##############################################################################
##############################################################################
###
### Running command:
###
###   F:\biocbuild\bbs-3.19-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.19-bioc\R\library --no-vignettes --timings HPiP_1.10.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory 'F:/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck'
* using R version 4.4.0 (2024-04-24 ucrt)
* using platform: x86_64-w64-mingw32
* R was compiled by
    gcc.exe (GCC) 13.2.0
    GNU Fortran (GCC) 13.2.0
* running under: Windows Server 2022 x64 (build 20348)
* 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 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
FSmethod      34.18   2.05   36.36
var_imp       33.50   1.52   35.02
corr_plot     33.03   1.79   34.83
pred_ensembel 14.89   0.84   11.45
enrichfindP    0.61   0.07   14.40
* 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
  'F:/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck/00check.log'
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   F:\biocbuild\bbs-3.19-bioc\R\bin\R.exe CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library 'F:/biocbuild/bbs-3.19-bioc/R/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 ucrt) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64

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 96.985759 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.503323 
iter  10 value 93.815818
final  value 93.813958 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.086269 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.015424 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.909605 
final  value 94.467391 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.980938 
iter  10 value 94.465059
iter  20 value 94.052907
final  value 94.052435 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.648536 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.541320 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.765678 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.464548 
final  value 94.052434 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.777684 
iter  10 value 94.264859
final  value 94.264858 
converged
Fitting Repeat 2 

# weights:  507
initial  value 112.880852 
final  value 94.467391 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.638978 
final  value 94.484206 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.727656 
iter  10 value 94.379748
iter  10 value 94.379747
iter  10 value 94.379747
final  value 94.379747 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.360551 
iter  10 value 89.867571
iter  20 value 87.132656
iter  30 value 86.630964
iter  40 value 82.754418
iter  50 value 82.425641
final  value 82.425477 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.137599 
iter  10 value 94.504383
iter  20 value 94.488575
iter  30 value 94.116256
iter  40 value 93.928396
iter  50 value 88.354952
iter  60 value 85.329935
iter  70 value 85.059638
iter  80 value 85.015134
iter  90 value 84.611590
iter 100 value 84.489382
final  value 84.489382 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 102.987952 
iter  10 value 94.487148
iter  20 value 94.171121
iter  30 value 94.127759
iter  40 value 94.123517
iter  50 value 93.192997
iter  60 value 89.291462
iter  70 value 87.676864
iter  80 value 86.330496
iter  90 value 85.018647
iter 100 value 84.150503
final  value 84.150503 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 130.074530 
iter  10 value 94.470038
iter  20 value 89.365901
iter  30 value 88.047541
iter  40 value 87.264630
iter  50 value 86.260937
iter  60 value 85.653551
iter  70 value 85.230921
iter  80 value 85.103345
iter  90 value 85.080088
final  value 85.078429 
converged
Fitting Repeat 4 

# weights:  103
initial  value 112.377681 
iter  10 value 94.573486
iter  20 value 93.704654
iter  30 value 87.048148
iter  40 value 86.611469
iter  50 value 86.147011
iter  60 value 85.505017
iter  70 value 85.489840
final  value 85.489670 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.103526 
iter  10 value 94.488600
iter  20 value 94.390895
iter  30 value 92.240677
iter  40 value 86.725942
iter  50 value 86.401047
iter  60 value 86.259943
iter  70 value 86.199429
iter  80 value 85.431396
iter  90 value 84.107902
iter 100 value 83.839985
final  value 83.839985 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 108.910782 
iter  10 value 94.644419
iter  20 value 93.703915
iter  30 value 90.858897
iter  40 value 90.568428
iter  50 value 90.160440
iter  60 value 88.407810
iter  70 value 86.648501
iter  80 value 84.937777
iter  90 value 84.455381
iter 100 value 83.615378
final  value 83.615378 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.115528 
iter  10 value 89.021055
iter  20 value 87.132604
iter  30 value 85.788335
iter  40 value 85.068938
iter  50 value 84.926702
iter  60 value 84.199389
iter  70 value 83.921160
iter  80 value 83.854820
iter  90 value 83.601465
iter 100 value 83.470622
final  value 83.470622 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 112.136937 
iter  10 value 94.251197
iter  20 value 90.256512
iter  30 value 89.126893
iter  40 value 86.790849
iter  50 value 85.236787
iter  60 value 84.923490
iter  70 value 84.914046
iter  80 value 84.899761
iter  90 value 84.721820
iter 100 value 83.543085
final  value 83.543085 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.391354 
iter  10 value 94.486268
iter  20 value 94.381139
iter  30 value 93.093010
iter  40 value 87.864785
iter  50 value 85.927454
iter  60 value 85.427492
iter  70 value 85.026093
iter  80 value 84.712828
iter  90 value 83.795334
iter 100 value 83.073522
final  value 83.073522 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 135.856002 
iter  10 value 98.680571
iter  20 value 95.970953
iter  30 value 94.497904
iter  40 value 94.329795
iter  50 value 91.866745
iter  60 value 90.478835
iter  70 value 87.991631
iter  80 value 85.716395
iter  90 value 84.090491
iter 100 value 83.529022
final  value 83.529022 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 111.452202 
iter  10 value 94.501022
iter  20 value 90.110397
iter  30 value 89.304545
iter  40 value 88.946695
iter  50 value 87.171865
iter  60 value 86.236405
iter  70 value 85.602546
iter  80 value 84.920041
iter  90 value 84.376855
iter 100 value 83.603839
final  value 83.603839 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 126.526981 
iter  10 value 94.190187
iter  20 value 87.183749
iter  30 value 86.441758
iter  40 value 85.447521
iter  50 value 85.207673
iter  60 value 84.996348
iter  70 value 84.432913
iter  80 value 83.551378
iter  90 value 83.122362
iter 100 value 82.715995
final  value 82.715995 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.260865 
iter  10 value 94.257300
iter  20 value 87.514923
iter  30 value 86.209609
iter  40 value 85.023562
iter  50 value 83.127303
iter  60 value 82.857567
iter  70 value 82.576632
iter  80 value 82.529300
iter  90 value 82.496913
iter 100 value 82.479063
final  value 82.479063 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 114.129422 
iter  10 value 96.168633
iter  20 value 90.907092
iter  30 value 87.014069
iter  40 value 86.544249
iter  50 value 85.167154
iter  60 value 84.871831
iter  70 value 84.113314
iter  80 value 83.103647
iter  90 value 82.838063
iter 100 value 82.336738
final  value 82.336738 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.202046 
iter  10 value 94.657395
iter  20 value 94.393884
iter  30 value 88.961351
iter  40 value 86.676987
iter  50 value 86.044611
iter  60 value 85.064013
iter  70 value 84.746588
iter  80 value 83.715932
iter  90 value 82.671702
iter 100 value 82.329430
final  value 82.329430 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.632543 
final  value 94.485807 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.669968 
final  value 94.485990 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.871511 
final  value 94.486052 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.849762 
final  value 94.485978 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.551378 
final  value 94.485716 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.917308 
iter  10 value 94.472348
iter  20 value 94.468103
final  value 94.467414 
converged
Fitting Repeat 2 

