##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.17-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.17-bioc/R/site-library --timings HPiP_1.5.4.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.17-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2023-02-14 r83833)
* using platform: x86_64-pc-linux-gnu (64-bit)
* R was compiled by
    gcc (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0
    GNU Fortran (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0
* running under: Ubuntu 20.04.6 LTS
* using session charset: UTF-8
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.5.4’
* 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       37.092  1.040  38.135
corr_plot     34.246  0.824  35.553
FSmethod      33.841  0.663  35.611
pred_ensembel 14.083  0.474  11.038
enrichfindP    0.450  0.060  51.329
getFASTA       0.099  0.012   5.003
* 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-3.17-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.17-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.17-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 Under development (unstable) (2023-02-14 r83833) -- "Unsuffered Consequences"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: x86_64-pc-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
avNNet
Loading required package: ggplot2
Loading required package: lattice
Fitting Repeat 1 

# weights:  103
initial  value 103.578215 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.644600 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.240499 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.505991 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.764134 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.621620 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 112.171737 
iter  10 value 94.484212
iter  10 value 94.484211
iter  10 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.398139 
final  value 93.701657 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.399810 
iter  10 value 94.300330
iter  20 value 92.214593
iter  30 value 92.210364
iter  40 value 92.209883
iter  40 value 92.209883
iter  40 value 92.209883
final  value 92.209883 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.518173 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.591302 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.924153 
iter  10 value 94.264859
iter  10 value 94.264858
iter  10 value 94.264858
final  value 94.264858 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.005810 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.912252 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 109.319849 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 110.039822 
iter  10 value 94.490802
iter  20 value 94.314270
iter  30 value 91.388358
iter  40 value 88.847313
iter  50 value 88.376297
iter  60 value 87.032344
iter  70 value 87.027402
final  value 87.027397 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.796018 
iter  10 value 94.486407
iter  20 value 91.672509
iter  30 value 87.940720
iter  40 value 87.579687
iter  50 value 87.120950
iter  60 value 87.034115
iter  70 value 87.028063
final  value 87.028058 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.690460 
iter  10 value 94.457641
iter  20 value 86.509918
iter  30 value 85.871352
iter  40 value 85.788541
iter  50 value 85.711258
iter  60 value 85.668123
final  value 85.664386 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.934361 
iter  10 value 94.487789
iter  20 value 91.417510
iter  30 value 90.094788
iter  40 value 87.662679
iter  50 value 87.143327
iter  60 value 87.027658
final  value 87.027398 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.545769 
iter  10 value 89.809294
iter  20 value 87.701294
iter  30 value 84.355170
iter  40 value 84.154475
iter  50 value 83.903932
iter  60 value 83.715249
iter  70 value 83.544814
iter  80 value 83.520464
final  value 83.520417 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.959514 
iter  10 value 94.434756
iter  20 value 86.928385
iter  30 value 84.979074
iter  40 value 84.714269
iter  50 value 84.004426
iter  60 value 83.385202
iter  70 value 83.088686
iter  80 value 83.065377
iter  90 value 83.035601
iter 100 value 82.989469
final  value 82.989469 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.126689 
iter  10 value 94.493703
iter  20 value 93.100488
iter  30 value 89.274620
iter  40 value 86.822070
iter  50 value 85.144969
iter  60 value 84.377431
iter  70 value 84.162127
iter  80 value 83.512962
iter  90 value 83.103771
iter 100 value 82.912107
final  value 82.912107 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.072941 
iter  10 value 94.490130
iter  20 value 87.951517
iter  30 value 86.743744
iter  40 value 86.018576
iter  50 value 85.858620
iter  60 value 84.688913
iter  70 value 84.045740
iter  80 value 83.930018
iter  90 value 83.862596
iter 100 value 83.768187
final  value 83.768187 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.762943 
iter  10 value 94.500675
iter  20 value 90.451649
iter  30 value 84.954207
iter  40 value 84.274969
iter  50 value 83.872585
iter  60 value 83.820605
iter  70 value 83.764156
iter  80 value 83.517260
iter  90 value 83.349401
iter 100 value 82.983733
final  value 82.983733 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.130417 
iter  10 value 94.355753
iter  20 value 90.038560
iter  30 value 86.221823
iter  40 value 85.859354
iter  50 value 85.024005
iter  60 value 83.546968
iter  70 value 83.221941
iter  80 value 82.987285
iter  90 value 82.754689
iter 100 value 82.459950
final  value 82.459950 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 111.350864 
iter  10 value 94.526991
iter  20 value 89.665615
iter  30 value 85.422061
iter  40 value 84.803747
iter  50 value 83.854713
iter  60 value 83.336723
iter  70 value 82.889131
iter  80 value 82.509519
iter  90 value 82.350927
iter 100 value 82.261015
final  value 82.261015 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.619631 
iter  10 value 93.638789
iter  20 value 88.883512
iter  30 value 86.503988
iter  40 value 85.342196
iter  50 value 85.119971
iter  60 value 84.846201
iter  70 value 84.117713
iter  80 value 83.627407
iter  90 value 83.084876
iter 100 value 82.776675
final  value 82.776675 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 129.320924 
iter  10 value 94.565523
iter  20 value 91.848748
iter  30 value 89.020534
iter  40 value 86.100891
iter  50 value 85.005229
iter  60 value 84.536537
iter  70 value 84.150510
iter  80 value 83.692429
iter  90 value 82.500206
iter 100 value 82.246728
final  value 82.246728 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 119.633336 
iter  10 value 95.931207
iter  20 value 91.791111
iter  30 value 86.393810
iter  40 value 84.835607
iter  50 value 83.645961
iter  60 value 82.883050
iter  70 value 82.814729
iter  80 value 82.663121
iter  90 value 82.405281
iter 100 value 82.306657
final  value 82.306657 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 134.501667 
iter  10 value 96.564636
iter  20 value 86.870998
iter  30 value 85.634470
iter  40 value 83.783408
iter  50 value 83.087012
iter  60 value 82.899365
iter  70 value 82.759898
iter  80 value 82.495280
iter  90 value 82.360395
iter 100 value 82.270838
final  value 82.270838 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.212283 
final  value 94.430393 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.153097 
iter  10 value 94.485735
iter  20 value 94.355535
iter  30 value 89.636503
iter  40 value 88.898332
iter  50 value 85.986688
iter  60 value 85.977603
final  value 85.977514 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.161197 
iter  10 value 94.430970
iter  20 value 94.293708
iter  30 value 94.159456
final  value 94.157650 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.786517 
final  value 94.485885 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.469371 
final  value 94.485656 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.609189 
iter  10 value 94.491947
iter  20 value 93.985430
iter  30 value 90.849789
iter  40 value 90.845292
iter  50 value 90.844573
iter  60 value 90.843935
final  value 90.843916 
converged
Fitting Repeat 2 

