##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.20-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.20-bioc/R/site-library --timings HPiP_1.12.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/media/volume/teran2_disk/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck’
* using R version 4.4.2 (2024-10-31)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 13.2.0-23ubuntu4) 13.2.0
    GNU Fortran (Ubuntu 13.2.0-23ubuntu4) 13.2.0
* running under: Ubuntu 24.04.1 LTS
* using session charset: UTF-8
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.12.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
var_imp       26.097  0.422  26.531
FSmethod      25.711  0.272  25.989
corr_plot     24.653  0.125  24.950
pred_ensembel  9.448  0.181   8.649
enrichfindP    0.321  0.040  14.086
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE

Status: 3 NOTEs
See
  ‘/media/volume/teran2_disk/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.20-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/media/volume/teran2_disk/biocbuild/bbs-3.20-bioc/R/site-library’
* installing *source* package ‘HPiP’ ...
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R version 4.4.2 (2024-10-31) -- "Pile of Leaves"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

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

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

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

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

# weights:  103
initial  value 101.623993 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.098426 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.395975 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.275979 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.370765 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.216702 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.112379 
final  value 94.354396 
converged
Fitting Repeat 3 

# weights:  305
initial  value 112.029565 
iter  10 value 93.465505
iter  20 value 93.464286
iter  20 value 93.464286
iter  20 value 93.464286
final  value 93.464286 
converged
Fitting Repeat 4 

# weights:  305
initial  value 109.979767 
iter  10 value 94.401697
iter  20 value 91.543685
iter  30 value 86.686528
iter  40 value 86.196565
iter  50 value 86.108977
iter  60 value 84.961672
iter  70 value 83.214847
iter  80 value 82.912525
iter  90 value 82.749302
iter 100 value 82.578653
final  value 82.578653 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.433796 
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.460418 
iter  10 value 87.590965
final  value 87.590732 
converged
Fitting Repeat 2 

# weights:  507
initial  value 119.187477 
iter  10 value 94.354396
iter  10 value 94.354396
iter  10 value 94.354396
final  value 94.354396 
converged
Fitting Repeat 3 

# weights:  507
initial  value 110.337345 
final  value 94.354395 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.274149 
iter  10 value 93.312179
iter  20 value 93.010992
iter  30 value 93.009742
iter  40 value 92.994167
iter  50 value 92.990273
final  value 92.990260 
converged
Fitting Repeat 5 

# weights:  507
initial  value 111.867713 
final  value 94.449438 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.647095 
iter  10 value 94.486511
iter  20 value 94.321120
iter  30 value 94.114378
iter  40 value 94.082081
iter  50 value 93.650856
iter  60 value 89.535499
iter  70 value 87.718315
iter  80 value 87.159032
iter  90 value 86.802494
iter 100 value 86.700413
final  value 86.700413 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.265700 
iter  10 value 93.454369
iter  20 value 88.405683
iter  30 value 88.182492
iter  40 value 86.634908
iter  50 value 84.990221
iter  60 value 84.720294
final  value 84.715472 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.969142 
iter  10 value 94.521439
iter  20 value 94.426915
iter  30 value 94.176354
iter  40 value 93.715897
iter  50 value 93.649998
iter  60 value 93.619992
iter  70 value 93.609210
iter  80 value 90.310145
iter  90 value 88.611814
iter 100 value 88.017311
final  value 88.017311 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.671240 
iter  10 value 94.486382
iter  20 value 94.402407
iter  30 value 92.413736
iter  40 value 87.364068
iter  50 value 87.255252
iter  60 value 87.033562
iter  70 value 86.896964
iter  80 value 86.894970
final  value 86.894912 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.777281 
iter  10 value 94.290837
iter  20 value 92.915190
iter  30 value 90.579660
iter  40 value 89.197051
iter  50 value 87.253581
iter  60 value 86.033425
iter  70 value 84.973657
iter  80 value 84.903661
iter  90 value 84.879873
iter 100 value 84.720041
final  value 84.720041 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 108.591281 
iter  10 value 94.388664
iter  20 value 93.186913
iter  30 value 87.027017
iter  40 value 86.274326
iter  50 value 85.250949
iter  60 value 85.177620
iter  70 value 84.607560
iter  80 value 84.012032
iter  90 value 83.744147
iter 100 value 83.481377
final  value 83.481377 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 112.133910 
iter  10 value 94.560534
iter  20 value 94.098078
iter  30 value 90.417339
iter  40 value 88.237541
iter  50 value 88.198484
iter  60 value 86.048636
iter  70 value 84.980059
iter  80 value 84.673869
iter  90 value 84.464657
iter 100 value 84.048636
final  value 84.048636 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 124.412204 
iter  10 value 94.741793
iter  20 value 91.079842
iter  30 value 87.005652
iter  40 value 86.300209
iter  50 value 85.273298
iter  60 value 84.963083
iter  70 value 84.771800
iter  80 value 84.558015
iter  90 value 84.356675
iter 100 value 84.285185
final  value 84.285185 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 120.820378 
iter  10 value 95.064537
iter  20 value 94.483698
iter  30 value 94.009297
iter  40 value 92.766024
iter  50 value 92.500119
iter  60 value 89.898882
iter  70 value 87.403196
iter  80 value 86.629398
iter  90 value 85.583246
iter 100 value 83.846414
final  value 83.846414 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 122.263562 
iter  10 value 94.511328
iter  20 value 93.936715
iter  30 value 88.697616
iter  40 value 86.186944
iter  50 value 84.284138
iter  60 value 84.000388
iter  70 value 83.878941
iter  80 value 83.424879
iter  90 value 83.367619
iter 100 value 83.357111
final  value 83.357111 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 121.744185 
iter  10 value 94.964835
iter  20 value 90.757397
iter  30 value 87.310148
iter  40 value 86.453101
iter  50 value 85.546604
iter  60 value 85.098561
iter  70 value 84.614476
iter  80 value 83.981980
iter  90 value 83.742249
iter 100 value 83.710320
final  value 83.710320 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.130780 
iter  10 value 96.085594
iter  20 value 94.620030
iter  30 value 89.513475
iter  40 value 88.101941
iter  50 value 87.192026
iter  60 value 86.801239
iter  70 value 86.390786
iter  80 value 86.010212
iter  90 value 85.236151
iter 100 value 84.338179
final  value 84.338179 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.770579 
iter  10 value 90.639157
iter  20 value 87.371884
iter  30 value 86.100269
iter  40 value 85.608519
iter  50 value 85.252439
iter  60 value 84.892932
iter  70 value 84.637309
iter  80 value 84.418071
iter  90 value 84.077453
iter 100 value 83.811477
final  value 83.811477 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.100440 
iter  10 value 94.547403
iter  20 value 93.838706
iter  30 value 90.601374
iter  40 value 89.189299
iter  50 value 85.305224
iter  60 value 84.536317
iter  70 value 83.753621
iter  80 value 83.355727
iter  90 value 83.238971
iter 100 value 83.028511
final  value 83.028511 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.567988 
iter  10 value 95.463680
iter  20 value 94.384264
iter  30 value 89.908142
iter  40 value 87.882545
iter  50 value 87.416052
iter  60 value 85.932969
iter  70 value 84.611113
iter  80 value 84.199589
iter  90 value 83.942787
iter 100 value 83.596158
final  value 83.596158 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 109.820493 
final  value 94.485726 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.134008 
iter  10 value 94.356249
iter  20 value 94.354660
final  value 94.354487 
converged
Fitting Repeat 3 

