##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R-4.3.0/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/R/R-4.3.0/site-library --timings HPiP_1.7.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.18-bioc/meat/HPiP.Rcheck’
* using R version 4.3.0 (2023-04-21)
* using platform: aarch64-unknown-linux-gnu (64-bit)
* R was compiled by
    gcc (GCC) 10.3.1
    GNU Fortran (GCC) 10.3.1
* running under: openEuler 22.03 (LTS-SP1)
* using session charset: UTF-8
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.7.0’
* 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 ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking R 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 ... OK
* 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       39.933  0.717  40.755
corr_plot     38.268  0.415  38.748
FSmethod      37.730  0.455  38.248
pred_ensembel 18.076  0.294  16.057
enrichfindP    0.426  0.012  15.856
getFASTA       0.074  0.008   7.451
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes in ‘inst/doc’ ... OK
* checking running R code from vignettes ...
  ‘HPiP_tutorial.Rmd’ using ‘UTF-8’... OK
 NONE
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE

Status: 1 NOTE
See
  ‘/home/biocbuild/bbs-3.18-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R-4.3.0/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/R/R-4.3.0/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 4.3.0 (2023-04-21) -- "Already Tomorrow"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu (64-bit)

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
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 101.873314 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.874924 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 116.484083 
final  value 94.252921 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.946891 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.548644 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.429637 
iter  10 value 92.001576
iter  20 value 90.085107
iter  30 value 90.077844
final  value 90.077811 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.017425 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.487676 
iter  10 value 91.034768
iter  20 value 85.999363
iter  30 value 84.435385
iter  40 value 84.429523
final  value 84.429415 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.006879 
final  value 94.484212 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.269624 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.057565 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.599126 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.961469 
iter  10 value 93.496112
iter  20 value 93.484136
final  value 93.484123 
converged
Fitting Repeat 4 

# weights:  507
initial  value 124.788664 
final  value 94.252920 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.122426 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.545384 
iter  10 value 94.233853
iter  20 value 94.040394
iter  30 value 93.394982
iter  40 value 90.054907
iter  50 value 89.203255
iter  60 value 87.344259
iter  70 value 87.090929
iter  80 value 87.031849
final  value 87.031733 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.545236 
iter  10 value 94.488529
iter  20 value 93.935490
iter  30 value 91.286991
iter  40 value 89.916365
iter  50 value 89.542259
iter  60 value 89.306235
iter  70 value 85.510224
iter  80 value 85.050598
iter  90 value 84.646082
final  value 84.646016 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.881867 
iter  10 value 94.406695
iter  20 value 88.203458
iter  30 value 85.963596
iter  40 value 85.519748
iter  50 value 85.269325
iter  60 value 84.717005
iter  70 value 84.646019
final  value 84.646016 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.501462 
iter  10 value 94.486436
iter  20 value 93.927018
iter  30 value 93.733266
iter  40 value 88.093362
iter  50 value 87.499146
iter  60 value 86.884407
iter  70 value 86.348265
iter  80 value 86.313150
iter  90 value 86.308457
final  value 86.308445 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.689977 
iter  10 value 94.452089
iter  20 value 93.859069
iter  30 value 93.729373
iter  40 value 91.996842
iter  50 value 90.079738
iter  60 value 89.627788
iter  70 value 89.409521
iter  80 value 86.538500
iter  90 value 86.322908
iter 100 value 86.308531
final  value 86.308531 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 110.486181 
iter  10 value 90.952345
iter  20 value 89.112802
iter  30 value 87.869995
iter  40 value 87.563366
iter  50 value 85.667270
iter  60 value 85.091589
iter  70 value 84.971554
iter  80 value 84.192274
iter  90 value 84.069117
iter 100 value 84.064568
final  value 84.064568 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.831221 
iter  10 value 94.546793
iter  20 value 94.425315
iter  30 value 94.097141
iter  40 value 90.227950
iter  50 value 86.912409
iter  60 value 86.128852
iter  70 value 84.780192
iter  80 value 84.154645
iter  90 value 84.052474
iter 100 value 83.965281
final  value 83.965281 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.708597 
iter  10 value 94.432507
iter  20 value 88.794123
iter  30 value 86.283452
iter  40 value 84.965763
iter  50 value 84.775092
iter  60 value 84.540298
iter  70 value 84.517625
final  value 84.517504 
converged
Fitting Repeat 4 