# weights:  305
initial  value 124.819231 
iter  10 value 94.489495
iter  20 value 94.350835
iter  30 value 87.131207
iter  40 value 87.071627
iter  50 value 84.932790
iter  60 value 83.390225
iter  70 value 83.235569
iter  80 value 83.076419
iter  90 value 83.075824
iter 100 value 83.046365
final  value 83.046365 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.245640 
iter  10 value 87.109908
iter  20 value 87.081095
final  value 87.080076 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.028663 
iter  10 value 87.042671
iter  20 value 86.744211
iter  30 value 86.742249
final  value 86.742142 
converged
Fitting Repeat 5 

# weights:  305
initial  value 123.023449 
iter  10 value 94.280286
iter  20 value 94.277497
iter  30 value 88.872471
iter  40 value 88.707105
iter  50 value 88.703817
iter  60 value 85.487452
iter  70 value 85.331492
iter  70 value 85.331491
iter  70 value 85.331491
final  value 85.331491 
converged
Fitting Repeat 1 

# weights:  507
initial  value 128.770886 
iter  10 value 94.283514
iter  20 value 94.277348
iter  30 value 94.275484
final  value 94.275472 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.455947 
iter  10 value 94.217371
iter  20 value 94.210450
iter  30 value 94.076188
iter  40 value 88.008386
iter  50 value 85.488946
iter  60 value 85.343592
iter  70 value 85.331393
iter  80 value 85.331272
iter  90 value 85.330671
iter  90 value 85.330671
final  value 85.330671 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.468743 
iter  10 value 93.702060
iter  20 value 93.452305
iter  30 value 93.450558
iter  40 value 93.449908
iter  50 value 93.448783
iter  60 value 92.841901
iter  70 value 89.662741
final  value 89.662432 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.993821 
iter  10 value 94.491762
iter  20 value 93.367989
iter  30 value 83.588556
iter  40 value 83.368624
iter  50 value 83.274068
final  value 83.274041 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.935015 
iter  10 value 90.090510
iter  20 value 90.026317
iter  30 value 89.970043
iter  40 value 89.685346
iter  50 value 89.648392
final  value 89.648000 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.999473 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.359474 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.209889 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.539716 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.524684 
final  value 93.867391 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.373138 
iter  10 value 93.737832
iter  20 value 92.522433
iter  30 value 92.522048
final  value 92.522043 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.011113 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.711412 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.024530 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 111.392435 
final  value 94.052909 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.366960 
iter  10 value 92.475116
iter  20 value 83.706335
iter  30 value 83.662316
final  value 83.661890 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.679057 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.508973 
iter  10 value 89.537940
iter  20 value 89.059100
iter  30 value 88.448897
final  value 88.448880 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.099033 
iter  10 value 91.645844
iter  20 value 88.449509
iter  30 value 86.898054
iter  40 value 86.895935
final  value 86.895932 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.412772 
final  value 93.867391 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.192318 
iter  10 value 93.936734
iter  20 value 92.134489
iter  30 value 91.051057
iter  40 value 90.742831
iter  50 value 90.527834
final  value 90.517269 
converged
Fitting Repeat 2 