# weights:  103
initial  value 114.131911 
final  value 94.485959 
converged
Fitting Repeat 4 

# weights:  103
initial  value 115.246099 
iter  10 value 93.921371
iter  20 value 93.839000
iter  30 value 93.838968
iter  40 value 93.838319
iter  50 value 93.837547
final  value 93.837469 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.365242 
final  value 94.486262 
converged
Fitting Repeat 1 

# weights:  305
initial  value 121.460137 
iter  10 value 94.488987
iter  20 value 94.484233
final  value 94.484213 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.606496 
iter  10 value 94.217337
iter  20 value 87.607218
iter  30 value 87.602445
iter  40 value 87.597122
iter  50 value 87.146950
iter  60 value 86.844727
final  value 86.844628 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.301490 
iter  10 value 94.359546
iter  20 value 93.734125
iter  30 value 87.990288
iter  40 value 85.911962
iter  50 value 85.663292
iter  60 value 85.610175
iter  70 value 85.167627
iter  80 value 83.221437
iter  90 value 83.185101
final  value 83.184643 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.543559 
iter  10 value 94.488839
iter  20 value 94.484222
iter  30 value 94.073136
final  value 94.053589 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.033692 
iter  10 value 94.489199
iter  20 value 94.484483
final  value 94.484474 
converged
Fitting Repeat 1 

# weights:  507
initial  value 126.887304 
iter  10 value 94.362363
iter  20 value 94.126847
iter  30 value 90.521843
iter  40 value 87.303601
iter  50 value 87.082879
iter  60 value 86.709716
iter  70 value 86.665283
iter  80 value 86.073394
iter  90 value 85.707457
iter 100 value 85.707204
final  value 85.707204 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.511176 
iter  10 value 94.492575
iter  20 value 94.435563
iter  30 value 87.710978
iter  40 value 85.812295
iter  50 value 84.931661
iter  60 value 84.886525
iter  70 value 84.886263
final  value 84.886101 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.173503 
iter  10 value 94.362477
iter  20 value 94.354771
iter  30 value 94.334861
iter  40 value 93.313997
iter  50 value 92.330726
iter  60 value 92.240164
iter  70 value 92.239605
iter  80 value 92.238917
iter  90 value 92.238376
iter 100 value 92.238229
final  value 92.238229 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 124.387510 
iter  10 value 94.490902
iter  20 value 91.485193
iter  30 value 87.685178
iter  30 value 87.685178
iter  30 value 87.685178
final  value 87.685178 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.544022 
iter  10 value 94.362461
iter  20 value 94.356307
iter  30 value 93.604307
final  value 93.600677 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.170787 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.226982 
final  value 94.046753 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.975018 
final  value 93.969041 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.164448 
iter  10 value 94.020213
iter  20 value 93.645436
final  value 93.642191 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.221274 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.980025 
iter  10 value 93.966932
final  value 93.963025 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.563205 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.979113 
final  value 93.671508 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.096133 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.327644 
final  value 94.008696 
converged
Fitting Repeat 1 

# weights:  507
initial  value 115.733941 
iter  10 value 93.976145
iter  20 value 93.783209
final  value 93.782932 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.373220 
iter  10 value 94.039042
iter  20 value 89.593532
iter  30 value 87.509759
final  value 87.508032 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.004483 
iter  10 value 89.954205
iter  20 value 87.606522
iter  30 value 87.594531
iter  30 value 87.594530
iter  30 value 87.594530
final  value 87.594530 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.607138 
iter  10 value 92.170393
iter  20 value 90.261623
iter  30 value 87.472866
iter  40 value 87.156478
iter  50 value 86.981241
iter  60 value 84.558175
iter  70 value 84.453932
iter  80 value 84.444145
iter  80 value 84.444144
iter  80 value 84.444144
final  value 84.444144 
converged
Fitting Repeat 5 

