##############################################################################
##############################################################################
###
### Running command:
###
###   F:\biocbuild\bbs-3.20-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.20-bioc\R\library --no-vignettes --timings HPiP_1.12.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory 'F:/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck'
* using R version 4.4.2 (2024-10-31 ucrt)
* using platform: x86_64-w64-mingw32
* R was compiled by
    gcc.exe (GCC) 13.3.0
    GNU Fortran (GCC) 13.3.0
* 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 '1.12.0'
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking 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      35.17   2.22   37.64
var_imp       35.96   1.36   37.33
corr_plot     32.87   1.76   34.66
pred_ensembel 13.65   0.37   12.66
enrichfindP    0.57   0.11   14.94
* 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-3.20-bioc/meat/HPiP.Rcheck/00check.log'
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   F:\biocbuild\bbs-3.20-bioc\R\bin\R.exe CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library 'F:/biocbuild/bbs-3.20-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 4.4.2 (2024-10-31 ucrt) -- "Pile of Leaves"
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 94.434735 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.247075 
final  value 93.810011 
converged
Fitting Repeat 3 

# weights:  103
initial  value 108.712700 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.488354 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.700451 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.674804 
final  value 94.032967 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.007897 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 114.376782 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.203430 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.847933 
iter  10 value 92.096995
iter  20 value 92.095554
iter  30 value 92.010119
iter  40 value 91.297562
iter  40 value 91.297562
iter  40 value 91.297562
final  value 91.297562 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.486766 
iter  10 value 88.837271
iter  20 value 86.092527
iter  30 value 85.978603
final  value 85.972196 
converged
Fitting Repeat 2 

# weights:  507
initial  value 124.826022 
iter  10 value 93.685444
final  value 93.671508 
converged
Fitting Repeat 3 

# weights:  507
initial  value 115.133236 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.921825 
iter  10 value 93.832158
iter  20 value 93.831044
final  value 93.831042 
converged
Fitting Repeat 5 

# weights:  507
initial  value 118.532487 
iter  10 value 94.039781
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.134771 
iter  10 value 93.919315
iter  20 value 88.102465
iter  30 value 86.974495
iter  40 value 86.766850
iter  50 value 86.653798
iter  60 value 86.323676
iter  70 value 86.245557
iter  80 value 86.231573
final  value 86.231571 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.559248 
iter  10 value 94.221660
iter  20 value 89.087736
iter  30 value 86.831110
iter  40 value 86.464416
iter  50 value 86.386308
iter  60 value 85.802253
iter  70 value 85.509818
iter  80 value 85.119032
iter  90 value 84.208032
iter 100 value 83.880316
final  value 83.880316 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.025300 
iter  10 value 94.047203
iter  20 value 91.502601
iter  30 value 89.628119
iter  40 value 88.466591
iter  50 value 88.344167
iter  60 value 88.316005
iter  70 value 87.994356
iter  80 value 86.026183
iter  90 value 85.914984
iter 100 value 85.819535
final  value 85.819535 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 111.749996 
iter  10 value 93.598090
iter  20 value 88.541820
iter  30 value 86.833237
iter  40 value 84.846130
iter  50 value 84.689172
iter  60 value 84.603837
iter  70 value 84.433879
iter  80 value 84.387243
iter  90 value 84.141147
iter 100 value 83.883604
final  value 83.883604 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 95.995003 
iter  10 value 93.883446
iter  20 value 91.812370
iter  30 value 88.325367
iter  40 value 88.066655
iter  50 value 86.678755
iter  60 value 85.908719
iter  70 value 85.068734
iter  80 value 84.159994
iter  90 value 83.881140
final  value 83.878012 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.160413 
iter  10 value 94.048584
iter  20 value 93.831238
iter  30 value 91.155746
iter  40 value 89.270613
iter  50 value 85.969370
iter  60 value 85.402827
iter  70 value 85.144855
iter  80 value 84.269685
iter  90 value 83.307995
iter 100 value 82.867234
final  value 82.867234 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.309104 
iter  10 value 94.227524
iter  20 value 88.499292
iter  30 value 87.902491
iter  40 value 87.727507
iter  50 value 87.637207
iter  60 value 85.748250
iter  70 value 83.652943
iter  80 value 83.346977
iter  90 value 83.290656
iter 100 value 83.249713
final  value 83.249713 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.593974 
iter  10 value 93.871716
iter  20 value 89.144779
iter  30 value 87.382985
iter  40 value 86.985752
iter  50 value 84.637627
iter  60 value 83.729294
iter  70 value 83.227025
iter  80 value 83.124924
iter  90 value 82.823795
iter 100 value 82.664255
final  value 82.664255 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 118.516081 
iter  10 value 94.364130
iter  20 value 92.928129
iter  30 value 87.529879
iter  40 value 85.327097
iter  50 value 85.113050
iter  60 value 84.983329
iter  70 value 84.677266
iter  80 value 83.767096
iter  90 value 83.269514
iter 100 value 83.133229
final  value 83.133229 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.565608 
iter  10 value 94.003199
iter  20 value 91.177186
iter  30 value 87.244473
iter  40 value 85.785435
iter  50 value 84.819216
iter  60 value 84.043594
iter  70 value 83.110435
iter  80 value 82.975580
iter  90 value 82.941432
iter 100 value 82.834108
final  value 82.834108 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 113.983420 
iter  10 value 94.113355
iter  20 value 93.648132
iter  30 value 91.128506
iter  40 value 90.623207
iter  50 value 88.414129
iter  60 value 86.269346
iter  70 value 84.223716
iter  80 value 83.511632
iter  90 value 83.003054
iter 100 value 82.800231
final  value 82.800231 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.084563 
iter  10 value 95.879383
iter  20 value 91.320113
iter  30 value 86.231999
iter  40 value 84.938961
iter  50 value 84.011766
iter  60 value 83.349374
iter  70 value 83.064774
iter  80 value 82.966613
iter  90 value 82.897790
iter 100 value 82.869994
final  value 82.869994 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.097344 
iter  10 value 94.038791
iter  20 value 88.207987
iter  30 value 87.779580
iter  40 value 86.894762
iter  50 value 84.481513
iter  60 value 83.100380
iter  70 value 82.822663
iter  80 value 82.664849
iter  90 value 82.515233
iter 100 value 82.304039
final  value 82.304039 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.003455 
iter  10 value 93.354869
iter  20 value 89.677439
iter  30 value 86.567428
iter  40 value 85.222510
iter  50 value 83.242688
iter  60 value 82.816652
iter  70 value 82.699728
iter  80 value 82.565947
iter  90 value 82.321002
iter 100 value 82.265822
final  value 82.265822 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 136.036958 
iter  10 value 92.257009
iter  20 value 87.802917
iter  30 value 86.320879
iter  40 value 85.675158
iter  50 value 85.134596
iter  60 value 83.841587
iter  70 value 83.654546
iter  80 value 83.441821
iter  90 value 83.272068
iter 100 value 83.251370
final  value 83.251370 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.128403 
final  value 94.054633 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.644118 
final  value 94.054525 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.336444 
iter  10 value 93.841293
iter  20 value 93.839665
final  value 93.839630 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.362967 
iter  10 value 94.054335
iter  20 value 94.042652
final  value 93.839870 
converged
Fitting Repeat 5 