# weights:  103
initial  value 115.916962 
iter  10 value 94.866273
iter  20 value 94.049686
iter  30 value 90.157164
iter  40 value 88.394038
iter  50 value 84.722115
iter  60 value 83.397785
iter  70 value 83.012190
iter  80 value 82.970736
final  value 82.962702 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.788237 
iter  10 value 94.090697
iter  20 value 94.056736
iter  30 value 94.035111
iter  40 value 87.859136
iter  50 value 85.029112
iter  60 value 84.024417
iter  70 value 83.203038
iter  80 value 82.646357
iter  90 value 82.528926
final  value 82.528662 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.035836 
iter  10 value 93.951449
iter  20 value 88.442019
iter  30 value 86.822134
iter  40 value 84.552900
iter  50 value 83.153397
iter  60 value 82.688870
iter  70 value 82.399980
iter  80 value 82.015791
final  value 82.015781 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.718100 
iter  10 value 94.064434
iter  20 value 94.052955
iter  30 value 84.532641
iter  40 value 84.247880
iter  50 value 82.193278
iter  60 value 80.471688
iter  70 value 80.411566
iter  80 value 79.985842
final  value 79.984018 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.024087 
iter  10 value 94.314698
iter  20 value 85.158372
iter  30 value 83.816941
iter  40 value 81.193817
iter  50 value 79.695910
iter  60 value 79.571515
iter  70 value 79.003661
iter  80 value 78.758368
iter  90 value 78.716963
iter 100 value 78.706820
final  value 78.706820 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.504311 
iter  10 value 92.440781
iter  20 value 85.281099
iter  30 value 84.079382
iter  40 value 83.815242
iter  50 value 83.011977
iter  60 value 81.375903
iter  70 value 79.871908
iter  80 value 79.094943
iter  90 value 79.012527
iter 100 value 78.849169
final  value 78.849169 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 112.507307 
iter  10 value 95.109476
iter  20 value 85.793346
iter  30 value 84.796634
iter  40 value 84.313543
iter  50 value 84.201169
iter  60 value 82.650619
iter  70 value 79.606811
iter  80 value 79.163493
iter  90 value 78.836068
iter 100 value 78.684904
final  value 78.684904 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.381291 
iter  10 value 93.866933
iter  20 value 81.632949
iter  30 value 81.031326
iter  40 value 80.018783
iter  50 value 79.345347
iter  60 value 79.015938
iter  70 value 78.966942
iter  80 value 78.935963
iter  90 value 78.574423
iter 100 value 78.341915
final  value 78.341915 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.019455 
iter  10 value 94.231697
iter  20 value 93.935229
iter  30 value 87.104957
iter  40 value 84.775777
iter  50 value 83.716447
iter  60 value 83.155086
iter  70 value 80.571686
iter  80 value 78.997436
iter  90 value 78.725941
iter 100 value 78.655677
final  value 78.655677 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.972979 
iter  10 value 99.714158
iter  20 value 95.522147
iter  30 value 94.069707
iter  40 value 93.077924
iter  50 value 92.017630
iter  60 value 83.676863
iter  70 value 81.014376
iter  80 value 80.182826
iter  90 value 80.097010
iter 100 value 79.767184
final  value 79.767184 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.195100 
iter  10 value 94.464936
iter  20 value 88.651975
iter  30 value 85.688810
iter  40 value 84.335957
iter  50 value 83.789219
iter  60 value 80.532351
iter  70 value 79.616220
iter  80 value 79.334388
iter  90 value 78.641513
iter 100 value 78.519672
final  value 78.519672 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.805288 
iter  10 value 95.117452
iter  20 value 90.454489
iter  30 value 86.254611
iter  40 value 83.066668
iter  50 value 82.806556
iter  60 value 82.513391
iter  70 value 81.508272
iter  80 value 81.176745
iter  90 value 81.023280
iter 100 value 80.924571
final  value 80.924571 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.675111 
iter  10 value 94.840803
iter  20 value 93.119136
iter  30 value 91.449560
iter  40 value 89.518050
iter  50 value 85.283703
iter  60 value 84.960337
iter  70 value 83.205877
iter  80 value 82.888186
iter  90 value 82.417077
iter 100 value 80.901771
final  value 80.901771 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 143.581045 
iter  10 value 94.800062
iter  20 value 86.480367
iter  30 value 83.944084
iter  40 value 82.948124
iter  50 value 81.892895
iter  60 value 79.109956
iter  70 value 78.859587
iter  80 value 78.705614
iter  90 value 78.650595
iter 100 value 78.598474
final  value 78.598474 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.377302 
final  value 94.054400 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.368338 
final  value 94.054308 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.271904 
final  value 94.056913 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.634485 
iter  10 value 85.309348
final  value 84.095402 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.532289 
iter  10 value 93.520130
iter  20 value 89.737896
iter  30 value 87.634575
iter  40 value 87.206250
iter  50 value 84.413126
iter  60 value 84.359894
iter  70 value 84.358879
iter  80 value 84.343047
iter  90 value 83.179554
final  value 83.178525 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.033437 
iter  10 value 94.058270
iter  20 value 94.047596
final  value 93.867466 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.126284 
iter  10 value 94.057769
iter  20 value 93.902084
iter  30 value 86.548683
iter  40 value 86.022669
iter  50 value 83.353737
iter  60 value 83.097448
final  value 83.095996 
converged
Fitting Repeat 3 