# weights:  507
initial  value 114.807518 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.837915 
iter  10 value 94.081355
iter  20 value 94.054907
iter  30 value 94.013076
iter  40 value 92.901146
iter  50 value 92.063448
iter  60 value 91.722020
iter  70 value 89.742045
iter  80 value 88.078907
iter  90 value 87.772788
iter 100 value 86.013827
final  value 86.013827 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 98.036074 
iter  10 value 94.124687
iter  20 value 93.903000
iter  30 value 93.744530
iter  40 value 93.598280
iter  50 value 89.855234
iter  60 value 87.333872
iter  70 value 86.012698
iter  80 value 85.885100
final  value 85.881237 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.369410 
iter  10 value 93.182973
iter  20 value 89.074396
iter  30 value 88.876269
iter  40 value 88.334140
iter  50 value 85.856730
iter  60 value 85.854010
iter  70 value 85.853563
iter  80 value 85.852596
final  value 85.852529 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.653717 
iter  10 value 94.042300
iter  20 value 87.153131
iter  30 value 86.743325
iter  40 value 86.108336
iter  50 value 85.881681
iter  60 value 85.852740
final  value 85.852528 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.330687 
iter  10 value 93.992429
iter  20 value 86.959818
iter  30 value 86.326786
iter  40 value 86.086542
iter  50 value 85.989628
iter  60 value 85.893492
iter  70 value 85.852806
iter  80 value 85.852573
final  value 85.852563 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.566706 
iter  10 value 94.540946
iter  20 value 94.195660
iter  30 value 93.248300
iter  40 value 91.601773
iter  50 value 89.408296
iter  60 value 86.297203
iter  70 value 84.908195
iter  80 value 83.644790
iter  90 value 83.386572
iter 100 value 82.973736
final  value 82.973736 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.438663 
iter  10 value 94.289977
iter  20 value 89.163543
iter  30 value 84.819379
iter  40 value 84.121370
iter  50 value 83.526623
iter  60 value 83.249474
iter  70 value 82.855565
iter  80 value 82.768310
iter  90 value 82.569522
iter 100 value 82.397885
final  value 82.397885 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 133.521928 
iter  10 value 94.135937
iter  20 value 88.955517
iter  30 value 87.848804
iter  40 value 86.412740
iter  50 value 84.757120
iter  60 value 84.502320
iter  70 value 84.304390
iter  80 value 84.034624
iter  90 value 83.881963
iter 100 value 83.598911
final  value 83.598911 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.408768 
iter  10 value 90.222875
iter  20 value 89.065543
iter  30 value 86.560994
iter  40 value 85.497084
iter  50 value 84.764915
iter  60 value 84.411262
iter  70 value 83.829207
iter  80 value 83.229845
iter  90 value 82.258560
iter 100 value 82.032061
final  value 82.032061 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.628387 
iter  10 value 93.488353
iter  20 value 89.561116
iter  30 value 87.559112
iter  40 value 85.711561
iter  50 value 84.311234
iter  60 value 83.389317
iter  70 value 82.677684
iter  80 value 82.490014
iter  90 value 82.377491
iter 100 value 82.325435
final  value 82.325435 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.563787 
iter  10 value 94.037114
iter  20 value 93.950961
iter  30 value 87.885485
iter  40 value 86.517922
iter  50 value 85.890693
iter  60 value 84.547574
iter  70 value 83.384568
iter  80 value 83.160805
iter  90 value 83.037114
iter 100 value 82.934933
final  value 82.934933 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 101.570897 
iter  10 value 94.854800
iter  20 value 87.359716
iter  30 value 86.755095
iter  40 value 84.623845
iter  50 value 83.903781
iter  60 value 83.716657
iter  70 value 83.493748
iter  80 value 83.075413
iter  90 value 82.914841
iter 100 value 82.358933
final  value 82.358933 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.780814 
iter  10 value 93.949440
iter  20 value 89.773048
iter  30 value 88.984811
iter  40 value 87.777180
iter  50 value 84.588632
iter  60 value 83.600925
iter  70 value 83.064185
iter  80 value 82.484985
iter  90 value 82.328296
iter 100 value 82.207585
final  value 82.207585 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.770534 
iter  10 value 94.122305
iter  20 value 88.854327
iter  30 value 85.730741
iter  40 value 85.065358
iter  50 value 84.788702
iter  60 value 84.278643
iter  70 value 83.689774
iter  80 value 83.322947
iter  90 value 82.698177
iter 100 value 82.501290
final  value 82.501290 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.194056 
iter  10 value 93.997583
iter  20 value 92.861550
iter  30 value 86.643509
iter  40 value 84.704774
iter  50 value 83.644508
iter  60 value 83.270263
iter  70 value 83.142426
iter  80 value 82.897764
iter  90 value 82.775732
iter 100 value 82.706104
final  value 82.706104 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.167540 
iter  10 value 94.054751
final  value 94.052919 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.494833 
final  value 94.056031 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.939444 
final  value 94.054476 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.354696 
final  value 94.054471 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.901939 
final  value 94.054198 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.902500 
iter  10 value 94.058093
iter  20 value 94.053550
final  value 94.053399 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.388060 
iter  10 value 94.056462
final  value 94.052929 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.095857 
iter  10 value 94.013564
iter  20 value 94.008787
iter  30 value 90.426671
iter  40 value 83.298339
iter  50 value 82.581373
iter  60 value 82.548394
iter  60 value 82.548393
final  value 82.548393 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.768214 
iter  10 value 93.976843
iter  20 value 93.973287
iter  30 value 93.966609
iter  40 value 93.965242
iter  50 value 88.104617
iter  60 value 87.511830
iter  70 value 87.511665
final  value 87.511491 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.819894 
iter  10 value 94.056291
iter  20 value 93.820394
iter  30 value 90.228078
iter  40 value 88.601551
iter  50 value 88.291304
iter  60 value 88.008846
iter  70 value 87.762388
iter  80 value 86.817413
iter  90 value 84.092172
iter 100 value 81.516813
final  value 81.516813 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 116.145609 
iter  10 value 93.527220
iter  20 value 92.794021
iter  30 value 91.686198
iter  40 value 86.084035
iter  50 value 86.080752
iter  60 value 85.697896
iter  70 value 85.692519
iter  80 value 85.687197
iter  80 value 85.687197
final  value 85.687197 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.849398 
iter  10 value 94.061081
iter  20 value 93.852560
iter  30 value 93.015681
iter  40 value 92.529216
iter  50 value 88.499746
iter  60 value 86.911998
iter  70 value 86.865155
iter  80 value 86.863150
iter  90 value 85.840543
iter 100 value 85.548933
final  value 85.548933 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 96.071878 
iter  10 value 94.060564
iter  20 value 93.920153
iter  30 value 93.708303
final  value 93.671669 
converged
Fitting Repeat 4 

