##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.19-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.19-bioc/R/site-library --timings HPiP_1.10.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck’
* using R version 4.4.1 (2024-06-14)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
    GNU Fortran (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
* running under: Ubuntu 22.04.5 LTS
* using session charset: UTF-8
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.10.0’
* 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 ... NOTE
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
var_imp       35.459  1.036  36.496
FSmethod      34.335  0.808  35.145
corr_plot     33.998  0.456  34.455
pred_ensembel 14.102  0.719  11.117
enrichfindP    0.488  0.029  10.238
* 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: 3 NOTEs
See
  ‘/home/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.19-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.19-bioc/R/site-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: 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 101.296530 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.871564 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.062683 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.584673 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.577449 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.625796 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.587275 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.015790 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 108.133883 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  305
initial  value 110.718961 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.507267 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 120.694655 
iter  10 value 93.395503
final  value 93.281385 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.423250 
iter  10 value 94.399715
final  value 94.395066 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.091192 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.592167 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  103
initial  value 111.523541 
iter  10 value 94.416416
iter  20 value 87.625828
iter  30 value 81.142516
iter  40 value 80.401798
iter  50 value 79.863978
iter  60 value 79.674105
iter  70 value 79.455328
iter  80 value 79.401652
final  value 79.401649 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.081188 
iter  10 value 95.326050
iter  20 value 94.493758
iter  30 value 94.355645
iter  40 value 88.847815
iter  50 value 86.028940
iter  60 value 83.260925
iter  70 value 81.232117
iter  80 value 80.220478
iter  90 value 79.635379
iter 100 value 79.403342
final  value 79.403342 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.779278 
iter  10 value 94.458841
iter  20 value 84.749220
iter  30 value 82.305370
iter  40 value 81.792578
iter  50 value 81.425459
iter  60 value 81.288116
iter  70 value 81.214797
final  value 81.206619 
converged
Fitting Repeat 4 