# weights:  305
initial  value 111.329756 
iter  10 value 94.270307
iter  20 value 94.266457
iter  30 value 93.070848
iter  40 value 86.338280
iter  50 value 86.181790
iter  60 value 86.178950
iter  70 value 85.525992
final  value 85.523948 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.165747 
iter  10 value 94.472734
final  value 94.469709 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.987056 
iter  10 value 94.489303
iter  20 value 94.314118
iter  30 value 87.422743
iter  40 value 87.320229
iter  50 value 86.643562
iter  60 value 86.107550
iter  70 value 86.106893
final  value 86.105726 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.406425 
iter  10 value 94.485722
iter  20 value 90.129636
iter  30 value 86.282869
iter  40 value 86.266871
iter  50 value 85.323911
iter  60 value 85.213108
final  value 85.211734 
converged
Fitting Repeat 1 

# weights:  507
initial  value 118.919955 
iter  10 value 94.492568
iter  20 value 94.479696
final  value 94.467485 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.909297 
iter  10 value 94.491594
iter  20 value 94.467694
iter  30 value 92.421739
iter  40 value 92.307795
iter  50 value 92.108175
iter  60 value 92.105468
iter  70 value 92.105158
final  value 92.105066 
converged
Fitting Repeat 3 

# weights:  507
initial  value 114.105831 
iter  10 value 94.488953
iter  20 value 93.865175
iter  30 value 93.852322
final  value 93.851283 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.875755 
iter  10 value 94.475596
iter  20 value 94.467741
final  value 94.467689 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.928454 
iter  10 value 91.178021
iter  20 value 90.752781
iter  30 value 90.475887
iter  40 value 90.443008
iter  50 value 88.475414
iter  60 value 87.539408
iter  70 value 86.438006
iter  80 value 86.432359
iter  90 value 86.426055
iter 100 value 86.338714
final  value 86.338714 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.113155 
final  value 94.052911 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.190483 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.622078 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.328389 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.371449 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.751902 
final  value 92.701657 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.941875 
final  value 93.473743 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.469470 
iter  10 value 93.994006
iter  10 value 93.994006
iter  10 value 93.994006
final  value 93.994006 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.392713 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.822540 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.184319 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.049432 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.571079 
iter  10 value 94.052448
iter  10 value 94.052448
iter  10 value 94.052448
final  value 94.052448 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.656316 
iter  10 value 88.820249
iter  20 value 86.563862
final  value 86.563710 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.008505 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.509637 
iter  10 value 94.065760
iter  20 value 92.271372
iter  30 value 89.739046
iter  40 value 87.100732
iter  50 value 85.494474
iter  60 value 85.135428
iter  70 value 85.073108
iter  80 value 85.062017
final  value 85.061926 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.359244 
iter  10 value 94.287526
iter  20 value 93.998195
iter  30 value 92.409765
iter  40 value 91.154493
iter  50 value 91.029095
iter  60 value 89.878248
iter  70 value 86.187563
iter  80 value 84.944521
iter  90 value 84.420421
iter 100 value 83.670232
final  value 83.670232 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 108.741412 
iter  10 value 93.653748
iter  20 value 92.352760
iter  30 value 84.801916
iter  40 value 84.445549
iter  50 value 84.003997
iter  60 value 82.974880
iter  70 value 82.062866
iter  80 value 81.333379
iter  90 value 81.210742
iter 100 value 81.210535
final  value 81.210535 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.112835 
iter  10 value 94.003512
iter  20 value 90.620505
iter  30 value 88.120355
iter  40 value 87.755890
iter  50 value 87.173779
iter  60 value 85.739079
iter  70 value 85.491915
iter  80 value 85.181728
iter  90 value 85.069491
iter 100 value 85.061959
final  value 85.061959 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 102.536404 
iter  10 value 94.045965
iter  20 value 93.557950
iter  30 value 92.425994
iter  40 value 86.627194
iter  50 value 83.075647
iter  60 value 82.720538
iter  70 value 82.518742
iter  80 value 82.454063
iter  90 value 82.369307
iter 100 value 82.095782
final  value 82.095782 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 101.683394 
iter  10 value 94.085380
iter  20 value 93.986233
iter  30 value 89.644604
iter  40 value 88.807751
iter  50 value 86.068102
iter  60 value 85.132582
iter  70 value 84.011199
iter  80 value 83.189342
iter  90 value 82.769572
iter 100 value 82.686424
final  value 82.686424 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.071612 
iter  10 value 94.038069
iter  20 value 93.563223
iter  30 value 93.537389
iter  40 value 92.201065
iter  50 value 86.449419
iter  60 value 85.813814
iter  70 value 85.083278
iter  80 value 83.776263
iter  90 value 82.928390
iter 100 value 80.574264
final  value 80.574264 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.042179 
iter  10 value 94.043879
iter  20 value 91.397492
iter  30 value 87.954420
iter  40 value 85.595101
iter  50 value 85.462533
iter  60 value 85.109786
iter  70 value 84.440652
iter  80 value 83.278515
iter  90 value 82.953350
iter 100 value 82.592482
final  value 82.592482 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.720622 
iter  10 value 93.620575
iter  20 value 92.780473
iter  30 value 85.195150
iter  40 value 84.061824
iter  50 value 82.745167
iter  60 value 81.993452
iter  70 value 80.944937
iter  80 value 80.509223
iter  90 value 80.467714
iter 100 value 80.427215
final  value 80.427215 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 114.399444 
iter  10 value 94.450700
iter  20 value 91.424737
