##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:HPiP.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings HPiP_1.10.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck’
* using R version 4.4.0 (2024-04-24)
* using platform: x86_64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 12.2.0
* running under: macOS Monterey 12.7.1
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.10.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
var_imp       35.009  2.326  37.753
corr_plot     33.133  2.112  35.462
FSmethod      33.024  2.012  35.229
pred_ensembel 13.657  0.489  10.113
enrichfindP    0.533  0.070   9.530
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 3 NOTEs
See
  ‘/Users/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library’
* installing *source* package ‘HPiP’ ...
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R version 4.4.0 (2024-04-24) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20

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

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

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

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

# weights:  103
initial  value 94.347906 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.178403 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.000367 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.026257 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.916168 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.864565 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.876273 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.839830 
final  value 94.052911 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.254739 
final  value 94.042012 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.398891 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.190425 
iter  10 value 92.531739
iter  20 value 89.558388
iter  30 value 89.214308
iter  40 value 88.522731
iter  50 value 88.449152
final  value 88.449090 
converged
Fitting Repeat 2 

# weights:  507
initial  value 127.107618 
final  value 94.032967 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.642100 
iter  10 value 91.933601
iter  20 value 87.174176
iter  30 value 87.074055
iter  40 value 87.073748
final  value 87.073738 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.999052 
iter  10 value 91.405895
iter  20 value 90.553448
iter  30 value 90.208638
iter  40 value 90.170229
iter  50 value 90.158375
iter  60 value 90.157145
final  value 90.157143 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.913744 
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.675492 
iter  10 value 94.069493
iter  20 value 94.056192
iter  30 value 93.941645
iter  40 value 93.572222
iter  50 value 91.765791
iter  60 value 87.605802
iter  70 value 84.897902
iter  80 value 83.390891
iter  90 value 83.185347
iter 100 value 83.021064
final  value 83.021064 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 95.813021 
iter  10 value 93.477533
iter  20 value 89.163811
iter  30 value 84.672743
iter  40 value 83.954945
iter  50 value 83.417552
iter  60 value 83.097304
iter  70 value 82.967081
iter  80 value 82.710276
iter  90 value 82.641300
final  value 82.641297 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.824188 
iter  10 value 94.055727
iter  20 value 93.884718
iter  30 value 93.670238
iter  40 value 93.556004
iter  50 value 93.553831
iter  60 value 93.552662
iter  70 value 87.557544
iter  80 value 86.917115
iter  90 value 86.473665
iter 100 value 86.184375
final  value 86.184375 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 98.320063 
iter  10 value 94.067466
iter  20 value 94.008367
iter  30 value 93.750145
iter  40 value 93.613021
iter  50 value 87.633683
iter  60 value 84.284220
iter  70 value 83.535783
iter  80 value 82.800302
iter  90 value 82.658227
final  value 82.641297 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.233602 
iter  10 value 94.047590
iter  20 value 87.790445
iter  30 value 85.352625
iter  40 value 83.886246
iter  50 value 83.473017
iter  60 value 83.457522
final  value 83.457519 
converged
Fitting Repeat 1 