# weights:  103
initial  value 112.599421 
iter  10 value 94.267588
iter  20 value 84.191168
iter  30 value 82.783154
iter  40 value 81.284726
iter  50 value 80.580162
iter  60 value 79.438718
iter  70 value 79.380498
final  value 79.380495 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.757007 
iter  10 value 94.486474
iter  20 value 94.339180
iter  30 value 83.020414
iter  40 value 81.366918
iter  50 value 80.333197
iter  60 value 79.976095
iter  70 value 79.415057
iter  80 value 77.887504
iter  90 value 77.654056
iter 100 value 77.512190
final  value 77.512190 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 110.456633 
iter  10 value 94.557287
iter  20 value 88.154522
iter  30 value 87.820188
iter  40 value 85.517416
iter  50 value 80.508283
iter  60 value 78.349251
iter  70 value 77.242546
iter  80 value 77.122662
iter  90 value 77.062334
iter 100 value 76.969160
final  value 76.969160 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.711123 
iter  10 value 95.259639
iter  20 value 94.431045
iter  30 value 88.059398
iter  40 value 87.383208
iter  50 value 84.652553
iter  60 value 81.624558
iter  70 value 80.708795
iter  80 value 79.937537
iter  90 value 78.187995
iter 100 value 77.206747
final  value 77.206747 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 110.423626 
iter  10 value 94.511784
iter  20 value 94.387502
iter  30 value 88.050580
iter  40 value 80.570496
iter  50 value 79.868140
iter  60 value 79.384310
iter  70 value 79.191195
iter  80 value 79.125437
iter  90 value 78.464800
iter 100 value 77.643191
final  value 77.643191 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.842306 
iter  10 value 94.479462
iter  20 value 86.610731
iter  30 value 83.396370
iter  40 value 81.625272
iter  50 value 79.907089
iter  60 value 78.000627
iter  70 value 77.519826
iter  80 value 76.967724
iter  90 value 76.562141
iter 100 value 76.350611
final  value 76.350611 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.673372 
iter  10 value 90.647955
iter  20 value 83.935573
iter  30 value 81.101200
iter  40 value 78.976610
iter  50 value 78.364561
iter  60 value 77.902507
iter  70 value 77.611306
iter  80 value 77.255919
iter  90 value 76.893908
iter 100 value 76.816981
final  value 76.816981 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.156542 
iter  10 value 94.622107
iter  20 value 86.600275
iter  30 value 84.953255
iter  40 value 84.689171
iter  50 value 80.948021
iter  60 value 80.626686
iter  70 value 79.831792
iter  80 value 78.118162
iter  90 value 77.292441
iter 100 value 76.410759
final  value 76.410759 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.300500 
iter  10 value 95.260090
iter  20 value 90.251441
iter  30 value 83.106080
iter  40 value 80.784937
iter  50 value 80.491303
iter  60 value 80.090177
iter  70 value 79.613242
iter  80 value 77.195777
iter  90 value 76.499942
iter 100 value 76.205819
final  value 76.205819 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.530623 
iter  10 value 94.855655
iter  20 value 84.053899
iter  30 value 82.253672
iter  40 value 80.350734
iter  50 value 77.426696
iter  60 value 76.596123
iter  70 value 76.312298
iter  80 value 76.252508
iter  90 value 76.194542
iter 100 value 76.038975
final  value 76.038975 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 129.406483 
iter  10 value 94.011991
iter  20 value 83.928760
iter  30 value 83.034844
iter  40 value 80.492435
iter  50 value 79.112078
iter  60 value 77.687844
iter  70 value 76.867128
iter  80 value 76.457957
iter  90 value 76.408218
iter 100 value 76.345699
final  value 76.345699 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.527043 
iter  10 value 94.490016
iter  20 value 94.327389
iter  30 value 93.972278
iter  40 value 86.242012
iter  50 value 83.390613
iter  60 value 82.524874
iter  70 value 78.567361
iter  80 value 77.205421
iter  90 value 76.301506
iter 100 value 76.105588
final  value 76.105588 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.151342 
iter  10 value 94.486056
iter  20 value 94.465666
iter  30 value 90.317454
iter  40 value 89.685931
iter  50 value 89.685516
final  value 89.685507 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.489395 
final  value 94.485754 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.937461 
final  value 94.486054 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.770016 
iter  10 value 94.485943
final  value 94.484237 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.728686 
final  value 94.485908 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.941561 
iter  10 value 94.488925
iter  20 value 94.471647
iter  30 value 83.544844
iter  40 value 78.782075
iter  50 value 78.513664
iter  60 value 78.379114
iter  70 value 78.166245
iter  80 value 77.819234
iter  90 value 77.657444
iter 100 value 77.629281
final  value 77.629281 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 96.199401 
iter  10 value 94.486368
iter  20 value 91.373680
iter  30 value 90.979930
iter  40 value 90.979413
final  value 90.979278 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.537127 
iter  10 value 94.515695
iter  20 value 94.509291
iter  30 value 93.291972
iter  40 value 91.831938
iter  50 value 91.470609
iter  60 value 91.206002
iter  70 value 90.939640
iter  80 value 90.933447
iter  90 value 89.974692
iter 100 value 83.061963
final  value 83.061963 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 95.999038 
iter  10 value 94.471734
iter  20 value 94.467512
iter  30 value 93.403011
iter  40 value 80.852578
iter  50 value 80.791016
iter  60 value 79.342616
iter  70 value 77.058487
iter  80 value 75.923673
iter  90 value 75.696770
iter 100 value 75.692988
final  value 75.692988 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.161575 
iter  10 value 94.488916
iter  20 value 94.323031
iter  30 value 87.697505
iter  40 value 87.666394
final  value 87.663717 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.510568 
iter  10 value 94.492425
iter  20 value 94.485379
iter  30 value 89.088345
iter  40 value 81.426423
iter  50 value 80.840777
final  value 80.840702 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.345788 
iter  10 value 85.171351
iter  20 value 85.167399
iter  30 value 85.001200
iter  40 value 85.000646
iter  50 value 83.238472
iter  60 value 83.187419
iter  70 value 83.186430
iter  80 value 83.184446
iter  90 value 83.106604
iter 100 value 83.096999
final  value 83.096999 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 97.648433 
iter  10 value 84.274878
iter  20 value 83.004490
final  value 83.003932 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.210726 
iter  10 value 94.491845
iter  20 value 86.673908
iter  30 value 81.057599
iter  40 value 80.594667
iter  50 value 80.562616
iter  60 value 80.360217
iter  70 value 80.132632
iter  80 value 76.224006
iter  90 value 75.402453
iter 100 value 75.388463
final  value 75.388463 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.165910 
iter  10 value 94.475141
iter  20 value 94.452144
iter  30 value 86.365113
iter  40 value 85.897573
final  value 85.897526 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.932506 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.865385 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.779789 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.363328 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.103541 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.437553 
final  value 94.057229 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.788317 
final  value 94.443243 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.953574 
iter  10 value 93.625648
iter  20 value 87.305370
iter  30 value 86.830562
iter  40 value 86.827228
iter  50 value 86.826178
final  value 86.826175 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.712069 
iter  10 value 92.997053
iter  20 value 89.474451
iter  30 value 89.411810
final  value 89.411765 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.987840 
final  value 94.443243 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.510161 
final  value 94.443243 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.674796 
iter  10 value 94.057230
final  value 94.057229 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.779601 
iter  10 value 94.478292
iter  10 value 94.478291
iter  10 value 94.478291
final  value 94.478291 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.122768 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 112.200485 
iter  10 value 93.984085
final  value 93.984053 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.506056 
iter  10 value 94.081166
iter  20 value 85.885221
iter  30 value 85.743104
iter  40 value 85.617895
iter  50 value 85.608217
final  value 85.608096 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.227178 
iter  10 value 94.505568
iter  20 value 94.483020
iter  30 value 90.288430
iter  40 value 88.997385
iter  50 value 87.272198
iter  60 value 86.679051
iter  70 value 86.655316
final  value 86.655216 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.807040 
iter  10 value 94.486613
iter  20 value 94.187741
iter  30 value 89.816779
iter  40 value 88.548896
iter  50 value 84.799930
iter  60 value 83.828781
iter  70 value 83.666250
iter  80 value 83.405005
iter  90 value 83.249052
iter 100 value 83.186260
final  value 83.186260 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 101.675507 
iter  10 value 94.422722
iter  20 value 88.287171
iter  30 value 86.135246
iter  40 value 85.929871
iter  50 value 85.714687
iter  60 value 85.638595
iter  70 value 85.608104
final  value 85.608088 
converged
Fitting Repeat 5 

# weights:  103
initial  value 107.471815 
iter  10 value 94.482729
iter  20 value 94.102427
iter  30 value 93.928760
iter  40 value 93.202617
iter  50 value 88.062965
iter  60 value 86.359515
iter  70 value 85.740620
iter  80 value 85.638027
iter  90 value 85.608404
final  value 85.608088 
converged
Fitting Repeat 1 

