.631709
iter  80 value 82.548950
iter  90 value 82.219904
iter 100 value 81.974415
final  value 81.974415 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.081819 
iter  10 value 94.129453
iter  20 value 93.859950
iter  30 value 89.572124
iter  40 value 88.678957
iter  50 value 86.207598
iter  60 value 85.638399
iter  70 value 85.476116
iter  80 value 85.333806
iter  90 value 85.171979
iter 100 value 84.480683
final  value 84.480683 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.660983 
iter  10 value 94.133577
iter  20 value 92.604002
iter  30 value 91.707512
iter  40 value 88.418261
iter  50 value 87.916499
iter  60 value 86.789932
iter  70 value 84.104178
iter  80 value 83.656861
iter  90 value 83.536733
iter 100 value 83.156420
final  value 83.156420 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 118.324007 
iter  10 value 94.019256
iter  20 value 91.108277
iter  30 value 86.259793
iter  40 value 84.980735
iter  50 value 83.604851
iter  60 value 82.303841
iter  70 value 81.889982
iter  80 value 81.680021
iter  90 value 81.636417
iter 100 value 81.518433
final  value 81.518433 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 130.656479 
iter  10 value 94.434549
iter  20 value 90.534188
iter  30 value 86.777796
iter  40 value 86.532769
iter  50 value 86.016986
iter  60 value 85.140912
iter  70 value 84.664802
iter  80 value 84.361283
iter  90 value 83.607643
iter 100 value 82.985366
final  value 82.985366 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.577863 
iter  10 value 89.552477
iter  20 value 86.536852
iter  30 value 86.303839
iter  40 value 85.395993
iter  50 value 85.057951
iter  60 value 84.871957
iter  70 value 84.477588
iter  80 value 83.794786
iter  90 value 83.710194
iter 100 value 83.457542
final  value 83.457542 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 127.598502 
iter  10 value 97.604287
iter  20 value 89.835002
iter  30 value 89.091279
iter  40 value 88.065315
iter  50 value 85.231864
iter  60 value 84.613893
iter  70 value 83.594495
iter  80 value 83.196935
iter  90 value 83.007265
iter 100 value 82.388417
final  value 82.388417 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.097246 
iter  10 value 94.514748
iter  20 value 92.576539
iter  30 value 88.026420
iter  40 value 86.459068
iter  50 value 85.523061
iter  60 value 85.167551
iter  70 value 84.026602
iter  80 value 84.001867
iter  90 value 83.918309
iter 100 value 83.517365
final  value 83.517365 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.187543 
final  value 94.054600 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.823222 
iter  10 value 93.418650
iter  20 value 93.323474
iter  30 value 93.323307
iter  40 value 93.084096
iter  40 value 93.084095
iter  40 value 93.084095
final  value 93.084095 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.137247 
final  value 94.054622 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.829951 
final  value 94.043575 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.178084 
iter  10 value 94.054396
iter  20 value 94.049860
iter  30 value 87.440847
iter  40 value 86.331992
final  value 86.331822 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.128233 
iter  10 value 93.071305
iter  20 value 89.981580
iter  30 value 85.600799
iter  40 value 85.445630
iter  50 value 84.763188
iter  60 value 84.557392
iter  70 value 84.411629
iter  80 value 84.365865
iter  90 value 84.364659
iter 100 value 84.194846
final  value 84.194846 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 120.027617 
iter  10 value 94.057798
iter  20 value 92.586137
iter  30 value 86.735237
iter  40 value 86.009487
iter  50 value 85.480984
iter  60 value 83.397288
iter  70 value 82.019864
iter  80 value 81.888640
iter  90 value 81.787343
iter 100 value 81.735682
final  value 81.735682 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 95.421241 
iter  10 value 94.055598
iter  20 value 91.993899
iter  30 value 85.854883
iter  40 value 85.194988
iter  50 value 85.184156
final  value 85.184111 
converged
Fitting Repeat 4 

# weights:  305
initial  value 110.854583 
iter  10 value 92.707016
iter  20 value 92.705272
iter  30 value 92.702125
final  value 92.701977 
converged
Fitting Repeat 5 

# weights:  305
initial  value 117.307190 
iter  10 value 94.058471
iter  20 value 91.538110
iter  30 value 85.738215
iter  40 value 85.540756
final  value 85.536763 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.277491 