# weights:  305
initial  value 122.770313 
iter  10 value 94.115034
iter  20 value 92.683865
iter  30 value 86.274728
iter  40 value 84.414037
iter  50 value 82.520013
iter  60 value 82.088605
iter  70 value 81.889636
iter  80 value 81.703051
iter  90 value 81.521004
iter 100 value 81.368748
final  value 81.368748 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 116.201126 
iter  10 value 93.554414
iter  20 value 89.923954
iter  30 value 85.118633
iter  40 value 83.819349
iter  50 value 83.453845
iter  60 value 83.363854
iter  70 value 83.203384
iter  80 value 83.143903
iter  90 value 82.848403
iter 100 value 82.388416
final  value 82.388416 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.466888 
iter  10 value 94.183262
iter  20 value 90.878029
iter  30 value 84.162885
iter  40 value 83.288003
iter  50 value 83.067252
iter  60 value 82.395237
iter  70 value 82.215573
iter  80 value 82.074859
iter  90 value 81.936330
iter 100 value 81.931199
final  value 81.931199 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.945080 
iter  10 value 93.830324
iter  20 value 86.574989
iter  30 value 86.395588
iter  40 value 84.610208
iter  50 value 84.121950
iter  60 value 84.007980
iter  70 value 83.638412
iter  80 value 83.606148
iter  90 value 83.594488
iter 100 value 83.471108
final  value 83.471108 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 98.989719 
iter  10 value 94.057563
iter  20 value 92.734432
iter  30 value 89.061062
iter  40 value 88.525052
iter  50 value 88.335679
iter  60 value 85.589095
iter  70 value 85.168502
iter  80 value 83.400370
iter  90 value 82.359783
iter 100 value 82.151369
final  value 82.151369 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.300996 
iter  10 value 94.627541
iter  20 value 93.403018
iter  30 value 88.591358
iter  40 value 84.221897
iter  50 value 83.826298
iter  60 value 83.540030
iter  70 value 83.187691
iter  80 value 82.298458
iter  90 value 81.691265
iter 100 value 81.501762
final  value 81.501762 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 110.323602 
iter  10 value 93.822910
iter  20 value 87.590468
iter  30 value 85.440109
iter  40 value 83.640478
iter  50 value 82.651059
iter  60 value 82.250173
iter  70 value 81.906750
iter  80 value 81.504091
iter  90 value 81.356976
iter 100 value 81.242138
final  value 81.242138 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.381141 
iter  10 value 94.115124
iter  20 value 94.057176
iter  30 value 93.709276
iter  40 value 92.126678
iter  50 value 88.115205
iter  60 value 84.428886
iter  70 value 84.082740
iter  80 value 83.515972
iter  90 value 83.202560
iter 100 value 82.647704
final  value 82.647704 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 114.894129 
iter  10 value 93.568154
iter  20 value 90.205106
iter  30 value 87.274181
iter  40 value 84.695271
iter  50 value 83.333578
iter  60 value 82.324066
iter  70 value 82.232710
iter  80 value 82.059697
iter  90 value 81.946816
iter 100 value 81.844806
final  value 81.844806 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.150822 
iter  10 value 93.971868
iter  20 value 89.761686
iter  30 value 89.341623
iter  40 value 88.420413
iter  50 value 86.454412
iter  60 value 84.711838
iter  70 value 83.365070
iter  80 value 83.254614
iter  90 value 83.036384
iter 100 value 82.819847
final  value 82.819847 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 105.235805 
iter  10 value 94.054773
iter  20 value 93.796502
iter  30 value 89.668830
iter  40 value 89.318888
iter  50 value 89.036615
iter  60 value 88.878115
iter  70 value 88.693964
final  value 88.693739 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.126874 
final  value 94.056073 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.663243 
final  value 94.054659 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.088519 
final  value 94.054362 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.416130 
final  value 94.054431 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.442978 
iter  10 value 93.444450
iter  20 value 93.300479
iter  30 value 93.298425
iter  40 value 93.297498
final  value 93.295862 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.107857 
iter  10 value 94.037714
iter  20 value 93.852843
iter  30 value 93.600616
iter  40 value 93.513396
iter  50 value 93.473190
iter  60 value 87.761230
final  value 86.166662 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.556125 
iter  10 value 94.058060
iter  20 value 94.052951
iter  30 value 86.348136
iter  40 value 85.114295
iter  50 value 84.479387
iter  60 value 83.060162
iter  70 value 82.691697
iter  80 value 82.642984
iter  80 value 82.642984
final  value 82.642984 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.319774 
iter  10 value 94.057607
iter  20 value 94.025098
iter  30 value 93.526931
iter  40 value 92.588132
iter  50 value 88.406685
iter  60 value 87.503323
iter  70 value 86.679786
iter  80 value 86.422637
iter  90 value 86.301430
iter 100 value 85.221323
final  value 85.221323 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 94.204131 
iter  10 value 94.056499
iter  20 value 92.423189
iter  30 value 86.369961
final  value 86.005286 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.518902 
iter  10 value 94.041444
iter  20 value 94.033175
iter  30 value 92.002747
iter  40 value 84.267049
iter  50 value 82.101492
iter  60 value 81.735677
iter  70 value 81.633952
final  value 81.633437 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.128835 
iter  10 value 94.055166
iter  20 value 94.040953
iter  30 value 94.035231
iter  40 value 94.032998
iter  50 value 84.279605
iter  60 value 84.124288
iter  70 value 83.945032
iter  80 value 83.009506
iter  90 value 82.653340
iter 100 value 82.396807
final  value 82.396807 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 112.793969 
iter  10 value 93.181101
iter  20 value 91.997181
iter  30 value 91.994782
iter  40 value 91.897366
iter  50 value 91.893886
iter  60 value 91.872564
iter  70 value 91.848998
final  value 91.848958 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.730448 
iter  10 value 93.440806
iter  20 value 93.308618
iter  30 value 93.242187
iter  40 value 93.082041
iter  50 value 93.055580
iter  60 value 93.055232
iter  70 value 93.054749
iter  80 value 91.942941
iter  90 value 89.739124
iter 100 value 86.073049
final  value 86.073049 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 94.361577 
iter  10 value 93.540031
iter  20 value 93.433880
iter  30 value 93.259250
iter  40 value 92.465388
iter  50 value 92.150881
iter  60 value 92.149714
iter  70 value 92.059288
final  value 92.053947 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.710069 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 113.960661 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.235730 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 111.124961 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.744596 
final  value 94.325949 
converged
Fitting Repeat 1 

# weights:  305
initial  value 115.620216 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 116.978116 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.446463 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.668465 
iter  10 value 93.394962
final  value 93.394928 
converged
Fitting Repeat 5 

# weights:  305
initial  value 111.773766 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.695445 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.159212 
iter  10 value 92.079295
iter  20 value 86.127735
iter  30 value 85.757037
iter  40 value 84.589331
final  value 84.588745 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.623976 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 113.815792 
iter  10 value 93.394936
final  value 93.394928 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.764305 
iter  10 value 90.809519
iter  20 value 86.221188
final  value 86.061212 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.811205 
iter  10 value 94.476789
iter  20 value 81.824187
iter  30 value 81.647426
iter  40 value 81.399276
iter  50 value 80.204514
iter  60 value 79.577659
iter  70 value 79.563106
iter  70 value 79.563106
iter  70 value 79.563106
final  value 79.563106 
converged
Fitting Repeat 2 

# weights:  103
initial  value 109.773198 
iter  10 value 94.474101
iter  20 value 93.679195
iter  30 value 93.677673
iter  40 value 92.920047
iter  50 value 87.389638
iter  60 value 85.950621
iter  70 value 85.109004
iter  80 value 84.425633
iter  90 value 84.111192
final  value 84.107092 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.787071 
iter  10 value 88.348886
iter  20 value 86.214602
iter  30 value 86.088704
iter  40 value 85.494719
iter  50 value 84.694577
iter  60 value 84.108852
final  value 84.107092 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.453179 
iter  10 value 93.332324
iter  20 value 92.753261
iter  30 value 87.220800
iter  40 value 86.109317
iter  50 value 82.155359
iter  60 value 81.111737
iter  70 value 80.666290
iter  80 value 79.644206
iter  90 value 79.486104
iter 100 value 79.481855
final  value 79.481855 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 101.049575 
iter  10 value 92.542577
iter  20 value 90.455358
iter  30 value 90.425854
iter  40 value 85.434182
iter  50 value 82.805494
iter  60 value 81.861438
iter  70 value 80.102363
iter  80 value 79.565486
iter  90 value 79.563243
final  value 79.563107 
converged
Fitting Repeat 1 