# weights:  305
initial  value 118.213231 
iter  10 value 94.510825
iter  20 value 90.861818
iter  30 value 87.516952
iter  40 value 86.079442
iter  50 value 85.522107
iter  60 value 83.859420
iter  70 value 83.283684
iter  80 value 83.100847
iter  90 value 82.954125
iter 100 value 82.637168
final  value 82.637168 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.474756 
iter  10 value 94.586156
iter  20 value 88.165146
iter  30 value 88.017716
iter  40 value 87.691008
iter  50 value 86.320015
iter  60 value 84.380791
iter  70 value 83.291043
iter  80 value 83.119915
iter  90 value 82.890424
iter 100 value 82.675990
final  value 82.675990 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.633985 
iter  10 value 94.500320
iter  20 value 93.003056
iter  30 value 84.620815
iter  40 value 83.363473
iter  50 value 82.964143
iter  60 value 82.736214
iter  70 value 82.580905
iter  80 value 82.534504
iter  90 value 82.409472
iter 100 value 82.270573
final  value 82.270573 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.609348 
iter  10 value 94.605549
iter  20 value 94.498167
iter  30 value 89.386326
iter  40 value 86.533835
iter  50 value 86.140900
iter  60 value 84.222585
iter  70 value 83.818392
iter  80 value 83.604072
iter  90 value 83.469944
iter 100 value 83.244543
final  value 83.244543 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.023220 
iter  10 value 91.084189
iter  20 value 86.603770
iter  30 value 85.871023
iter  40 value 85.665780
iter  50 value 84.602410
iter  60 value 84.153485
iter  70 value 84.038509
iter  80 value 83.744546
iter  90 value 82.755251
iter 100 value 82.310638
final  value 82.310638 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.642099 
iter  10 value 96.148653
iter  20 value 88.415509
iter  30 value 87.803136
iter  40 value 86.568190
iter  50 value 84.911830
iter  60 value 84.541285
iter  70 value 84.021059
iter  80 value 83.094027
iter  90 value 82.582987
iter 100 value 82.253121
final  value 82.253121 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 124.509373 
iter  10 value 94.771909
iter  20 value 89.076084
iter  30 value 86.472744
iter  40 value 84.573824
iter  50 value 83.983691
iter  60 value 83.703198
iter  70 value 83.452247
iter  80 value 83.402820
iter  90 value 83.348119
iter 100 value 83.064583
final  value 83.064583 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.607091 
iter  10 value 94.620074
iter  20 value 94.397094
iter  30 value 92.544547
iter  40 value 90.646747
iter  50 value 88.083011
iter  60 value 87.811135
iter  70 value 85.557755
iter  80 value 84.353144
iter  90 value 83.681122
iter 100 value 82.862661
final  value 82.862661 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 117.514378 
iter  10 value 94.999154
iter  20 value 92.341001
iter  30 value 88.802410
iter  40 value 87.602006
iter  50 value 87.196468
iter  60 value 85.628432
iter  70 value 85.247331
iter  80 value 83.427042
iter  90 value 82.645086
iter 100 value 82.113105
final  value 82.113105 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 128.350384 
iter  10 value 94.357602
iter  20 value 88.666240
iter  30 value 88.030728
iter  40 value 87.549039
iter  50 value 85.580728
iter  60 value 84.039682
iter  70 value 82.031816
iter  80 value 81.646369
iter  90 value 81.499920
iter 100 value 81.409344
final  value 81.409344 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.295250 
final  value 94.444954 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.919434 
final  value 94.485946 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.044150 
iter  10 value 90.400241
iter  20 value 90.119583
iter  30 value 90.058463
final  value 90.058460 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.233751 
final  value 94.485727 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.767631 
final  value 94.485665 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.787720 
iter  10 value 94.488300
iter  20 value 94.481071
iter  30 value 87.389673
iter  40 value 87.372379
iter  50 value 87.319577
iter  60 value 86.506799
iter  70 value 86.401193
iter  80 value 86.388609
iter  90 value 84.812808
iter 100 value 83.768974
final  value 83.768974 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 97.811104 
iter  10 value 94.488070
final  value 94.484279 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.569325 
iter  10 value 94.488913
iter  20 value 94.480506
iter  30 value 93.716174
iter  40 value 93.568201
iter  50 value 93.191249
iter  60 value 93.107643
iter  70 value 91.582415
iter  80 value 91.386811
iter  90 value 91.283733
iter 100 value 91.283197
final  value 91.283197 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 96.760404 
iter  10 value 94.448254
iter  20 value 87.178471
iter  30 value 86.636352
final  value 86.505371 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.736708 
iter  10 value 94.119211
iter  20 value 93.568297
iter  30 value 84.715198
iter  40 value 84.170226
final  value 84.114422 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.833010 
iter  10 value 94.494435
iter  20 value 94.486827
iter  30 value 86.189139
iter  40 value 83.373444
iter  50 value 83.369354
iter  60 value 83.302595
iter  70 value 82.474706
iter  80 value 82.409339
iter  90 value 82.408644
final  value 82.407615 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.724629 
iter  10 value 94.271422
iter  20 value 94.185542
iter  30 value 94.079834
iter  40 value 94.078270
final  value 94.077805 
converged
Fitting Repeat 3 

# weights:  507
initial  value 122.235471 
iter  10 value 94.491641
iter  20 value 94.481852
iter  30 value 87.678627
iter  40 value 87.317019
iter  50 value 87.289819
iter  60 value 87.286099
iter  70 value 87.157359
iter  80 value 86.560798
iter  90 value 83.157661
iter 100 value 82.303911
final  value 82.303911 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.885270 
iter  10 value 94.491889
iter  20 value 93.653087
iter  30 value 88.397823
iter  40 value 88.007132
iter  50 value 87.765016
iter  60 value 85.595428
iter  70 value 84.027919
iter  80 value 83.886657
iter  90 value 83.259294
iter 100 value 82.526119
final  value 82.526119 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.048131 
iter  10 value 94.236252
iter  20 value 94.233001
iter  30 value 91.352371
iter  40 value 88.353760
iter  50 value 87.629431
iter  60 value 87.275396
iter  70 value 87.101549
iter  80 value 86.719270
final  value 86.719165 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.263243 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.558227 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.679651 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.305809 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.411714 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.052340 
iter  10 value 94.053050
final  value 94.052874 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.058738 
final  value 93.582418 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.888862 
iter  10 value 93.582418
iter  10 value 93.582417
iter  10 value 93.582417
final  value 93.582417 
converged
Fitting Repeat 4 