iter  10 value 88.215366
iter  20 value 85.161278
iter  30 value 85.153038
iter  40 value 85.142338
iter  50 value 85.095678
iter  60 value 84.709747
iter  70 value 84.661258
iter  80 value 84.590000
iter  90 value 84.132394
iter 100 value 84.048469
final  value 84.048469 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.265244 
iter  10 value 93.573434
iter  20 value 93.540564
iter  30 value 92.925141
iter  40 value 92.896030
iter  50 value 92.892929
iter  60 value 88.345459
iter  70 value 85.247144
iter  80 value 85.170359
iter  90 value 85.168367
final  value 85.168202 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.518658 
iter  10 value 94.040543
iter  20 value 94.039363
iter  30 value 94.038360
iter  40 value 93.893354
iter  50 value 91.415847
iter  60 value 89.431646
iter  70 value 87.220825
iter  80 value 84.357453
iter  90 value 83.836795
iter 100 value 83.833882
final  value 83.833882 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.637298 
iter  10 value 94.052889
iter  20 value 94.044546
iter  30 value 91.433528
iter  40 value 85.271149
iter  50 value 83.835665
iter  60 value 83.492009
iter  70 value 82.750481
iter  80 value 82.249455
iter  90 value 82.243890
iter 100 value 82.242675
final  value 82.242675 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.159417 
iter  10 value 94.060723
iter  20 value 93.972088
iter  30 value 87.601864
iter  40 value 84.974299
iter  50 value 84.886546
iter  60 value 84.494957
iter  70 value 83.203304
iter  80 value 83.042930
iter  90 value 81.343101
iter 100 value 80.409503
final  value 80.409503 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 106.947943 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.109669 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.874195 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 113.611034 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.795590 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.978498 
iter  10 value 93.645257
final  value 93.643491 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.306893 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 110.058756 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 108.110972 
final  value 94.354396 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.529871 
iter  10 value 92.776778
iter  20 value 86.029012
iter  30 value 82.798580
iter  40 value 82.789208
iter  50 value 82.788232
iter  60 value 82.787994
iter  70 value 82.769898
iter  80 value 82.663410
final  value 82.663181 
converged
Fitting Repeat 1 

# weights:  507
initial  value 110.152037 
iter  10 value 90.513790
iter  20 value 86.106880
iter  30 value 85.647642
iter  40 value 85.633713
iter  50 value 85.442400
iter  60 value 85.304768
iter  70 value 85.296457
iter  80 value 85.293677
final  value 85.291026 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.238772 
iter  10 value 93.665025
final  value 93.623583 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.585687 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.459140 
final  value 94.354396 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.636414 
iter  10 value 94.359148
iter  20 value 94.354397
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.603103 
iter  10 value 94.424091
iter  20 value 86.441476
iter  30 value 83.845438
iter  40 value 83.510255
iter  50 value 83.344648
iter  60 value 83.303630
iter  70 value 83.302743
final  value 83.302686 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.899719 
iter  10 value 94.526808
iter  20 value 94.488214
iter  30 value 93.767682
iter  40 value 93.742983
iter  50 value 93.675945
iter  60 value 91.196215
iter  70 value 84.473778
iter  80 value 84.299262
iter  90 value 84.059695
iter 100 value 83.987604
final  value 83.987604 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 100.399122 
iter  10 value 94.488825
iter  20 value 94.155975
iter  30 value 91.880979
iter  40 value 91.527889
iter  50 value 86.587726
iter  60 value 83.851939
iter  70 value 83.834209
iter  80 value 83.778286
iter  90 value 83.749240
iter 100 value 83.721907
final  value 83.721907 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 98.654823 
iter  10 value 94.242481
iter  20 value 93.743073
iter  30 value 93.672656
iter  40 value 92.100568
iter  50 value 91.091184
iter  60 value 88.517976
iter  70 value 86.613950
iter  80 value 82.781486
iter  90 value 82.045294
iter 100 value 81.916132