# weights:  305
initial  value 122.960396 
iter  10 value 94.779242
iter  20 value 94.356002
iter  30 value 93.125035
iter  40 value 89.355925
iter  50 value 84.617071
iter  60 value 82.489125
iter  70 value 78.805987
iter  80 value 77.698001
iter  90 value 76.727300
iter 100 value 76.302199
final  value 76.302199 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.437033 
iter  10 value 90.498893
iter  20 value 84.863303
iter  30 value 81.107662
iter  40 value 77.776070
iter  50 value 77.444003
iter  60 value 76.949113
iter  70 value 76.788202
iter  80 value 76.774315
iter  90 value 76.768417
iter 100 value 76.767572
final  value 76.767572 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 107.429726 
iter  10 value 91.796477
iter  20 value 89.406681
iter  30 value 89.016646
iter  40 value 87.822140
iter  50 value 80.607855
iter  60 value 79.757041
iter  70 value 78.902158
iter  80 value 78.235266
iter  90 value 76.729631
iter 100 value 76.452174
final  value 76.452174 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 118.103889 
iter  10 value 93.579610
iter  20 value 91.443495
iter  30 value 82.500895
iter  40 value 80.842045
iter  50 value 80.118853
iter  60 value 78.985371
iter  70 value 77.601040
iter  80 value 77.225812
iter  90 value 76.960113
iter 100 value 76.920695
final  value 76.920695 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.128828 
iter  10 value 94.819789
iter  20 value 86.417645
iter  30 value 78.566619
iter  40 value 76.795846
iter  50 value 76.596044
iter  60 value 76.557665
iter  70 value 76.538225
iter  80 value 76.497274
iter  90 value 76.361033
iter 100 value 76.190934
final  value 76.190934 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.085282 
iter  10 value 91.839766
iter  20 value 89.261684
iter  30 value 86.608372
iter  40 value 81.463569
iter  50 value 79.549278
iter  60 value 79.159151
iter  70 value 78.577600
iter  80 value 77.871421
iter  90 value 77.661368
iter 100 value 76.797711
final  value 76.797711 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.492219 
iter  10 value 94.466414
iter  20 value 83.342609
iter  30 value 81.975365
iter  40 value 78.954366
iter  50 value 78.544888
iter  60 value 77.890225
iter  70 value 77.590938
iter  80 value 77.135499
iter  90 value 76.698559
iter 100 value 76.459377
final  value 76.459377 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 123.470599 
iter  10 value 93.887344
iter  20 value 92.511706
iter  30 value 82.347530
iter  40 value 81.462800
iter  50 value 80.032215
iter  60 value 78.213064
iter  70 value 77.824447
iter  80 value 76.759280
iter  90 value 76.524006
iter 100 value 76.398813
final  value 76.398813 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 124.807616 
iter  10 value 103.342879
iter  20 value 102.090553
iter  30 value 91.808420
iter  40 value 89.075649
iter  50 value 82.678535
iter  60 value 80.811482
iter  70 value 80.430170
iter  80 value 78.922828
iter  90 value 78.262051
iter 100 value 78.108934
final  value 78.108934 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 147.888024 
iter  10 value 95.433527
iter  20 value 93.740685
iter  30 value 89.858442
iter  40 value 80.211397
iter  50 value 78.404735
iter  60 value 77.521055
iter  70 value 77.347832
iter  80 value 77.145392
iter  90 value 77.061376
iter 100 value 77.045574
final  value 77.045574 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.163914 
iter  10 value 94.485341
final  value 94.484413 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.575319 
final  value 94.485828 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.050519 
final  value 94.485774 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.824365 
final  value 94.485928 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.274218 
final  value 94.485830 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.977450 
iter  10 value 94.488733
iter  20 value 94.187365
final  value 93.395731 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.837649 
iter  10 value 94.489334
iter  20 value 94.475725
iter  30 value 93.396594
iter  40 value 93.389520
iter  50 value 91.310613
iter  60 value 91.215082
iter  70 value 91.213776
iter  80 value 91.213281
iter  90 value 90.985381
iter 100 value 88.871671
final  value 88.871671 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 118.089916 
iter  10 value 89.913231
iter  20 value 88.789312
iter  30 value 88.613735
iter  40 value 88.607363
iter  50 value 88.599255
iter  60 value 88.433673
iter  70 value 88.433357
iter  80 value 88.389101
iter  90 value 87.995883
iter 100 value 87.994045
final  value 87.994045 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.112701 
iter  10 value 91.374712
iter  20 value 87.562583
iter  30 value 87.553974
iter  40 value 87.155291
final  value 87.152517 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.169372 
iter  10 value 89.641458
iter  20 value 89.635957
iter  30 value 89.632141
iter  40 value 80.084270
iter  50 value 79.308545
iter  60 value 77.014797
iter  70 value 75.651374
iter  80 value 75.143968
iter  90 value 74.694766
iter 100 value 74.651990
final  value 74.651990 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 126.741036 
iter  10 value 94.492611
iter  20 value 94.437912
iter  30 value 93.395508
iter  30 value 93.395508
iter  30 value 93.395508
final  value 93.395508 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.729287 
iter  10 value 93.405004
iter  20 value 93.403589
iter  30 value 93.395101
iter  40 value 90.789189
iter  50 value 83.238697
iter  60 value 83.187857
iter  70 value 78.426821
iter  80 value 77.522887
iter  90 value 77.130531
iter 100 value 77.094994
final  value 77.094994 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.429328 
iter  10 value 94.362571
iter  20 value 94.049152
iter  30 value 93.340057
iter  40 value 91.281930
iter  50 value 87.107686
iter  60 value 87.104506
iter  70 value 86.948465
iter  80 value 86.829080
iter  90 value 86.828895
iter 100 value 86.828699
final  value 86.828699 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 99.311313 
iter  10 value 94.492120
iter  20 value 93.805924
final  value 93.023048 
converged
Fitting Repeat 5 

