##############################################################################
##############################################################################
###
### 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_1.11.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory 'F:/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck'
* using R version 4.4.0 RC (2024-04-16 r86468 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 '1.11.0'
* 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      32.18   1.82   34.09
var_imp       32.47   1.26   33.75
corr_plot     31.73   1.48   33.22
pred_ensembel 14.33   0.66   10.62
enrichfindP    0.63   0.16   14.23
* 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 4.4.0 RC (2024-04-16 r86468 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 99.510449 
iter  10 value 94.484211
iter  10 value 94.484211
iter  10 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.523070 
iter  10 value 87.038557
final  value 86.955823 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.228938 
final  value 94.428839 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.870900 
final  value 94.428839 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.111713 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.182531 
final  value 93.701657 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.086596 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.816202 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 108.707265 
final  value 94.467391 
converged
Fitting Repeat 5 

# weights:  305
initial  value 111.067035 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 131.737088 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.624173 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.148487 
final  value 94.467392 
converged
Fitting Repeat 4 

# weights:  507
initial  value 138.074961 
final  value 94.467391 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.415498 
final  value 94.484210 
converged
Fitting Repeat 1 

# weights:  103
initial  value 106.081078 
iter  10 value 94.289603
iter  20 value 88.293946
iter  30 value 86.617152
iter  40 value 84.090929
iter  50 value 80.836267
iter  60 value 80.157220
iter  70 value 80.080461
iter  80 value 79.805813
iter  90 value 79.420081
final  value 79.419751 
converged
Fitting Repeat 2 