# weights:  305
initial  value 109.905775 
iter  10 value 94.493216
iter  20 value 87.911246
iter  30 value 86.981597
iter  40 value 86.230550
iter  50 value 85.965652
iter  60 value 85.952643
iter  70 value 85.613152
iter  80 value 84.249373
iter  90 value 84.128425
iter 100 value 84.087089
final  value 84.087089 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.304240 
iter  10 value 94.309854
iter  20 value 92.583526
iter  30 value 87.926337
iter  40 value 84.847410
iter  50 value 84.442683
iter  60 value 84.323639
iter  70 value 84.234089
iter  80 value 83.958524
iter  90 value 83.530450
iter 100 value 83.265098
final  value 83.265098 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.609773 
iter  10 value 94.713513
iter  20 value 93.554529
iter  30 value 91.199179
iter  40 value 88.833469
iter  50 value 87.988002
iter  60 value 85.260207
iter  70 value 84.814795
iter  80 value 84.500316
iter  90 value 83.690236
iter 100 value 83.278427
final  value 83.278427 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 119.632214 
iter  10 value 94.276562
iter  20 value 91.816405
iter  30 value 85.981396
iter  40 value 84.308574
iter  50 value 83.362788
iter  60 value 83.188245
iter  70 value 83.006530
iter  80 value 82.887623
iter  90 value 82.804972
iter 100 value 82.762184
final  value 82.762184 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 134.930961 
iter  10 value 94.604303
iter  20 value 94.089816
iter  30 value 91.891233
iter  40 value 85.346048
iter  50 value 84.476522
iter  60 value 84.055256
iter  70 value 83.736240
iter  80 value 83.575043
iter  90 value 83.470994
iter 100 value 83.168602
final  value 83.168602 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.252912 
iter  10 value 94.387274
iter  20 value 90.500537
iter  30 value 88.413259
iter  40 value 87.017545
iter  50 value 86.537109
iter  60 value 86.043638
iter  70 value 85.628228
iter  80 value 84.528009
iter  90 value 84.370781
iter 100 value 84.284199
final  value 84.284199 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.706797 
iter  10 value 94.527160
iter  20 value 93.581998
iter  30 value 93.326309
iter  40 value 92.146970
iter  50 value 91.572601
iter  60 value 89.176480
iter  70 value 87.379910
iter  80 value 84.826119
iter  90 value 83.787060
iter 100 value 83.394817
final  value 83.394817 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.528867 
final  value 94.485975 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.368465 
final  value 94.485843 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.557710 
final  value 94.486049 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.737729 
final  value 94.485921 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.001633 
final  value 94.485962 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.067294 
iter  10 value 94.489409
iter  20 value 94.484476
iter  30 value 94.264865
iter  40 value 93.881478
iter  50 value 87.074193
iter  60 value 86.736057
final  value 86.736004 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.699669 
iter  10 value 94.269266
iter  20 value 94.262009
iter  30 value 93.905031
iter  40 value 87.530675
final  value 86.944500 
converged
Fitting Repeat 3 

# weights:  305
initial  value 115.884394 
iter  10 value 94.257629
iter  20 value 94.244347
iter  30 value 93.967778
iter  40 value 93.915499
iter  50 value 93.904945
final  value 93.904916 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.298202 
iter  10 value 94.489156
iter  20 value 94.451026
iter  30 value 92.930905
iter  40 value 92.366738
final  value 92.365244 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.449114 
iter  10 value 91.514085
iter  20 value 91.340548
iter  30 value 91.217060
iter  40 value 91.212964
iter  50 value 91.193554
iter  60 value 91.178916
iter  70 value 91.175899
iter  80 value 90.946826
final  value 90.877550 
converged
Fitting Repeat 1 

# weights:  507
initial  value 123.063067 
iter  10 value 94.474712
iter  20 value 94.467206
iter  30 value 94.148033
iter  40 value 93.444303
iter  50 value 93.418229
iter  60 value 92.582452
iter  70 value 92.527505
iter  80 value 92.527391
final  value 92.527165 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.137535 
iter  10 value 94.474845
iter  20 value 94.468089
iter  30 value 94.462755
iter  40 value 89.942485
iter  50 value 89.487274
final  value 89.325445 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.592256 
iter  10 value 93.668740
iter  20 value 89.770402
iter  30 value 85.202141
iter  40 value 84.778253
iter  50 value 84.751507
iter  60 value 84.050144
iter  70 value 83.822445
iter  80 value 83.811645
iter  90 value 82.830902
iter 100 value 82.604113
final  value 82.604113 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 98.462886 
iter  10 value 94.474230
iter  20 value 94.405029
iter  30 value 92.295968
iter  40 value 92.067324
iter  50 value 91.862267
final  value 91.862250 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.073761 
iter  10 value 94.474670
iter  20 value 94.169222
iter  30 value 93.977196
iter  40 value 90.533093
iter  50 value 86.961385
iter  60 value 86.944278
iter  70 value 86.858479
iter  80 value 86.679317
iter  90 value 86.331884
iter 100 value 86.214214
final  value 86.214214 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.260013 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.526112 
final  value 94.026542 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.806013 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.890866 
iter  10 value 94.026542
iter  10 value 94.026542
iter  10 value 94.026542
final  value 94.026542 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.218205 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 127.065383 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.861639 
iter  10 value 94.499627
final  value 94.484135 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.196230 
iter  10 value 94.474338
final  value 94.474336 
converged
Fitting Repeat 4 

# weights:  305
initial  value 108.884633 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.141746 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 131.104731 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.855313 
final  value 94.461207 
converged
Fitting Repeat 3 