# weights:  305
initial  value 109.516891 
final  value 93.582418 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.680487 
iter  10 value 88.075673
iter  20 value 88.016499
final  value 88.016394 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.580558 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.934247 
final  value 94.025289 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.849623 
final  value 93.469994 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.738766 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 112.823051 
iter  10 value 94.025831
final  value 94.025290 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.942740 
iter  10 value 90.011203
iter  20 value 86.827826
iter  30 value 86.186280
iter  40 value 85.866521
iter  50 value 83.033182
iter  60 value 82.802209
iter  70 value 82.780318
iter  80 value 82.740726
final  value 82.740502 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.138507 
iter  10 value 94.057582
iter  20 value 93.984324
iter  30 value 93.771346
iter  40 value 89.145450
iter  50 value 88.219390
iter  60 value 88.144605
iter  70 value 87.970379
iter  80 value 86.023863
iter  90 value 85.512265
iter 100 value 83.904349
final  value 83.904349 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.826896 
iter  10 value 94.191300
iter  20 value 93.747508
iter  30 value 93.443790
iter  40 value 88.036590
iter  50 value 86.789887
iter  60 value 86.295174
iter  70 value 85.174194
iter  80 value 84.992436
iter  90 value 82.754965
final  value 82.689849 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.377776 
iter  10 value 94.041065
iter  20 value 93.691136
iter  30 value 92.994902
iter  40 value 90.745519
iter  50 value 90.142297
iter  60 value 87.686405
iter  70 value 86.892545
iter  80 value 86.630173
iter  90 value 86.052929
iter 100 value 85.853571
final  value 85.853571 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 98.178317 
iter  10 value 93.777698
iter  20 value 90.486846
iter  30 value 90.277238
iter  40 value 89.824650
iter  50 value 88.021864
iter  60 value 85.356420
iter  70 value 83.980542
iter  80 value 83.428361
iter  90 value 82.791968
iter 100 value 82.755005
final  value 82.755005 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 100.057814 
iter  10 value 94.057883
iter  20 value 93.717728
iter  30 value 93.463932
iter  40 value 88.069998
iter  50 value 87.005977
iter  60 value 85.628987
iter  70 value 83.616915
iter  80 value 83.050333
iter  90 value 82.689265
iter 100 value 82.579771
final  value 82.579771 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.771317 
iter  10 value 94.198460
iter  20 value 88.340441
iter  30 value 86.912737
iter  40 value 84.814965
iter  50 value 83.990971
iter  60 value 83.756387
iter  70 value 82.891176
iter  80 value 82.826029
iter  90 value 82.634254
iter 100 value 81.981925
final  value 81.981925 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 110.208631 
iter  10 value 94.122438
iter  20 value 93.861271
iter  30 value 90.343446
iter  40 value 88.112973
iter  50 value 86.346192
iter  60 value 86.183630
iter  70 value 85.191584
iter  80 value 83.765244
iter  90 value 82.641265
iter 100 value 82.366959
final  value 82.366959 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.615324 
iter  10 value 94.183741
iter  20 value 93.816134
iter  30 value 92.112804
iter  40 value 87.817355
iter  50 value 86.072494
iter  60 value 85.640704
iter  70 value 85.097455
iter  80 value 84.441833
iter  90 value 83.376944
iter 100 value 83.057122
final  value 83.057122 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 115.784686 
iter  10 value 92.172795
iter  20 value 88.107136
iter  30 value 86.024440
iter  40 value 85.524923
iter  50 value 83.508946
iter  60 value 82.282694
iter  70 value 82.107043
iter  80 value 81.636344
iter  90 value 81.600842
iter 100 value 81.596840
final  value 81.596840 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.487513 
iter  10 value 94.144085
iter  20 value 86.240448
iter  30 value 84.547438
iter  40 value 83.964204
iter  50 value 83.617858
iter  60 value 83.535632
iter  70 value 83.382175
iter  80 value 83.204721
iter  90 value 82.728417
iter 100 value 82.372988
final  value 82.372988 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.393062 
iter  10 value 94.025013
iter  20 value 90.230449
iter  30 value 86.305079
iter  40 value 85.173054
iter  50 value 84.120228
iter  60 value 83.626736
iter  70 value 83.269247
iter  80 value 82.623961
iter  90 value 82.500613
iter 100 value 82.486231
final  value 82.486231 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 128.717069 
iter  10 value 94.292866
iter  20 value 93.568856
iter  30 value 87.914737
iter  40 value 84.713373
iter  50 value 84.197868
iter  60 value 83.285807
iter  70 value 82.520691
iter  80 value 82.051542
iter  90 value 81.963758
iter 100 value 81.573742
final  value 81.573742 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.915771 
iter  10 value 93.934778
iter  20 value 90.984274
iter  30 value 85.985366
iter  40 value 84.744208
iter  50 value 84.115989
iter  60 value 83.346028
iter  70 value 82.734268
iter  80 value 82.158125
iter  90 value 81.572310
iter 100 value 81.296648
final  value 81.296648 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 116.536052 
iter  10 value 94.210218
iter  20 value 93.821790
iter  30 value 93.369073
iter  40 value 88.538141
iter  50 value 86.062997
iter  60 value 84.239181
iter  70 value 82.374495
iter  80 value 82.247613
iter  90 value 82.141003
iter 100 value 82.102458
final  value 82.102458 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 109.630480 
iter  10 value 93.969293
iter  20 value 93.901874
iter  30 value 93.901251
final  value 93.900064 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.741176 
iter  10 value 94.054676
iter  20 value 93.884119
iter  30 value 87.037875
final  value 86.235576 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.250429 
final  value 94.054707 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.621688 
final  value 94.054966 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.422779 
final  value 94.054457 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.157646 
iter  10 value 94.058124
iter  20 value 93.760814
iter  30 value 86.370071
iter  40 value 83.873181
iter  50 value 82.286478
iter  60 value 82.133953
iter  70 value 82.120625
iter  80 value 81.643942
iter  90 value 81.610665
iter 100 value 81.599423
final  value 81.599423 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.282545 
iter  10 value 90.964203
iter  20 value 90.299093
iter  30 value 90.239324
iter  40 value 90.235563
iter  50 value 89.971265
iter  60 value 89.962877
iter  70 value 89.887480
iter  80 value 89.882795
iter  90 value 89.841870
iter 100 value 85.253317
final  value 85.253317 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 112.479907 
iter  10 value 93.893264
iter  20 value 93.585985
iter  30 value 93.583493
iter  40 value 93.324867
iter  50 value 89.325467
iter  60 value 83.569036
iter  70 value 83.189230
iter  80 value 83.178679
iter  90 value 83.087625
iter 100 value 83.006615
final  value 83.006615 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 114.617406 
iter  10 value 92.410939
iter  20 value 91.602197
iter  30 value 91.435432
iter  40 value 91.431608
iter  50 value 91.429376
iter  60 value 91.428838
iter  70 value 91.428410
iter  80 value 91.427846
final  value 91.427596 
converged
Fitting Repeat 5 