# weights:  103
initial  value 109.496342 
iter  10 value 93.493954
iter  20 value 84.709596
iter  30 value 83.155603
iter  40 value 83.003426
iter  50 value 82.551319
iter  60 value 82.315382
iter  70 value 82.248494
final  value 82.248478 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.726319 
iter  10 value 94.488630
iter  20 value 93.327594
iter  30 value 91.639473
iter  40 value 91.513466
iter  50 value 91.505308
final  value 91.505283 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.352294 
iter  10 value 94.478792
iter  20 value 84.632992
iter  30 value 83.544197
iter  40 value 82.497258
iter  50 value 81.753841
iter  60 value 81.738065
iter  70 value 81.713194
iter  80 value 81.604719
iter  90 value 81.561537
final  value 81.560308 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.286398 
iter  10 value 94.475334
iter  20 value 92.202248
iter  30 value 87.829328
iter  40 value 82.624595
iter  50 value 81.990405
iter  60 value 81.749044
iter  70 value 81.641957
iter  80 value 81.005340
iter  90 value 79.696583
iter 100 value 79.419853
final  value 79.419853 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 100.129468 
iter  10 value 92.755847
iter  20 value 90.719060
iter  30 value 90.330760
iter  40 value 90.060030
iter  50 value 86.947487
iter  60 value 85.062024
iter  70 value 84.434193
iter  80 value 83.534608
iter  90 value 83.251106
iter 100 value 82.944916
final  value 82.944916 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.097524 
iter  10 value 94.569864
iter  20 value 85.919164
iter  30 value 82.728827
iter  40 value 81.096265
iter  50 value 79.997698
iter  60 value 79.742941
iter  70 value 79.517982
iter  80 value 78.848169
iter  90 value 78.767077
iter 100 value 78.465580
final  value 78.465580 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.680063 
iter  10 value 94.820110
iter  20 value 94.444408
iter  30 value 84.845347
iter  40 value 84.059034
iter  50 value 83.314219
iter  60 value 80.353956
iter  70 value 79.805251
iter  80 value 79.112912
iter  90 value 78.180974
iter 100 value 77.700247
final  value 77.700247 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.882274 
iter  10 value 94.478937
iter  20 value 87.398618
iter  30 value 84.915139
iter  40 value 83.647807
iter  50 value 82.966024
iter  60 value 82.141942
iter  70 value 81.356322
iter  80 value 79.189395
iter  90 value 78.715663
iter 100 value 78.358234
final  value 78.358234 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.361982 
iter  10 value 94.501224
iter  20 value 92.007013
iter  30 value 83.921608
iter  40 value 78.749556
iter  50 value 78.036385
iter  60 value 77.459984
iter  70 value 77.362425
iter  80 value 77.332366
iter  90 value 77.314559
iter 100 value 77.290879
final  value 77.290879 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 142.040497 
iter  10 value 94.274931
iter  20 value 88.147486
iter  30 value 81.494650
iter  40 value 80.933082
iter  50 value 80.223454
iter  60 value 79.535812
iter  70 value 78.461493
iter  80 value 78.368929
iter  90 value 78.262762
iter 100 value 77.818413
final  value 77.818413 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.259715 
iter  10 value 95.942034
iter  20 value 86.900715
iter  30 value 85.053639
iter  40 value 84.695474
iter  50 value 84.554633
iter  60 value 83.346448
iter  70 value 79.556100
iter  80 value 78.024190
iter  90 value 77.704078
iter 100 value 77.626893
final  value 77.626893 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.354515 
iter  10 value 95.023116
iter  20 value 94.276971
iter  30 value 91.927511
iter  40 value 90.323752
iter  50 value 83.645068
iter  60 value 80.823787
iter  70 value 80.178485
iter  80 value 80.060999
iter  90 value 79.493860
iter 100 value 78.555269
final  value 78.555269 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 117.456041 
iter  10 value 95.105932
iter  20 value 94.590904
iter  30 value 94.103738
iter  40 value 89.725219
iter  50 value 88.670842
iter  60 value 86.859541
iter  70 value 85.543787
iter  80 value 84.907204
iter  90 value 83.440124
iter 100 value 82.212089
final  value 82.212089 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 115.464367 
iter  10 value 94.198331
iter  20 value 87.586686
iter  30 value 83.000568
iter  40 value 79.576573
iter  50 value 78.684676
iter  60 value 78.176374
iter  70 value 77.851748
iter  80 value 77.642693
iter  90 value 77.460536
iter 100 value 77.328454
final  value 77.328454 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.169389 
final  value 94.485722 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.698833 
final  value 94.477889 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.390807 
final  value 94.485860 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.314896 
final  value 94.468854 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.198833 
final  value 94.486291 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.688677 
iter  10 value 94.489051
iter  20 value 94.249302
iter  30 value 91.856070
iter  40 value 85.650908
iter  50 value 79.832289
iter  60 value 79.627343
iter  70 value 79.625577
final  value 79.624271 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.487073 
iter  10 value 93.019249
iter  20 value 81.532865
iter  30 value 80.719553
iter  40 value 80.706540
iter  50 value 80.191594
iter  60 value 79.812802
iter  70 value 79.812220
iter  80 value 79.806245
iter  90 value 79.418851
iter 100 value 79.412788
final  value 79.412788 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.049585 
iter  10 value 94.489168
iter  20 value 94.369215
iter  30 value 90.786834
iter  40 value 90.618173
iter  50 value 90.595587
iter  60 value 87.075788
iter  70 value 85.755966
iter  80 value 85.752695
iter  90 value 85.722866
iter 100 value 85.722508
final  value 85.722508 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.943286 
iter  10 value 94.489695
iter  20 value 94.362315
iter  30 value 86.108152
iter  40 value 85.606584
iter  50 value 84.575954
iter  60 value 81.422401
iter  70 value 80.989362
iter  80 value 80.983111
iter  90 value 80.981811
iter 100 value 80.979936
final  value 80.979936 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.852430 
iter  10 value 94.488601
iter  20 value 87.716618
iter  30 value 86.743027
iter  40 value 86.734975
final  value 86.734935 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.250794 
iter  10 value 94.491758
iter  20 value 91.068843
iter  30 value 87.197812
iter  30 value 87.197811
iter  30 value 87.197811
final  value 87.197811 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.758847 
iter  10 value 94.477058
iter  20 value 94.330086
iter  30 value 86.870160
iter  40 value 85.935224
iter  50 value 85.929997
iter  60 value 84.894146
iter  70 value 84.416497
iter  80 value 83.689408
final  value 83.688774 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.479733 
iter  10 value 94.475180
iter  20 value 94.464152
iter  30 value 85.103189
iter  40 value 81.909914
iter  50 value 81.851551
iter  60 value 79.541238
iter  70 value 79.455975
iter  80 value 79.398577
iter  90 value 79.398445
iter 100 value 79.397209
final  value 79.397209 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 125.940171 
iter  10 value 87.124685
iter  20 value 84.868565
iter  30 value 84.867605
iter  40 value 84.344862
iter  50 value 83.931478
iter  60 value 83.930598
iter  70 value 82.418372
iter  80 value 79.795264
iter  90 value 79.749468
iter 100 value 79.142086
final  value 79.142086 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.837132 
iter  10 value 94.475291
iter  20 value 94.468774
final  value 94.468735 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.557028 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.520027 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.311132 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 108.319736 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.205903 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.961571 
iter  10 value 92.936330
final  value 92.936166 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.565379 
iter  10 value 94.373055
final  value 94.373019 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.322771 
final  value 94.455556 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.298266 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.778559 
final  value 94.312038 
converged
Fitting Repeat 1 