iter  30 value 90.865815
iter  40 value 90.630347
iter  50 value 88.937368
iter  60 value 84.533047
iter  70 value 83.406588
iter  80 value 81.231523
iter  90 value 80.465139
iter 100 value 80.187617
final  value 80.187617 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.608192 
iter  10 value 93.962315
iter  20 value 93.435453
iter  30 value 93.412175
iter  40 value 92.259046
iter  50 value 88.254695
iter  60 value 85.083219
iter  70 value 84.614538
iter  80 value 84.376775
iter  90 value 83.885092
iter 100 value 82.275836
final  value 82.275836 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 115.787650 
iter  10 value 91.765165
iter  20 value 85.651341
iter  30 value 85.423674
iter  40 value 84.664714
iter  50 value 83.278047
iter  60 value 83.049788
iter  70 value 82.763215
iter  80 value 82.473329
iter  90 value 81.556403
iter 100 value 81.151866
final  value 81.151866 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.500408 
iter  10 value 94.243864
iter  20 value 90.173262
iter  30 value 85.506008
iter  40 value 85.069718
iter  50 value 84.150692
iter  60 value 82.094383
iter  70 value 81.104205
iter  80 value 80.969253
iter  90 value 80.699418
iter 100 value 80.463073
final  value 80.463073 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.067302 
iter  10 value 94.241549
iter  20 value 93.365709
iter  30 value 86.816193
iter  40 value 85.533483
iter  50 value 85.238825
iter  60 value 83.857391
iter  70 value 81.399734
iter  80 value 80.514472
iter  90 value 80.056494
iter 100 value 79.914480
final  value 79.914480 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 120.017351 
iter  10 value 93.588980
iter  20 value 91.369891
iter  30 value 86.560426
iter  40 value 86.362997
iter  50 value 85.416930
iter  60 value 85.118959
iter  70 value 82.900469
iter  80 value 82.414556
iter  90 value 81.767104
iter 100 value 81.340226
final  value 81.340226 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.849065 
final  value 94.054456 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.280216 
iter  10 value 93.283744
iter  20 value 93.276115
iter  30 value 93.275259
final  value 93.274475 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.494922 
final  value 94.054377 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.955890 
iter  10 value 93.330487
iter  20 value 93.328944
iter  30 value 93.328544
iter  40 value 93.286853
iter  50 value 92.205582
iter  60 value 86.107304
iter  70 value 86.101366
iter  80 value 86.093318
iter  90 value 86.092350
iter 100 value 86.088982
final  value 86.088982 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 95.330831 
final  value 94.054682 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.742484 
iter  10 value 94.057848
iter  20 value 94.014902
final  value 93.328683 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.746287 
iter  10 value 94.057661
iter  20 value 94.052942
final  value 94.052927 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.132826 
iter  10 value 93.333585
iter  20 value 93.331540
iter  30 value 93.328914
iter  40 value 89.805910
iter  50 value 88.078927
iter  60 value 88.067621
iter  70 value 87.207465
iter  80 value 86.340017
iter  90 value 86.159742
iter 100 value 85.953337
final  value 85.953337 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.760974 
iter  10 value 94.011949
iter  20 value 93.960885
iter  30 value 93.958930
iter  40 value 93.874180
iter  50 value 93.871731
iter  60 value 93.354189
iter  70 value 93.291642
iter  80 value 92.098433
iter  90 value 92.093808
final  value 92.093686 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.824543 
iter  10 value 94.057752
final  value 94.052932 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.554339 
iter  10 value 93.883833
iter  20 value 93.197985
iter  30 value 93.189059
iter  40 value 93.011184
iter  50 value 92.827498
iter  60 value 92.793767
iter  70 value 92.792551
iter  80 value 92.792135
iter  90 value 92.790203
iter 100 value 92.790124
final  value 92.790124 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 100.242533 
iter  10 value 93.338472
iter  20 value 93.335290
iter  30 value 93.328664
final  value 93.325275 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.776103 
iter  10 value 93.337530
iter  20 value 93.335675
iter  30 value 87.636013
iter  40 value 84.404407
iter  50 value 84.134792
iter  60 value 84.028354
iter  70 value 84.027525
iter  80 value 83.015172
iter  90 value 81.020032
iter 100 value 80.340204
final  value 80.340204 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 96.471650 
iter  10 value 94.060485
iter  20 value 94.057110
iter  30 value 93.910683
iter  40 value 93.410950
iter  50 value 93.294140
final  value 93.274867 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.224880 
iter  10 value 93.438951
iter  20 value 93.337592
iter  30 value 93.330651
iter  40 value 93.330433
iter  50 value 93.286900
iter  60 value 93.269789
final  value 93.269787 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.109440 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.303579 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.431234 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.417432 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.751340 
iter  10 value 85.842660
iter  20 value 85.840152
final  value 85.840146 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.853395 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.136442 
final  value 94.088889 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.110085 
iter  10 value 94.469963
final  value 94.466832 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.312440 
iter  10 value 88.419573
iter  20 value 88.251664
iter  30 value 88.250780
final  value 88.250778 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.666058 
iter  10 value 94.448481
iter  20 value 94.433727
final  value 94.381461 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.572033 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.612513 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.311498 
final  value 94.482478 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.995994 
iter  10 value 94.430300
final  value 94.430236 
converged
Fitting Repeat 5 