# weights:  305
initial  value 111.859683 
iter  10 value 93.587572
iter  20 value 93.582937
final  value 93.582589 
converged
Fitting Repeat 1 

# weights:  507
initial  value 110.813176 
iter  10 value 93.938126
iter  20 value 90.864923
iter  30 value 87.506065
iter  40 value 87.276106
iter  50 value 84.952592
iter  60 value 84.888917
iter  70 value 84.576150
iter  80 value 83.836892
iter  90 value 82.378319
iter 100 value 81.028891
final  value 81.028891 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.905169 
iter  10 value 94.058621
iter  20 value 92.236019
iter  30 value 85.597014
iter  40 value 84.887803
iter  50 value 84.874914
iter  60 value 84.864529
iter  70 value 83.566262
iter  80 value 81.385881
iter  90 value 81.120189
iter 100 value 80.898307
final  value 80.898307 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 98.243154 
iter  10 value 94.057409
iter  20 value 94.018353
iter  30 value 92.110052
iter  40 value 85.248807
iter  50 value 83.158110
iter  60 value 82.997956
iter  70 value 82.997596
iter  80 value 82.995277
iter  90 value 82.779088
iter 100 value 82.320639
final  value 82.320639 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 114.380368 
iter  10 value 94.060309
iter  20 value 90.726329
iter  30 value 86.490813
iter  40 value 86.350440
iter  50 value 86.066158
iter  60 value 86.041947
iter  70 value 86.041796
final  value 86.041775 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.383800 
iter  10 value 89.821726
iter  20 value 86.188631
iter  30 value 86.082921
iter  40 value 85.921258
iter  50 value 85.879312
iter  60 value 85.870815
iter  70 value 85.737724
iter  80 value 84.359916
iter  90 value 83.381429
iter 100 value 82.246821
final  value 82.246821 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.764013 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.350153 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.988594 
iter  10 value 88.887471
iter  20 value 88.058534
iter  30 value 87.296322
iter  40 value 87.110556
iter  50 value 87.100337
iter  60 value 87.100206
final  value 87.100187 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.585475 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.510356 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.073314 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 108.548738 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.469917 
iter  10 value 93.640394
final  value 93.640336 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.574956 
iter  10 value 93.915746
iter  10 value 93.915746
iter  10 value 93.915746
final  value 93.915746 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.561429 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.949395 
final  value 93.915746 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.324575 
final  value 93.371808 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.133705 
iter  10 value 93.901059
iter  20 value 93.900545
final  value 93.900539 
converged
Fitting Repeat 4 