# weights:  507
initial  value 121.363266 
iter  10 value 94.312039
iter  10 value 94.312039
iter  10 value 94.312039
final  value 94.312039 
converged
Fitting Repeat 2 

# weights:  507
initial  value 123.687987 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.639034 
iter  10 value 93.176902
iter  20 value 93.129903
final  value 93.129890 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.370649 
final  value 94.467391 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.569035 
final  value 94.467386 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.223555 
iter  10 value 94.456635
iter  20 value 88.648030
iter  30 value 85.039516
iter  40 value 84.804198
iter  50 value 84.501019
iter  60 value 84.114200
iter  70 value 83.926398
iter  80 value 83.717850
iter  90 value 83.640320
iter 100 value 83.593877
final  value 83.593877 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.302540 
iter  10 value 93.810904
iter  20 value 85.131560
iter  30 value 84.705678
iter  40 value 84.354664
iter  50 value 84.255827
iter  60 value 84.179414
iter  70 value 83.808020
iter  80 value 83.595657
final  value 83.593863 
converged
Fitting Repeat 3 

# weights:  103
initial  value 115.516353 
iter  10 value 94.475665
iter  20 value 92.370562
iter  30 value 90.549716
iter  40 value 90.499215
iter  50 value 84.922498
iter  60 value 83.382465
iter  70 value 83.032259
iter  80 value 82.699175
iter  90 value 82.468058
iter 100 value 82.169136
final  value 82.169136 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 98.890517 
iter  10 value 94.508181
iter  20 value 91.000503
iter  30 value 90.267162
iter  40 value 86.713234
iter  50 value 84.293281
iter  60 value 83.508993
iter  70 value 83.306708
iter  80 value 83.198071
iter  90 value 83.169604
iter 100 value 83.147478
final  value 83.147478 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 103.038249 
iter  10 value 94.492218
iter  20 value 94.417971
iter  30 value 87.479204
iter  40 value 86.254933
iter  50 value 85.817332
iter  60 value 85.327132
iter  70 value 85.121718
iter  80 value 85.110193
iter  90 value 85.019857
final  value 84.998279 
converged
Fitting Repeat 1 