# weights:  305
initial  value 123.592107 
iter  10 value 93.873462
iter  20 value 93.869337
iter  30 value 86.580486
iter  40 value 85.933889
iter  50 value 85.932941
iter  50 value 85.932940
iter  50 value 85.932940
final  value 85.932940 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.671455 
iter  10 value 94.057923
iter  20 value 93.905292
iter  30 value 92.266809
iter  40 value 91.566191
iter  50 value 83.980085
iter  60 value 83.492770
iter  70 value 83.336394
iter  80 value 83.336260
iter  90 value 83.335338
final  value 83.335283 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.673742 
iter  10 value 93.436018
iter  20 value 92.840407
iter  30 value 92.834475
iter  40 value 92.833380
iter  50 value 92.831625
final  value 92.831443 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.465570 
iter  10 value 92.121459
iter  20 value 91.525711
iter  30 value 85.842222
iter  40 value 83.993459
iter  50 value 83.992076
iter  60 value 83.991660
iter  70 value 83.986796
iter  80 value 81.971656
iter  90 value 80.278647
iter 100 value 79.273616
final  value 79.273616 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 98.185290 
iter  10 value 94.057563
iter  20 value 93.542051
iter  30 value 93.540694
final  value 93.540683 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.445764 
iter  10 value 93.748843
iter  20 value 93.714389
iter  30 value 93.709420
iter  40 value 93.706086
iter  50 value 90.424791
iter  60 value 87.271253
iter  70 value 87.257939
iter  80 value 87.257105
iter  90 value 87.094300
iter 100 value 86.146704
final  value 86.146704 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 116.385047 
iter  10 value 93.875653
iter  20 value 93.786431
iter  30 value 92.874464
iter  40 value 92.831774
iter  50 value 92.830434
iter  60 value 92.830364
final  value 92.830267 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.614623 
iter  10 value 93.519554
iter  20 value 93.237029
iter  30 value 93.233279
iter  40 value 93.230685
iter  50 value 93.229129
final  value 93.229007 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.208750 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.990203 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.161921 
final  value 94.026542 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.324149 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.600839 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.269300 
iter  10 value 93.776741
iter  10 value 93.776741
final  value 93.776721 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.134432 
final  value 93.320225 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.606146 
final  value 94.026542 
converged
Fitting Repeat 4 