# weights:  103
initial  value 110.495571 
iter  10 value 94.029579
iter  20 value 94.029423
iter  30 value 92.867100
iter  40 value 89.631513
iter  50 value 88.450704
iter  60 value 88.445182
iter  70 value 88.423930
iter  80 value 87.723359
iter  90 value 87.717484
iter 100 value 87.716365
final  value 87.716365 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 127.405193 
iter  10 value 94.057664
iter  20 value 94.025707
iter  30 value 91.726063
iter  40 value 88.123616
iter  50 value 87.923798
iter  60 value 87.779681
iter  70 value 87.720435
iter  80 value 86.949203
iter  90 value 82.739251
iter 100 value 82.340064
final  value 82.340064 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 118.997009 
iter  10 value 93.676401
iter  20 value 90.493537
iter  30 value 87.092916
iter  40 value 84.276827
iter  50 value 83.325934
iter  60 value 82.581627
iter  70 value 82.580924
final  value 82.580625 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.807538 
iter  10 value 94.057606
iter  20 value 94.052928
iter  20 value 94.052927
iter  20 value 94.052927
final  value 94.052927 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.557711 
iter  10 value 94.057638
iter  20 value 92.977831
iter  30 value 92.047768
iter  40 value 92.046692
final  value 92.046635 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.871145 
iter  10 value 94.057246
iter  20 value 87.602402
iter  30 value 85.833523
iter  40 value 85.712342
iter  50 value 85.711814
iter  60 value 85.710890
iter  70 value 85.707731
iter  80 value 85.706580
iter  90 value 84.172826
iter 100 value 83.411139
final  value 83.411139 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 101.463436 
iter  10 value 94.059971
iter  20 value 93.987716
iter  30 value 91.429441
iter  40 value 90.146584
iter  50 value 87.811834
iter  60 value 86.597353
iter  70 value 85.413257
iter  80 value 85.327029
iter  90 value 85.326081
iter 100 value 85.325734
final  value 85.325734 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 119.614472 
iter  10 value 94.040940
iter  20 value 94.021681
iter  30 value 92.746181
iter  40 value 88.138491
iter  50 value 84.834522
iter  60 value 83.955552
iter  70 value 83.632652
iter  80 value 82.654599
iter  90 value 82.538217
iter 100 value 82.528365
final  value 82.528365 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 96.335764 
iter  10 value 93.679251
iter  20 value 93.672731
iter  30 value 92.734843
iter  40 value 88.823506
iter  50 value 86.336743
iter  60 value 86.128298
iter  70 value 86.104536
final  value 86.104461 
converged
Fitting Repeat 4 

# weights:  507
initial  value 116.737030 
iter  10 value 94.043197
iter  20 value 94.035720
iter  30 value 94.034627
iter  40 value 94.034096
iter  50 value 94.033696
final  value 94.033684 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.951066 
iter  10 value 93.839806
iter  20 value 93.834296
iter  30 value 89.752146
iter  40 value 88.979840
iter  50 value 85.922520
iter  60 value 83.804263
iter  70 value 83.351495
iter  80 value 83.224382
iter  90 value 83.161049
iter 100 value 83.160342
final  value 83.160342 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.253645 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.106429 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.183552 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.255405 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.174375 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.689056 
final  value 93.922222 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.803827 
iter  10 value 86.484729
iter  20 value 83.307118
iter  30 value 83.283762
iter  40 value 82.882899
final  value 82.881718 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.374831 
iter  10 value 93.539022
iter  20 value 92.178146
iter  30 value 92.151314
iter  40 value 91.855594
final  value 91.852510 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.434296 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.013883 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.631608 
final  value 94.252920 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.498160 
final  value 93.922222 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.967763 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  507
initial  value 121.301613 
final  value 93.102857 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.965219 
iter  10 value 88.417674
iter  20 value 83.064303
final  value 83.045768 
converged
Fitting Repeat 1 