# weights:  305
initial  value 120.670006 
iter  10 value 94.489834
iter  20 value 88.364985
iter  30 value 87.594636
iter  40 value 85.191284
iter  50 value 84.490269
iter  60 value 84.024608
iter  70 value 83.722475
iter  80 value 83.578301
iter  90 value 82.970798
iter 100 value 82.615869
final  value 82.615869 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.587231 
iter  10 value 92.729411
iter  20 value 91.836448
iter  30 value 88.532484
iter  40 value 87.063945
iter  50 value 85.214586
iter  60 value 81.958266
iter  70 value 80.784694
iter  80 value 80.451264
iter  90 value 80.364958
iter 100 value 80.169961
final  value 80.169961 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 113.655374 
iter  10 value 94.405799
iter  20 value 93.915997
iter  30 value 90.233459
iter  40 value 86.607111
iter  50 value 85.754357
iter  60 value 83.326480
iter  70 value 82.259057
iter  80 value 81.770822
iter  90 value 81.162393
iter 100 value 80.963493
final  value 80.963493 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.575487 
iter  10 value 94.443131
iter  20 value 92.892096
iter  30 value 87.042540
iter  40 value 84.186855
iter  50 value 83.755047
iter  60 value 82.905937
iter  70 value 82.333461
iter  80 value 81.147860
iter  90 value 80.794623
iter 100 value 80.573282
final  value 80.573282 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.226828 
iter  10 value 94.431512
iter  20 value 91.149571
iter  30 value 83.749585
iter  40 value 82.708535
iter  50 value 81.735645
iter  60 value 81.443093
iter  70 value 81.078106
iter  80 value 80.958318
iter  90 value 80.809820
iter 100 value 80.807617
final  value 80.807617 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 124.269753 
iter  10 value 95.937192
iter  20 value 90.040469
iter  30 value 86.207060
iter  40 value 84.240349
iter  50 value 83.474938
iter  60 value 82.580130
iter  70 value 81.994843
iter  80 value 81.698772
iter  90 value 81.237749
iter 100 value 80.985246
final  value 80.985246 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 127.364411 
iter  10 value 94.710531
iter  20 value 94.469699
iter  30 value 93.940771
iter  40 value 92.223132
iter  50 value 91.935727
iter  60 value 89.912433
iter  70 value 83.739616
iter  80 value 82.875202
iter  90 value 82.176860
iter 100 value 81.070676
final  value 81.070676 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.069913 
iter  10 value 94.284359
iter  20 value 86.852173
iter  30 value 85.735488
iter  40 value 83.070523
iter  50 value 82.800826
iter  60 value 82.360506
iter  70 value 81.763756
iter  80 value 81.143759
iter  90 value 80.671914
iter 100 value 80.386054
final  value 80.386054 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.153195 
iter  10 value 94.882688
iter  20 value 94.250812
iter  30 value 93.518643
iter  40 value 86.524338
iter  50 value 83.269353
iter  60 value 82.122576
iter  70 value 81.804090
iter  80 value 81.363804
iter  90 value 80.978563
iter 100 value 80.857262
final  value 80.857262 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.495949 
iter  10 value 95.102138
iter  20 value 86.293468
iter  30 value 84.272691
iter  40 value 83.060994
iter  50 value 81.861942
iter  60 value 80.827498
iter  70 value 80.455194
iter  80 value 80.325342
iter  90 value 80.175097
iter 100 value 80.020888
final  value 80.020888 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.786419 
final  value 94.489349 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.909217 
final  value 94.486182 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.507980 
final  value 94.485649 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.268998 
iter  10 value 94.486034
iter  20 value 94.483979
iter  30 value 94.142325
final  value 93.783952 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.772779 
final  value 94.485755 
converged
Fitting Repeat 1 

# weights:  305
initial  value 111.527434 
iter  10 value 94.488041
iter  20 value 94.484048
iter  30 value 84.824473
iter  40 value 83.576521
iter  50 value 82.375696
iter  60 value 82.155610
iter  70 value 81.919995
final  value 81.919254 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.878607 
iter  10 value 91.027200
iter  20 value 91.006826
iter  30 value 91.002156
iter  40 value 90.985405
iter  50 value 86.511131
iter  60 value 86.355074
iter  70 value 86.352058
final  value 86.352022 
converged
Fitting Repeat 3 