final  value 81.916132 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 103.279500 
iter  10 value 90.642562
iter  20 value 86.396781
iter  30 value 84.257498
iter  40 value 83.403893
iter  50 value 83.368615
iter  60 value 83.365585
iter  70 value 83.362344
iter  80 value 83.310872
final  value 83.302572 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.581838 
iter  10 value 94.531324
iter  20 value 94.344909
iter  30 value 86.643853
iter  40 value 85.911402
iter  50 value 84.152060
iter  60 value 83.346170
iter  70 value 81.809796
iter  80 value 81.235799
iter  90 value 81.003296
iter 100 value 80.988563
final  value 80.988563 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.323791 
iter  10 value 95.387866
iter  20 value 93.731212
iter  30 value 91.573343
iter  40 value 86.263370
iter  50 value 85.418836
iter  60 value 83.783727
iter  70 value 82.104471
iter  80 value 81.504364
iter  90 value 81.439685
iter 100 value 81.373696
final  value 81.373696 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.011772 
iter  10 value 94.529217
iter  20 value 84.689016
iter  30 value 84.062774
iter  40 value 83.629110
iter  50 value 81.555659
iter  60 value 80.500612
iter  70 value 80.342993
iter  80 value 80.113511
iter  90 value 79.938401
iter 100 value 79.759668
final  value 79.759668 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.059653 
iter  10 value 94.538781
iter  20 value 87.524585
iter  30 value 86.779088
iter  40 value 86.198730
iter  50 value 86.007050
iter  60 value 84.796566
iter  70 value 82.615559
iter  80 value 82.157129
iter  90 value 81.955859
iter 100 value 81.846636
final  value 81.846636 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 114.805167 
iter  10 value 94.513552
iter  20 value 93.454988
iter  30 value 86.963729
iter  40 value 83.268246
iter  50 value 83.074994
iter  60 value 82.778888
iter  70 value 82.289515
iter  80 value 82.092942
iter  90 value 81.425742
iter 100 value 80.976061
final  value 80.976061 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.319201 
iter  10 value 94.304214
iter  20 value 85.864107
iter  30 value 82.545359
iter  40 value 82.046850
iter  50 value 81.530321
iter  60 value 80.844185
iter  70 value 80.553170
iter  80 value 80.441614
iter  90 value 80.418795
iter 100 value 80.366445
final  value 80.366445 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.052641 
iter  10 value 93.920158
iter  20 value 85.888962
iter  30 value 84.334673
iter  40 value 83.589786
iter  50 value 83.386354
iter  60 value 82.458102
iter  70 value 81.849173
iter  80 value 81.015484
iter  90 value 80.259431
iter 100 value 79.839026
final  value 79.839026 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 115.764021 
iter  10 value 94.508759
iter  20 value 93.626214
iter  30 value 92.533675
iter  40 value 83.902764
iter  50 value 82.325868
iter  60 value 80.880081
iter  70 value 80.070905
iter  80 value 79.916726
iter  90 value 79.777706
iter 100 value 79.635937
final  value 79.635937 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 122.576930 
iter  10 value 94.847375
iter  20 value 87.947842
iter  30 value 84.675402
iter  40 value 83.554948
iter  50 value 83.294673
iter  60 value 82.854305
iter  70 value 81.723544
iter  80 value 81.243102
iter  90 value 81.057107
iter 100 value 80.811319
final  value 80.811319 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.406360 
iter  10 value 94.439795
iter  20 value 89.033180
iter  30 value 86.816805
iter  40 value 86.187398
iter  50 value 85.334435
iter  60 value 83.008227
iter  70 value 81.364750
iter  80 value 81.079875
iter  90 value 80.673763
iter 100 value 80.186243
final  value 80.186243 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.302844 
final  value 94.485836 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.982252 
final  value 94.485911 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.239953 
final  value 94.355918 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.207497 
final  value 94.486319 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.074735 
final  value 94.485990 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.089567 
iter  10 value 94.488736
iter  20 value 94.484252
final  value 94.484242 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.470914 
iter  10 value 93.815118
iter  20 value 89.871447
iter  30 value 88.148412
iter  40 value 88.021560
iter  50 value 87.931053
final  value 87.907499 
converged
Fitting Repeat 3 