# weights:  103
initial  value 107.081242 
iter  10 value 94.429754
iter  20 value 86.627937
iter  30 value 86.032024
iter  40 value 80.815163
iter  50 value 80.313924
iter  60 value 80.198554
iter  70 value 79.145015
iter  80 value 78.889560
final  value 78.880593 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.980751 
iter  10 value 94.273665
iter  20 value 84.689904
iter  30 value 82.294473
iter  40 value 81.602101
iter  50 value 81.382880
iter  60 value 81.155059
iter  70 value 80.937575
iter  80 value 79.405068
iter  90 value 79.102870
iter 100 value 79.050730
final  value 79.050730 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.038431 
iter  10 value 94.049565
iter  20 value 92.532242
iter  30 value 92.258637
iter  40 value 92.149551
iter  50 value 84.421323
iter  60 value 81.812848
iter  70 value 80.461506
iter  80 value 80.120625
iter  90 value 80.000625
iter 100 value 79.474247
final  value 79.474247 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 101.509982 
iter  10 value 94.466824
iter  20 value 87.648440
iter  30 value 84.309332
iter  40 value 83.625736
iter  50 value 82.937491
iter  60 value 82.303302
iter  70 value 81.868982
iter  80 value 81.680041
iter  90 value 81.044138
iter 100 value 80.724396
final  value 80.724396 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 98.487604 
iter  10 value 93.919097
iter  20 value 81.784989
iter  30 value 81.217695
iter  40 value 80.820907
iter  50 value 80.705030
iter  60 value 80.664391
iter  70 value 79.063418
iter  80 value 78.689590
iter  90 value 78.687371
final  value 78.687365 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.070125 
iter  10 value 94.451098
iter  20 value 92.848673
iter  30 value 82.427244
iter  40 value 80.603175
iter  50 value 79.317105
iter  60 value 78.278986
iter  70 value 78.023000
iter  80 value 77.921346
iter  90 value 77.843928
iter 100 value 77.760100
final  value 77.760100 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 97.853514 
iter  10 value 85.627759
iter  20 value 84.310407
iter  30 value 81.988385
iter  40 value 80.434740
iter  50 value 80.267324
iter  60 value 79.248426
iter  70 value 78.939825
iter  80 value 78.719403
iter  90 value 78.451854
iter 100 value 77.994722
final  value 77.994722 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.325023 
iter  10 value 94.447718
iter  20 value 84.263655
iter  30 value 82.442282
iter  40 value 82.265401
iter  50 value 82.081024
iter  60 value 80.645001
iter  70 value 80.092458
iter  80 value 79.996860
iter  90 value 79.104258
iter 100 value 78.860150
final  value 78.860150 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 121.770869 
iter  10 value 94.500547
iter  20 value 90.232870
iter  30 value 85.620627
iter  40 value 84.444064
iter  50 value 84.097719
iter  60 value 81.972212
iter  70 value 80.003522
iter  80 value 79.746718
iter  90 value 78.618519
iter 100 value 78.385018
final  value 78.385018 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 121.995771 
iter  10 value 94.554079
iter  20 value 93.207954
iter  30 value 86.051339
iter  40 value 85.656889
iter  50 value 84.893051
iter  60 value 82.136553
iter  70 value 81.564240
iter  80 value 80.083401
iter  90 value 79.872753
iter 100 value 79.371956
final  value 79.371956 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 131.602541 
iter  10 value 94.527769
iter  20 value 87.925187
iter  30 value 82.772717
iter  40 value 80.183153
iter  50 value 78.830485
iter  60 value 78.497529
iter  70 value 78.313266
iter  80 value 78.287693
iter  90 value 78.038207
iter 100 value 77.666505
final  value 77.666505 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 140.823881 
iter  10 value 98.069949
iter  20 value 93.657099
iter  30 value 82.025087
iter  40 value 81.151637
iter  50 value 80.825986
iter  60 value 80.800989
iter  70 value 80.548081
iter  80 value 79.098142
iter  90 value 78.999615
iter 100 value 78.932123
final  value 78.932123 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 124.427728 
iter  10 value 95.370948
iter  20 value 82.952412
iter  30 value 82.532796
iter  40 value 82.295937
iter  50 value 81.312449
iter  60 value 79.932866
iter  70 value 79.094423
iter  80 value 78.706452
iter  90 value 78.245021
iter 100 value 77.776500
final  value 77.776500 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.618921 
iter  10 value 94.486614
iter  20 value 90.987816
iter  30 value 89.871256
iter  40 value 82.560944
iter  50 value 80.241893
iter  60 value 78.540664
iter  70 value 78.087940
iter  80 value 77.832860
iter  90 value 77.757583
iter 100 value 77.725483
final  value 77.725483 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.807558 
iter  10 value 94.478487
iter  20 value 93.876876
iter  30 value 92.030123
iter  40 value 86.618236
iter  50 value 82.418328
iter  60 value 80.745430
iter  70 value 79.967071
iter  80 value 79.343921
iter  90 value 79.319242
iter 100 value 79.230473
final  value 79.230473 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.082561 
iter  10 value 94.485745
final  value 94.484383 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.505615 
final  value 94.485926 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.670237 
final  value 94.032354 
converged
Fitting Repeat 4 