# weights:  507
initial  value 115.746475 
iter  10 value 94.492519
iter  20 value 94.368411
iter  30 value 90.710161
iter  40 value 81.386325
iter  50 value 80.985156
iter  60 value 79.688491
iter  70 value 79.660232
iter  80 value 78.900261
iter  90 value 78.483806
iter 100 value 78.474654
final  value 78.474654 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.173915 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.901777 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.268754 
iter  10 value 91.696522
iter  20 value 91.371380
iter  30 value 91.323311
final  value 91.323278 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.509251 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.098236 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.330335 
iter  10 value 85.504000
iter  20 value 83.406771
final  value 83.406763 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.366252 
final  value 94.326054 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.470130 
final  value 93.567525 
converged
Fitting Repeat 4 

# weights:  305
initial  value 109.454961 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.956190 
iter  10 value 92.935178
final  value 92.934880 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.221899 
iter  10 value 93.551031
iter  20 value 93.322282
iter  30 value 93.245693
final  value 93.245666 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.247510 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.580123 
iter  10 value 93.331960
final  value 93.286554 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.398358 
iter  10 value 93.726272
iter  20 value 93.473012
final  value 93.472847 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.670965 
final  value 94.291892 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.602476 
iter  10 value 94.445074
iter  20 value 89.133112
iter  30 value 85.501992
iter  40 value 84.232809
iter  50 value 84.006986
iter  60 value 83.782965
iter  70 value 83.483931
iter  80 value 83.384452
iter  90 value 83.315138
final  value 83.315067 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.938055 
iter  10 value 92.906210
iter  20 value 84.297172
iter  30 value 83.750022
iter  40 value 83.534265
iter  50 value 82.973477
iter  60 value 82.775569
iter  70 value 82.712874
final  value 82.712427 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.099776 
iter  10 value 94.486475
iter  20 value 93.165676
iter  30 value 93.014386
iter  40 value 92.943397
iter  50 value 92.941502
iter  60 value 92.699093
iter  70 value 92.651444
iter  80 value 86.345224
iter  90 value 83.874356
iter 100 value 83.287005
final  value 83.287005 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.320763 
iter  10 value 94.430409
iter  20 value 93.498288
iter  30 value 91.484273
iter  40 value 84.723551
iter  50 value 83.731994
iter  60 value 83.259626
iter  70 value 82.731237
iter  80 value 82.715165
iter  90 value 82.713308
iter 100 value 82.712463
final  value 82.712463 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 101.515736 
iter  10 value 94.490794
iter  20 value 87.471218
iter  30 value 85.100089
iter  40 value 84.630664
iter  50 value 83.910904
iter  60 value 83.105900
iter  70 value 82.520093
final  value 82.519833 
converged
Fitting Repeat 1 

# weights:  305
initial  value 134.153719 
iter  10 value 94.483011
iter  20 value 93.087022
iter  30 value 85.117447
iter  40 value 83.745094
iter  50 value 82.240693
iter  60 value 81.290535
iter  70 value 80.153007
iter  80 value 79.807077
iter  90 value 79.280015
iter 100 value 79.066107
final  value 79.066107 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.535804 
iter  10 value 94.476632
iter  20 value 90.324214
iter  30 value 87.385596
iter  40 value 87.096695
iter  50 value 86.172750
iter  60 value 85.877522
iter  70 value 83.272042
iter  80 value 83.043367
iter  90 value 82.589456
iter 100 value 81.061922
final  value 81.061922 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 121.956284 
iter  10 value 94.527299
iter  20 value 94.326713
iter  30 value 86.571614
iter  40 value 84.573780
iter  50 value 83.574825
iter  60 value 83.454605
iter  70 value 81.682784
iter  80 value 80.820733
iter  90 value 80.397389
iter 100 value 80.005629
final  value 80.005629 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 118.716854 
iter  10 value 94.858904
iter  20 value 90.145939
iter  30 value 89.772718
iter  40 value 89.418103
iter  50 value 84.350841
iter  60 value 83.505874
iter  70 value 80.739666
iter  80 value 79.896911
iter  90 value 79.739027
iter 100 value 79.388971
final  value 79.388971 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 125.692158 
iter  10 value 94.436366
iter  20 value 91.878205
iter  30 value 89.379613
iter  40 value 87.231113
iter  50 value 82.766617
iter  60 value 81.978986
iter  70 value 81.031376
iter  80 value 80.633276
iter  90 value 80.182447
iter 100 value 80.027497
final  value 80.027497 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.957392 
iter  10 value 94.542823
iter  20 value 94.056447
iter  30 value 84.973850
iter  40 value 83.711646
iter  50 value 83.434849
iter  60 value 81.213360
iter  70 value 80.370194
iter  80 value 79.981657
iter  90 value 79.636501
iter 100 value 79.082174
final  value 79.082174 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 131.690945 
iter  10 value 101.949900
iter  20 value 87.167629
iter  30 value 85.415424
iter  40 value 83.499140
iter  50 value 83.148769
iter  60 value 81.231147
iter  70 value 80.117485
iter  80 value 79.645034
iter  90 value 79.279267
iter 100 value 78.876656
final  value 78.876656 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.457472 
iter  10 value 96.511618
iter  20 value 92.534876
iter  30 value 85.421436
iter  40 value 84.433018
iter  50 value 83.160458
iter  60 value 81.565545
iter  70 value 80.165884
iter  80 value 79.633801
iter  90 value 79.101920
iter 100 value 79.016947
final  value 79.016947 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 114.340397 
iter  10 value 96.171061
iter  20 value 88.060978
iter  30 value 83.723578
iter  40 value 83.237826
iter  50 value 82.267872
iter  60 value 81.330066
iter  70 value 80.683788
iter  80 value 79.636291
iter  90 value 79.237018
iter 100 value 78.936637
final  value 78.936637 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.331708 
iter  10 value 94.385498
iter  20 value 91.577954
iter  30 value 86.922876
iter  40 value 85.277388
iter  50 value 81.735441
iter  60 value 80.837046
iter  70 value 80.108824
iter  80 value 79.505260
iter  90 value 79.289900
iter 100 value 79.095684
final  value 79.095684 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.264637 
final  value 94.485945 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.972276 
final  value 94.431813 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.018641 
final  value 94.485781 
converged
Fitting Repeat 4 