# weights:  507
initial  value 111.720056 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.951566 
iter  10 value 94.484449
iter  20 value 88.232764
iter  30 value 86.011868
iter  40 value 85.749816
iter  50 value 85.696021
iter  60 value 85.610548
iter  70 value 85.247980
iter  80 value 85.174479
iter  90 value 85.158805
final  value 85.157743 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.377328 
iter  10 value 94.518068
iter  20 value 94.486430
iter  30 value 92.570462
iter  40 value 90.774827
iter  50 value 84.494612
iter  60 value 84.134314
iter  70 value 84.085477
iter  80 value 83.792794
iter  90 value 83.380015
iter 100 value 83.369076
final  value 83.369076 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.742972 
iter  10 value 94.470391
iter  20 value 93.216780
iter  30 value 93.123147
iter  40 value 92.828014
iter  50 value 92.777472
iter  60 value 91.572263
iter  70 value 91.321078
iter  80 value 91.309679
final  value 91.309676 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.341855 
iter  10 value 94.389208
iter  20 value 89.307990
iter  30 value 87.474617
iter  40 value 86.056796
iter  50 value 85.924515
iter  60 value 85.763334
iter  70 value 85.680125
iter  80 value 85.652862
iter  80 value 85.652862
iter  80 value 85.652862
final  value 85.652862 
converged
Fitting Repeat 5 

# weights:  103
initial  value 109.683917 
iter  10 value 94.311779
iter  20 value 88.482677
iter  30 value 85.349777
iter  40 value 84.744114
iter  50 value 84.141462
iter  60 value 83.637838
iter  70 value 83.504911
iter  80 value 83.451365
iter  90 value 83.392216
iter 100 value 83.367835
final  value 83.367835 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 110.261583 
iter  10 value 94.415819
iter  20 value 92.151172
iter  30 value 89.981287
iter  40 value 85.934530
iter  50 value 84.543349
iter  60 value 84.416443
iter  70 value 84.296560
iter  80 value 83.240516
iter  90 value 82.665545
iter 100 value 82.575804
final  value 82.575804 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.144731 
iter  10 value 95.895926
iter  20 value 89.897208
iter  30 value 85.993392
iter  40 value 85.039996
iter  50 value 84.096921
iter  60 value 83.159403
iter  70 value 82.808386
iter  80 value 82.749182
iter  90 value 82.685216
iter 100 value 82.624726
final  value 82.624726 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 120.544648 
iter  10 value 95.405060
iter  20 value 94.362138
iter  30 value 87.119578
iter  40 value 86.635206
iter  50 value 85.790319
iter  60 value 85.483091
iter  70 value 85.226524
iter  80 value 83.743977
iter  90 value 83.290559
iter 100 value 82.988988
final  value 82.988988 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.597397 
iter  10 value 88.364174
iter  20 value 86.556720
iter  30 value 85.748923
iter  40 value 85.469284
iter  50 value 85.418310
iter  60 value 85.366789
iter  70 value 85.120348
iter  80 value 83.554492
iter  90 value 82.850486
iter 100 value 82.347261
final  value 82.347261 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.561296 
iter  10 value 94.625784
iter  20 value 92.044821
iter  30 value 87.960847
iter  40 value 86.820992
iter  50 value 85.624833
iter  60 value 83.780347
iter  70 value 83.494213
iter  80 value 83.386127
iter  90 value 83.181269
iter 100 value 82.992845
final  value 82.992845 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.260024 
iter  10 value 90.424206
iter  20 value 85.848314
iter  30 value 83.325686
iter  40 value 83.143364
iter  50 value 82.465179
iter  60 value 82.444961
iter  70 value 82.407811
iter  80 value 82.388887
iter  90 value 82.375870
iter 100 value 82.298368
final  value 82.298368 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 140.595566 
iter  10 value 95.249281
iter  20 value 93.712427
iter  30 value 92.532615
iter  40 value 87.147709
iter  50 value 84.047156
iter  60 value 83.111330
iter  70 value 82.878886
iter  80 value 82.546462
iter  90 value 82.331172
iter 100 value 82.272262
final  value 82.272262 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.588771 
iter  10 value 93.862320
iter  20 value 87.424545
iter  30 value 83.454960
iter  40 value 82.489686
iter  50 value 82.341604
iter  60 value 82.143710
iter  70 value 82.121860