# weights:  305
initial  value 113.782504 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 112.226958 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 152.859187 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.202773 
iter  10 value 93.788077
iter  10 value 93.788076
iter  10 value 93.788076
final  value 93.788076 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.170316 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.280029 
final  value 94.472273 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.595904 
final  value 94.026542 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.693635 
iter  10 value 94.258955
iter  20 value 93.514087
iter  30 value 84.112106
iter  40 value 82.842248
iter  50 value 82.188802
iter  60 value 81.390848
iter  70 value 81.101459
final  value 81.101451 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.194278 
iter  10 value 94.462105
iter  20 value 90.877996
iter  30 value 89.148644
iter  40 value 82.717173
iter  50 value 81.183219
iter  60 value 81.073184
final  value 81.073035 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.631517 
iter  10 value 94.529667
iter  20 value 91.606588
iter  30 value 86.985729
iter  40 value 81.760168
iter  50 value 80.980164
iter  60 value 80.729763
iter  70 value 80.667372
final  value 80.667281 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.827267 
iter  10 value 94.454270
iter  20 value 94.003491
iter  30 value 93.734396
iter  40 value 87.108040
iter  50 value 84.876004
iter  60 value 83.165828
iter  70 value 81.652419
iter  80 value 81.328895
iter  90 value 81.268677
iter 100 value 81.266830
final  value 81.266830 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 102.824195 
iter  10 value 94.486591
iter  20 value 93.630644
iter  30 value 86.550836
iter  40 value 85.159553
iter  50 value 84.966065
iter  60 value 84.616920
iter  70 value 80.494538
iter  80 value 79.770977
iter  90 value 79.279589
iter 100 value 79.110072
final  value 79.110072 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 116.077085 
iter  10 value 94.811475
iter  20 value 93.873807
iter  30 value 91.547651
iter  40 value 91.000369
iter  50 value 90.724977
iter  60 value 90.634248
iter  70 value 87.578794
iter  80 value 81.318312
iter  90 value 79.909994
iter 100 value 78.285164
final  value 78.285164 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.521407 
iter  10 value 94.280328
iter  20 value 89.946064
iter  30 value 89.627486
iter  40 value 86.038437
iter  50 value 82.026995
iter  60 value 80.800953
iter  70 value 79.953163
iter  80 value 79.617837
iter  90 value 79.511475
iter 100 value 79.284138
final  value 79.284138 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.138477 
iter  10 value 91.773348
iter  20 value 84.760175
iter  30 value 84.345387
iter  40 value 81.430605
iter  50 value 79.443315
iter  60 value 78.887244
iter  70 value 78.499346
iter  80 value 78.215950
iter  90 value 77.995237
iter 100 value 77.986165
final  value 77.986165 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.676941 
iter  10 value 94.247575
iter  20 value 83.941294
iter  30 value 82.473356
iter  40 value 80.065596
iter  50 value 78.703860
iter  60 value 78.351504
iter  70 value 78.145264
iter  80 value 77.949851
iter  90 value 77.920935
iter 100 value 77.916901
final  value 77.916901 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.342944 
iter  10 value 94.568899
iter  20 value 93.373501
iter  30 value 84.358663
iter  40 value 83.694549
iter  50 value 83.032393
iter  60 value 80.968168
iter  70 value 80.817083
iter  80 value 80.264198
iter  90 value 79.871907
iter 100 value 79.470245
final  value 79.470245 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 130.822436 
iter  10 value 94.755097
iter  20 value 92.619801
iter  30 value 89.056786
iter  40 value 83.569663
iter  50 value 82.668192
iter  60 value 79.884355
iter  70 value 78.677333
iter  80 value 78.260253
iter  90 value 77.979947
iter 100 value 77.690319
final  value 77.690319 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 136.898828 
iter  10 value 94.203966
iter  20 value 88.222691
iter  30 value 86.347524
iter  40 value 85.448298
iter  50 value 82.878054
iter  60 value 78.851260
iter  70 value 78.239423
iter  80 value 78.056617
iter  90 value 77.958912
iter 100 value 77.880108
final  value 77.880108 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.065181 
iter  10 value 94.249011
iter  20 value 85.069569
iter  30 value 82.505923
iter  40 value 81.252548
iter  50 value 80.735266
iter  60 value 80.559648
iter  70 value 80.491472
iter  80 value 79.251368
iter  90 value 77.747778
iter 100 value 77.424991
final  value 77.424991 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.268095 
iter  10 value 94.197397
iter  20 value 91.060463
iter  30 value 85.815025
iter  40 value 81.580773
iter  50 value 81.048282
iter  60 value 80.858566
iter  70 value 80.414797
iter  80 value 78.932101
iter  90 value 78.272608
iter 100 value 78.095311
final  value 78.095311 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 116.637791 
iter  10 value 94.452204
iter  20 value 93.316939
iter  30 value 83.125277
iter  40 value 81.055429
iter  50 value 79.378099
iter  60 value 79.201598
iter  70 value 79.092850
iter  80 value 78.758384
iter  90 value 78.236568
iter 100 value 77.922301
final  value 77.922301 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.425733 
final  value 94.485758 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.208893 
final  value 94.485852 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.994020 
iter  10 value 94.497913
final  value 94.495304 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.677194 
final  value 94.485786 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.621485 
iter  10 value 94.486116
iter  20 value 94.484231
final  value 94.484221 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.497664 
iter  10 value 94.488831
iter  20 value 94.484351
iter  30 value 93.788245
final  value 93.788242 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.663927 
iter  10 value 91.628317
iter  20 value 82.363594
iter  30 value 82.308127
iter  40 value 82.306394
iter  50 value 80.307968
iter  60 value 80.150931
iter  70 value 80.150483
iter  80 value 80.149327
iter  90 value 80.146818
iter 100 value 80.146715
final  value 80.146715 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 98.199036 
iter  10 value 94.489600
iter  20 value 94.313028
iter  30 value 94.031423
iter  40 value 94.027137
final  value 94.027084 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.790140 
iter  10 value 93.794539
iter  20 value 93.552440
final  value 93.322556 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.468692 
iter  10 value 94.489166
iter  20 value 94.484337
iter  30 value 91.800078
iter  40 value 82.285656
iter  50 value 80.458518
iter  60 value 80.305311
iter  70 value 80.297044
iter  80 value 80.289682
iter  90 value 80.162457
iter 100 value 79.439811
final  value 79.439811 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.096783 
iter  10 value 94.491955
iter  20 value 93.559006
iter  30 value 93.309248
final  value 93.308514 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.829066 
iter  10 value 91.160800
iter  20 value 91.044369
iter  30 value 91.042551
iter  40 value 91.039500
iter  50 value 91.037211
final  value 91.036790 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.987011 
iter  10 value 94.250492
iter  20 value 92.347108
iter  30 value 91.943265
iter  40 value 91.934433
iter  50 value 91.933405
iter  60 value 91.872984
iter  70 value 82.944229
iter  80 value 81.263556
iter  90 value 80.885027
iter 100 value 80.880325
final  value 80.880325 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.043550 
iter  10 value 94.491163
iter  20 value 90.929021
iter  30 value 82.905387
iter  30 value 82.905387
iter  30 value 82.905387
final  value 82.905387 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.465425 
iter  10 value 94.492625
iter  20 value 84.294138
iter  30 value 82.908050
iter  40 value 82.905673
iter  50 value 81.771198
iter  60 value 81.576427
iter  70 value 81.249963
final  value 81.235376 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.773656 
iter  10 value 93.463582
iter  20 value 83.688434
final  value 83.652697 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.349591 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.415325 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.831053 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.461598 
final  value 94.466822 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.452865 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.750991 
final  value 94.117498 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.671428 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.798090 
iter  10 value 94.144481
iter  10 value 94.144481
iter  10 value 94.144481
final  value 94.144481 
converged
Fitting Repeat 5 