# weights:  103
initial  value 119.257481 
final  value 94.485975 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.733745 
iter  10 value 94.486108
iter  20 value 94.484216
iter  20 value 94.484216
final  value 94.484216 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.137986 
iter  10 value 94.460168
iter  20 value 94.299243
iter  30 value 94.292009
iter  30 value 94.292009
final  value 94.292009 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.424373 
iter  10 value 94.488501
iter  20 value 94.160268
iter  30 value 86.138641
iter  40 value 86.088038
iter  50 value 86.044258
iter  60 value 86.026573
iter  70 value 86.017161
iter  80 value 85.937864
iter  90 value 85.927854
iter 100 value 85.836397
final  value 85.836397 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.199718 
iter  10 value 94.296549
iter  20 value 94.292295
iter  30 value 92.705580
iter  40 value 85.212185
final  value 84.632053 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.338967 
iter  10 value 86.617247
iter  20 value 83.840675
iter  30 value 82.261464
iter  40 value 82.156062
iter  50 value 82.056584
iter  60 value 82.056065
iter  70 value 81.959673
iter  80 value 81.061522
iter  90 value 78.636200
iter 100 value 78.029428
final  value 78.029428 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.350249 
iter  10 value 94.487829
iter  20 value 94.117562
iter  30 value 84.661496
iter  40 value 84.192892
iter  50 value 84.063719
iter  60 value 84.058726
iter  70 value 83.660567
iter  80 value 82.617356
iter  90 value 82.614680
iter 100 value 82.459754
final  value 82.459754 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 99.499691 
iter  10 value 94.492377
iter  20 value 94.484786
iter  30 value 93.452635
iter  40 value 93.050257
iter  50 value 84.322358
iter  60 value 83.220856
iter  70 value 83.023222
iter  80 value 82.990948
iter  90 value 82.954386
iter 100 value 82.899646
final  value 82.899646 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 93.786394 
iter  10 value 83.739892
iter  20 value 83.425688
iter  30 value 83.397799
iter  40 value 83.070246
iter  50 value 83.032501
iter  60 value 82.981849
iter  70 value 82.968130
iter  80 value 82.965144
iter  90 value 82.962690
iter 100 value 82.960273
final  value 82.960273 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.633145 
iter  10 value 94.492365
iter  20 value 94.394575
iter  30 value 93.570083
iter  40 value 93.362611
iter  50 value 84.521384
iter  60 value 84.433984
iter  70 value 81.626149
iter  80 value 80.003391
iter  90 value 78.300710
iter 100 value 78.237825
final  value 78.237825 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.761887 
iter  10 value 94.492267
iter  20 value 94.412365
iter  30 value 85.508507
iter  40 value 84.807626
iter  50 value 80.567983
iter  60 value 78.709300
iter  70 value 78.336569
iter  80 value 78.280173
iter  90 value 78.073902
iter 100 value 78.072670
final  value 78.072670 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 117.809342 
iter  10 value 94.300524
iter  20 value 93.626596
iter  30 value 87.246143
iter  40 value 85.460112
iter  50 value 83.393825
iter  60 value 83.070451
iter  70 value 83.059657
iter  80 value 83.059331
final  value 83.059284 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.647547 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.813802 
final  value 93.869755 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.000182 
final  value 93.915746 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.666354 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.867174 
final  value 93.915746 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.833494 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 115.274479 
final  value 93.915746 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.058059 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.852628 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 114.430515 
final  value 93.915746 
converged
Fitting Repeat 1 

# weights:  507
initial  value 117.475099 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 122.159518 
final  value 93.915743 
converged
Fitting Repeat 3 

# weights:  507
initial  value 112.111527 
iter  10 value 94.052127
iter  20 value 93.999495
iter  30 value 92.491825
iter  40 value 92.333319
final  value 92.330141 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.390360 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 115.767069 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.399838 
iter  10 value 94.053477
iter  20 value 92.632121
iter  30 value 88.977188
iter  40 value 88.627635
iter  50 value 88.510119
iter  60 value 86.852684
iter  70 value 86.391568
iter  80 value 86.365264
iter  90 value 86.363313
final  value 86.363299 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.234318 
iter  10 value 94.060146
iter  20 value 90.256791
iter  30 value 87.767914
iter  40 value 86.614467
iter  50 value 86.485025
iter  60 value 86.396512
iter  70 value 86.363750
final  value 86.363299 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.484199 
iter  10 value 94.053814
iter  20 value 93.907381
iter  30 value 93.845399
iter  40 value 93.684051
iter  50 value 90.135290
iter  60 value 86.030250
iter  70 value 85.400575
iter  80 value 85.180489
iter  90 value 84.888185
iter 100 value 84.810301
final  value 84.810301 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 100.652906 
iter  10 value 93.859040
iter  20 value 91.283846
iter  30 value 89.617926
iter  40 value 88.545526
iter  50 value 88.212537
iter  60 value 85.376492
iter  70 value 85.094224
iter  80 value 84.473118
iter  90 value 84.033882
iter 100 value 84.023016
final  value 84.023016 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 96.287430 
iter  10 value 94.056846
iter  20 value 93.845673
iter  30 value 90.275226
iter  40 value 89.308152
iter  50 value 89.206727
iter  60 value 88.464775
iter  70 value 86.686058
iter  80 value 85.756698
iter  90 value 85.743722
final  value 85.743193 
converged
Fitting Repeat 1 