# weights:  507
initial  value 111.174261 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.880974 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.506947 
iter  10 value 94.063256
iter  20 value 93.866102
iter  30 value 93.589151
iter  40 value 93.579432
iter  50 value 86.071891
iter  60 value 85.854742
iter  70 value 85.503166
iter  80 value 84.439238
iter  90 value 84.091461
iter 100 value 84.032452
final  value 84.032452 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.572894 
iter  10 value 89.225299
iter  20 value 86.675303
iter  30 value 85.947312
iter  40 value 85.362595
iter  50 value 85.232550
final  value 85.232075 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.629054 
iter  10 value 94.056637
iter  20 value 93.938120
iter  30 value 93.586871
iter  40 value 93.580516
iter  50 value 87.059362
iter  60 value 85.599478
iter  70 value 84.885846
iter  80 value 83.823580
iter  90 value 83.776871
iter 100 value 83.732032
final  value 83.732032 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 103.652885 
iter  10 value 90.640680
iter  20 value 88.270439
iter  30 value 87.036435
iter  40 value 86.177775
iter  50 value 85.975914
iter  60 value 85.761226
iter  70 value 85.363706
iter  80 value 85.331193
final  value 85.331190 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.039035 
iter  10 value 94.044211
iter  20 value 93.581352
iter  30 value 93.579608
iter  40 value 93.579495
iter  50 value 88.553732
iter  60 value 88.100587
iter  70 value 87.865598
iter  80 value 85.414396
iter  90 value 85.332303
iter 100 value 85.331248
final  value 85.331248 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 100.639516 
iter  10 value 93.807727
iter  20 value 87.941746
iter  30 value 84.548316
iter  40 value 84.245732
iter  50 value 84.171218
iter  60 value 84.099982
iter  70 value 83.959995
iter  80 value 83.878176
iter  90 value 83.685267
iter 100 value 83.486223
final  value 83.486223 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.166248 
iter  10 value 94.034275
iter  20 value 93.854796
iter  30 value 93.605798
iter  40 value 93.580521
iter  50 value 93.080664
iter  60 value 89.097235
iter  70 value 87.480166
iter  80 value 85.506332
iter  90 value 85.008253
iter 100 value 84.616110
final  value 84.616110 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 119.175815 
iter  10 value 93.988025
iter  20 value 87.097278
iter  30 value 86.137903
iter  40 value 85.619834
iter  50 value 85.507530
iter  60 value 85.094547
iter  70 value 84.220294
iter  80 value 83.526996
iter  90 value 82.600392
iter 100 value 82.177454
final  value 82.177454 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 118.205256 
iter  10 value 94.067235
iter  20 value 93.619601
iter  30 value 87.989528
iter  40 value 86.233574
iter  50 value 85.679731
iter  60 value 85.324768
iter  70 value 84.859615
iter  80 value 84.301215
iter  90 value 83.169701
iter 100 value 82.699617
final  value 82.699617 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.208901 
iter  10 value 94.086498
iter  20 value 94.048825
iter  30 value 86.650846
iter  40 value 85.751462
iter  50 value 85.568158
iter  60 value 84.680195
iter  70 value 83.040698
iter  80 value 82.460352
iter  90 value 82.264845
iter 100 value 82.184271
final  value 82.184271 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 121.322475 
iter  10 value 93.679706
iter  20 value 87.211301
iter  30 value 86.272849
iter  40 value 85.527207
iter  50 value 85.404749
iter  60 value 85.304519
iter  70 value 85.026066
iter  80 value 84.446335
iter  90 value 84.267218
iter 100 value 83.643013
final  value 83.643013 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.412782 
iter  10 value 94.409562
iter  20 value 93.550323
iter  30 value 90.689235
iter  40 value 85.658608
iter  50 value 84.976752
iter  60 value 83.648139
iter  70 value 83.248366
iter  80 value 82.588614
iter  90 value 82.368074
iter 100 value 82.315159
final  value 82.315159 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.043163 
iter  10 value 96.583352
iter  20 value 87.757845
iter  30 value 85.113942
iter  40 value 83.572210
iter  50 value 83.372627
iter  60 value 82.991175
iter  70 value 82.444351
iter  80 value 82.122728
iter  90 value 81.941772
iter 100 value 81.747157
final  value 81.747157 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 117.911064 
iter  10 value 93.343008
iter  20 value 92.223507
iter  30 value 86.657249
iter  40 value 85.203632
iter  50 value 85.149117
iter  60 value 84.687282
iter  70 value 84.389965
iter  80 value 84.366519
iter  90 value 84.340827
iter 100 value 84.305472
final  value 84.305472 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 132.030515 
iter  10 value 94.067607
iter  20 value 87.623802
iter  30 value 85.852670
iter  40 value 85.148428
iter  50 value 83.926341
iter  60 value 82.726243
iter  70 value 82.250960
iter  80 value 81.924551
iter  90 value 81.865201
iter 100 value 81.854728
final  value 81.854728 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.186906 
final  value 94.054431 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.956657 
final  value 94.054371 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.630508 
iter  10 value 91.178095
iter  20 value 86.036717
iter  30 value 86.036351
iter  40 value 85.932742
iter  40 value 85.932741
iter  40 value 85.932741
final  value 85.932741 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.136581 
final  value 94.054478 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.037888 
final  value 93.917777 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.188817 
iter  10 value 94.058106
iter  20 value 93.530945
iter  30 value 87.618526
iter  40 value 87.618229
iter  50 value 87.443614
iter  60 value 85.445143
iter  70 value 83.733479
iter  80 value 83.370513
iter  90 value 83.342572
iter 100 value 83.330626
final  value 83.330626 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 127.672079 
iter  10 value 94.058162
iter  20 value 94.053218
iter  30 value 93.479339
iter  40 value 92.967200
final  value 92.954565 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.179751 
iter  10 value 90.729335
iter  20 value 87.656653
iter  30 value 87.614306
iter  40 value 87.551485
final  value 87.551414 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.808377 
iter  10 value 93.920477
iter  20 value 93.313307
iter  30 value 93.189073
iter  40 value 91.076255
iter  50 value 86.491966
iter  60 value 85.905992
iter  70 value 85.278310
iter  80 value 84.797852
iter  90 value 83.046441
iter 100 value 82.446249
final  value 82.446249 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 122.255850 
iter  10 value 93.928324
iter  20 value 93.923376
iter  30 value 93.922838
iter  40 value 93.921278
iter  50 value 93.539668
iter  60 value 93.537586
iter  70 value 93.534809
iter  80 value 93.532389
iter  90 value 93.531972
final  value 93.531927 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.522110 
iter  10 value 94.061514
iter  20 value 94.052363
iter  30 value 86.993832
iter  40 value 84.158481
iter  50 value 83.886918
iter  60 value 83.860008
iter  70 value 83.834139
iter  80 value 83.818129
iter  90 value 82.048179
iter 100 value 81.415072
final  value 81.415072 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 100.124147 
iter  10 value 94.060405
iter  20 value 93.373497
iter  30 value 93.088917
iter  40 value 93.081137
iter  50 value 92.538486
iter  60 value 89.568907
iter  70 value 88.216829
iter  80 value 86.155956
iter  90 value 85.623768
final  value 85.623710 
converged
Fitting Repeat 3 