# weights:  507
initial  value 118.566856 
iter  10 value 90.175285
iter  20 value 89.434639
iter  30 value 87.839685
iter  40 value 87.744782
iter  50 value 87.613619
iter  60 value 87.594275
iter  70 value 87.540653
iter  80 value 86.471739
iter  90 value 86.434996
iter 100 value 86.354947
final  value 86.354947 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.030388 
iter  10 value 94.016631
iter  20 value 94.010680
final  value 94.008759 
converged
Fitting Repeat 1 

# weights:  103
initial  value 94.432919 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.827630 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 109.537986 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.404300 
final  value 93.371808 
converged
Fitting Repeat 5 

# weights:  103
initial  value 108.526079 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.072116 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.616977 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.405353 
final  value 94.052926 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.437964 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.716748 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.655788 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 112.305126 
iter  10 value 93.519960
iter  10 value 93.519960
iter  10 value 93.519960
final  value 93.519960 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.272056 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 109.687967 
iter  10 value 93.766000
final  value 93.765896 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.728894 
final  value 93.836066 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.158687 
iter  10 value 94.045666
iter  20 value 88.353945
iter  30 value 86.977467
iter  40 value 85.039761
iter  50 value 83.250680
iter  60 value 81.798693
iter  70 value 81.256482
iter  80 value 80.913088
iter  90 value 80.620005
final  value 80.490919 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.443945 
iter  10 value 94.074583
iter  20 value 93.479054
iter  30 value 87.850291
iter  40 value 87.087899
iter  50 value 85.762418
iter  60 value 84.511496
iter  70 value 84.166624
iter  80 value 83.789232
iter  90 value 83.307521
iter 100 value 83.243733
final  value 83.243733 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.600906 
iter  10 value 94.057150
iter  20 value 93.977036
iter  30 value 89.287774
iter  40 value 84.459328
iter  50 value 83.782796
iter  60 value 83.270864
iter  70 value 83.229022
final  value 83.228882 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.459192 
iter  10 value 93.845535
iter  20 value 89.294670
iter  30 value 88.450092
iter  40 value 87.673605
iter  50 value 87.032964
iter  60 value 82.125016
iter  70 value 80.982012
iter  80 value 80.358960
iter  90 value 80.299330
final  value 80.299148 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.184073 
iter  10 value 94.056874
iter  20 value 93.846940
iter  30 value 90.991494
iter  40 value 89.356774
iter  50 value 85.677308
iter  60 value 85.007636
iter  70 value 84.772063
iter  80 value 84.477624
iter  90 value 84.342771
final  value 84.342610 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.347083 
iter  10 value 94.199277
iter  20 value 91.321055
iter  30 value 85.831313
iter  40 value 84.391513
iter  50 value 84.016822
iter  60 value 83.669673
iter  70 value 83.169527
iter  80 value 82.999136
iter  90 value 82.988214
iter 100 value 82.951739
final  value 82.951739 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.304137 
iter  10 value 94.211251
iter  20 value 89.086474
iter  30 value 85.300138
iter  40 value 82.970359
iter  50 value 82.810747
iter  60 value 82.726991
iter  70 value 81.933864
iter  80 value 80.356635
iter  90 value 79.929335
iter 100 value 79.896719
final  value 79.896719 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 107.632088 
iter  10 value 94.119144
iter  20 value 93.830144
iter  30 value 93.565131
iter  40 value 88.628359
iter  50 value 88.376403
iter  60 value 85.287372
iter  70 value 83.215587
iter  80 value 82.335285
iter  90 value 82.082557
iter 100 value 81.940248
final  value 81.940248 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 114.327817 
iter  10 value 93.934560
iter  20 value 87.975101
iter  30 value 85.230961
iter  40 value 84.800836
iter  50 value 83.748056
iter  60 value 81.335508
iter  70 value 80.068956
iter  80 value 79.468484
iter  90 value 79.378906
iter 100 value 79.210042
final  value 79.210042 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.628511 
iter  10 value 94.207284
iter  20 value 89.993876
iter  30 value 84.839807
iter  40 value 84.709536
iter  50 value 83.651913
iter  60 value 82.035073
iter  70 value 80.277094
iter  80 value 79.998944
iter  90 value 79.892607
iter 100 value 79.872450
final  value 79.872450 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.481802 
iter  10 value 94.534932
iter  20 value 88.569498
iter  30 value 84.409012
iter  40 value 84.078344
iter  50 value 83.896499
iter  60 value 83.375680
iter  70 value 81.309129
iter  80 value 80.587332
iter  90 value 79.664368
iter 100 value 79.195346
final  value 79.195346 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 127.956573 
iter  10 value 94.047151
iter  20 value 92.575683
iter  30 value 87.354051
iter  40 value 84.084589
iter  50 value 82.588758
iter  60 value 80.963229
iter  70 value 79.556370
iter  80 value 79.391988
iter  90 value 78.814165
iter 100 value 78.622188
final  value 78.622188 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.674596 
iter  10 value 93.879837
iter  20 value 92.473911
iter  30 value 86.772035
iter  40 value 83.902884
iter  50 value 82.413417
iter  60 value 81.634882
iter  70 value 80.634547
iter  80 value 80.130733
iter  90 value 79.942502
iter 100 value 79.754253
final  value 79.754253 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.567350 
iter  10 value 91.871810
iter  20 value 86.563488
iter  30 value 82.938608
iter  40 value 80.644309
iter  50 value 80.394898
iter  60 value 80.089257
iter  70 value 79.675259
iter  80 value 79.398336
iter  90 value 79.247546
iter 100 value 79.142397
final  value 79.142397 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.853145 
iter  10 value 93.997519
iter  20 value 88.522009
iter  30 value 86.528052
iter  40 value 83.405943
iter  50 value 81.703570
iter  60 value 80.623020
iter  70 value 79.724396
iter  80 value 79.040478
iter  90 value 78.852657
iter 100 value 78.721567
final  value 78.721567 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.017924 
final  value 94.054376 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.725721 
final  value 94.054438 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.018030 
final  value 93.837850 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.050378 
iter  10 value 93.767692
iter  20 value 93.734094
final  value 93.734088 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.111249 
iter  10 value 92.345659
iter  20 value 87.817881
iter  30 value 87.814412
iter  40 value 85.868874
iter  50 value 85.849249
iter  60 value 85.747779
iter  70 value 85.745259
iter  80 value 85.742555
final  value 85.740837 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.661856 
iter  10 value 94.056883
iter  20 value 92.798215
iter  30 value 83.396818
iter  40 value 81.915114
iter  50 value 79.691167
iter  60 value 78.758995
iter  70 value 78.671545
iter  80 value 78.671156
iter  90 value 78.671131
iter  90 value 78.671130
iter  90 value 78.671130
final  value 78.671130 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.340735 
iter  10 value 94.057836
iter  20 value 94.052925
iter  30 value 85.599552
iter  40 value 85.591923
iter  50 value 85.590713
iter  60 value 85.359686
iter  70 value 85.227965
iter  80 value 81.983061
iter  90 value 80.510544
iter 100 value 80.423929
final  value 80.423929 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.303213 
iter  10 value 93.770750
iter  20 value 91.522207
iter  30 value 86.583568
final  value 86.561699 
converged
Fitting Repeat 4 