# weights:  305
initial  value 117.504315 
iter  10 value 94.086533
iter  20 value 93.948629
iter  30 value 93.149451
iter  40 value 89.802422
iter  50 value 87.855897
iter  60 value 86.806496
iter  70 value 84.692638
iter  80 value 83.660634
iter  90 value 83.132757
iter 100 value 83.081252
final  value 83.081252 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.651765 
iter  10 value 94.084775
iter  20 value 93.968722
iter  30 value 93.600317
iter  40 value 90.896216
iter  50 value 86.537930
iter  60 value 85.785577
iter  70 value 85.337974
iter  80 value 84.542475
iter  90 value 84.196373
iter 100 value 83.824205
final  value 83.824205 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 113.937437 
iter  10 value 93.992956
iter  20 value 93.692052
iter  30 value 93.627571
iter  40 value 87.858914
iter  50 value 86.739420
iter  60 value 85.860922
iter  70 value 84.289405
iter  80 value 84.018152
iter  90 value 83.634763
iter 100 value 83.603483
final  value 83.603483 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.780560 
iter  10 value 89.336256
iter  20 value 86.959330
iter  30 value 85.765086
iter  40 value 85.532280
iter  50 value 85.484263
iter  60 value 85.449701
iter  70 value 85.230464
iter  80 value 84.023510
iter  90 value 83.397882
iter 100 value 83.220507
final  value 83.220507 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 110.452136 
iter  10 value 93.745335
iter  20 value 87.520577
iter  30 value 86.551435
iter  40 value 85.800262
iter  50 value 85.294139
iter  60 value 85.000686
iter  70 value 84.856379
iter  80 value 84.695253
iter  90 value 83.880335
iter 100 value 83.598946
final  value 83.598946 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.962923 
iter  10 value 95.480328
iter  20 value 88.054717
iter  30 value 85.620480
iter  40 value 84.061730
iter  50 value 82.708136
iter  60 value 82.412796
iter  70 value 82.367198
iter  80 value 82.340453
iter  90 value 82.316696
iter 100 value 82.302733
final  value 82.302733 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.098262 
iter  10 value 94.132768
iter  20 value 93.770816
iter  30 value 89.434864
iter  40 value 86.704406
iter  50 value 85.350926
iter  60 value 84.231395
iter  70 value 83.509302
iter  80 value 83.381650
iter  90 value 83.079740
iter 100 value 82.813448
final  value 82.813448 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 115.340530 
iter  10 value 93.841464
iter  20 value 86.867964
iter  30 value 86.017980
iter  40 value 84.712704
iter  50 value 83.338981
iter  60 value 82.876674
iter  70 value 82.707626
iter  80 value 82.547753
iter  90 value 82.437662
iter 100 value 82.328331
final  value 82.328331 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 117.129416 
iter  10 value 94.083706
iter  20 value 93.791728
iter  30 value 90.922870
iter  40 value 87.856574
iter  50 value 86.646522
iter  60 value 85.898734
iter  70 value 85.842689
iter  80 value 85.570194
iter  90 value 85.189661
iter 100 value 84.923955
final  value 84.923955 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.809940 
iter  10 value 94.259758
iter  20 value 93.757181
iter  30 value 93.662078
iter  40 value 88.215472
iter  50 value 86.303231
iter  60 value 85.516915
iter  70 value 84.172158
iter  80 value 83.795933
iter  90 value 83.219508
iter 100 value 83.059188
final  value 83.059188 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.543342 
final  value 94.054584 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.819347 
iter  10 value 93.917351
iter  20 value 93.916050
iter  30 value 93.654825
iter  40 value 93.636077
iter  50 value 93.632376
final  value 93.632300 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.406344 
final  value 94.054525 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.464390 
final  value 94.054634 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.870226 
iter  10 value 90.028390
iter  20 value 88.467643
iter  30 value 86.293652
iter  40 value 86.271621
iter  50 value 85.646827
iter  60 value 85.597682
iter  70 value 85.597566
final  value 85.597541 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.772079 
iter  10 value 93.874439
iter  20 value 93.870012
final  value 93.869900 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.514315 
iter  10 value 94.057346
iter  20 value 93.985478
iter  30 value 93.655183
final  value 93.654582 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.230665 
iter  10 value 93.718632
iter  20 value 93.714096
iter  30 value 93.620932
iter  40 value 88.905637
iter  50 value 87.913010
iter  60 value 87.120697
iter  70 value 87.036588
iter  80 value 86.990425
iter  90 value 86.988600
iter 100 value 86.987399
final  value 86.987399 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 97.715723 
iter  10 value 93.676094
iter  20 value 93.543079
iter  30 value 88.620161
iter  40 value 88.304318
iter  50 value 88.302643
final  value 88.302547 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.476720 
iter  10 value 91.180783
iter  20 value 86.972072
iter  30 value 86.908331
iter  40 value 86.904588
iter  50 value 86.896889
iter  60 value 86.893982
iter  60 value 86.893981
iter  60 value 86.893981
final  value 86.893981 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.809104 
iter  10 value 93.923606
iter  20 value 93.917208
final  value 93.916893 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.153435 
iter  10 value 94.052696
iter  20 value 93.948004
iter  30 value 93.674088
iter  40 value 86.998526
final  value 86.998427 
converged
Fitting Repeat 3 