# weights:  507
initial  value 114.594012 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.678164 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.435634 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.347229 
iter  10 value 94.489066
iter  20 value 94.243106
iter  30 value 94.213388
iter  40 value 94.188069
iter  50 value 87.947838
iter  60 value 86.425139
iter  70 value 85.911287
iter  80 value 85.807005
iter  90 value 85.747443
iter 100 value 85.643484
final  value 85.643484 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.573364 
iter  10 value 94.490181
iter  20 value 93.328141
iter  30 value 86.737433
iter  40 value 84.103515
iter  50 value 83.835076
iter  60 value 83.732504
iter  70 value 83.490628
iter  80 value 83.361281
iter  90 value 83.323890
iter 100 value 83.319510
final  value 83.319510 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.803550 
iter  10 value 94.486328
iter  20 value 89.160550
iter  30 value 87.429763
iter  40 value 85.452376
iter  50 value 84.655768
iter  60 value 83.667282
iter  70 value 83.385988
iter  80 value 83.333392
iter  90 value 83.319596
final  value 83.319493 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.663129 
iter  10 value 94.449545
iter  20 value 94.127454
iter  30 value 94.125946
iter  40 value 93.790957
iter  50 value 87.330329
iter  60 value 86.524997
iter  70 value 86.436371
iter  80 value 86.392465
iter  90 value 86.339403
iter 100 value 84.189298
final  value 84.189298 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 102.856613 
iter  10 value 92.156911
iter  20 value 88.349722
iter  30 value 87.721957
iter  40 value 86.802583
iter  50 value 84.834152
iter  60 value 83.620277
iter  70 value 83.468482
iter  80 value 83.321890
iter  90 value 83.319510
final  value 83.319493 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.325228 
iter  10 value 94.445984
iter  20 value 89.985486
iter  30 value 88.529604
iter  40 value 86.197930
iter  50 value 82.224467
iter  60 value 81.934975
iter  70 value 81.489589
iter  80 value 81.322533
iter  90 value 80.659648
iter 100 value 80.281436
final  value 80.281436 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 118.640688 
iter  10 value 93.285321
iter  20 value 88.782471
iter  30 value 86.810535
iter  40 value 85.938865
iter  50 value 85.820380
iter  60 value 85.788853
iter  70 value 85.587546
iter  80 value 82.681832
iter  90 value 81.705270
iter 100 value 80.996327
final  value 80.996327 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.500224 
iter  10 value 91.525686
iter  20 value 86.762820
iter  30 value 86.197679
iter  40 value 85.903945
iter  50 value 84.832322
iter  60 value 83.712212
iter  70 value 83.299594
iter  80 value 83.193643
iter  90 value 83.042488
iter 100 value 82.933548
final  value 82.933548 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.462654 
iter  10 value 94.578551
iter  20 value 91.484183
iter  30 value 89.297354
iter  40 value 84.034763
iter  50 value 83.725841
iter  60 value 83.390202
iter  70 value 82.206792
iter  80 value 82.134774
iter  90 value 82.005280
iter 100 value 81.486417
final  value 81.486417 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.690500 
iter  10 value 94.516524
iter  20 value 88.383560
iter  30 value 84.687386
iter  40 value 83.843324
iter  50 value 83.612710
iter  60 value 83.496058
iter  70 value 83.407601
iter  80 value 83.289274
iter  90 value 83.266554
iter 100 value 82.186152
final  value 82.186152 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 126.332748 
iter  10 value 94.212212
iter  20 value 94.093091
iter  30 value 92.859714
iter  40 value 84.859550
iter  50 value 83.510727
iter  60 value 81.565453
iter  70 value 80.586131
iter  80 value 80.402974
iter  90 value 80.264976
iter 100 value 80.151184
final  value 80.151184 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 123.999615 
iter  10 value 94.621664
iter  20 value 91.606845
iter  30 value 88.497783
iter  40 value 87.675340
iter  50 value 83.200795
iter  60 value 81.927443
iter  70 value 81.424137
iter  80 value 81.214423
iter  90 value 80.889256
iter 100 value 80.802670
final  value 80.802670 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 117.088808 
iter  10 value 94.660584
iter  20 value 94.122746
iter  30 value 87.008399
iter  40 value 86.165144
iter  50 value 85.116275
iter  60 value 84.275236
iter  70 value 83.682135
iter  80 value 83.107184
iter  90 value 82.952728
iter 100 value 82.860564
final  value 82.860564 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.908625 
iter  10 value 94.514732
iter  20 value 93.330556
iter  30 value 87.321678
iter  40 value 84.508632
iter  50 value 84.071948
iter  60 value 82.571199
iter  70 value 81.817080
iter  80 value 81.499370
iter  90 value 81.163540
iter 100 value 80.825501
final  value 80.825501 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.742703 
iter  10 value 90.725031
iter  20 value 87.919620
iter  30 value 83.099509
iter  40 value 81.688494
iter  50 value 81.151501
iter  60 value 80.875413
iter  70 value 80.624715
iter  80 value 80.446417
iter  90 value 80.345588
iter 100 value 80.298430
final  value 80.298430 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.223639 
iter  10 value 94.486048
final  value 94.485966 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.027608 
final  value 94.485862 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.901229 
final  value 94.485939 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.617481 
final  value 94.486111 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.227208 
final  value 94.485677 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.315371 
iter  10 value 94.475384
iter  20 value 94.030770
iter  30 value 94.028465
iter  40 value 94.026710
iter  50 value 94.026365
final  value 94.026345 
converged
Fitting Repeat 2 

# weights:  305
initial  value 133.672760 
iter  10 value 94.488675
iter  20 value 94.264974
iter  30 value 94.031265
iter  40 value 94.027312
iter  50 value 93.794517
iter  60 value 89.126286
iter  70 value 88.531812
iter  80 value 88.524033
iter  90 value 88.523706
final  value 88.523668 
converged
Fitting Repeat 3 

# weights:  305
initial  value 111.302048 
iter  10 value 94.087672
iter  20 value 94.081951
iter  30 value 94.079895
iter  40 value 94.046129
iter  50 value 94.027908
final  value 94.027882 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.347823 
iter  10 value 94.488207
iter  20 value 94.484183
iter  30 value 94.278203
iter  40 value 91.854618
iter  50 value 86.495293
iter  60 value 84.408043
iter  70 value 83.872903
final  value 83.812634 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.106293 
iter  10 value 94.489066
iter  20 value 94.139967
final  value 94.026774 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.785316 
iter  10 value 94.034425
iter  20 value 94.029214
iter  30 value 93.880677
iter  40 value 89.870134
iter  50 value 85.534732
iter  60 value 81.913933
iter  70 value 81.865751
iter  80 value 81.584688
iter  90 value 81.347107
iter 100 value 81.344513
final  value 81.344513 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 99.506332 
iter  10 value 92.845492
iter  20 value 92.845249
iter  20 value 92.845249
final  value 92.845246 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.714513 
iter  10 value 85.777413
iter  20 value 84.794382
iter  30 value 84.766359
iter  40 value 84.422126
iter  50 value 84.360275
iter  60 value 84.328500
final  value 84.324554 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.840918 
iter  10 value 94.491764
iter  20 value 94.361981
iter  30 value 92.075577
iter  40 value 87.365692
iter  50 value 87.141520
iter  60 value 82.765973
iter  70 value 82.163614
iter  80 value 82.025069
iter  90 value 81.736341
iter 100 value 81.713540
final  value 81.713540 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 96.892203 
iter  10 value 94.489494
iter  20 value 94.425184
iter  30 value 94.025022
iter  40 value 87.228163
iter  50 value 86.938724
iter  60 value 85.978708
iter  70 value 83.731306
iter  80 value 83.697281
iter  90 value 83.494580
iter 100 value 82.893393
final  value 82.893393 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.818418 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.698502 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.220112 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.599530 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.255768 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.540250 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.993040 
iter  10 value 93.454489
final  value 93.288889 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.856430 
iter  10 value 94.008696
iter  10 value 94.008696
iter  10 value 94.008696
final  value 94.008696 
converged
Fitting Repeat 4 