# weights:  305
initial  value 109.315307 
iter  10 value 92.060988
iter  20 value 91.598626
iter  30 value 91.595289
iter  40 value 91.020827
iter  50 value 85.946178
iter  60 value 85.359184
iter  70 value 84.884511
iter  80 value 84.694973
iter  90 value 83.863147
iter 100 value 83.482357
final  value 83.482357 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 96.536788 
iter  10 value 94.488774
iter  20 value 93.792770
iter  30 value 83.945380
iter  40 value 83.758868
iter  50 value 83.758327
iter  60 value 83.663438
iter  70 value 82.941613
iter  80 value 82.116495
iter  90 value 81.561606
iter 100 value 81.557531
final  value 81.557531 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 110.935014 
iter  10 value 94.488818
iter  20 value 94.322490
final  value 94.312377 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.002484 
iter  10 value 94.475269
iter  20 value 94.473856
iter  30 value 94.473032
iter  40 value 94.467617
iter  50 value 89.662865
iter  60 value 87.592735
final  value 87.592728 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.525593 
iter  10 value 93.791818
iter  20 value 93.784139
iter  30 value 86.567912
iter  40 value 83.978480
iter  50 value 83.706553
iter  60 value 82.872747
iter  70 value 82.853862
iter  80 value 82.661772
iter  90 value 82.651519
iter 100 value 82.645539
final  value 82.645539 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 121.021454 
iter  10 value 94.493381
iter  20 value 94.486034
iter  30 value 90.611779
final  value 87.592613 
converged
Fitting Repeat 4 

# weights:  507
initial  value 158.710774 
iter  10 value 94.491916
iter  20 value 94.250979
iter  30 value 91.694569
iter  40 value 83.700944
iter  50 value 82.762348
iter  60 value 82.574050
iter  70 value 82.473871
iter  80 value 81.705431
iter  90 value 79.977521
iter 100 value 79.344765
final  value 79.344765 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 94.623430 
iter  10 value 91.629277
iter  20 value 83.965788
iter  30 value 83.963350
iter  40 value 83.959688
iter  50 value 83.479602
iter  60 value 82.393764
iter  70 value 82.389473
iter  80 value 82.137260
iter  90 value 81.960264
iter 100 value 81.959456
final  value 81.959456 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.729567 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.241204 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.768306 
iter  10 value 93.670031
iter  20 value 93.632536
iter  30 value 93.590647
iter  40 value 93.535441
final  value 93.535434 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.352191 
final  value 94.484137 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.058584 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.862220 
iter  10 value 93.775010
iter  20 value 93.708902
iter  30 value 93.484141
final  value 93.484125 
converged
Fitting Repeat 2 

# weights:  305
initial  value 106.523490 
iter  10 value 89.480227
iter  20 value 85.890334
iter  30 value 85.601250
iter  40 value 85.507267
final  value 85.507265 
converged
Fitting Repeat 3 

# weights:  305
initial  value 111.165550 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.718899 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.382363 
iter  10 value 93.772998
final  value 93.772973 
converged
Fitting Repeat 1 

# weights:  507
initial  value 113.685797 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 126.021265 
iter  10 value 93.773013
final  value 93.772973 
converged
Fitting Repeat 3 