# weights:  305
initial  value 126.985508 
iter  10 value 94.048646
iter  20 value 93.743566
iter  30 value 91.666981
iter  40 value 90.460080
iter  50 value 90.425355
iter  60 value 90.194165
iter  70 value 90.008978
iter  80 value 90.008779
iter  90 value 90.008097
final  value 90.008023 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.356842 
iter  10 value 93.770791
iter  20 value 93.536811
final  value 93.535671 
converged
Fitting Repeat 1 

# weights:  507
initial  value 111.987166 
iter  10 value 93.943758
iter  20 value 93.939534
iter  30 value 90.074741
iter  40 value 82.836887
iter  50 value 81.180702
iter  60 value 80.746985
final  value 80.741454 
converged
Fitting Repeat 2 

# weights:  507
initial  value 94.899065 
iter  10 value 92.382657
iter  20 value 87.754786
iter  30 value 86.941220
iter  40 value 86.928561
iter  50 value 85.611673
iter  60 value 85.463746
iter  70 value 85.462018
iter  80 value 85.457277
iter  90 value 85.454331
final  value 85.453905 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.961852 
iter  10 value 93.844251
iter  20 value 89.845434
iter  30 value 86.309130
iter  40 value 83.720432
iter  50 value 81.381358
iter  60 value 80.532245
iter  70 value 80.216022
iter  80 value 79.978162
iter  90 value 79.931142
iter 100 value 79.928621
final  value 79.928621 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 98.116084 
iter  10 value 92.627486
iter  20 value 83.444505
iter  30 value 83.438567
iter  40 value 83.434831
iter  50 value 83.432100
iter  60 value 83.350398
iter  70 value 83.320183
iter  80 value 83.318049
iter  90 value 83.317322
final  value 83.317254 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.666586 
iter  10 value 94.061356
iter  20 value 93.858499
iter  30 value 83.828814
iter  40 value 80.198893
iter  50 value 79.260787
iter  60 value 79.242066
iter  70 value 79.216659
iter  80 value 79.026632
iter  90 value 78.559313
iter 100 value 78.530606
final  value 78.530606 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.813148 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.751507 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.632096 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.224714 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.623670 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.404034 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.544925 
iter  10 value 94.275366
final  value 94.275362 
converged
Fitting Repeat 3 

# weights:  305
initial  value 108.603171 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.779935 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.510793 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 112.974982 
iter  10 value 93.210064
iter  20 value 83.847197
iter  30 value 82.651176
final  value 82.649363 
converged
Fitting Repeat 2 