# weights:  305
initial  value 108.889396 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 91.794749 
iter  10 value 82.048034
iter  20 value 81.844503
iter  30 value 81.830138
final  value 81.829860 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.839076 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.575326 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.936577 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 131.458200 
iter  10 value 94.052910
iter  10 value 94.052910
iter  10 value 94.052910
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.064877 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.075635 
iter  10 value 93.969735
iter  20 value 93.074554
iter  30 value 85.177836
iter  40 value 80.375241
iter  50 value 79.574719
iter  60 value 79.030595
iter  70 value 78.948485
iter  80 value 78.946670
iter  80 value 78.946669
iter  80 value 78.946669
final  value 78.946669 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.784256 
iter  10 value 93.893389
iter  20 value 91.146818
iter  30 value 89.793145
iter  40 value 89.695469
iter  50 value 89.658739
iter  60 value 82.387262
iter  70 value 79.870917
iter  80 value 78.804009
iter  90 value 77.908737
iter 100 value 77.512651
final  value 77.512651 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.062781 
iter  10 value 93.689936
iter  20 value 86.774088
iter  30 value 80.781939
iter  40 value 78.609353
iter  50 value 78.176449
iter  60 value 77.559188
iter  70 value 77.287600
iter  80 value 77.259540
iter  90 value 77.155732
final  value 77.113791 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.905320 
iter  10 value 93.942202
iter  20 value 81.729947
iter  30 value 80.299390
iter  40 value 80.163315
iter  50 value 79.877103
iter  60 value 79.103467
iter  70 value 78.698020
iter  80 value 78.689009
final  value 78.689004 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.466195 
iter  10 value 94.014876
iter  20 value 89.387647
iter  30 value 82.595518
iter  40 value 81.800584
iter  50 value 81.484023
iter  60 value 81.362901
iter  70 value 81.353512
iter  80 value 81.343491
final  value 81.343333 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.551753 
iter  10 value 91.119304
iter  20 value 81.961376
iter  30 value 80.107727
iter  40 value 78.276667
iter  50 value 76.322380
iter  60 value 76.056506
iter  70 value 75.573628
iter  80 value 75.376379
iter  90 value 75.266750
iter 100 value 75.241262
final  value 75.241262 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.975565 
iter  10 value 94.180062
iter  20 value 92.898339
iter  30 value 91.000364
iter  40 value 88.849258
iter  50 value 88.649210
final  value 88.571758 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.712628 
iter  10 value 94.992970
iter  20 value 94.052548
iter  30 value 91.051425
iter  40 value 90.784015
iter  50 value 90.619641
iter  60 value 89.755852
iter  70 value 88.541709
iter  80 value 88.276595
iter  90 value 81.792187
iter 100 value 79.553061
final  value 79.553061 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.098261 
iter  10 value 94.928169
iter  20 value 81.286483
iter  30 value 79.165719
iter  40 value 76.843588
iter  50 value 76.283045
iter  60 value 76.038274
iter  70 value 75.725776
iter  80 value 75.690695
iter  90 value 75.660748
iter 100 value 75.624377
final  value 75.624377 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 113.098150 
iter  10 value 93.050364
iter  20 value 83.268068
iter  30 value 82.500991
iter  40 value 81.489294
iter  50 value 80.524900
iter  60 value 78.498029
iter  70 value 78.068222
iter  80 value 77.570510
iter  90 value 77.468093
iter 100 value 77.277266
final  value 77.277266 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 121.306357 
iter  10 value 94.892340
iter  20 value 87.034204
iter  30 value 79.998727
iter  40 value 78.667542
iter  50 value 76.401028
iter  60 value 75.916486
iter  70 value 75.601780
iter  80 value 75.369712
iter  90 value 75.180261
iter 100 value 75.081178
final  value 75.081178 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 115.281750 
iter  10 value 96.868487
iter  20 value 85.906864
iter  30 value 83.779869
iter  40 value 82.483835
iter  50 value 81.150689
iter  60 value 80.659794
iter  70 value 80.320307
iter  80 value 79.793089
iter  90 value 77.483619
iter 100 value 77.036722
final  value 77.036722 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.349415 
iter  10 value 94.059160
iter  20 value 93.278860
iter  30 value 91.926994
iter  40 value 91.706966
iter  50 value 91.347457
iter  60 value 91.146378
iter  70 value 86.744539
iter  80 value 82.420074
iter  90 value 78.789698
iter 100 value 76.942332
final  value 76.942332 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.325041 
iter  10 value 94.025532
iter  20 value 88.151140
iter  30 value 81.628042
iter  40 value 79.431942
iter  50 value 78.878490
iter  60 value 78.656592
iter  70 value 78.436359
iter  80 value 78.306183
iter  90 value 78.154363
iter 100 value 77.770661
final  value 77.770661 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 121.777041 
iter  10 value 99.991514
iter  20 value 91.164177
iter  30 value 85.740968
iter  40 value 81.125932
iter  50 value 79.428294
iter  60 value 78.907973
iter  70 value 78.850813
iter  80 value 78.706496
iter  90 value 78.249842
iter 100 value 77.638192
final  value 77.638192 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.424574 
final  value 94.054774 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.759938 
final  value 94.010280 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.667778 
final  value 94.054375 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.414507 
final  value 94.054530 
converged
Fitting Repeat 5 