iter  80 value 82.112638
iter  90 value 82.028833
iter 100 value 81.908112
final  value 81.908112 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.733690 
iter  10 value 94.832913
iter  20 value 86.364128
iter  30 value 85.870692
iter  40 value 85.387456
iter  50 value 84.595732
iter  60 value 84.130696
iter  70 value 83.466324
iter  80 value 83.026457
iter  90 value 82.559295
iter 100 value 82.480551
final  value 82.480551 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.052727 
iter  10 value 94.602594
iter  20 value 89.702355
iter  30 value 87.740681
iter  40 value 85.693847
iter  50 value 85.241875
iter  60 value 83.663281
iter  70 value 82.967859
iter  80 value 82.768254
iter  90 value 82.625410
iter 100 value 82.490060
final  value 82.490060 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.373698 
final  value 94.485749 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.131113 
final  value 94.486081 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.236120 
final  value 94.485888 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.347922 
final  value 94.485544 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.791336 
final  value 94.486020 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.030330 
iter  10 value 94.489531
iter  20 value 94.484342
iter  30 value 94.325853
iter  40 value 94.203670
iter  50 value 91.311465
iter  60 value 87.533744
final  value 87.533661 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.188295 
iter  10 value 94.359466
iter  20 value 94.354517
iter  30 value 92.376904
iter  40 value 85.327046
iter  50 value 83.269863
iter  60 value 82.903186
iter  70 value 82.620913
iter  80 value 82.605322
iter  90 value 82.583645
iter 100 value 82.557847
final  value 82.557847 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 96.271461 
iter  10 value 94.489095
iter  20 value 94.217763
iter  30 value 92.224324
iter  40 value 91.290732
final  value 91.278460 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.636748 
iter  10 value 94.489235
iter  20 value 94.482744
iter  30 value 93.925707
iter  40 value 87.979091
iter  50 value 87.966376
iter  60 value 85.836969
iter  70 value 84.826501
iter  80 value 84.813494
iter  90 value 84.547800
iter 100 value 84.533028
final  value 84.533028 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 96.369596 
iter  10 value 94.489124
iter  20 value 94.484272
iter  30 value 86.914448
iter  40 value 86.385427
iter  50 value 86.335948
iter  60 value 86.331998
final  value 86.331783 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.205030 
iter  10 value 94.490743
iter  20 value 94.482613
iter  30 value 88.937083
iter  40 value 87.060467
iter  50 value 86.244522
iter  60 value 84.284227
iter  70 value 84.278753
final  value 84.278129 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.563257 
iter  10 value 94.492210
iter  20 value 94.464397
iter  30 value 87.158525
iter  40 value 83.759943
iter  50 value 82.135099
iter  60 value 81.542605
iter  70 value 81.464459
iter  80 value 81.120475
iter  90 value 81.014989
iter 100 value 80.970075
final  value 80.970075 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 96.817665 
iter  10 value 94.492496
iter  20 value 94.484727
iter  30 value 92.216337
iter  40 value 87.865589
iter  50 value 87.824273
iter  60 value 87.785584
iter  70 value 87.734311
iter  80 value 85.911124
iter  90 value 85.484916
iter 100 value 85.046150
final  value 85.046150 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 97.963277 
iter  10 value 94.491240
iter  20 value 88.105021
iter  30 value 87.518862
iter  40 value 86.489639
iter  50 value 86.467114
iter  60 value 86.467002
iter  70 value 86.459107
iter  80 value 85.408825
iter  90 value 85.379597
iter 100 value 85.379469
final  value 85.379469 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.326475 
iter  10 value 94.492639
iter  20 value 94.461565
iter  30 value 92.588774
iter  40 value 92.588179
iter  40 value 92.588178
iter  40 value 92.588178
final  value 92.588178 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.424510 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.625474 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.066511 
final  value 94.484207 
converged
Fitting Repeat 4 