# weights:  507
initial  value 111.929722 
iter  10 value 93.923956
iter  20 value 92.994638
iter  30 value 85.597104
iter  40 value 82.593276
iter  50 value 82.284565
iter  60 value 82.189106
iter  70 value 82.170160
iter  80 value 82.162213
iter  90 value 82.156421
iter 100 value 82.104049
final  value 82.104049 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.477982 
iter  10 value 94.060842
iter  20 value 93.792354
iter  30 value 93.654056
iter  40 value 92.082154
iter  50 value 86.513655
iter  60 value 86.473770
iter  70 value 85.342893
iter  80 value 83.917215
iter  90 value 83.906051
iter 100 value 83.904747
final  value 83.904747 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.120083 
iter  10 value 94.119118
iter  20 value 92.012183
iter  30 value 85.163938
iter  40 value 83.104951
iter  50 value 83.093217
iter  60 value 83.011563
iter  70 value 82.932326
iter  80 value 82.913140
iter  90 value 82.595320
iter 100 value 82.584388
final  value 82.584388 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 93.766365 
iter  10 value 92.316562
iter  20 value 92.237109
final  value 92.237027 
converged
Fitting Repeat 2 

# weights:  103
initial  value 109.354621 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.024994 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.674099 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 113.618624 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.015358 
iter  10 value 94.443244
iter  10 value 94.443243
iter  10 value 94.443243
final  value 94.443243 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.497368 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.418313 
final  value 94.443243 
converged
Fitting Repeat 4 

# weights:  305
initial  value 108.512514 
final  value 94.455556 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.295390 
iter  10 value 86.686022
iter  20 value 85.833890
final  value 85.833868 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.273256 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.018137 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.241286 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 108.821686 
iter  10 value 93.056659
iter  20 value 87.890112
iter  30 value 87.647672
final  value 87.647667 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.741015 
final  value 94.483810 
converged
Fitting Repeat 1 

# weights:  103
initial  value 111.563272 
iter  10 value 94.444992
iter  20 value 87.796422
iter  30 value 86.342525
iter  40 value 82.202950
iter  50 value 81.647698
iter  60 value 81.551485
iter  70 value 81.370036
iter  80 value 81.265848
iter  90 value 81.264713
final  value 81.264601 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.341477 
iter  10 value 94.298152
iter  20 value 92.068241
iter  30 value 91.857667
iter  40 value 85.467320
iter  50 value 82.951060
iter  60 value 81.562968
iter  70 value 81.341735
iter  80 value 80.422733
iter  90 value 80.148485
final  value 80.148244 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.744613 
iter  10 value 94.338787
iter  20 value 88.306769
iter  30 value 83.467567
iter  40 value 82.300809
iter  50 value 81.317072
iter  60 value 81.264509
iter  60 value 81.264509
iter  60 value 81.264509
final  value 81.264509 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.892015 
iter  10 value 94.474722
iter  20 value 94.013047
iter  30 value 91.043121
iter  40 value 85.782626
iter  50 value 84.019841
iter  60 value 82.778633
iter  70 value 82.621594
iter  80 value 82.108802
iter  90 value 81.635486
final  value 81.591117 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.571568 
iter  10 value 94.563194
iter  20 value 94.487222
iter  30 value 90.603208
iter  40 value 83.360981
iter  50 value 82.687974
iter  60 value 81.837028
iter  70 value 81.308557
final  value 81.264509 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.705994 
iter  10 value 93.829711
iter  20 value 87.745592
iter  30 value 87.195391
iter  40 value 84.959375
iter  50 value 84.718135
iter  60 value 84.246313
iter  70 value 83.978822
iter  80 value 81.463773
iter  90 value 81.237369
iter 100 value 79.787118
final  value 79.787118 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.506001 
iter  10 value 90.704583
iter  20 value 84.670427
iter  30 value 81.965365
iter  40 value 80.735210
iter  50 value 80.503199
iter  60 value 80.213664
iter  70 value 79.866257
iter  80 value 78.953522
iter  90 value 78.658564
iter 100 value 78.526048
final  value 78.526048 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 109.049535 
iter  10 value 93.441888
iter  20 value 86.843157
iter  30 value 86.090200
iter  40 value 82.942086
iter  50 value 81.906422
iter  60 value 81.048282
iter  70 value 80.730696
iter  80 value 80.019540
iter  90 value 79.784723
iter 100 value 79.319301
final  value 79.319301 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.424817 
iter  10 value 94.432466
iter  20 value 92.494262
iter  30 value 83.718524
iter  40 value 81.973195
iter  50 value 81.533923
iter  60 value 81.458098
iter  70 value 81.411327
iter  80 value 81.236887
iter  90 value 80.238910
iter 100 value 79.740892
final  value 79.740892 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.564003 
iter  10 value 94.758003
iter  20 value 91.706845
iter  30 value 87.228793
iter  40 value 84.038043
iter  50 value 82.756458
iter  60 value 82.528376
iter  70 value 81.925058
iter  80 value 81.175115
iter  90 value 80.887570
iter 100 value 80.731428
final  value 80.731428 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 100.802266 
iter  10 value 94.435568
iter  20 value 82.688440
iter  30 value 80.684326
iter  40 value 79.395818
iter  50 value 79.073881
iter  60 value 78.997797
iter  70 value 78.513628
iter  80 value 78.440381
iter  90 value 78.429994
iter 100 value 78.379541
final  value 78.379541 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.881041 
iter  10 value 94.505629
iter  20 value 91.399804
iter  30 value 85.177462
iter  40 value 84.447350
iter  50 value 84.228145
iter  60 value 82.628171
iter  70 value 80.685149
iter  80 value 79.499803
iter  90 value 79.192489
iter 100 value 79.176120
final  value 79.176120 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.765930 
iter  10 value 93.043437
iter  20 value 84.038828
iter  30 value 82.775914
iter  40 value 82.496014
iter  50 value 81.987324
iter  60 value 79.982828
iter  70 value 79.057669
iter  80 value 78.425233
iter  90 value 78.225667
iter 100 value 78.147880
final  value 78.147880 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.672314 
iter  10 value 94.586165
iter  20 value 93.042280
iter  30 value 87.929048
iter  40 value 85.219045
iter  50 value 83.773769
iter  60 value 82.721045
iter  70 value 81.494018
iter  80 value 81.164342
iter  90 value 81.097264
iter 100 value 80.603941
final  value 80.603941 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.201402 
iter  10 value 94.882200
iter  20 value 93.056457
iter  30 value 87.393951
iter  40 value 85.632531
iter  50 value 84.177124
iter  60 value 84.010509
iter  70 value 83.974371
iter  80 value 83.705293
iter  90 value 82.361243
iter 100 value 81.093458
final  value 81.093458 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.632652 
final  value 94.486057 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.065903 
iter  10 value 94.485874
iter  20 value 92.590662
iter  30 value 83.785171
iter  40 value 83.053319
final  value 83.040068 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.257707 
final  value 94.485880 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.751484 
final  value 94.485709 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.966502 
final  value 94.485747 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.330840 
iter  10 value 94.488960
iter  20 value 94.189548
iter  30 value 83.833366
iter  40 value 80.685594
iter  50 value 79.939665
iter  60 value 79.905210
iter  70 value 79.900966
iter  80 value 79.547995
iter  90 value 77.434499
iter 100 value 77.386940
final  value 77.386940 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.193457 
iter  10 value 94.447710
iter  20 value 94.443723
final  value 94.443289 
converged
Fitting Repeat 3 