# weights:  103
initial  value 108.603724 
iter  10 value 94.082226
iter  20 value 94.077583
final  value 94.052913 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.644216 
iter  10 value 94.057791
iter  20 value 94.029635
iter  30 value 89.381060
iter  40 value 89.004380
iter  50 value 88.995266
iter  60 value 88.988621
iter  70 value 88.988088
iter  70 value 88.988088
final  value 88.988088 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.370636 
iter  10 value 93.989446
iter  20 value 93.985607
iter  30 value 92.862338
iter  40 value 90.658502
iter  40 value 90.658502
iter  40 value 90.658502
final  value 90.658502 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.466386 
iter  10 value 94.058019
iter  20 value 94.052987
iter  30 value 92.496839
iter  40 value 83.990780
iter  50 value 83.889531
iter  60 value 83.888664
iter  70 value 83.886497
iter  80 value 83.885445
iter  90 value 83.885236
final  value 83.884951 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.151790 
iter  10 value 94.057810
iter  20 value 93.732641
iter  30 value 89.456356
final  value 89.454663 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.785898 
iter  10 value 94.013646
iter  20 value 94.009748
iter  30 value 91.711993
iter  40 value 91.656756
final  value 91.656703 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.936324 
iter  10 value 94.060072
iter  20 value 94.041961
iter  30 value 93.532863
iter  40 value 81.419832
iter  50 value 81.314532
iter  60 value 81.313561
final  value 81.313430 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.380894 
iter  10 value 94.061101
iter  20 value 81.843363
iter  30 value 81.606003
iter  40 value 77.484374
iter  50 value 77.458236
iter  60 value 77.304208
iter  70 value 76.554237
iter  80 value 76.467723
iter  90 value 76.439773
iter 100 value 76.347191
final  value 76.347191 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.475228 
iter  10 value 94.061690
iter  20 value 94.003676
iter  30 value 92.257451
iter  40 value 92.252674
iter  50 value 90.721203
iter  60 value 90.478557
iter  70 value 90.477590
iter  80 value 90.466204
iter  90 value 90.390988
final  value 90.390630 
converged
Fitting Repeat 4 

# weights:  507
initial  value 119.528707 
iter  10 value 94.061853
iter  20 value 94.015176
iter  30 value 94.011127
iter  40 value 93.933179
iter  50 value 82.307392
iter  60 value 82.165326
iter  70 value 82.064944
iter  80 value 80.867801
iter  90 value 80.858352
iter 100 value 80.214401
final  value 80.214401 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 97.639987 
iter  10 value 93.219528
iter  20 value 93.216595
iter  30 value 90.414645
iter  40 value 87.578674
iter  50 value 87.315663
iter  60 value 84.636035
iter  70 value 84.590121
iter  80 value 83.487605
iter  90 value 78.453477
iter 100 value 78.345964
final  value 78.345964 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.992312 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.941917 
final  value 94.275362 
converged
Fitting Repeat 3 

# weights:  103
initial  value 112.553930 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.712384 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.649266 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.224021 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.636621 
final  value 94.275362 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.563362 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.980942 
iter  10 value 81.786715
iter  20 value 81.582194
iter  30 value 81.392884
iter  40 value 81.379346
final  value 81.377468 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.797847 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.334400 
final  value 94.275362 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.094945 
final  value 94.275363 
converged
Fitting Repeat 3 

# weights:  507
initial  value 108.180895 
iter  10 value 91.903864
iter  20 value 85.394034
final  value 85.393874 
converged
Fitting Repeat 4 

# weights:  507
initial  value 109.334289 
iter  10 value 93.053542
iter  20 value 92.935006
iter  30 value 91.764228
iter  40 value 91.614909
final  value 91.614716 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.246526 
iter  10 value 94.144736
iter  20 value 93.695232
iter  30 value 93.691074
final  value 93.691059 
converged
Fitting Repeat 1 