# weights:  103
initial  value 108.279417 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.033048 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.567234 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.956121 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.139296 
iter  10 value 90.599074
iter  20 value 90.433077
iter  30 value 90.369813
final  value 90.369812 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.140097 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.964706 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.394927 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.235258 
iter  10 value 94.482954
iter  10 value 94.482954
iter  10 value 94.482954
final  value 94.482954 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.079515 
iter  10 value 85.126779
iter  20 value 85.097494
iter  30 value 84.751155
iter  40 value 84.569742
iter  50 value 84.364424
final  value 84.351004 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.440546 
iter  10 value 94.186667
iter  10 value 94.186667
iter  10 value 94.186667
final  value 94.186667 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.955678 
iter  10 value 87.196092
iter  20 value 86.464909
final  value 86.464077 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.761336 
iter  10 value 94.416782
iter  20 value 93.208071
iter  30 value 84.975263
iter  40 value 82.886892
iter  50 value 82.282621
iter  60 value 82.259569
iter  70 value 81.415935
iter  80 value 80.000697
iter  90 value 79.628565
iter 100 value 79.595020
final  value 79.595020 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 101.135638 
iter  10 value 94.502660
iter  20 value 89.168783
iter  30 value 87.886271
iter  40 value 86.649604
iter  50 value 84.424330
iter  60 value 84.261481
iter  70 value 83.167990
iter  80 value 80.363160
iter  90 value 80.251523
iter 100 value 79.931474
final  value 79.931474 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.941144 
iter  10 value 94.488221
iter  20 value 94.007746
iter  30 value 92.199380
iter  40 value 85.415002
iter  50 value 84.394602
iter  60 value 84.269648
iter  70 value 80.181102
iter  80 value 79.600213
iter  90 value 79.571640
final  value 79.557711 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.834025 
iter  10 value 94.333726
iter  20 value 94.329063
iter  30 value 92.865813
iter  40 value 85.779477
iter  50 value 82.656090
iter  60 value 82.192373
iter  70 value 81.523370
iter  80 value 81.239654
iter  90 value 81.096470
iter 100 value 80.569711
final  value 80.569711 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 104.754691 
iter  10 value 94.491173
iter  20 value 86.824872
iter  30 value 86.437630
iter  40 value 86.024819
iter  50 value 83.726850
iter  60 value 82.366312
iter  70 value 82.215697
iter  80 value 82.205801
iter  90 value 82.186816
final  value 82.185220 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.777809 
iter  10 value 94.572539
iter  20 value 87.227500
iter  30 value 83.510542
iter  40 value 81.691396
iter  50 value 80.254122
iter  60 value 79.930277
iter  70 value 79.805490
iter  80 value 79.782532
iter  90 value 79.711302
iter 100 value 79.306486
final  value 79.306486 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.458750 
iter  10 value 94.509279
iter  20 value 94.160214
iter  30 value 93.868849
iter  40 value 93.136187
iter  50 value 87.492877
iter  60 value 86.651395
iter  70 value 85.498708
iter  80 value 81.059654
iter  90 value 79.349502
iter 100 value 78.942130
final  value 78.942130 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 98.436241 
iter  10 value 87.158287
iter  20 value 82.739676
iter  30 value 80.311978
iter  40 value 78.917279
iter  50 value 78.377693
iter  60 value 78.233472
iter  70 value 77.979034
iter  80 value 77.891187
iter  90 value 77.878280
iter 100 value 77.876153
final  value 77.876153 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.413501 
iter  10 value 94.121832
iter  20 value 92.868702
iter  30 value 86.643682
iter  40 value 85.821973
iter  50 value 85.548861
iter  60 value 82.719047
iter  70 value 82.234539
iter  80 value 82.097482
iter  90 value 81.167157
iter 100 value 80.217827
final  value 80.217827 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 112.512072 
iter  10 value 94.420658
iter  20 value 85.972375
iter  30 value 84.571015
iter  40 value 84.373561
iter  50 value 83.087279
iter  60 value 80.323719
iter  70 value 79.451249
iter  80 value 79.192933
iter  90 value 78.935521
iter 100 value 78.544450
final  value 78.544450 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.220810 
iter  10 value 95.602868
iter  20 value 94.037011
iter  30 value 93.899651
iter  40 value 92.922272
iter  50 value 87.261475
iter  60 value 83.177224
iter  70 value 80.181283
iter  80 value 79.245940
iter  90 value 78.677437
iter 100 value 78.438647
final  value 78.438647 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 122.105076 
iter  10 value 94.506052
iter  20 value 94.326293
iter  30 value 90.067328
iter  40 value 87.664965
iter  50 value 85.199881
iter  60 value 81.171367
iter  70 value 80.039052
iter  80 value 79.304909
iter  90 value 78.741922
iter 100 value 78.587395
final  value 78.587395 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 118.584677 
iter  10 value 94.365417
iter  20 value 89.329294
iter  30 value 86.161007
iter  40 value 84.873994
iter  50 value 84.652829
iter  60 value 82.135963
iter  70 value 81.588233
iter  80 value 79.898891
iter  90 value 79.210983
iter 100 value 78.886845
final  value 78.886845 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 128.793936 
iter  10 value 94.954010
iter  20 value 94.258950
iter  30 value 88.008533
iter  40 value 86.859279
iter  50 value 86.105945
iter  60 value 81.433345
iter  70 value 80.233032
iter  80 value 78.661442
iter  90 value 78.020939
iter 100 value 77.826901
final  value 77.826901 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 118.605207 
iter  10 value 94.843189
iter  20 value 94.095219
iter  30 value 93.472627
iter  40 value 87.566014
iter  50 value 84.417371
iter  60 value 79.737938
iter  70 value 79.373874
iter  80 value 79.062951
iter  90 value 78.505758
iter 100 value 78.274648
final  value 78.274648 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 106.658725 
iter  10 value 94.485907
iter  10 value 94.485907
iter  10 value 94.485906
final  value 94.485906 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.696426 
final  value 94.485828 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.280425 
iter  10 value 88.843260
iter  20 value 85.193227
iter  30 value 85.146585
iter  40 value 85.142815
iter  50 value 85.121714
iter  60 value 84.844654
iter  70 value 84.770416
iter  80 value 84.767622
iter  90 value 84.763648
final  value 84.762930 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.524485 
iter  10 value 94.277111
iter  20 value 94.186035
iter  30 value 92.163042
iter  40 value 92.162230
final  value 92.161873 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.758137 
final  value 94.277065 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.074911 
iter  10 value 94.489216
iter  20 value 94.478107
iter  30 value 88.760359
iter  40 value 86.202862
iter  50 value 84.906791
iter  60 value 84.876201
iter  70 value 84.868930
iter  80 value 84.786293
iter  90 value 82.885295
iter 100 value 82.767151
final  value 82.767151 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.576425 
iter  10 value 93.894200
iter  20 value 93.891903
iter  30 value 89.254784
iter  40 value 88.801202
final  value 88.793845 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.752178 
iter  10 value 94.489062
iter  20 value 94.351142
iter  30 value 94.240700
iter  40 value 92.794620
iter  50 value 91.985418
iter  60 value 90.832449
iter  70 value 90.675210
iter  70 value 90.675209
iter  70 value 90.675209
final  value 90.675209 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.508141 
iter  10 value 94.488983
iter  20 value 94.484212
iter  30 value 93.874656
iter  40 value 93.739941
final  value 93.739538 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.310819 
iter  10 value 94.170270
iter  20 value 93.795214
iter  30 value 92.902389
iter  40 value 92.874401
iter  50 value 92.871492
iter  60 value 92.871285
iter  70 value 92.871027
final  value 92.870925 
converged
Fitting Repeat 1 