# weights:  103
initial  value 110.404651 
final  value 94.485834 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.784874 
final  value 94.485668 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.409402 
iter  10 value 90.616448
iter  20 value 86.151265
iter  30 value 86.096559
final  value 86.096234 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.051175 
iter  10 value 94.488784
iter  20 value 93.882869
iter  30 value 84.494382
iter  40 value 83.857093
iter  50 value 83.373243
iter  60 value 83.330851
iter  70 value 80.151250
iter  80 value 79.915161
iter  90 value 79.763810
iter 100 value 79.762625
final  value 79.762625 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 113.289205 
iter  10 value 94.471812
iter  20 value 94.432653
iter  30 value 90.748301
iter  40 value 85.061721
iter  50 value 84.752112
iter  60 value 80.144286
iter  70 value 78.597108
iter  80 value 77.939681
iter  90 value 77.938825
iter 100 value 77.937608
final  value 77.937608 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 97.005151 
iter  10 value 94.488296
iter  20 value 93.647204
iter  30 value 81.784425
iter  40 value 81.555422
iter  50 value 81.554000
iter  60 value 81.540838
iter  70 value 81.538786
iter  80 value 81.536416
final  value 81.535681 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.823940 
iter  10 value 94.471261
iter  20 value 94.335976
iter  30 value 94.095745
iter  40 value 93.813026
iter  50 value 93.484538
iter  60 value 93.484392
final  value 93.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.496250 
iter  10 value 94.388073
iter  20 value 94.387618
iter  30 value 94.382114
iter  40 value 94.230650
iter  50 value 81.789956
iter  60 value 81.102721
iter  70 value 81.092967
iter  80 value 81.043199
iter  90 value 81.042693
iter 100 value 80.890632
final  value 80.890632 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 93.493746 
iter  10 value 92.276051
iter  20 value 92.270913
iter  30 value 92.066039
iter  40 value 91.340271
iter  50 value 83.915303
iter  60 value 83.413311
iter  70 value 83.353021
final  value 83.353010 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.777775 
iter  10 value 94.491982
iter  20 value 94.413499
iter  30 value 83.423494
iter  40 value 80.303376
iter  50 value 78.548399
iter  60 value 77.066565
iter  70 value 76.984653
iter  80 value 76.954594
iter  90 value 76.829315
iter 100 value 76.717590
final  value 76.717590 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.509094 
iter  10 value 94.486472
iter  20 value 91.840385
iter  30 value 82.975131
final  value 82.974681 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.365231 
iter  10 value 94.495431
iter  20 value 94.475378
iter  30 value 93.693026
iter  40 value 93.691498
iter  50 value 93.511506
iter  60 value 89.053434
iter  70 value 88.854568
iter  80 value 88.853549
iter  90 value 87.588598
iter 100 value 87.540629
final  value 87.540629 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.551920 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.333232 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.325802 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.945960 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.126298 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.152255 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.036148 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.265480 
final  value 93.356643 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.133780 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.685584 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.220814 
iter  10 value 93.582418
iter  10 value 93.582418
iter  10 value 93.582418
final  value 93.582418 
converged
Fitting Repeat 2 

# weights:  507
initial  value 94.443797 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.335829 
final  value 93.582418 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.475259 
iter  10 value 92.293928
final  value 92.293924 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.733229 
final  value 93.582418 
converged
Fitting Repeat 1 

# weights:  103
initial  value 110.311225 
iter  10 value 93.966023
iter  20 value 87.701130
iter  30 value 83.432717
iter  40 value 83.097516
iter  50 value 82.736666
iter  60 value 82.628245
iter  70 value 82.625332
final  value 82.625328 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.915437 
iter  10 value 94.121140
iter  20 value 94.041199
iter  30 value 90.207048
iter  40 value 88.015627
iter  50 value 87.546031
iter  60 value 85.742446
iter  70 value 85.447407
iter  80 value 85.333243
iter  90 value 82.602057
iter 100 value 82.253508
final  value 82.253508 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.040446 
iter  10 value 94.056850
iter  20 value 94.055030
final  value 94.054870 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.394792 
iter  10 value 94.069915
iter  20 value 94.057160
iter  30 value 88.030511
iter  40 value 84.936532
iter  50 value 83.507466
iter  60 value 83.218616
iter  70 value 82.704404
iter  80 value 82.625716
iter  90 value 82.625317
final  value 82.625301 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.556953 
iter  10 value 93.841434
iter  20 value 89.596499
iter  30 value 85.029101
iter  40 value 81.372195
iter  50 value 80.545885
iter  60 value 80.055557
iter  70 value 79.675622
iter  80 value 79.632689
iter  90 value 79.613981
final  value 79.613648 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.031459 
iter  10 value 93.464093
iter  20 value 91.978542
iter  30 value 91.388097
iter  40 value 84.427606
iter  50 value 81.162418
iter  60 value 80.976107
iter  70 value 80.619584
iter  80 value 80.464505
iter  90 value 80.280796
iter 100 value 79.779919
final  value 79.779919 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.723034 
iter  10 value 94.794111
iter  20 value 91.587213
iter  30 value 85.761611
iter  40 value 84.715811
iter  50 value 83.031810
iter  60 value 82.140772
iter  70 value 81.508049
iter  80 value 80.987896
iter  90 value 79.807171
iter 100 value 79.422908
final  value 79.422908 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 125.300069 
iter  10 value 94.782317
iter  20 value 94.203921
iter  30 value 89.925485
iter  40 value 84.713700
iter  50 value 83.848286
iter  60 value 82.185127
iter  70 value 81.298491
iter  80 value 80.854085
iter  90 value 80.025652
iter 100 value 79.941399
final  value 79.941399 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 120.883667 
iter  10 value 94.063153
iter  20 value 93.649592
iter  30 value 92.614985
iter  40 value 87.720903
iter  50 value 82.868325
iter  60 value 79.721915
iter  70 value 78.748864
iter  80 value 78.711477
iter  90 value 78.448039
iter 100 value 78.416778
final  value 78.416778 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.626433 
iter  10 value 94.060478
iter  20 value 90.041642
iter  30 value 85.584982
iter  40 value 83.073576
iter  50 value 82.451960
iter  60 value 82.263344
iter  70 value 81.102606
iter  80 value 80.184285
iter  90 value 79.432414
iter 100 value 78.483705
final  value 78.483705 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.624273 
iter  10 value 94.120407
iter  20 value 93.468405
iter  30 value 90.175755
iter  40 value 88.719767
iter  50 value 88.228390
iter  60 value 81.553023
iter  70 value 80.392013
iter  80 value 79.646799
iter  90 value 78.855460
iter 100 value 78.611314
final  value 78.611314 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.486505 
iter  10 value 94.027832
iter  20 value 91.967617
iter  30 value 89.818045
iter  40 value 84.804317
iter  50 value 79.717814
iter  60 value 78.928853
iter  70 value 78.718848
iter  80 value 78.688840
iter  90 value 78.654214
iter 100 value 78.556547
final  value 78.556547 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 122.731443 
iter  10 value 93.947642
iter  20 value 84.864791
iter  30 value 83.195701
iter  40 value 80.031604
iter  50 value 79.531807
iter  60 value 79.219137
iter  70 value 78.682900
iter  80 value 78.583064
iter  90 value 78.371427
iter 100 value 78.148526
final  value 78.148526 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 117.728084 
iter  10 value 92.933119
iter  20 value 86.213136
iter  30 value 85.485866
iter  40 value 84.795685
iter  50 value 83.851587
iter  60 value 80.989453
iter  70 value 80.405035
iter  80 value 79.352449
iter  90 value 78.760467
iter 100 value 78.667085
final  value 78.667085 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.270536 
iter  10 value 94.348232
iter  20 value 93.716581
iter  30 value 92.646406
iter  40 value 86.608927
iter  50 value 83.661202
iter  60 value 82.855520
iter  70 value 79.697033
iter  80 value 79.498260
iter  90 value 78.915549
iter 100 value 78.707676
final  value 78.707676 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.811497 
final  value 94.054496 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.430620 
final  value 94.054875 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.254760 
final  value 94.054567 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.728922 
iter  10 value 93.870699
final  value 93.870675 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.322152 
iter  10 value 94.054691
final  value 94.052918 
converged
Fitting Repeat 1 