# weights:  305
initial  value 112.077984 
iter  10 value 94.359236
iter  20 value 94.356119
iter  30 value 94.354571
final  value 94.354562 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.865777 
iter  10 value 94.489088
iter  20 value 93.814662
iter  30 value 93.312703
iter  40 value 93.308947
iter  50 value 84.075908
iter  60 value 83.455332
iter  70 value 83.450708
iter  80 value 82.019478
iter  90 value 81.543750
iter 100 value 81.330772
final  value 81.330772 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.028950 
iter  10 value 94.097833
iter  20 value 93.814678
iter  30 value 93.700738
iter  40 value 93.643856
final  value 93.643854 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.641037 
iter  10 value 93.709968
iter  20 value 93.628190
iter  30 value 91.220188
iter  40 value 83.282625
iter  50 value 82.917299
iter  60 value 82.827772
final  value 82.827443 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.431715 
iter  10 value 94.492291
iter  20 value 94.484212
iter  30 value 93.921210
iter  40 value 93.595444
final  value 93.590832 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.169086 
iter  10 value 94.316424
iter  20 value 94.289920
iter  30 value 84.349472
iter  40 value 81.535381
iter  50 value 81.527839
iter  60 value 81.466239
iter  70 value 81.164236
iter  80 value 79.648559
iter  90 value 79.383549
iter 100 value 79.351754
final  value 79.351754 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 95.176016 
iter  10 value 94.492602
iter  20 value 93.665307
iter  30 value 87.571378
iter  40 value 82.900149
iter  50 value 82.767191
iter  60 value 82.722435
iter  70 value 82.721785
iter  80 value 82.720900
final  value 82.720895 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.387901 
iter  10 value 93.070966
iter  20 value 87.394184
iter  30 value 85.644765
iter  40 value 85.641459
iter  50 value 85.640492
final  value 85.640467 
converged
Fitting Repeat 1 

# weights:  103
initial  value 107.978959 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.524742 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.832820 
final  value 93.671508 
converged
Fitting Repeat 4 

# weights:  103
initial  value 114.032171 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.851874 
iter  10 value 90.527847
iter  20 value 85.621384
iter  30 value 84.747505
final  value 84.747127 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.817665 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.997263 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.080735 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 112.468790 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.709858 
final  value 93.551913 
converged
Fitting Repeat 1 

# weights:  507
initial  value 111.764452 
iter  10 value 93.606492
iter  20 value 93.590871
final  value 93.590851 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.468247 
iter  10 value 93.314188
final  value 93.309302 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.821747 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.878399 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.844117 
final  value 93.722222 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.860740 
iter  10 value 93.639745
iter  20 value 85.937480
iter  30 value 85.109992
iter  40 value 83.399797
iter  50 value 83.340191
iter  60 value 82.917143
iter  70 value 82.386562
iter  80 value 82.279735
final  value 82.276922 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.193956 
iter  10 value 94.056691
iter  20 value 89.176205
iter  30 value 85.247623
iter  40 value 82.743274
iter  50 value 82.443506
iter  60 value 82.168413
iter  70 value 81.951140
iter  80 value 81.912176
final  value 81.911852 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.798707 
iter  10 value 93.638332
iter  20 value 85.226975
iter  30 value 82.408747
iter  40 value 81.702562
iter  50 value 81.514165
iter  60 value 81.464564
iter  70 value 81.297698
iter  80 value 80.953002
iter  90 value 80.411361
iter 100 value 80.363613
final  value 80.363613 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 100.740793 
iter  10 value 93.862315
iter  20 value 87.642104
iter  30 value 83.557425
iter  40 value 82.956204
iter  50 value 82.503679
iter  60 value 82.321913
iter  70 value 81.148404
iter  80 value 80.693909
iter  90 value 80.673067
iter 100 value 80.631958
final  value 80.631958 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 116.846397 