# weights:  507
initial  value 115.013553 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 115.902195 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.952864 
iter  10 value 85.238490
iter  20 value 81.464384
iter  30 value 81.271486
iter  40 value 81.270042
final  value 81.269954 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.455270 
final  value 94.286550 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.862410 
iter  10 value 94.660046
iter  20 value 94.442301
iter  30 value 94.316852
iter  40 value 94.284678
iter  50 value 85.000153
iter  60 value 84.040825
iter  70 value 82.376443
iter  80 value 80.972883
iter  90 value 80.022394
iter 100 value 79.649328
final  value 79.649328 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 98.372920 
iter  10 value 94.192014
iter  20 value 89.938196
iter  30 value 83.980812
iter  40 value 83.163991
iter  50 value 79.901736
iter  60 value 79.338059
iter  70 value 79.251432
iter  80 value 79.208902
final  value 79.208858 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.478006 
iter  10 value 94.345570
iter  20 value 91.952088
iter  30 value 83.202286
iter  40 value 82.354330
iter  50 value 82.098433
iter  60 value 82.011515
iter  70 value 81.887136
final  value 81.884195 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.397080 
iter  10 value 94.488496
iter  20 value 93.897177
iter  30 value 86.951681
iter  40 value 86.231447
iter  50 value 85.180139
iter  60 value 82.631052
final  value 82.624739 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.980257 
iter  10 value 94.498582
iter  20 value 94.342965
iter  30 value 90.861087
iter  40 value 89.583549
iter  50 value 89.437725
iter  60 value 85.665513
iter  70 value 82.862750
iter  80 value 80.821321
iter  90 value 80.074487
iter 100 value 79.916951
final  value 79.916951 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 102.303272 
iter  10 value 94.687529
iter  20 value 94.330934
iter  30 value 93.163272
iter  40 value 84.025941
iter  50 value 82.797375
iter  60 value 82.614616
iter  70 value 81.089525
iter  80 value 80.140829
iter  90 value 79.961843
iter 100 value 79.659294
final  value 79.659294 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.630950 
iter  10 value 94.487984
iter  20 value 92.417277
iter  30 value 85.357847
iter  40 value 81.629261
iter  50 value 80.700331
iter  60 value 79.841761
iter  70 value 79.164909
iter  80 value 79.063953
iter  90 value 78.808589
iter 100 value 78.701074
final  value 78.701074 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 109.218725 
iter  10 value 94.407286
iter  20 value 86.198931
iter  30 value 83.114703
iter  40 value 82.638226
iter  50 value 80.251789
iter  60 value 79.793555
iter  70 value 79.531734
iter  80 value 79.364563
iter  90 value 78.729897
iter 100 value 78.147368
final  value 78.147368 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.021974 
iter  10 value 94.954802
iter  20 value 94.487361
iter  30 value 94.289117
iter  40 value 86.564060
iter  50 value 83.735692
iter  60 value 82.626079
iter  70 value 82.069995
iter  80 value 81.830290
iter  90 value 80.138952
iter 100 value 79.322410
final  value 79.322410 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.338818 
iter  10 value 94.113473
iter  20 value 87.876688
iter  30 value 84.950445
iter  40 value 84.502368
iter  50 value 83.984164
iter  60 value 82.072794
iter  70 value 79.269232
iter  80 value 79.040616
iter  90 value 78.865549
iter 100 value 78.758805
final  value 78.758805 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 136.988336 
iter  10 value 94.385429
iter  20 value 86.155019
iter  30 value 82.329916
iter  40 value 80.531958
iter  50 value 79.985766
iter  60 value 79.823799
iter  70 value 79.703311
iter  80 value 79.471284
iter  90 value 79.281773
iter 100 value 78.596608
final  value 78.596608 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.052846 
iter  10 value 93.274917
iter  20 value 86.720776
iter  30 value 85.314492
iter  40 value 82.674805
iter  50 value 80.660738
iter  60 value 79.107705
iter  70 value 78.068906
iter  80 value 77.636033
iter  90 value 77.358659
iter 100 value 77.134735
final  value 77.134735 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.129831 
iter  10 value 95.670396
iter  20 value 89.811845
iter  30 value 84.978440
iter  40 value 81.474870
iter  50 value 79.821789
iter  60 value 78.688571
iter  70 value 78.547755
iter  80 value 78.346262
iter  90 value 77.906845
iter 100 value 77.752956
final  value 77.752956 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.576772 
iter  10 value 94.643923
iter  20 value 88.135193
iter  30 value 86.623865
iter  40 value 84.970680
iter  50 value 83.378540
iter  60 value 79.462578
iter  70 value 78.536119
iter  80 value 78.236357
iter  90 value 78.148312
iter 100 value 78.078260
final  value 78.078260 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 112.333623 
iter  10 value 94.517838
iter  20 value 92.755779
iter  30 value 89.705271
iter  40 value 86.400314
iter  50 value 81.949887
iter  60 value 81.435161
iter  70 value 79.958579
iter  80 value 78.683118
iter  90 value 78.269191
iter 100 value 77.720789
final  value 77.720789 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.712023 
final  value 94.485860 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.552329 
final  value 94.485762 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.000124 
final  value 94.485918 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.164039 
iter  10 value 94.177927
final  value 94.167580 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.432036 
final  value 94.486034 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.277903 
iter  10 value 94.489570
iter  20 value 94.478840
iter  30 value 93.849501
iter  40 value 85.248546
iter  50 value 84.594704
iter  60 value 84.588208
iter  70 value 84.222272
iter  80 value 84.218604
iter  90 value 79.107185
iter 100 value 78.502774
final  value 78.502774 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 96.003864 
iter  10 value 92.418621
iter  20 value 92.380958
iter  30 value 81.715054
iter  40 value 81.629839
iter  50 value 81.159374
iter  60 value 81.156314
iter  70 value 81.156185
final  value 81.156184 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.515174 
iter  10 value 94.466549
iter  20 value 94.432908
iter  30 value 90.267122
iter  40 value 85.399323
iter  50 value 85.293787
iter  60 value 83.439970
iter  70 value 82.793379
iter  80 value 82.790994
final  value 82.790905 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.113559 
iter  10 value 94.488868
iter  20 value 94.337942
iter  30 value 87.697228
iter  40 value 82.999077
iter  50 value 82.650915
final  value 82.650816 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.402091 
iter  10 value 94.489323
iter  20 value 94.484642
iter  30 value 94.254621
iter  30 value 94.254621
iter  30 value 94.254621
final  value 94.254621 
converged
Fitting Repeat 1 