# weights:  305
initial  value 119.366084 
iter  10 value 94.057532
iter  20 value 93.995080
iter  30 value 84.135582
iter  40 value 84.061027
iter  50 value 83.993746
final  value 83.993744 
converged
Fitting Repeat 2 

# weights:  305
initial  value 113.129087 
iter  10 value 94.057431
iter  20 value 93.936633
iter  30 value 91.808172
iter  40 value 87.053189
iter  50 value 82.055460
iter  60 value 81.582939
iter  70 value 81.581835
iter  80 value 81.579749
iter  90 value 81.578302
iter 100 value 81.522535
final  value 81.522535 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 98.752199 
iter  10 value 94.057956
final  value 94.054192 
converged
Fitting Repeat 4 

# weights:  305
initial  value 123.922254 
iter  10 value 84.863306
iter  20 value 84.809380
iter  30 value 84.653852
iter  40 value 84.652758
iter  50 value 84.633535
iter  60 value 81.700125
iter  70 value 81.226900
final  value 81.220230 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.060441 
iter  10 value 94.058241
iter  20 value 94.052926
final  value 94.052919 
converged
Fitting Repeat 1 

# weights:  507
initial  value 113.620464 
iter  10 value 94.060751
iter  20 value 94.052200
iter  30 value 93.368345
final  value 93.357534 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.144290 
iter  10 value 94.060809
iter  20 value 93.578854
iter  30 value 91.483440
iter  40 value 83.151790
iter  50 value 81.354265
iter  60 value 80.406349
iter  70 value 80.386649
iter  80 value 80.132433
iter  90 value 78.937329
iter 100 value 78.275304
final  value 78.275304 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 95.305227 
iter  10 value 92.699463
iter  20 value 91.475910
iter  30 value 91.474603
iter  40 value 89.670175
iter  50 value 85.205622
iter  60 value 82.598935
iter  70 value 82.408413
iter  80 value 81.982070
iter  90 value 81.977705
iter 100 value 81.972244
final  value 81.972244 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 94.394579 
iter  10 value 94.061078
iter  20 value 88.804748
iter  30 value 86.148287
iter  40 value 82.003930
iter  50 value 81.997836
iter  60 value 81.834107
iter  70 value 81.140498
iter  80 value 81.132682
final  value 81.132093 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.057006 
iter  10 value 91.149974
iter  20 value 79.929587
iter  30 value 79.374634
iter  40 value 79.374252
iter  50 value 79.366444
iter  60 value 79.314746
iter  70 value 79.310454
iter  80 value 79.309095
iter  90 value 78.959778
iter 100 value 78.941331
final  value 78.941331 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.797237 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 114.340354 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.927380 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.080178 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.425463 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.432522 
final  value 94.443243 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.637138 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.965809 
iter  10 value 94.443355
final  value 94.443243 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.984536 
final  value 94.443243 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.221608 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.224282 
iter  10 value 92.659687
iter  20 value 90.597387
final  value 90.594100 
converged
Fitting Repeat 2 