iter  10 value 93.715237
iter  20 value 85.168599
iter  30 value 83.126009
iter  40 value 82.677876
iter  50 value 82.497082
iter  60 value 82.290612
iter  70 value 82.276923
final  value 82.276922 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.099908 
iter  10 value 94.059232
iter  20 value 91.281484
iter  30 value 86.237044
iter  40 value 83.224296
iter  50 value 82.990115
iter  60 value 82.456252
iter  70 value 82.153761
iter  80 value 81.965129
iter  90 value 81.864072
iter 100 value 81.420958
final  value 81.420958 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.979476 
iter  10 value 95.130660
iter  20 value 91.339683
iter  30 value 85.384055
iter  40 value 84.347654
iter  50 value 83.005512
iter  60 value 82.100917
iter  70 value 81.552125
iter  80 value 79.881219
iter  90 value 79.400199
iter 100 value 79.065075
final  value 79.065075 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.496999 
iter  10 value 93.252559
iter  20 value 82.973288
iter  30 value 81.494810
iter  40 value 81.251886
iter  50 value 80.695216
iter  60 value 79.657509
iter  70 value 79.304670
iter  80 value 78.936316
iter  90 value 78.840751
iter 100 value 78.812452
final  value 78.812452 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 112.475894 
iter  10 value 96.341234
iter  20 value 94.408812
iter  30 value 94.012914
iter  40 value 87.304982
iter  50 value 86.160512
iter  60 value 85.294447
iter  70 value 82.443391
iter  80 value 81.437677
iter  90 value 80.946279
iter 100 value 80.774682
final  value 80.774682 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.525665 
iter  10 value 94.184647
iter  20 value 93.050550
iter  30 value 90.285733
iter  40 value 84.668365
iter  50 value 83.887543
iter  60 value 83.721082
iter  70 value 83.186855
iter  80 value 82.418774
iter  90 value 82.182940
iter 100 value 81.920535
final  value 81.920535 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.232062 
iter  10 value 94.018855
iter  20 value 85.071617
iter  30 value 83.915060
iter  40 value 83.437642
iter  50 value 82.297011
iter  60 value 80.125531
iter  70 value 79.876000
iter  80 value 79.757517
iter  90 value 79.518312
iter 100 value 79.294230
final  value 79.294230 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 145.007031 
iter  10 value 97.321498
iter  20 value 90.371766
iter  30 value 84.732234
iter  40 value 83.487002
iter  50 value 82.098663
iter  60 value 80.583828
iter  70 value 79.707086
iter  80 value 79.426760
iter  90 value 78.892972
iter 100 value 78.778963
final  value 78.778963 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.204433 
iter  10 value 95.750545
iter  20 value 95.253313
iter  30 value 86.538988
iter  40 value 84.695493
iter  50 value 82.906545
iter  60 value 81.725601
iter  70 value 80.548697
iter  80 value 80.385961
iter  90 value 80.271729
iter 100 value 80.269167
final  value 80.269167 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.957358 
iter  10 value 93.906291
iter  20 value 92.207912
iter  30 value 86.877087
iter  40 value 84.820874
iter  50 value 84.417610
iter  60 value 83.600135
iter  70 value 82.033036
iter  80 value 81.483460
iter  90 value 79.960084
iter 100 value 79.430393
final  value 79.430393 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 118.213897 
iter  10 value 94.399805
iter  20 value 85.483443
iter  30 value 84.155167
iter  40 value 83.762965
iter  50 value 82.548797
iter  60 value 81.455259
iter  70 value 80.607010
iter  80 value 79.790029
iter  90 value 79.537536
iter 100 value 79.268746
final  value 79.268746 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.946706 
iter  10 value 94.054340
iter  20 value 94.052948
final  value 94.052915 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.227807 
final  value 94.044872 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.189798 
final  value 94.054441 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.183399 
final  value 94.054439 
converged
Fitting Repeat 5 

# weights:  103
initial  value 108.342104 
final  value 94.054493 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.786928 
iter  10 value 94.058109
iter  20 value 94.031718
iter  30 value 92.463562
iter  40 value 86.878541
iter  50 value 83.142069
iter  60 value 80.769386
iter  70 value 79.979596
iter  80 value 79.961095
iter  90 value 79.892309
iter 100 value 79.522848
final  value 79.522848 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.778683 