# weights:  103
initial  value 107.343265 
iter  10 value 94.234691
iter  20 value 86.920171
iter  30 value 86.188561
iter  40 value 83.412303
iter  50 value 82.565038
iter  60 value 82.395260
iter  70 value 82.381699
final  value 82.381424 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.739939 
iter  10 value 94.347706
iter  20 value 94.329913
iter  30 value 91.763813
iter  40 value 88.265998
iter  50 value 85.853657
iter  60 value 83.832642
iter  70 value 83.321065
iter  80 value 82.591692
iter  90 value 82.382719
final  value 82.382481 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.409546 
iter  10 value 94.491847
iter  20 value 94.040151
iter  30 value 93.734597
iter  40 value 93.684126
iter  50 value 92.646724
iter  60 value 83.185873
iter  70 value 81.922674
iter  80 value 81.311302
iter  90 value 80.240479
iter 100 value 80.054603
final  value 80.054603 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.987027 
iter  10 value 94.367367
iter  20 value 90.537615
iter  30 value 86.464845
iter  40 value 83.505379
iter  50 value 83.336062
iter  60 value 83.137287
iter  70 value 82.635369
iter  80 value 82.460716
iter  90 value 82.382796
final  value 82.381424 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.661920 
iter  10 value 93.620703
iter  20 value 92.857635
iter  30 value 88.236906
iter  40 value 87.067106
iter  50 value 85.826086
iter  60 value 83.250047
iter  70 value 82.662294
iter  80 value 82.395883
final  value 82.382524 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.038562 
iter  10 value 94.487407
iter  20 value 93.111353
iter  30 value 86.392376
iter  40 value 81.255805
iter  50 value 80.278273
iter  60 value 80.100960
iter  70 value 79.583202
iter  80 value 79.547035
iter  90 value 79.532182
iter 100 value 79.507274
final  value 79.507274 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.175087 
iter  10 value 94.350316
iter  20 value 93.099778
iter  30 value 86.820596
iter  40 value 84.410735
iter  50 value 81.909339
iter  60 value 81.242806
iter  70 value 79.954998
iter  80 value 79.486945
iter  90 value 79.420893
iter 100 value 79.216307
final  value 79.216307 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.035988 
iter  10 value 94.505003
iter  20 value 93.946617
iter  30 value 85.593584
iter  40 value 82.297854
iter  50 value 81.743196
iter  60 value 80.711006
iter  70 value 79.523310
iter  80 value 79.334857
iter  90 value 79.190370
iter 100 value 79.110472
final  value 79.110472 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 136.193111 
iter  10 value 94.537199
iter  20 value 94.359642
iter  30 value 87.635231
iter  40 value 81.715053
iter  50 value 80.086472
iter  60 value 79.575463
iter  70 value 78.859438
iter  80 value 78.817546
iter  90 value 78.812053
iter 100 value 78.707601
final  value 78.707601 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 113.096783 
iter  10 value 94.067085
iter  20 value 84.980485
iter  30 value 82.967070
iter  40 value 82.020667
iter  50 value 80.276146
iter  60 value 79.384052
iter  70 value 78.794990
iter  80 value 78.555644
iter  90 value 78.438836
iter 100 value 78.405944
final  value 78.405944 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 113.645102 
iter  10 value 97.270931
iter  20 value 87.752670
iter  30 value 84.692125
iter  40 value 83.480730
iter  50 value 82.251988
iter  60 value 79.395717
iter  70 value 79.100285
iter  80 value 78.923169
iter  90 value 78.806641
iter 100 value 78.792361
final  value 78.792361 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.003542 
iter  10 value 94.344470
iter  20 value 90.718581
iter  30 value 85.731339
iter  40 value 85.076613
iter  50 value 84.899410
iter  60 value 84.818978
iter  70 value 83.358290
iter  80 value 82.934821
iter  90 value 82.546938
iter 100 value 82.067735
final  value 82.067735 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 116.889750 
iter  10 value 93.298303
iter  20 value 92.270820
iter  30 value 84.759936
iter  40 value 82.398229
iter  50 value 81.793523
iter  60 value 81.262987
iter  70 value 80.633614
iter  80 value 79.197299
iter  90 value 78.953416
iter 100 value 78.943658
final  value 78.943658 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.738511 
iter  10 value 93.739883
iter  20 value 91.807005
iter  30 value 85.617908
iter  40 value 84.526387
iter  50 value 82.956141
iter  60 value 81.020411
iter  70 value 80.028238
iter  80 value 79.508416
iter  90 value 79.381198
iter 100 value 79.366735
final  value 79.366735 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.446663 
iter  10 value 94.544864
iter  20 value 93.963342
iter  30 value 91.777526
iter  40 value 86.457173
iter  50 value 85.766193
iter  60 value 84.743410
iter  70 value 81.692379
iter  80 value 80.004664
iter  90 value 79.574052
iter 100 value 78.997183
final  value 78.997183 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.743831 
iter  10 value 88.842996
iter  20 value 84.372292
iter  30 value 84.370809
iter  40 value 82.138358
iter  50 value 81.638195
iter  60 value 81.629605
iter  70 value 81.580726
iter  80 value 81.548570
final  value 81.548401 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.525360 
final  value 94.277038 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.965425 
iter  10 value 94.485908
iter  20 value 94.484249
final  value 94.484217 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.337498 
final  value 94.485838 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.817801 
iter  10 value 94.485868
iter  20 value 94.484267
iter  30 value 93.863592
iter  40 value 93.542228
final  value 93.542223 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.062221 
iter  10 value 94.489188
iter  20 value 94.484228
iter  30 value 93.519093
iter  40 value 93.181114
iter  50 value 86.299004
iter  60 value 85.574623
iter  70 value 85.560415
final  value 85.560410 
converged
Fitting Repeat 2 

# weights:  305
initial  value 114.542159 
iter  10 value 94.281038
iter  20 value 94.279723
iter  30 value 90.546570
iter  40 value 84.183800
iter  50 value 83.840553
final  value 83.840476 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.742177 
iter  10 value 94.180668
iter  20 value 94.110368
iter  30 value 94.107129
iter  40 value 84.423315
iter  50 value 84.365570
iter  60 value 84.351310
iter  70 value 84.311928
iter  80 value 83.817903
iter  90 value 81.479823
iter 100 value 80.587653
final  value 80.587653 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.397008 
iter  10 value 94.489209
iter  20 value 94.282728
iter  30 value 88.596706
iter  40 value 84.380665
iter  50 value 84.373452
iter  60 value 84.302910
iter  70 value 81.565258
iter  80 value 81.474641
final  value 81.474616 
converged
Fitting Repeat 5 