# weights:  305
initial  value 111.794756 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 110.143361 
iter  10 value 94.484211
iter  10 value 94.484211
iter  10 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.431062 
iter  10 value 86.377238
iter  20 value 81.863103
iter  30 value 81.769304
iter  40 value 81.763316
final  value 81.762741 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.020537 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.807532 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 116.980104 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.105878 
iter  10 value 91.767326
iter  20 value 86.736091
iter  30 value 83.153882
iter  40 value 82.536557
iter  50 value 82.508220
iter  60 value 82.476426
final  value 82.476394 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.523246 
iter  10 value 93.537815
iter  20 value 84.747353
iter  30 value 82.571396
iter  40 value 82.527407
iter  50 value 82.477477
final  value 82.476394 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.494612 
iter  10 value 94.453359
iter  20 value 94.173230
iter  30 value 92.449054
iter  40 value 92.338014
iter  50 value 91.947420
iter  60 value 87.061916
final  value 87.052552 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.032296 
iter  10 value 94.426233
iter  20 value 87.956546
iter  30 value 86.056576
iter  40 value 85.812284
iter  50 value 85.442109
iter  60 value 85.307006
iter  70 value 82.482755
final  value 82.476394 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.348633 
iter  10 value 94.531806
iter  20 value 94.272538
iter  30 value 87.240837
iter  40 value 83.510273
iter  50 value 82.708017
iter  60 value 81.931779
iter  70 value 81.843984
iter  80 value 81.795635
iter  90 value 81.761104
iter 100 value 81.677047
final  value 81.677047 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 116.310785 
iter  10 value 94.506205
iter  20 value 84.041445
iter  30 value 83.030503
iter  40 value 82.840446
iter  50 value 82.267149
iter  60 value 82.178568
iter  70 value 82.147685
iter  80 value 81.981648
iter  90 value 81.016400
iter 100 value 80.825224
final  value 80.825224 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.771530 
iter  10 value 94.540972
iter  20 value 94.275739
iter  30 value 91.544499
iter  40 value 84.441581
iter  50 value 83.507889
iter  60 value 83.223649
iter  70 value 83.023186
iter  80 value 82.821303
iter  90 value 82.477319
iter 100 value 82.070628
final  value 82.070628 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 118.620802 
iter  10 value 94.395270
iter  20 value 89.656255
iter  30 value 85.201076
iter  40 value 82.608612
iter  50 value 81.935025
iter  60 value 81.567209
iter  70 value 81.191571
iter  80 value 80.353530
iter  90 value 80.176552
iter 100 value 80.143223
final  value 80.143223 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 118.148097 
iter  10 value 94.411981
iter  20 value 91.354111
iter  30 value 86.471224
iter  40 value 83.376322
iter  50 value 82.628865
iter  60 value 82.028397
iter  70 value 81.765872
iter  80 value 80.928506
iter  90 value 80.247371
iter 100 value 80.028551
final  value 80.028551 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.081295 
iter  10 value 94.453490
iter  20 value 90.356563
iter  30 value 86.534347
iter  40 value 83.674183
iter  50 value 81.314965
iter  60 value 80.958437
iter  70 value 80.733962
iter  80 value 80.515113
iter  90 value 80.287924
iter 100 value 80.186664
final  value 80.186664 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.432248 
iter  10 value 94.397535
iter  20 value 88.800328
iter  30 value 86.578256
iter  40 value 85.553814
iter  50 value 84.756161
iter  60 value 83.596767
iter  70 value 82.132545
iter  80 value 81.309490
iter  90 value 80.916119
iter 100 value 80.772577
final  value 80.772577 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.416126 
iter  10 value 94.455212
iter  20 value 90.332819
iter  30 value 84.629131
iter  40 value 82.765583
iter  50 value 82.076775
iter  60 value 82.019717
iter  70 value 81.650406
iter  80 value 81.101671
iter  90 value 80.836377
iter 100 value 80.533582
final  value 80.533582 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 118.555140 
iter  10 value 94.984748
iter  20 value 93.899440
iter  30 value 90.523657
iter  40 value 89.558420
iter  50 value 84.499005
iter  60 value 82.775646
iter  70 value 82.269943
iter  80 value 82.199764
iter  90 value 82.015373
iter 100 value 81.117045
final  value 81.117045 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.229931 
iter  10 value 95.221142
iter  20 value 87.222231
iter  30 value 85.426136
iter  40 value 83.057045
iter  50 value 82.430884
iter  60 value 82.098502
iter  70 value 81.537330
iter  80 value 81.232970
iter  90 value 81.110535
iter 100 value 81.051503
final  value 81.051503 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 115.809646 
iter  10 value 95.129375
iter  20 value 94.383070
iter  30 value 84.726303
iter  40 value 82.812281
iter  50 value 82.456569
iter  60 value 82.174088
iter  70 value 81.606374
iter  80 value 81.313031
iter  90 value 80.610162
iter 100 value 80.371027
final  value 80.371027 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.902648 
iter  10 value 94.485868
iter  20 value 94.484227
final  value 94.484221 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.660311 
final  value 94.485796 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.828921 
final  value 94.485814 
converged
Fitting Repeat 4 

# weights:  103
initial  value 110.917218 
iter  10 value 94.486122
final  value 94.484283 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.509025 
iter  10 value 94.468664
iter  20 value 94.467036
iter  30 value 83.349150
iter  40 value 82.484291
iter  50 value 81.767838
iter  60 value 81.766871
iter  70 value 81.633843
iter  80 value 80.662274
final  value 80.647066 
converged
Fitting Repeat 1 

# weights:  305
initial  value 120.830663 
iter  10 value 94.260026
iter  20 value 94.258417
iter  30 value 92.667900
iter  40 value 83.572261
iter  50 value 81.326477
final  value 81.326349 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.528013 
iter  10 value 94.488117
iter  20 value 94.458664
iter  30 value 94.002083
iter  40 value 93.693816
iter  50 value 93.693343
iter  60 value 93.693100
iter  70 value 93.691411
iter  80 value 93.456397
iter  90 value 85.079352
iter 100 value 85.058149
final  value 85.058149 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.699078 
iter  10 value 94.492090
iter  20 value 94.124751
iter  30 value 87.162754
iter  40 value 86.637306
iter  50 value 86.636735
iter  60 value 83.063317
iter  70 value 82.712286
iter  80 value 81.785203
iter  90 value 81.682772
iter 100 value 81.638849
final  value 81.638849 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.352857 
iter  10 value 94.488583
iter  20 value 94.396918
iter  30 value 94.147617
iter  40 value 94.147367
iter  50 value 94.146262
iter  60 value 94.118528
final  value 94.117606 
converged
Fitting Repeat 5 