iter  10 value 93.556851
iter  20 value 93.552423
iter  30 value 89.115023
iter  40 value 85.021564
iter  50 value 84.108037
iter  60 value 82.566406
iter  70 value 82.522743
final  value 82.522638 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.468593 
iter  10 value 85.507766
iter  20 value 84.735422
iter  30 value 84.686337
iter  40 value 83.810219
iter  50 value 83.487869
iter  60 value 83.487083
final  value 83.484182 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.390118 
iter  10 value 93.547844
iter  20 value 93.498087
iter  30 value 93.495756
iter  40 value 92.801024
iter  50 value 90.121579
iter  60 value 90.087456
iter  70 value 90.086743
iter  80 value 90.086520
iter  90 value 89.485186
iter 100 value 89.039407
final  value 89.039407 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.051876 
iter  10 value 93.740856
iter  20 value 92.772955
iter  30 value 92.770073
iter  40 value 92.177171
iter  50 value 92.110563
iter  60 value 92.087043
iter  70 value 92.061767
iter  80 value 92.059976
iter  90 value 91.095885
final  value 91.095786 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.487269 
iter  10 value 93.685092
iter  20 value 86.896957
iter  30 value 86.688745
iter  40 value 85.174462
iter  50 value 83.762471
iter  60 value 83.740387
iter  70 value 83.737542
iter  80 value 83.673585
iter  90 value 83.364665
iter 100 value 81.976880
final  value 81.976880 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.798315 
iter  10 value 93.335233
iter  20 value 93.330694
iter  30 value 85.274979
iter  40 value 82.659922
iter  50 value 79.942696
iter  60 value 79.419159
iter  70 value 78.709116
iter  80 value 78.397946
iter  90 value 78.206669
iter 100 value 78.001059
final  value 78.001059 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 97.468134 
iter  10 value 84.557806
iter  20 value 82.543892
iter  30 value 82.186363
iter  40 value 82.141871
iter  50 value 81.470966
iter  60 value 81.371858
iter  70 value 81.270363
iter  80 value 81.268597
iter  90 value 81.266930
final  value 81.266096 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.961945 
iter  10 value 94.051258
iter  20 value 94.043559
iter  30 value 92.930193
iter  40 value 84.882510
iter  50 value 84.879729
iter  60 value 84.879249
iter  70 value 81.474081
iter  80 value 81.180375
iter  80 value 81.180375
final  value 81.180375 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.343893 
iter  10 value 84.771158
iter  20 value 84.763074
iter  30 value 84.067349
iter  40 value 83.889492
iter  50 value 82.793667
iter  60 value 82.244043
iter  70 value 82.200954
iter  80 value 82.111689
iter  90 value 79.705835
iter 100 value 79.687014
final  value 79.687014 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 124.032709 
iter  10 value 117.897411
iter  20 value 117.828399
iter  30 value 108.394686
iter  40 value 106.557218
iter  50 value 106.552812
iter  60 value 106.533815
iter  70 value 106.524182
iter  80 value 106.523042
iter  90 value 106.518729
iter 100 value 106.518045
final  value 106.518045 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 123.321294 
iter  10 value 115.151256
iter  20 value 114.205184
iter  30 value 112.773675
iter  40 value 112.640118
iter  50 value 111.592047
iter  60 value 111.462024
iter  70 value 111.452188
iter  80 value 111.306345
iter  90 value 108.211519
iter 100 value 105.516109
final  value 105.516109 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 154.868601 
iter  10 value 117.901115
iter  20 value 117.819486
iter  30 value 110.190279
iter  40 value 105.670155
iter  50 value 104.814104
iter  60 value 104.813320
iter  70 value 104.719522
final  value 104.689521 
converged
Fitting Repeat 4 

# weights:  507
initial  value 119.972547 
iter  10 value 117.557815
iter  20 value 109.509941
iter  30 value 109.488812
final  value 109.488111 
converged
Fitting Repeat 5 

# weights:  507
initial  value 119.566015 
iter  10 value 110.673539
iter  20 value 107.966485
iter  30 value 107.062452
iter  40 value 106.959692
iter  50 value 106.945852
iter  60 value 106.941450
iter  70 value 106.937018
iter  80 value 105.107819
iter  90 value 104.343322
iter 100 value 104.304189
final  value 104.304189 
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 -- Sat Nov  9 04:48:46 2024 
*********************************************** 
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 
 15.441   0.506  25.256