# weights:  305
initial  value 112.506702 
iter  10 value 94.488883
iter  20 value 94.244440
iter  30 value 85.432139
iter  40 value 83.158626
iter  50 value 80.605025
iter  60 value 79.998720
iter  70 value 79.258743
iter  80 value 78.385297
iter  90 value 77.259802
iter 100 value 77.212641
final  value 77.212641 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 101.955734 
iter  10 value 92.332147
iter  20 value 92.026433
iter  30 value 91.200508
iter  40 value 91.199359
iter  50 value 84.906143
iter  60 value 84.594866
iter  70 value 81.312818
iter  80 value 78.912404
iter  90 value 78.683902
iter 100 value 78.024147
final  value 78.024147 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.952327 
iter  10 value 94.283723
iter  20 value 94.109689
iter  30 value 89.047584
iter  40 value 83.894248
iter  50 value 83.850688
iter  60 value 83.831876
iter  60 value 83.831875
iter  60 value 83.831875
final  value 83.831875 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.885382 
iter  10 value 93.566894
iter  20 value 93.530938
iter  30 value 88.038996
iter  40 value 86.268524
iter  50 value 86.267738
final  value 86.267670 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.270026 
iter  10 value 94.283616
iter  20 value 93.420640
iter  30 value 88.406477
iter  40 value 88.392955
iter  50 value 88.391443
final  value 88.390796 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.083567 
iter  10 value 94.492921
iter  20 value 94.444610
iter  30 value 81.634459
final  value 81.633554 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.915272 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.237281 
final  value 94.032967 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.529782 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.135511 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.101280 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.523576 
iter  10 value 93.856181
final  value 93.855784 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.636282 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.367552 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.023028 
iter  10 value 93.008970
final  value 93.008966 
converged
Fitting Repeat 5 

# weights:  305
initial  value 113.845969 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.221938 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.894295 
iter  10 value 92.748826
iter  20 value 86.013420
iter  30 value 84.997753
iter  40 value 84.770848
final  value 84.768825 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.897580 
final  value 94.032967 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.731932 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.246164 
iter  10 value 90.680421
iter  20 value 85.583093
iter  30 value 84.713751
iter  40 value 83.902404
iter  50 value 83.718230
iter  60 value 82.320204
iter  70 value 81.802143
iter  80 value 81.053890
iter  90 value 80.778169
iter 100 value 80.720172
final  value 80.720172 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.544569 
iter  10 value 94.055887
iter  20 value 89.184321
iter  30 value 87.175357
iter  40 value 85.352100
iter  50 value 85.170796
iter  60 value 84.151517
iter  70 value 83.713039
iter  80 value 83.272422
iter  90 value 82.746692
iter 100 value 82.679888
final  value 82.679888 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 101.994582 
iter  10 value 94.051685
iter  20 value 88.641568
iter  30 value 86.440551
iter  40 value 85.492547
iter  50 value 84.890727
iter  60 value 84.463492
final  value 84.463377 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.082730 
iter  10 value 93.117675
iter  20 value 87.741781
iter  30 value 86.057628
iter  40 value 85.640514
iter  50 value 85.593775
final  value 85.593619 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.126580 
iter  10 value 94.056149
iter  20 value 87.934931
iter  30 value 87.159390
iter  40 value 85.413295
iter  50 value 85.307812
iter  60 value 85.210266
iter  70 value 85.194116
final  value 85.194067 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.101593 
iter  10 value 94.058305
iter  20 value 93.982031
iter  30 value 93.404334
iter  40 value 88.215860
iter  50 value 86.994194
iter  60 value 86.314374
iter  70 value 84.367918
iter  80 value 83.210426
iter  90 value 82.766235
iter 100 value 82.582467
final  value 82.582467 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 99.588967 
iter  10 value 94.082609
iter  20 value 93.890229
iter  30 value 93.043853
iter  40 value 90.274894
iter  50 value 87.101490
iter  60 value 85.301068
iter  70 value 84.238870
iter  80 value 83.306975
iter  90 value 82.577618
iter 100 value 81.857058
final  value 81.857058 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.598240 
iter  10 value 96.189965
iter  20 value 92.524587
iter  30 value 90.252644
iter  40 value 89.089560
iter  50 value 86.270405
iter  60 value 85.923435
iter  70 value 85.585012
iter  80 value 84.672859
iter  90 value 82.819829
iter 100 value 82.482044
final  value 82.482044 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 117.627073 
iter  10 value 93.600892
iter  20 value 88.696425
iter  30 value 85.925940
iter  40 value 83.405918
iter  50 value 82.736805
iter  60 value 82.090239
iter  70 value 81.962479
iter  80 value 81.937191
iter  90 value 81.817616
iter 100 value 81.566527
final  value 81.566527 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.209468 
iter  10 value 93.173604
iter  20 value 86.943726
iter  30 value 86.485218
iter  40 value 86.069593
iter  50 value 85.332502
iter  60 value 84.641274
iter  70 value 83.535422
iter  80 value 83.080984
iter  90 value 82.560767
iter 100 value 82.093989
final  value 82.093989 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.556388 
iter  10 value 94.069021
iter  20 value 91.960175
iter  30 value 86.794488
iter  40 value 85.718244
iter  50 value 85.598674
iter  60 value 85.545436
iter  70 value 85.044560
iter  80 value 84.532362
iter  90 value 83.376147
iter 100 value 82.643302
final  value 82.643302 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 119.435207 
iter  10 value 94.255118
iter  20 value 91.896195
iter  30 value 87.083337
iter  40 value 86.415375
iter  50 value 86.031509
iter  60 value 85.528287
iter  70 value 85.343305
iter  80 value 84.909185
iter  90 value 83.891001
iter 100 value 82.661303
final  value 82.661303 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 118.037356 
iter  10 value 93.995052
iter  20 value 91.707468
iter  30 value 86.467049
iter  40 value 86.210136
iter  50 value 85.552988
iter  60 value 82.811301
iter  70 value 82.146399
iter  80 value 82.008083
iter  90 value 81.892948
iter 100 value 81.683588
final  value 81.683588 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.603045 
iter  10 value 93.992929
iter  20 value 89.812607
iter  30 value 85.797663
iter  40 value 83.390816
iter  50 value 82.994558
iter  60 value 82.479268
iter  70 value 82.221703
iter  80 value 81.884092
iter  90 value 81.687318
iter 100 value 81.566125
final  value 81.566125 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 126.057573 
iter  10 value 94.291019
iter  20 value 90.546477
iter  30 value 88.136305
iter  40 value 85.642593
iter  50 value 84.498437
iter  60 value 83.339429
iter  70 value 83.215150
iter  80 value 82.822323
iter  90 value 82.294088
iter 100 value 81.775107
final  value 81.775107 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.304310 
iter  10 value 94.077838
iter  20 value 93.101509
iter  30 value 88.992876
iter  40 value 84.512008
iter  50 value 83.585376
iter  60 value 82.477830
iter  70 value 81.994653
iter  80 value 81.613037
iter  90 value 81.047766
iter 100 value 80.883109
final  value 80.883109 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 105.020357 
final  value 94.054680 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.869312 
final  value 94.054613 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.283055 
final  value 94.054556 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.421218 
iter  10 value 94.034917
iter  20 value 94.032361
iter  30 value 90.257308
iter  40 value 86.948421
final  value 86.938454 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.438013 
final  value 94.054870 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.879645 
iter  10 value 94.057697
iter  20 value 94.052997
iter  30 value 87.395788
iter  40 value 87.378004
iter  50 value 87.377189
iter  60 value 87.249762
iter  70 value 87.248680
iter  70 value 87.248680
final  value 87.248680 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.561259 
iter  10 value 94.057699
iter  20 value 94.023087
iter  30 value 89.065464
iter  40 value 87.119045
iter  50 value 86.931389
iter  60 value 86.930345
iter  70 value 86.930308
iter  70 value 86.930308
iter  70 value 86.930308
final  value 86.930308 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.654342 
iter  10 value 94.056843
iter  20 value 94.052908
iter  30 value 93.769688
iter  40 value 93.766238
iter  50 value 92.910757
iter  60 value 90.874139
iter  70 value 90.859700
iter  80 value 88.372396
iter  90 value 87.544089
iter 100 value 87.509102
final  value 87.509102 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 98.274494 
iter  10 value 94.057586
iter  20 value 91.552735
iter  30 value 86.809311
iter  40 value 86.784642
iter  50 value 86.783318
final  value 86.781628 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.054619 
iter  10 value 94.057738
iter  20 value 94.024664
iter  30 value 93.383295
final  value 93.371986 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.824087 
iter  10 value 94.041272
iter  20 value 94.034466
final  value 94.034083 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.252485 
iter  10 value 94.041330
iter  20 value 94.032552
iter  30 value 87.479140
iter  40 value 87.377278
iter  50 value 87.218161
iter  60 value 87.066513
iter  70 value 87.042218
iter  70 value 87.042218
iter  70 value 87.042218
final  value 87.042218 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.613791 
iter  10 value 94.060063
iter  20 value 94.020603
iter  30 value 92.041400
iter  40 value 90.508148
iter  50 value 90.431836
iter  60 value 90.431079
iter  70 value 90.259793
iter  80 value 89.731184
iter  90 value 89.077036
iter 100 value 84.549665
final  value 84.549665 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.295644 
iter  10 value 87.618905
iter  20 value 87.616425
iter  30 value 87.259920
iter  40 value 87.259439
iter  50 value 87.256994
iter  60 value 87.232772
final  value 87.232582 
converged
Fitting Repeat 5 