# weights:  507
initial  value 94.505148 
iter  10 value 94.327256
iter  20 value 94.085036
final  value 94.084848 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.396446 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 127.121514 
iter  10 value 94.267500
iter  10 value 94.267500
iter  10 value 94.267500
final  value 94.267500 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.625863 
iter  10 value 94.480312
iter  20 value 94.447087
final  value 94.443243 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.116277 
iter  10 value 94.361723
iter  20 value 91.595085
iter  30 value 85.881662
iter  40 value 84.420686
iter  50 value 83.907298
iter  60 value 83.401325
iter  70 value 83.391312
iter  70 value 83.391312
iter  70 value 83.391312
final  value 83.391312 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.444105 
iter  10 value 94.502693
iter  20 value 94.486603
iter  30 value 86.008416
iter  40 value 84.565965
iter  50 value 83.580466
iter  60 value 83.422446
iter  70 value 81.740255
iter  80 value 81.332311
iter  90 value 81.276956
iter 100 value 81.263113
final  value 81.263113 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.187947 
iter  10 value 94.463714
iter  20 value 94.244495
iter  30 value 88.163456
iter  40 value 86.006091
iter  50 value 85.396083
iter  60 value 85.059532
iter  70 value 85.025837
iter  80 value 85.017640
final  value 85.017470 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.344715 
iter  10 value 94.488750
iter  20 value 90.116000
iter  30 value 85.140203
iter  40 value 85.033792
iter  50 value 84.262523
iter  60 value 83.733358
iter  70 value 83.374068
iter  80 value 83.197825
iter  90 value 83.142264
final  value 83.142208 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.807434 
iter  10 value 94.205283
iter  20 value 86.365775
iter  30 value 85.683342
iter  40 value 84.728699
iter  50 value 83.643126
iter  60 value 83.567570
final  value 83.567545 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.520471 
iter  10 value 94.409592
iter  20 value 84.088502
iter  30 value 83.075008
iter  40 value 82.093368
iter  50 value 81.214218
iter  60 value 81.079464
iter  70 value 80.168301
iter  80 value 79.822408
iter  90 value 79.723389
iter 100 value 79.693804
final  value 79.693804 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 113.586264 
iter  10 value 94.455510
iter  20 value 88.701635
iter  30 value 87.707194
iter  40 value 84.744473
iter  50 value 82.918741
iter  60 value 81.773436
iter  70 value 81.054667
iter  80 value 80.742573
iter  90 value 80.360658
iter 100 value 80.215989
final  value 80.215989 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.449164 
iter  10 value 94.508852
iter  20 value 89.281158
iter  30 value 88.589537
iter  40 value 88.288888
iter  50 value 87.412037
iter  60 value 84.176709
iter  70 value 81.518327
iter  80 value 80.976931
iter  90 value 80.891556
iter 100 value 80.706283
final  value 80.706283 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.337432 
iter  10 value 91.673933
iter  20 value 84.967212
iter  30 value 82.354780
iter  40 value 80.883648
iter  50 value 80.391968
iter  60 value 80.103156
iter  70 value 80.008190
iter  80 value 79.955396
iter  90 value 79.951521
iter 100 value 79.951136
final  value 79.951136 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.096330 
iter  10 value 97.354586
iter  20 value 91.961988
iter  30 value 91.680375
iter  40 value 90.731488
iter  50 value 88.265093
iter  60 value 86.152559
iter  70 value 85.012695
iter  80 value 84.221217
iter  90 value 83.805770
iter 100 value 82.327886
final  value 82.327886 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 113.283947 
iter  10 value 94.561793
iter  20 value 89.388839
iter  30 value 86.102709
iter  40 value 84.431835
iter  50 value 80.864555
iter  60 value 80.300934
iter  70 value 79.924674
iter  80 value 79.530843
iter  90 value 79.486441
iter 100 value 79.445934
final  value 79.445934 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.216201 
iter  10 value 94.493532
iter  20 value 86.970560
iter  30 value 83.822063
iter  40 value 81.212292
iter  50 value 80.876418
iter  60 value 80.194334
iter  70 value 79.589631
iter  80 value 79.396247
iter  90 value 79.358749
iter 100 value 79.238921
final  value 79.238921 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.427534 
iter  10 value 90.359912
iter  20 value 85.803541
iter  30 value 83.724968
iter  40 value 81.212257
iter  50 value 80.356601
iter  60 value 80.274656
iter  70 value 80.211454
iter  80 value 79.975593
iter  90 value 79.890496
iter 100 value 79.875096
final  value 79.875096 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.592925 
iter  10 value 95.157150
iter  20 value 88.102753
iter  30 value 84.436355
iter  40 value 83.445937
iter  50 value 82.174257
iter  60 value 81.656029
iter  70 value 80.548489
iter  80 value 80.160139
iter  90 value 79.629778
iter 100 value 79.520230
final  value 79.520230 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 132.069039 
iter  10 value 94.891959
iter  20 value 85.374432
iter  30 value 82.353787
iter  40 value 81.648651
iter  50 value 80.679529
iter  60 value 80.154803
iter  70 value 80.032085
iter  80 value 79.807743
iter  90 value 79.710169
iter 100 value 79.643543
final  value 79.643543 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.330844 
iter  10 value 94.485893
iter  20 value 94.458190
iter  30 value 93.270762
iter  40 value 87.458107
iter  50 value 87.223703
iter  60 value 87.223217
iter  70 value 87.222817
final  value 87.222816 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.950322 
final  value 94.485948 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.392872 
final  value 94.485879 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.655898 
final  value 94.485968 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.664595 
final  value 94.485964 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.760638 
iter  10 value 89.504221
iter  20 value 87.301527
iter  30 value 87.237159
iter  40 value 87.236059
iter  50 value 87.232171
iter  60 value 87.231718
iter  70 value 87.231103
iter  80 value 87.229631
final  value 87.229556 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.353376 
iter  10 value 94.488809
iter  20 value 94.212068
iter  30 value 93.483634
iter  40 value 93.482014
iter  50 value 92.504788
final  value 87.785076 
converged
Fitting Repeat 3 

# weights:  305
initial  value 113.934679 
iter  10 value 94.489488
iter  20 value 92.261726
iter  30 value 83.703451
iter  40 value 83.437771
iter  50 value 83.437218
iter  60 value 83.433735
iter  70 value 82.958981
iter  80 value 82.956838
iter  90 value 82.225789
iter 100 value 79.640614
final  value 79.640614 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.606645 
iter  10 value 94.448170
iter  20 value 93.874387
iter  30 value 86.052938
final  value 86.052606 
converged
Fitting Repeat 5 

# weights:  305
initial  value 111.455093 
iter  10 value 94.448422
iter  20 value 93.717050
iter  30 value 84.934709
iter  40 value 84.556146
iter  50 value 84.553264
final  value 84.553261 
converged
Fitting Repeat 1 