# weights:  305
initial  value 110.885664 
iter  10 value 94.487957
iter  20 value 94.483444
final  value 94.466916 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.634940 
iter  10 value 94.492031
iter  20 value 94.329776
iter  30 value 87.143127
iter  40 value 82.228154
iter  50 value 81.170572
iter  60 value 81.037011
iter  70 value 81.011768
iter  80 value 81.003834
iter  90 value 80.952780
iter 100 value 80.189004
final  value 80.189004 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.140075 
iter  10 value 87.350788
iter  20 value 87.295288
iter  30 value 86.972634
iter  40 value 86.551776
iter  50 value 84.987136
iter  60 value 82.392596
iter  70 value 80.997790
iter  80 value 80.031892
iter  90 value 79.952609
iter 100 value 79.952223
final  value 79.952223 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 98.026721 
iter  10 value 94.475478
iter  20 value 91.414518
iter  30 value 85.100639
iter  40 value 85.094630
iter  50 value 82.809956
iter  60 value 82.099325
iter  70 value 82.088417
iter  80 value 81.044830
final  value 81.044799 
converged
Fitting Repeat 4 

# weights:  507
initial  value 109.273472 
iter  10 value 94.474705
iter  20 value 94.467419
iter  30 value 93.277708
iter  40 value 84.344405
iter  50 value 84.239924
iter  60 value 84.238121
iter  70 value 84.232304
iter  80 value 83.979433
iter  90 value 83.824130
iter 100 value 83.817196
final  value 83.817196 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 99.307952 
iter  10 value 94.488201
iter  20 value 91.869976
iter  30 value 91.078266
iter  40 value 87.167391
iter  50 value 82.185781
iter  60 value 81.923317
iter  70 value 80.894004
iter  80 value 80.777147
iter  90 value 80.775849
iter 100 value 80.774852
final  value 80.774852 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.536379 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.272118 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.359159 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.544843 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.839653 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.440923 
final  value 93.582418 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.124562 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 110.699601 
iter  10 value 93.523810
iter  10 value 93.523810
iter  10 value 93.523810
final  value 93.523810 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.294692 
final  value 94.033149 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.631701 
iter  10 value 88.430025
iter  20 value 87.713932
iter  30 value 87.665601
iter  30 value 87.665600
iter  30 value 87.665600
final  value 87.665600 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.946708 
iter  10 value 93.582419
iter  10 value 93.582418
iter  10 value 93.582418
final  value 93.582418 
converged
Fitting Repeat 2 

# weights:  507
initial  value 118.715916 
iter  10 value 93.570482
final  value 93.569788 
converged
Fitting Repeat 3 

# weights:  507
initial  value 108.362063 
final  value 93.356642 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.061335 
iter  10 value 86.310073
iter  20 value 83.995001
iter  30 value 83.972688
iter  40 value 83.972546
iter  50 value 83.972479
final  value 83.972454 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.101809 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.514114 
iter  10 value 94.082897
iter  20 value 94.052649
iter  30 value 92.224342
iter  40 value 88.848472
iter  50 value 86.495745
iter  60 value 86.213563
iter  70 value 86.159007
final  value 86.158457 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.888737 
iter  10 value 94.023420
iter  20 value 88.250027
iter  30 value 86.530909
iter  40 value 86.428989
final  value 86.408552 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.269028 
iter  10 value 94.056713
iter  20 value 88.038668
iter  30 value 86.385117
iter  40 value 86.307613
iter  50 value 86.095650
iter  60 value 85.514487
iter  70 value 85.361404
iter  80 value 84.773697
iter  90 value 84.361910
final  value 84.359656 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.231952 
iter  10 value 93.076013
iter  20 value 90.908054
iter  30 value 89.255635
iter  40 value 87.363594
iter  50 value 82.865990
iter  60 value 81.708183
iter  70 value 81.120930
final  value 81.114774 
converged
Fitting Repeat 5 