# weights:  507
initial  value 115.804455 
iter  10 value 94.486546
iter  20 value 94.366174
iter  30 value 84.660245
iter  40 value 82.647288
iter  50 value 82.462224
iter  60 value 82.431950
final  value 82.430212 
converged
Fitting Repeat 2 

# weights:  507
initial  value 116.703133 
iter  10 value 94.331739
iter  20 value 94.328018
iter  30 value 83.958046
iter  40 value 83.580524
iter  50 value 83.223123
iter  60 value 83.204980
iter  70 value 82.397717
iter  80 value 81.045960
iter  90 value 80.990790
iter 100 value 80.990483
final  value 80.990483 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 101.207558 
iter  10 value 93.880332
iter  20 value 93.875148
iter  30 value 93.772632
iter  40 value 93.754070
iter  50 value 93.753505
iter  60 value 93.751857
iter  70 value 93.737853
iter  80 value 93.221682
iter  90 value 84.521155
iter 100 value 83.404673
final  value 83.404673 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.351851 
iter  10 value 93.823136
iter  20 value 93.780887
iter  30 value 88.147593
iter  40 value 86.874434
iter  50 value 86.832676
iter  60 value 86.729309
iter  70 value 86.619874
iter  80 value 86.540554
iter  90 value 86.372798
iter 100 value 86.332727
final  value 86.332727 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 116.301910 
iter  10 value 94.492978
iter  20 value 94.452033
iter  30 value 90.789806
iter  40 value 87.341612
iter  50 value 87.299721
iter  60 value 85.438571
iter  70 value 85.305729
iter  80 value 85.305027
final  value 85.305026 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.938309 
final  value 94.052878 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.752369 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.735077 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.233273 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.984703 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.280150 
iter  10 value 89.845074
iter  20 value 81.909958
iter  30 value 79.494765
iter  40 value 79.147633
iter  50 value 79.117885
iter  60 value 78.194895
final  value 78.194863 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.056820 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 109.918678 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.958934 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.662584 
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  507
initial  value 113.659926 
iter  10 value 94.001767
iter  20 value 93.674745
iter  30 value 93.578708
final  value 93.578654 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.978537 
iter  10 value 91.253389
iter  20 value 89.336393
iter  30 value 89.335036
iter  40 value 89.334969
final  value 89.334957 
converged
Fitting Repeat 3 

# weights:  507
initial  value 129.611112 
final  value 94.032967 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.933107 
iter  10 value 91.077750
iter  20 value 85.867984
iter  30 value 85.858909
final  value 85.858892 
converged
Fitting Repeat 5 

# weights:  507
initial  value 120.772863 
iter  10 value 93.426574
iter  10 value 93.426573
iter  10 value 93.426573
final  value 93.426573 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.296953 
iter  10 value 94.027865
iter  20 value 93.439493
iter  30 value 93.178420
iter  40 value 92.117679
iter  50 value 83.474436
iter  60 value 80.128963
iter  70 value 80.034003
iter  80 value 79.969608
iter  90 value 79.505904
iter 100 value 78.454428
final  value 78.454428 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.612163 
iter  10 value 94.058144
iter  20 value 93.183675
iter  30 value 86.067505
iter  40 value 85.542100
iter  50 value 85.243915
iter  60 value 84.671948
iter  70 value 80.282806
iter  80 value 80.275282
final  value 80.275146 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.397497 
iter  10 value 86.499427
iter  20 value 82.025871
iter  30 value 81.253344
iter  40 value 79.966557
iter  50 value 79.618518
iter  60 value 79.153803
iter  70 value 79.110628
final  value 79.110625 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.667161 
iter  10 value 93.924208
iter  20 value 81.478009
iter  30 value 80.485095
iter  40 value 79.616821
iter  50 value 79.329321
final  value 79.329224 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.665670 
iter  10 value 94.005936
iter  20 value 83.032157
iter  30 value 80.853857
iter  40 value 80.257170
iter  50 value 79.558123
iter  60 value 79.110642
final  value 79.110625 
converged
Fitting Repeat 1 

# weights:  305
initial  value 120.239342 
iter  10 value 90.729597
iter  20 value 81.588306
iter  30 value 79.441110
iter  40 value 78.315823
iter  50 value 77.442877
iter  60 value 76.816347
iter  70 value 76.638314
iter  80 value 76.290631
iter  90 value 75.984847
iter 100 value 75.781126
final  value 75.781126 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.520347 
iter  10 value 94.709907
iter  20 value 85.825618
iter  30 value 85.120928
iter  40 value 84.859088
iter  50 value 79.620677
iter  60 value 77.165948
iter  70 value 76.470324
iter  80 value 76.315073
iter  90 value 76.221928
iter 100 value 75.812556
final  value 75.812556 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.187405 
iter  10 value 93.929113
iter  20 value 86.043884
iter  30 value 83.999975
iter  40 value 79.394207
iter  50 value 78.616569
iter  60 value 78.347612
iter  70 value 76.942797
iter  80 value 76.185397
iter  90 value 76.006768
iter 100 value 75.873035
final  value 75.873035 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 117.612519 
iter  10 value 93.033170
iter  20 value 81.259033
iter  30 value 80.840633
iter  40 value 80.555760
iter  50 value 80.273469
iter  60 value 79.227579
iter  70 value 79.125463
iter  80 value 78.564117
iter  90 value 77.672885
iter 100 value 77.477441
final  value 77.477441 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 117.626516 
iter  10 value 92.824476
iter  20 value 89.680851
iter  30 value 88.803347
iter  40 value 86.309573
iter  50 value 80.752951
iter  60 value 80.506130
iter  70 value 79.544240
iter  80 value 78.169031
iter  90 value 77.941585
iter 100 value 76.972301
final  value 76.972301 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 116.908227 
iter  10 value 94.092712
iter  20 value 86.238199
iter  30 value 85.407499
iter  40 value 85.198765
iter  50 value 81.085791
iter  60 value 78.307182
iter  70 value 76.970632
iter  80 value 76.244384
iter  90 value 76.209788
iter 100 value 76.169001
final  value 76.169001 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 122.808660 
iter  10 value 94.354078
iter  20 value 83.672432
iter  30 value 82.048960
iter  40 value 81.317795
iter  50 value 80.820529
iter  60 value 79.605630
iter  70 value 79.234954
iter  80 value 79.077327
iter  90 value 78.146716
iter 100 value 76.617517
final  value 76.617517 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 112.259616 
iter  10 value 93.854964
iter  20 value 91.316223
iter  30 value 89.994329
iter  40 value 83.374523
iter  50 value 82.212310
iter  60 value 80.296789
iter  70 value 77.861713
iter  80 value 77.644267
iter  90 value 77.425293
iter 100 value 77.244965
final  value 77.244965 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.383151 
iter  10 value 93.969010
iter  20 value 86.944458
iter  30 value 85.381305
iter  40 value 84.255337
iter  50 value 80.602817
iter  60 value 78.408748
iter  70 value 77.269175
iter  80 value 76.506533
iter  90 value 75.929822
iter 100 value 75.524079
final  value 75.524079 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.390541 
iter  10 value 95.632821
iter  20 value 83.326979
iter  30 value 81.666801
iter  40 value 80.369271
iter  50 value 78.272274
iter  60 value 78.036650
iter  70 value 77.516205
iter  80 value 77.428675
iter  90 value 77.321149
iter 100 value 77.139411
final  value 77.139411 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.587793 
final  value 94.054535 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.288962 
final  value 94.054583 
converged
Fitting Repeat 3 