# weights:  507
initial  value 126.438537 
iter  10 value 93.687067
iter  20 value 92.766571
iter  30 value 92.547086
iter  40 value 92.543815
iter  50 value 92.461774
iter  60 value 86.605740
iter  70 value 83.690201
iter  80 value 81.275465
iter  90 value 79.989154
iter 100 value 78.989889
final  value 78.989889 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 115.575488 
iter  10 value 92.413039
iter  20 value 84.129111
iter  30 value 81.576354
iter  40 value 80.662372
iter  50 value 80.654479
iter  60 value 80.651208
iter  70 value 80.446765
iter  80 value 79.769346
iter  90 value 79.308129
iter 100 value 79.117502
final  value 79.117502 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 97.322459 
iter  10 value 94.451456
iter  20 value 94.068556
iter  30 value 84.461038
iter  40 value 83.492180
iter  50 value 83.465862
iter  60 value 82.970700
iter  70 value 82.906971
iter  80 value 82.906594
iter  90 value 82.906093
iter 100 value 82.858257
final  value 82.858257 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 101.489216 
iter  10 value 94.492557
iter  20 value 94.484573
iter  30 value 94.162923
iter  40 value 86.132810
iter  50 value 84.260993
iter  60 value 84.097596
iter  70 value 84.097467
iter  80 value 84.097342
iter  90 value 83.674292
iter 100 value 83.587557
final  value 83.587557 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.123195 
iter  10 value 94.492933
iter  20 value 94.471190
iter  30 value 90.094107
iter  40 value 86.546546
iter  50 value 83.071504
iter  60 value 83.016800
iter  70 value 82.973718
iter  80 value 82.665037
iter  90 value 81.508027
iter 100 value 81.502087
final  value 81.502087 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.327454 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.647109 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.186800 
iter  10 value 86.669748
iter  20 value 86.622127
iter  20 value 86.622126
iter  20 value 86.622126
final  value 86.622126 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.504834 
final  value 94.482149 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.690185 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.672123 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.126942 
iter  10 value 94.484213
iter  10 value 94.484212
iter  10 value 94.484212
final  value 94.484212 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.073992 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.753388 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.982056 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.186286 
iter  10 value 94.484221
final  value 94.484212 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.360450 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.109146 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 108.561765 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.183025 
final  value 94.484137 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.398779 
iter  10 value 94.157173
iter  20 value 90.614159
iter  30 value 89.207364
iter  40 value 88.993871
iter  50 value 87.776097
iter  60 value 84.975657
iter  70 value 84.858201
iter  80 value 84.690195
final  value 84.689349 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.501522 
iter  10 value 94.488030
iter  20 value 86.626856
iter  30 value 86.265250
iter  40 value 86.134986
final  value 86.130043 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.763117 
iter  10 value 93.960670
iter  20 value 86.736797
iter  30 value 86.323685
iter  40 value 86.264105
iter  50 value 86.176542
iter  60 value 86.122471
final  value 86.122394 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.724020 
iter  10 value 94.545507
iter  20 value 88.665779
iter  30 value 87.894123
iter  40 value 86.522728
iter  50 value 86.201595
iter  60 value 86.193041
iter  70 value 86.174525
iter  80 value 86.131727
final  value 86.130043 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.698946 
iter  10 value 94.358296
iter  20 value 89.585068
iter  30 value 87.409801
iter  40 value 87.223297
iter  50 value 86.534212
iter  60 value 85.381320
iter  70 value 85.215272
iter  80 value 85.136747
iter  90 value 84.991054
iter 100 value 84.930197
final  value 84.930197 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 121.498542 
iter  10 value 95.134632
iter  20 value 94.498334
iter  30 value 87.285595
iter  40 value 85.172929
iter  50 value 84.788062
iter  60 value 84.614552
iter  70 value 84.603138
iter  80 value 84.386315
iter  90 value 83.682543
iter 100 value 83.428973
final  value 83.428973 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 113.747949 
iter  10 value 94.491436
iter  20 value 93.811066
iter  30 value 88.410084
iter  40 value 86.662972
iter  50 value 86.366201
iter  60 value 85.059551
iter  70 value 84.403919
iter  80 value 84.131246
iter  90 value 83.807555
iter 100 value 83.396070
final  value 83.396070 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.547011 
iter  10 value 94.357850
iter  20 value 93.589956
iter  30 value 89.790547
iter  40 value 87.183466
iter  50 value 86.616154
iter  60 value 84.672332
iter  70 value 83.600598
iter  80 value 83.004929
iter  90 value 82.167265
iter 100 value 81.803402
final  value 81.803402 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.208349 
iter  10 value 94.366266
iter  20 value 88.160337
iter  30 value 86.590049
iter  40 value 85.427969
iter  50 value 84.956567
iter  60 value 83.829031
iter  70 value 82.691875
iter  80 value 82.321942
iter  90 value 82.196001
iter 100 value 82.066756
final  value 82.066756 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.633988 
iter  10 value 93.643403
iter  20 value 90.128465
iter  30 value 88.078412
iter  40 value 87.191922
iter  50 value 86.879971
iter  60 value 84.488072
iter  70 value 82.368769
iter  80 value 82.170741
iter  90 value 82.082492
iter 100 value 82.003176
final  value 82.003176 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.331074 
iter  10 value 95.754642
iter  20 value 92.097779
iter  30 value 88.897756
iter  40 value 86.915268
iter  50 value 85.660540
iter  60 value 84.907203
iter  70 value 84.578126
iter  80 value 84.098613
iter  90 value 82.565312
iter 100 value 82.060006
final  value 82.060006 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.338663 
iter  10 value 93.562835
iter  20 value 85.672599
iter  30 value 84.857834
iter  40 value 84.353998
iter  50 value 82.866408
iter  60 value 82.282457
iter  70 value 81.977439
iter  80 value 81.957389
iter  90 value 81.905169
iter 100 value 81.864482
final  value 81.864482 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.699038 
iter  10 value 94.773750
iter  20 value 94.441517
iter  30 value 90.212583
iter  40 value 87.117945
iter  50 value 85.845608
iter  60 value 85.622363
iter  70 value 85.412494
iter  80 value 85.227361
iter  90 value 84.387703
iter 100 value 82.644465
final  value 82.644465 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 115.859408 
iter  10 value 94.122146
iter  20 value 91.730522
iter  30 value 87.914362
iter  40 value 87.623345
iter  50 value 84.470471
iter  60 value 83.454782
iter  70 value 82.307153
iter  80 value 82.143583
iter  90 value 82.019446
iter 100 value 81.934131
final  value 81.934131 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 115.768997 
iter  10 value 94.826396
iter  20 value 93.878871
iter  30 value 88.288523
iter  40 value 87.918096
iter  50 value 86.768870
iter  60 value 86.680821
iter  70 value 86.513948
iter  80 value 85.052550
iter  90 value 82.970244
iter 100 value 82.608431
final  value 82.608431 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.521543 
iter  10 value 94.277034
iter  20 value 94.275531
final  value 94.275438 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.889524 
iter  10 value 94.276731
final  value 94.276607 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.270174 
final  value 94.485892 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.451345 
final  value 94.485769 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.978885 
final  value 94.485986 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.429490 
iter  10 value 94.487515
iter  20 value 94.405893
iter  30 value 88.312613
iter  40 value 84.595393
iter  50 value 82.446019
iter  60 value 82.353707
iter  70 value 82.337022
iter  80 value 82.335060
final  value 82.335050 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.848409 
iter  10 value 94.488494
final  value 94.485420 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.841852 
iter  10 value 94.488429
iter  20 value 94.409699
iter  30 value 90.760039
iter  40 value 85.421232
iter  50 value 85.065024
iter  60 value 85.047997
iter  70 value 84.306145
iter  80 value 83.072802
final  value 83.038473 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.851201 
iter  10 value 94.280269
iter  20 value 94.258437
iter  30 value 93.421514
iter  40 value 90.559189
iter  50 value 86.526987
iter  60 value 86.517018
iter  70 value 86.516638
iter  80 value 86.516277
final  value 86.516188 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.064447 
iter  10 value 94.488923
iter  20 value 94.484255
final  value 94.484216 
converged
Fitting Repeat 1 