# weights:  507
initial  value 112.192591 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 127.158733 
iter  10 value 93.540608
final  value 93.540410 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.742188 
iter  10 value 93.773018
final  value 93.772973 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.870242 
iter  10 value 94.527605
iter  20 value 92.159213
iter  30 value 91.549677
iter  40 value 91.438784
iter  50 value 90.122674
iter  60 value 84.506223
iter  70 value 84.062975
iter  80 value 83.620094
iter  90 value 83.500686
final  value 83.499188 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.379549 
iter  10 value 94.494651
iter  20 value 94.485625
iter  30 value 89.553809
iter  40 value 87.117946
iter  50 value 86.931275
iter  60 value 86.906131
final  value 86.904563 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.389640 
iter  10 value 94.497573
iter  20 value 92.735188
iter  30 value 90.660203
iter  40 value 90.217839
iter  50 value 86.089742
iter  60 value 85.664746
iter  70 value 85.270007
iter  80 value 84.122993
iter  90 value 83.619508
final  value 83.601260 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.217496 
iter  10 value 94.453799
iter  20 value 93.622037
iter  30 value 90.632153
iter  40 value 85.093762
iter  50 value 84.933519
iter  60 value 84.784127
iter  70 value 84.074488
iter  80 value 83.689062
iter  90 value 83.601264
final  value 83.601260 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.273084 
iter  10 value 94.636167
iter  20 value 94.484538
iter  30 value 92.506568
iter  40 value 92.477434
iter  50 value 91.136140
iter  60 value 90.098403
iter  70 value 87.017048
iter  80 value 86.806409
iter  90 value 85.263182
iter 100 value 84.513179
final  value 84.513179 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 108.880842 
iter  10 value 94.076501
iter  20 value 89.764031
iter  30 value 87.224527
iter  40 value 86.040027
iter  50 value 83.954901
iter  60 value 83.718372
iter  70 value 83.200248
iter  80 value 82.842386
iter  90 value 82.765613
iter 100 value 82.746951
final  value 82.746951 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.597587 
iter  10 value 94.440961
iter  20 value 88.888632
iter  30 value 86.859516
iter  40 value 86.340998
iter  50 value 85.167093
iter  60 value 84.875603
iter  70 value 84.514540
iter  80 value 84.469663
iter  90 value 84.415494
iter 100 value 84.108097
final  value 84.108097 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.375345 
iter  10 value 94.119980
iter  20 value 89.472918
iter  30 value 88.782163
iter  40 value 87.234601
iter  50 value 85.362294
iter  60 value 84.706712
iter  70 value 84.495636
iter  80 value 83.975963
iter  90 value 83.320249
iter 100 value 82.815546
final  value 82.815546 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.491005 
iter  10 value 94.249431
iter  20 value 92.624964
iter  30 value 86.503359
iter  40 value 86.277481
iter  50 value 85.077272
iter  60 value 83.846970
iter  70 value 83.222465
iter  80 value 83.106147
iter  90 value 82.897346
iter 100 value 82.767072
final  value 82.767072 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.412656 
iter  10 value 94.538353
iter  20 value 92.847279
iter  30 value 91.392688
iter  40 value 88.765255
iter  50 value 85.968724
iter  60 value 84.393261
iter  70 value 83.618483
iter  80 value 82.825413
iter  90 value 82.533805
iter 100 value 82.433140
final  value 82.433140 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 136.165214 
iter  10 value 94.031802
iter  20 value 93.333881
iter  30 value 87.157850
iter  40 value 85.736108
iter  50 value 85.354919
iter  60 value 83.659233
iter  70 value 83.029153
iter  80 value 82.969973
iter  90 value 82.810011
iter 100 value 82.429989
final  value 82.429989 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.423138 
iter  10 value 94.309530
iter  20 value 92.034529
iter  30 value 91.504517
iter  40 value 90.340785
iter  50 value 88.384988
iter  60 value 85.351413
iter  70 value 84.747864
iter  80 value 84.015317
iter  90 value 83.497319
iter 100 value 83.426409
final  value 83.426409 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.862123 
iter  10 value 94.514546
iter  20 value 89.954557
iter  30 value 87.123842
iter  40 value 85.605990
iter  50 value 85.130745
iter  60 value 84.199277
iter  70 value 83.200006
iter  80 value 82.799786
iter  90 value 82.554984
iter 100 value 82.298656
final  value 82.298656 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.038339 
iter  10 value 94.703187
iter  20 value 93.794512
iter  30 value 88.048108
iter  40 value 86.988857
iter  50 value 85.669338
iter  60 value 85.115932
iter  70 value 84.628681
iter  80 value 84.361041
iter  90 value 84.120294
iter 100 value 83.971302
final  value 83.971302 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 126.753953 
iter  10 value 94.993444
iter  20 value 93.840110
iter  30 value 91.331811
iter  40 value 91.087577
iter  50 value 90.483453
iter  60 value 84.548771
iter  70 value 83.378410
iter  80 value 82.877215
iter  90 value 82.732385
iter 100 value 82.508899
final  value 82.508899 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.795598 
final  value 94.486042 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.749294 
iter  10 value 94.485897
final  value 94.484272 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.389034 
final  value 94.485935 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.718790 
final  value 94.486414 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.599952 
final  value 94.485716 
converged
Fitting Repeat 1 