# weights:  305
initial  value 130.437655 
iter  10 value 94.489822
iter  20 value 94.452560
iter  30 value 82.565129
iter  40 value 82.563864
iter  50 value 82.561560
final  value 82.561098 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.485599 
iter  10 value 94.448187
iter  20 value 94.444175
final  value 94.443594 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.892758 
iter  10 value 94.447707
iter  20 value 94.443557
iter  30 value 94.228534
iter  40 value 84.096951
iter  50 value 80.428092
iter  60 value 80.361644
final  value 80.361459 
converged
Fitting Repeat 1 

# weights:  507
initial  value 129.294139 
iter  10 value 94.449859
iter  20 value 92.425967
iter  30 value 81.171691
iter  40 value 81.145578
iter  50 value 81.117459
iter  60 value 81.095024
iter  70 value 79.781194
iter  80 value 79.678266
iter  90 value 79.674197
final  value 79.674171 
converged
Fitting Repeat 2 

# weights:  507
initial  value 125.603399 
iter  10 value 94.491739
iter  20 value 94.473564
iter  30 value 90.939198
iter  40 value 82.344442
iter  50 value 82.165210
iter  60 value 82.164839
final  value 82.163912 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.945803 
iter  10 value 94.451730
iter  20 value 94.443468
iter  30 value 88.929220
iter  40 value 85.281832
iter  50 value 85.052403
iter  60 value 83.358643
iter  70 value 83.307852
iter  80 value 80.713652
iter  90 value 79.582701
iter 100 value 79.394309
final  value 79.394309 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 95.994976 
iter  10 value 94.490689
iter  20 value 94.104603
iter  30 value 92.304537
iter  40 value 92.302844
iter  50 value 92.200216
iter  60 value 92.186133
final  value 92.185923 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.363015 
iter  10 value 94.492542
iter  20 value 94.484410
iter  30 value 93.520458
iter  40 value 86.876809
iter  50 value 81.753504
iter  60 value 77.838431
iter  70 value 77.033503
iter  80 value 76.872028
iter  90 value 76.871030
iter 100 value 76.833421
final  value 76.833421 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 124.840547 
iter  10 value 117.874184
iter  20 value 117.867603
iter  30 value 114.256373
final  value 114.253728 
converged
Fitting Repeat 2 

# weights:  507
initial  value 127.602748 
iter  10 value 117.745177
iter  20 value 117.712187
iter  30 value 116.647777
iter  40 value 106.638097
iter  50 value 103.322288
iter  60 value 101.838506
iter  70 value 101.534253
iter  80 value 101.032239
iter  90 value 100.393599
iter 100 value 100.390492
final  value 100.390492 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 131.346225 
iter  10 value 117.898925
iter  20 value 117.845171
iter  30 value 108.535607
iter  40 value 108.007776
iter  50 value 106.784637
iter  60 value 106.779873
iter  70 value 106.774738
iter  80 value 105.726993
iter  90 value 102.244314
iter 100 value 100.353677
final  value 100.353677 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 147.940788 
iter  10 value 117.767581
iter  20 value 117.759908
iter  30 value 115.021581
iter  40 value 106.151680
iter  50 value 105.913429
iter  60 value 105.908325
iter  70 value 105.865380
iter  80 value 105.792389
iter  80 value 105.792389
final  value 105.792389 
converged
Fitting Repeat 5 

# weights:  507
initial  value 123.157253 
iter  10 value 117.897943
iter  20 value 117.383313
iter  30 value 115.848599
iter  40 value 113.499381
iter  50 value 113.494782
final  value 113.494770 
converged
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 -- Thu Oct 17 01:31:51 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 
 43.971   1.915  44.359