# weights:  507
initial  value 123.827600 
iter  10 value 94.344437
iter  20 value 85.761724
iter  30 value 85.454564
iter  40 value 85.279915
iter  50 value 82.432169
iter  60 value 80.419207
iter  70 value 80.409839
iter  80 value 80.385620
iter  90 value 80.212215
iter 100 value 79.945101
final  value 79.945101 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.444988 
iter  10 value 94.078095
iter  20 value 94.019620
final  value 94.018390 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.767367 
iter  10 value 94.051656
iter  20 value 93.773510
iter  30 value 93.767300
iter  40 value 93.764516
iter  50 value 93.763476
iter  60 value 92.014747
iter  70 value 87.280455
iter  80 value 86.985455
iter  90 value 86.835055
iter 100 value 86.810202
final  value 86.810202 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.996548 
iter  10 value 94.492965
iter  20 value 94.477124
final  value 94.165958 
converged
Fitting Repeat 5 

# weights:  507
initial  value 116.358679 
iter  10 value 94.283788
iter  20 value 93.875293
iter  30 value 82.993539
iter  40 value 82.769252
iter  50 value 82.755117
iter  60 value 80.757606
iter  70 value 80.609246
iter  80 value 80.606879
iter  90 value 80.603437
iter 100 value 80.603104
final  value 80.603104 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.144380 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.997239 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.398564 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.893747 
final  value 94.484137 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.107579 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.501843 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.054413 
iter  10 value 94.484405
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.206745 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.521485 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.170776 
final  value 94.484137 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.540116 
iter  10 value 93.861035
final  value 93.851932 
converged
Fitting Repeat 2 

# weights:  507
initial  value 94.980300 
iter  10 value 86.893524
iter  20 value 85.912989
final  value 85.912179 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.901257 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.500112 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.380346 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.456519 
iter  10 value 94.495121
iter  20 value 88.994675
iter  30 value 84.682170
iter  40 value 84.443061
iter  50 value 83.684721
iter  60 value 83.611510
final  value 83.611508 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.620368 
iter  10 value 94.348881
iter  20 value 91.848437
iter  30 value 88.054461
iter  40 value 84.027703
iter  50 value 82.491264
iter  60 value 82.219823
iter  70 value 81.353442
iter  80 value 80.975769
iter  90 value 80.511240
iter 100 value 80.259933
final  value 80.259933 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.158711 
iter  10 value 94.339325
iter  20 value 87.390473
iter  30 value 84.528193
iter  40 value 83.159203
iter  50 value 82.050494
iter  60 value 81.743240
iter  70 value 81.660146
iter  80 value 81.650401
final  value 81.650233 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.900063 
iter  10 value 94.484747
iter  20 value 87.234429
iter  30 value 84.263011
iter  40 value 83.198301
iter  50 value 82.491100
iter  60 value 81.836896
iter  70 value 81.768852
iter  80 value 81.638857
iter  90 value 81.283755
iter 100 value 80.546226
final  value 80.546226 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.458920 
iter  10 value 94.269310
iter  20 value 86.987894
iter  30 value 85.335811
iter  40 value 84.662910
iter  50 value 83.413886
iter  60 value 82.832302
iter  70 value 82.814553
iter  80 value 82.773329
iter  90 value 82.696229
iter 100 value 82.569256
final  value 82.569256 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 102.136233 
iter  10 value 94.380581
iter  20 value 90.364444
iter  30 value 86.090745
iter  40 value 82.538109
iter  50 value 81.367295
iter  60 value 80.969296
iter  70 value 80.820240
iter  80 value 80.173727
iter  90 value 79.828189
iter 100 value 79.443863
final  value 79.443863 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 120.858363 
iter  10 value 94.798125
iter  20 value 94.497491
iter  30 value 93.596172
iter  40 value 84.698348
iter  50 value 83.080597
iter  60 value 82.047270
iter  70 value 79.787317
iter  80 value 79.312589
iter  90 value 79.053234
iter 100 value 78.835011
final  value 78.835011 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 109.284783 
iter  10 value 94.251577
iter  20 value 83.463543
iter  30 value 82.688671
iter  40 value 82.510837
iter  50 value 80.952499
iter  60 value 79.434336
iter  70 value 79.128447
iter  80 value 78.779848
iter  90 value 78.585599
iter 100 value 78.543395
final  value 78.543395 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.794189 
iter  10 value 94.401729
iter  20 value 93.393237
iter  30 value 87.382956
iter  40 value 82.342563
iter  50 value 79.820549
iter  60 value 78.881861
iter  70 value 78.726669
iter  80 value 78.566182
iter  90 value 78.467991
iter 100 value 78.455603
final  value 78.455603 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 112.972701 
iter  10 value 94.484954
iter  20 value 90.075032
iter  30 value 87.342008
iter  40 value 80.904715
iter  50 value 79.634033
iter  60 value 79.109963
iter  70 value 78.955073
iter  80 value 78.900118
iter  90 value 78.872213
iter 100 value 78.870324
final  value 78.870324 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.860902 
iter  10 value 91.997061
iter  20 value 86.557532
iter  30 value 84.265656
iter  40 value 83.566683
iter  50 value 83.111433
iter  60 value 81.820917
iter  70 value 81.154940
iter  80 value 80.748761
iter  90 value 80.683312
iter 100 value 79.431851
final  value 79.431851 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.353198 
iter  10 value 95.860843
iter  20 value 92.130600
iter  30 value 85.608585
iter  40 value 84.211930
iter  50 value 83.163040
iter  60 value 80.731232
iter  70 value 79.620192
iter  80 value 78.943167
iter  90 value 78.633112
iter 100 value 78.530938
final  value 78.530938 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.147149 
iter  10 value 94.479662
iter  20 value 84.320826
iter  30 value 83.372175
iter  40 value 83.137499
iter  50 value 82.397642
iter  60 value 82.210782
iter  70 value 82.145434
iter  80 value 81.706163
iter  90 value 80.628458
iter 100 value 80.382660
final  value 80.382660 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.385952 
iter  10 value 94.452101
iter  20 value 93.887504
iter  30 value 87.071274
iter  40 value 84.070659
iter  50 value 83.395379
iter  60 value 83.151382
iter  70 value 82.548349
iter  80 value 81.793453
iter  90 value 80.870908
iter 100 value 80.109714
final  value 80.109714 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 121.738968 
iter  10 value 94.515645
iter  20 value 94.461278
iter  30 value 92.212965
iter  40 value 91.513022
iter  50 value 83.851040
iter  60 value 81.285280
iter  70 value 81.003940
iter  80 value 80.692112
iter  90 value 80.601360
iter 100 value 80.558041
final  value 80.558041 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.601202 
iter  10 value 94.468530
iter  20 value 94.466861
iter  30 value 94.448984
iter  40 value 90.563019
iter  50 value 90.255603
iter  60 value 90.243355
final  value 90.243153 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.195409 
iter  10 value 94.485853
iter  20 value 94.484068
iter  30 value 94.440715
iter  40 value 91.819890
iter  50 value 91.807948
iter  60 value 91.148331
iter  70 value 91.146163
final  value 91.144803 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.105197 
final  value 94.430557 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.266574 
final  value 94.486004 
converged
Fitting Repeat 5 