# weights:  507
initial  value 108.875019 
iter  10 value 94.060561
iter  20 value 94.046642
iter  30 value 93.228266
iter  40 value 87.455508
iter  50 value 86.070760
iter  60 value 85.710600
iter  70 value 85.688136
final  value 85.681717 
converged
Fitting Repeat 4 

# weights:  507
initial  value 142.972194 
iter  10 value 93.763805
iter  20 value 93.665837
iter  30 value 93.662622
iter  40 value 87.007869
final  value 86.998900 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.296179 
iter  10 value 93.753476
iter  20 value 93.639488
iter  30 value 93.637970
iter  40 value 93.634770
iter  50 value 93.633523
iter  60 value 89.458081
iter  70 value 87.573381
iter  80 value 85.698314
iter  90 value 85.657255
iter 100 value 85.656547
final  value 85.656547 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.269900 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.526944 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.086980 
iter  10 value 93.786977
final  value 93.783647 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.134496 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.982375 
final  value 94.052434 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.197805 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.959542 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.374956 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 110.867146 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 115.416245 
iter  10 value 93.851385
iter  20 value 85.639774
iter  30 value 84.185830
iter  40 value 84.117304
final  value 84.117181 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.697271 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.630725 
final  value 94.275362 
converged
Fitting Repeat 3 

# weights:  507
initial  value 108.195772 
iter  10 value 87.872131
iter  20 value 87.852008
final  value 87.851959 
converged
Fitting Repeat 4 

# weights:  507
initial  value 111.190442 
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  507
initial  value 111.066897 
iter  10 value 93.209576
iter  20 value 93.205208
final  value 93.205180 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.284334 
iter  10 value 94.454027
iter  20 value 87.083909
iter  30 value 84.093878
iter  40 value 83.248410
iter  50 value 83.182694
iter  60 value 83.181193
final  value 83.181187 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.836442 
iter  10 value 94.486959
iter  20 value 93.881498
iter  30 value 93.824956
iter  40 value 93.345645
iter  50 value 89.291341
iter  60 value 88.155403
iter  70 value 87.958305
iter  80 value 84.441523
iter  90 value 83.371246
iter 100 value 82.729528
final  value 82.729528 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 103.614924 
iter  10 value 94.278616
iter  20 value 89.331616
iter  30 value 84.221208
iter  40 value 82.291757
iter  50 value 81.450032
iter  60 value 81.351911
iter  70 value 81.204142
iter  80 value 81.184273
iter  90 value 81.176177
final  value 81.175857 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.713229 
iter  10 value 94.488441
iter  20 value 93.623858
iter  30 value 86.884732
iter  40 value 85.084283
iter  50 value 84.524550
iter  60 value 83.588312
iter  70 value 83.435258
iter  80 value 83.434911
iter  80 value 83.434911
iter  80 value 83.434911
final  value 83.434911 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.619414 
iter  10 value 94.485935
iter  20 value 86.355112
iter  30 value 85.983221
iter  40 value 84.947062
iter  50 value 83.210035
iter  60 value 83.185109
iter  70 value 83.182098
iter  80 value 83.181436
final  value 83.181186 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.416463 
iter  10 value 96.909266
iter  20 value 90.954606
iter  30 value 83.652265
iter  40 value 83.484525
iter  50 value 83.314340
iter  60 value 83.249020
iter  70 value 83.174292
iter  80 value 81.328612
iter  90 value 80.783532
iter 100 value 79.783197
final  value 79.783197 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.420443 
iter  10 value 92.241394
iter  20 value 88.335948
iter  30 value 86.500666
iter  40 value 85.703325
iter  50 value 85.256544
iter  60 value 83.986709
iter  70 value 83.311134
iter  80 value 82.953838
iter  90 value 82.540411
iter 100 value 82.486085
final  value 82.486085 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.487503 
iter  10 value 94.432129
iter  20 value 92.914213
iter  30 value 87.171418
iter  40 value 84.404578
iter  50 value 82.887006
iter  60 value 80.874165
iter  70 value 80.766162
iter  80 value 80.504876
iter  90 value 80.045934
iter 100 value 79.823524
final  value 79.823524 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.810490 
iter  10 value 93.485151
iter  20 value 91.386721
iter  30 value 83.819090
iter  40 value 81.842447
iter  50 value 81.038552
iter  60 value 80.744829
iter  70 value 80.375331
iter  80 value 80.079974
iter  90 value 79.913751
iter 100 value 79.876595
final  value 79.876595 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.762573 
iter  10 value 95.682199
iter  20 value 93.531505
iter  30 value 84.147478
iter  40 value 83.412868
iter  50 value 83.190056
iter  60 value 82.782777
iter  70 value 80.838599
iter  80 value 79.923138
iter  90 value 79.697347
iter 100 value 79.655978
final  value 79.655978 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 121.557543 
iter  10 value 93.638056
iter  20 value 85.451017
iter  30 value 84.293841
iter  40 value 82.612419
iter  50 value 81.055101
iter  60 value 80.450320
iter  70 value 79.962244
iter  80 value 79.833113
iter  90 value 79.757373
iter 100 value 79.709494
final  value 79.709494 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.302474 
iter  10 value 94.418631
iter  20 value 92.592273
iter  30 value 84.667722
iter  40 value 83.906261
iter  50 value 83.203889
iter  60 value 81.437152
iter  70 value 80.737639
iter  80 value 80.441817
iter  90 value 79.856549
iter 100 value 79.643856
final  value 79.643856 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.308549 
iter  10 value 94.362032
iter  20 value 88.412280
iter  30 value 85.314927
iter  40 value 84.878588
iter  50 value 84.072253
iter  60 value 83.931735
iter  70 value 81.370842
iter  80 value 80.572257
iter  90 value 80.275529
iter 100 value 80.013392
final  value 80.013392 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 117.641022 
iter  10 value 94.538523
iter  20 value 94.445966
iter  30 value 93.845985
iter  40 value 88.842348
iter  50 value 86.668862
iter  60 value 86.071629
iter  70 value 84.536008
iter  80 value 82.569246
iter  90 value 81.343002
iter 100 value 80.855622
final  value 80.855622 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 125.357531 
iter  10 value 94.490045
iter  20 value 93.850043
iter  30 value 93.813704
iter  40 value 92.156872
iter  50 value 85.546545
iter  60 value 83.395643
iter  70 value 82.796013
iter  80 value 82.718223
iter  90 value 82.479279
iter 100 value 81.638956
final  value 81.638956 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.627364 
final  value 94.485661 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.804453 
final  value 94.485846 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.728137 
final  value 94.485859 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.862375 
final  value 94.054042 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.891727 
final  value 94.485955 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.150685 
iter  10 value 94.488331
iter  20 value 94.484217
iter  30 value 88.810059
iter  40 value 85.311335
iter  50 value 85.287830
iter  60 value 84.382639
iter  70 value 81.325496
iter  80 value 81.208623
iter  90 value 81.046116
iter 100 value 81.042309
final  value 81.042309 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 98.319725 
iter  10 value 94.491697
iter  20 value 94.024280
iter  30 value 84.584616
iter  40 value 84.256866
iter  50 value 84.249318
iter  60 value 82.646122
iter  70 value 81.287139
final  value 81.252836 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.809973 
iter  10 value 94.487834
iter  20 value 94.406345
iter  30 value 84.985485
iter  40 value 83.790978
iter  50 value 81.488852
iter  60 value 79.755371
iter  70 value 79.526574
iter  80 value 79.517975
iter  90 value 79.517841
iter 100 value 79.517331
final  value 79.517331 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.504658 
iter  10 value 94.487606
iter  20 value 93.815163
final  value 93.815123 
converged
Fitting Repeat 5 