# weights:  507
initial  value 110.697138 
iter  10 value 93.207282
iter  20 value 90.954945
iter  30 value 90.729492
iter  40 value 90.727587
iter  50 value 90.721321
iter  60 value 90.716076
iter  70 value 90.714643
iter  80 value 90.714541
iter  90 value 90.714401
iter 100 value 90.713065
final  value 90.713065 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 128.913221 
iter  10 value 122.838249
iter  20 value 118.444788
iter  30 value 112.871781
iter  40 value 111.896981
iter  50 value 109.352753
iter  60 value 108.363050
iter  70 value 105.668210
iter  80 value 105.015793
iter  90 value 104.466541
iter 100 value 103.229909
final  value 103.229909 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 134.023610 
iter  10 value 117.961111
iter  20 value 117.772695
iter  30 value 110.274748
iter  40 value 109.808670
iter  50 value 106.836114
iter  60 value 105.948349
iter  70 value 105.439870
iter  80 value 105.212146
iter  90 value 104.988340
iter 100 value 104.937333
final  value 104.937333 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 140.070119 
iter  10 value 117.786477
iter  20 value 113.886030
iter  30 value 110.512080
iter  40 value 109.751493
iter  50 value 104.570209
iter  60 value 103.861541
iter  70 value 102.711026
iter  80 value 101.315311
iter  90 value 100.902068
iter 100 value 100.842487
final  value 100.842487 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 123.841837 
iter  10 value 118.051263
iter  20 value 114.636914
iter  30 value 109.459812
iter  40 value 108.750509
iter  50 value 108.501026
iter  60 value 108.361308
iter  70 value 104.943987
iter  80 value 103.960291
iter  90 value 101.808046
iter 100 value 101.355854
final  value 101.355854 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 137.663242 
iter  10 value 117.807336
iter  20 value 117.594623
iter  30 value 109.067876
iter  40 value 107.939425
iter  50 value 104.676817
iter  60 value 102.975415
iter  70 value 102.229714
iter  80 value 101.917442
iter  90 value 101.701760
iter 100 value 101.646323
final  value 101.646323 
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 -- Tue Jun  6 00:16:15 2023 
*********************************************** 
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 
 54.131   1.516  68.765