# weights:  103
initial  value 108.963690 
final  value 94.486147 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.483122 
iter  10 value 94.488628
iter  20 value 94.483534
iter  30 value 82.406995
iter  40 value 81.391634
iter  50 value 81.273402
iter  60 value 81.272778
final  value 81.272776 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.392481 
iter  10 value 94.471956
iter  20 value 94.467248
iter  30 value 93.938694
iter  40 value 91.673883
iter  50 value 91.365463
iter  60 value 91.310327
iter  70 value 91.306355
iter  80 value 91.300763
iter  90 value 84.110673
iter 100 value 83.763221
final  value 83.763221 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 95.555084 
iter  10 value 94.488457
iter  20 value 93.931631
iter  30 value 82.317041
iter  40 value 81.636244
iter  50 value 81.593284
iter  60 value 80.852302
iter  70 value 80.849832
iter  80 value 80.847623
iter  90 value 80.843704
iter 100 value 80.462413
final  value 80.462413 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 116.506813 
iter  10 value 94.488944
iter  20 value 94.209854
iter  30 value 92.707216
iter  40 value 92.607188
iter  50 value 92.606993
iter  60 value 92.605415
iter  70 value 92.387471
iter  80 value 91.928486
iter  90 value 91.927619
iter 100 value 91.884154
final  value 91.884154 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.275764 
iter  10 value 94.481412
iter  20 value 93.144918
iter  30 value 87.534902
iter  40 value 83.502143
iter  50 value 83.276794
iter  60 value 82.145250
iter  70 value 82.056842
final  value 82.036940 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.188644 
iter  10 value 94.492523
iter  20 value 94.484844
iter  30 value 84.549124
final  value 83.983390 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.344794 
iter  10 value 94.437109
iter  20 value 87.126699
iter  30 value 86.960779
iter  40 value 85.817247
iter  50 value 85.146177
final  value 85.146145 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.234372 
iter  10 value 94.475151
iter  20 value 94.470401
iter  30 value 94.466980
iter  40 value 94.138188
iter  50 value 84.133069
iter  60 value 82.203999
iter  70 value 82.195471
final  value 82.195326 
converged
Fitting Repeat 4 

# weights:  507
initial  value 107.198495 
iter  10 value 94.439421
iter  20 value 93.649014
iter  30 value 93.642061
iter  40 value 93.639470
iter  50 value 93.638144
iter  60 value 86.388249
iter  70 value 84.158089
iter  80 value 84.080987
iter  90 value 84.080104
iter 100 value 84.078600
final  value 84.078600 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 96.763920 
iter  10 value 94.475177
iter  20 value 91.659453
iter  30 value 91.655521
iter  40 value 91.643685
iter  50 value 91.502040
iter  60 value 90.908218
iter  70 value 90.816192
iter  80 value 90.801604
iter  90 value 90.270253
iter 100 value 90.176957
final  value 90.176957 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 131.490033 
iter  10 value 118.801237
iter  20 value 110.448014
iter  30 value 104.421986
iter  40 value 102.856241
iter  50 value 102.486906
iter  60 value 101.810208
iter  70 value 101.560248
iter  80 value 100.913724
iter  90 value 100.773908
iter 100 value 100.726228
final  value 100.726228 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 128.183025 
iter  10 value 120.471022
iter  20 value 117.623163
iter  30 value 108.307935
iter  40 value 107.392715
iter  50 value 107.298289
iter  60 value 105.717495
iter  70 value 104.797927
iter  80 value 103.325610
iter  90 value 101.199460
iter 100 value 100.532128
final  value 100.532128 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 126.886641 
iter  10 value 118.058679
iter  20 value 117.342239
iter  30 value 109.390970
iter  40 value 106.395509
iter  50 value 105.747197
iter  60 value 103.506239
iter  70 value 101.686398
iter  80 value 101.448508
iter  90 value 101.302630
iter 100 value 101.106358
final  value 101.106358 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 142.969529 
iter  10 value 117.931132
iter  20 value 116.952106
iter  30 value 109.105095
iter  40 value 107.321465
iter  50 value 103.298108
iter  60 value 103.100424
iter  70 value 101.980615
iter  80 value 101.679454
iter  90 value 101.467761
iter 100 value 101.176732
final  value 101.176732 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 127.230264 
iter  10 value 117.726156
iter  20 value 107.399090
iter  30 value 105.895983
iter  40 value 105.627968
iter  50 value 103.599421
iter  60 value 102.356921
iter  70 value 101.942970
iter  80 value 101.176400
iter  90 value 101.054879
iter 100 value 100.992626
final  value 100.992626 
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 -- Wed Nov 20 04:30:26 2024 
*********************************************** 
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 
Warning messages:
1: `repeats` has no meaning for this resampling method. 
2: executing %dopar% sequentially: no parallel backend registered 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
 30.925   0.777  44.218