# weights:  305
initial  value 112.854261 
iter  10 value 94.503049
iter  20 value 93.204059
iter  30 value 88.915389
iter  40 value 85.888630
iter  50 value 84.610290
iter  60 value 84.319660
iter  70 value 84.269112
iter  80 value 84.260000
iter  90 value 82.842697
iter 100 value 82.823246
final  value 82.823246 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.507814 
iter  10 value 94.492267
iter  20 value 94.444927
iter  30 value 94.060867
iter  40 value 94.051672
final  value 94.051669 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.771288 
iter  10 value 94.285102
iter  20 value 94.282620
iter  30 value 93.754587
iter  40 value 93.753769
final  value 93.753648 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.545344 
iter  10 value 93.234595
iter  20 value 93.223382
iter  30 value 93.173571
iter  40 value 93.172127
iter  50 value 93.162468
iter  60 value 93.161556
final  value 93.161228 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.047912 
iter  10 value 93.617943
iter  20 value 93.183604
iter  30 value 87.825091
iter  40 value 87.802682
iter  50 value 84.371982
iter  60 value 83.529535
iter  70 value 81.809073
iter  80 value 81.340104
iter  90 value 80.103418
iter 100 value 80.006083
final  value 80.006083 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.410450 
iter  10 value 94.492411
iter  20 value 87.874250
iter  30 value 84.590172
iter  40 value 84.588370
iter  50 value 84.586920
iter  60 value 84.580476
iter  70 value 84.250639
iter  80 value 82.981580
final  value 82.978323 
converged
Fitting Repeat 1 

# weights:  507
initial  value 133.548164 
iter  10 value 117.327727
iter  20 value 107.365644
iter  30 value 105.866691
iter  40 value 105.006300
iter  50 value 104.284820
iter  60 value 103.670814
iter  70 value 103.559582
iter  80 value 103.179754
iter  90 value 102.321733
iter 100 value 101.626126
final  value 101.626126 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 128.978366 
iter  10 value 117.200579
iter  20 value 108.616198
iter  30 value 106.915854
iter  40 value 105.666944
iter  50 value 105.533901
iter  60 value 104.619602
iter  70 value 102.022411
iter  80 value 101.560780
iter  90 value 101.362816
iter 100 value 101.121385
final  value 101.121385 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 131.799323 
iter  10 value 120.385351
iter  20 value 108.426939
iter  30 value 106.523135
iter  40 value 105.718009
iter  50 value 102.476432
iter  60 value 101.706948
iter  70 value 101.405634
iter  80 value 101.370107
iter  90 value 101.165473
iter 100 value 101.015277
final  value 101.015277 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 127.121727 
iter  10 value 116.455609
iter  20 value 112.504295
iter  30 value 104.277164
iter  40 value 101.877548
iter  50 value 101.252940
iter  60 value 101.003381
iter  70 value 100.762737
iter  80 value 100.471435
iter  90 value 100.412938
iter 100 value 100.392947
final  value 100.392947 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 128.423060 
iter  10 value 118.211202
iter  20 value 117.988021
iter  30 value 117.669383
iter  40 value 108.117007
iter  50 value 107.400151
iter  60 value 107.348558
iter  70 value 106.171419
iter  80 value 102.815116
iter  90 value 102.045038
iter 100 value 101.580435
final  value 101.580435 
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 -- Mon Jun  3 04:26:26 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 
 39.634   1.946  41.604