# weights:  103
initial  value 117.468544 
iter  10 value 94.098160
iter  20 value 93.995322
iter  30 value 89.301898
iter  40 value 88.824257
iter  50 value 87.873583
iter  60 value 87.484782
iter  70 value 86.686502
iter  80 value 85.593649
iter  90 value 85.235474
iter 100 value 85.030462
final  value 85.030462 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 109.138845 
iter  10 value 94.046774
iter  20 value 93.526602
iter  30 value 91.506607
iter  40 value 86.815529
iter  50 value 84.553029
iter  60 value 82.989200
iter  70 value 82.634043
iter  80 value 82.431570
iter  90 value 81.850101
iter 100 value 80.947291
final  value 80.947291 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.605291 
iter  10 value 93.544249
iter  20 value 86.106928
iter  30 value 84.722352
iter  40 value 84.553318
iter  50 value 84.445313
iter  60 value 83.537532
iter  70 value 81.997922
iter  80 value 81.013568
iter  90 value 80.720607
iter 100 value 80.160739
final  value 80.160739 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.226135 
iter  10 value 93.734518
iter  20 value 93.644700
iter  30 value 90.573841
iter  40 value 87.249989
iter  50 value 86.081702
iter  60 value 83.693369
iter  70 value 82.962780
iter  80 value 82.540279
iter  90 value 81.453819
iter 100 value 80.819617
final  value 80.819617 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.449495 
iter  10 value 93.968569
iter  20 value 92.829130
iter  30 value 88.202035
iter  40 value 85.814695
iter  50 value 84.092503
iter  60 value 82.397596
iter  70 value 80.993257
iter  80 value 80.156317
iter  90 value 79.779622
iter 100 value 79.483294
final  value 79.483294 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 119.433911 
iter  10 value 94.088486
iter  20 value 92.777918
iter  30 value 86.609626
iter  40 value 84.939462
iter  50 value 83.743857
iter  60 value 82.295228
iter  70 value 80.650258
iter  80 value 80.442288
iter  90 value 80.142537
iter 100 value 80.079935
final  value 80.079935 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.078608 
iter  10 value 95.520282
iter  20 value 94.098516
iter  30 value 93.873295
iter  40 value 93.472171
iter  50 value 93.350470
iter  60 value 91.138610
iter  70 value 85.938575
iter  80 value 82.726710
iter  90 value 82.210888
iter 100 value 81.138258
final  value 81.138258 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.316935 
iter  10 value 94.015122
iter  20 value 93.580576
iter  30 value 91.965617
iter  40 value 89.948324
iter  50 value 83.150435
iter  60 value 81.638382
iter  70 value 80.767286
iter  80 value 80.282914
iter  90 value 79.877498
iter 100 value 79.821188
final  value 79.821188 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 119.359864 
iter  10 value 94.063490
iter  20 value 88.151104
iter  30 value 86.621157
iter  40 value 84.708524
iter  50 value 81.645599
iter  60 value 80.657206
iter  70 value 80.221976
iter  80 value 79.959165
iter  90 value 79.876095
iter 100 value 79.735471
final  value 79.735471 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.161639 
iter  10 value 94.564540
iter  20 value 93.746395
iter  30 value 86.136990
iter  40 value 82.777114
iter  50 value 81.454559
iter  60 value 80.588695
iter  70 value 80.339425
iter  80 value 80.306871
iter  90 value 80.291095
iter 100 value 80.276988
final  value 80.276988 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.206933 
iter  10 value 94.008379
iter  20 value 90.713204
iter  30 value 90.330818
iter  40 value 86.526391
iter  50 value 85.510303
iter  60 value 84.031059
iter  70 value 83.957745
iter  80 value 83.814346
iter  90 value 82.987990
iter 100 value 81.019795
final  value 81.019795 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.776904 
iter  10 value 93.549276
iter  20 value 93.483411
final  value 93.482319 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.651404 
iter  10 value 94.054694
final  value 94.052919 
converged
Fitting Repeat 3 

# weights:  103
initial  value 93.594116 
iter  10 value 88.476144
final  value 88.467041 
converged
Fitting Repeat 4 

# weights:  103
initial  value 111.185980 
iter  10 value 94.054702
iter  20 value 93.990358
iter  30 value 93.274860
final  value 93.270038 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.153528 
final  value 94.054423 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.723481 
iter  10 value 89.828819
iter  20 value 88.470251
iter  30 value 88.465261
iter  40 value 88.464560
iter  50 value 86.283815
iter  60 value 86.001835
iter  70 value 85.994549
final  value 85.994533 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.657958 
iter  10 value 94.057366
iter  20 value 94.052893
iter  30 value 88.467495
final  value 88.466300 
converged
Fitting Repeat 3 

# weights:  305
initial  value 108.533512 
iter  10 value 93.492608
iter  20 value 93.486089
iter  30 value 93.287441
final  value 93.284642 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.698638 
iter  10 value 94.037788
iter  20 value 87.701715
iter  30 value 86.919540
iter  40 value 86.915979
final  value 86.915973 
converged
Fitting Repeat 5 

# weights:  305
initial  value 116.484408 
iter  10 value 93.361365
iter  20 value 92.863502
iter  30 value 90.361388
iter  40 value 90.360481
iter  50 value 90.360363
final  value 90.360330 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.326174 
iter  10 value 93.591074
iter  20 value 93.584988
final  value 93.583511 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.719952 
iter  10 value 93.549507
iter  20 value 93.354611
iter  30 value 93.352952
iter  40 value 93.350529
iter  50 value 93.336331
iter  60 value 93.274294
iter  70 value 93.273381
iter  80 value 93.270384
final  value 93.270125 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.662347 
iter  10 value 94.054518
iter  20 value 94.014597
iter  30 value 94.014308
final  value 94.014186 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.532290 
iter  10 value 93.148879
iter  20 value 92.123073
iter  30 value 91.902086
iter  40 value 91.540418
iter  50 value 91.439546
iter  60 value 91.398490
iter  70 value 91.397302
final  value 91.397082 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.189240 
iter  10 value 93.590734
iter  20 value 93.584667
final  value 93.584583 
converged
Fitting Repeat 1 

# weights:  103
initial  value 120.989180 
final  value 117.891785 
converged
Fitting Repeat 2 

# weights:  103
initial  value 126.088828 
final  value 117.891835 
converged
Fitting Repeat 3 

# weights:  103
initial  value 118.304161 
final  value 117.760342 
converged
Fitting Repeat 4 

# weights:  103
initial  value 134.078694 
final  value 117.891857 
converged
Fitting Repeat 5 

# weights:  103
initial  value 122.079792 
final  value 117.891912 
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 -- Wed Apr 12 06:56:43 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 
 44.200   2.147  85.836