# weights:  507
initial  value 110.972234 
iter  10 value 94.283905
iter  20 value 94.271589
iter  30 value 93.940864
iter  40 value 92.578435
iter  50 value 91.865161
iter  60 value 91.854990
iter  70 value 91.854857
iter  80 value 91.854572
iter  90 value 91.844558
iter 100 value 88.203695
final  value 88.203695 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 97.544622 
iter  10 value 94.491531
iter  20 value 94.484233
final  value 94.275785 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.212791 
iter  10 value 94.419556
iter  20 value 94.277267
iter  30 value 94.276658
iter  40 value 94.275137
iter  50 value 89.565255
iter  60 value 83.837509
iter  70 value 83.833456
iter  80 value 83.825025
iter  90 value 83.705922
iter 100 value 83.652999
final  value 83.652999 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.230054 
iter  10 value 94.492905
iter  20 value 94.219215
iter  30 value 90.467777
final  value 90.434884 
converged
Fitting Repeat 5 

# weights:  507
initial  value 119.436891 
iter  10 value 94.452454
iter  20 value 94.419298
iter  30 value 94.283380
iter  40 value 94.045753
iter  50 value 88.669353
iter  60 value 88.474824
iter  70 value 88.471892
final  value 88.471871 
converged
Fitting Repeat 1 

# weights:  507
initial  value 140.619371 
iter  10 value 117.701125
iter  20 value 116.586052
iter  30 value 110.063697
iter  40 value 108.921165
iter  50 value 105.348523
iter  60 value 104.444689
iter  70 value 103.560046
iter  80 value 103.179119
iter  90 value 102.176162
iter 100 value 101.854902
final  value 101.854902 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 142.655497 
iter  10 value 117.841962
iter  20 value 114.017814
iter  30 value 108.470939
iter  40 value 107.203959
iter  50 value 105.686007
iter  60 value 105.008427
iter  70 value 104.866667
iter  80 value 103.832572
iter  90 value 103.384045
iter 100 value 103.061223
final  value 103.061223 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 131.584530 
iter  10 value 117.878374
iter  20 value 110.229523
iter  30 value 109.126699
iter  40 value 108.996971
iter  50 value 108.566042
iter  60 value 105.017086
iter  70 value 103.765957
iter  80 value 103.513334
iter  90 value 102.756506
iter 100 value 101.831757
final  value 101.831757 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 159.385835 
iter  10 value 119.034207
iter  20 value 112.328679
iter  30 value 108.941335
iter  40 value 106.761549
iter  50 value 105.740321
iter  60 value 103.972396
iter  70 value 102.158323
iter  80 value 101.655006
iter  90 value 101.556484
iter 100 value 101.438394
final  value 101.438394 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 156.542636 
iter  10 value 118.472386
iter  20 value 111.093382
iter  30 value 107.825056
iter  40 value 107.375419
iter  50 value 106.445229
iter  60 value 105.399406
iter  70 value 103.490297
iter  80 value 103.222694
iter  90 value 103.115086
iter 100 value 103.052791
final  value 103.052791 
stopped after 100 iterations
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Tue Dec 31 02:26:57 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 
  42.18    1.48   54.14