# weights:  103
initial  value 110.450071 
final  value 94.034696 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.631827 
final  value 94.054554 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.093169 
final  value 94.054885 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.899268 
iter  10 value 94.057953
iter  20 value 94.044716
iter  30 value 84.378428
iter  40 value 82.872682
iter  50 value 80.549606
final  value 80.546822 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.499267 
iter  10 value 94.000020
iter  20 value 93.894900
iter  30 value 93.894011
iter  30 value 93.894010
iter  30 value 93.894010
final  value 93.894010 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.371241 
iter  10 value 94.037176
iter  20 value 93.938536
iter  30 value 92.103175
iter  40 value 91.953605
iter  50 value 91.953181
iter  60 value 80.390917
iter  70 value 78.771598
iter  80 value 78.651850
iter  90 value 78.651672
final  value 78.651609 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.605246 
iter  10 value 91.164211
iter  20 value 84.131726
iter  30 value 84.123250
iter  40 value 84.094898
iter  50 value 83.287745
iter  60 value 80.596526
iter  70 value 77.770023
iter  80 value 77.750262
iter  90 value 77.749350
iter 100 value 77.739559
final  value 77.739559 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 113.622015 
iter  10 value 94.059001
iter  20 value 94.035864
iter  30 value 90.903642
iter  40 value 90.826069
iter  50 value 80.476565
iter  60 value 80.386320
iter  70 value 78.879129
iter  80 value 78.560330
iter  90 value 78.455665
iter 100 value 78.449964
final  value 78.449964 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 98.648293 
iter  10 value 94.057868
iter  20 value 88.169917
iter  30 value 85.446843
iter  40 value 85.444507
iter  50 value 84.232721
iter  60 value 80.106091
iter  70 value 80.094770
iter  80 value 79.404262
iter  90 value 79.312235
iter 100 value 79.310133
final  value 79.310133 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 101.319858 
iter  10 value 94.041025
iter  20 value 94.033018
iter  30 value 93.975607
iter  40 value 92.680344
final  value 92.665803 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.899249 
iter  10 value 93.831529
iter  20 value 93.819151
iter  30 value 92.990879
iter  40 value 85.824866
iter  50 value 85.047879
iter  60 value 83.854023
iter  70 value 83.853354
iter  80 value 83.849205
iter  90 value 83.848803
iter 100 value 83.760865
final  value 83.760865 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.527417 
iter  10 value 94.041322
iter  20 value 94.038952
iter  30 value 94.020561
iter  40 value 93.796124
iter  50 value 93.270205
iter  60 value 93.107303
iter  70 value 93.086442
iter  80 value 93.082846
iter  90 value 93.052681
iter 100 value 91.483627
final  value 91.483627 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.298526 
iter  10 value 90.597763
iter  20 value 90.477227
iter  30 value 89.242613
iter  40 value 89.137639
iter  50 value 85.742149
iter  60 value 85.211737
iter  70 value 85.102613
iter  80 value 85.088416
iter  90 value 85.087008
iter 100 value 85.003788
final  value 85.003788 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 148.476224 
iter  10 value 117.767160
iter  20 value 117.761992
iter  30 value 117.761485
iter  40 value 117.761140
iter  50 value 115.513908
iter  60 value 107.971363
iter  70 value 107.910393
final  value 107.910308 
converged
Fitting Repeat 2 

# weights:  507
initial  value 135.690584 
iter  10 value 117.767074
iter  20 value 117.725905
iter  30 value 107.614240
iter  40 value 106.825337
iter  50 value 106.784126
iter  60 value 106.764492
final  value 106.764266 
converged
Fitting Repeat 3 

# weights:  507
initial  value 141.731115 
iter  10 value 117.766963
iter  20 value 117.759688
final  value 117.759643 
converged
Fitting Repeat 4 

# weights:  507
initial  value 136.563803 
iter  10 value 117.766714
iter  20 value 117.743254
iter  30 value 115.616511
iter  40 value 107.003617
final  value 107.002639 
converged
Fitting Repeat 5 

# weights:  507
initial  value 136.422792 
iter  10 value 117.898339
iter  20 value 117.864523
iter  30 value 107.876732
iter  40 value 107.010165
iter  50 value 107.009748
iter  60 value 107.007810
iter  70 value 107.004737
iter  80 value 105.768111
iter  90 value 105.346562
iter 100 value 105.326843
final  value 105.326843 
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 -- Thu Jun 27 02:43:52 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 
  45.68    1.87   47.89