# weights:  305
initial  value 129.694138 
iter  10 value 94.489470
iter  20 value 94.478918
iter  30 value 93.773976
final  value 93.773960 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.715971 
iter  10 value 94.489731
final  value 94.484410 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.820437 
iter  10 value 94.484728
iter  20 value 88.532486
iter  30 value 87.408108
iter  40 value 87.405787
iter  50 value 87.364695
final  value 87.364329 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.826400 
iter  10 value 94.489376
iter  20 value 94.347053
iter  30 value 85.887180
iter  40 value 85.538183
iter  50 value 84.894588
iter  60 value 83.953052
iter  70 value 83.690182
iter  80 value 83.681216
iter  90 value 83.680253
iter 100 value 83.680169
final  value 83.680169 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 95.274118 
iter  10 value 94.488584
iter  20 value 93.774300
iter  30 value 93.684065
iter  40 value 88.736658
iter  50 value 85.991544
iter  60 value 85.963699
iter  70 value 85.693067
iter  80 value 85.691740
final  value 85.691739 
converged
Fitting Repeat 1 

# weights:  507
initial  value 127.759265 
iter  10 value 93.855705
iter  20 value 88.268784
iter  30 value 87.387014
iter  40 value 87.383760
iter  50 value 87.382423
iter  60 value 86.032863
iter  70 value 86.030426
iter  80 value 86.018976
iter  90 value 85.981068
iter 100 value 85.945337
final  value 85.945337 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.973700 
iter  10 value 94.491593
iter  20 value 91.699902
iter  30 value 86.707792
iter  40 value 85.220307
iter  50 value 84.796765
iter  60 value 83.577684
iter  70 value 83.537918
iter  80 value 83.464158
iter  90 value 83.307645
iter 100 value 83.287468
final  value 83.287468 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.736097 
iter  10 value 93.782030
iter  20 value 92.033739
iter  30 value 88.783423
iter  40 value 88.329172
iter  50 value 88.324119
iter  60 value 86.840193
iter  70 value 84.428239
iter  80 value 84.409364
iter  90 value 84.242313
iter 100 value 83.869568
final  value 83.869568 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.416209 
iter  10 value 93.561801
iter  20 value 93.491521
iter  30 value 93.487597
iter  40 value 91.059705
iter  50 value 91.022384
iter  60 value 90.962795
iter  70 value 90.937526
iter  80 value 89.252188
iter  90 value 89.127207
iter 100 value 85.211121
final  value 85.211121 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.786679 
iter  10 value 94.494453
iter  20 value 93.775812
iter  30 value 93.773670
iter  40 value 93.515354
iter  50 value 93.103246
iter  60 value 86.450322
iter  70 value 85.634299
iter  80 value 85.631813
iter  90 value 85.631617
iter 100 value 85.631429
final  value 85.631429 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.039149 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.886921 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.070088 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.991273 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.777687 
final  value 93.915746 
converged
Fitting Repeat 1 

# weights:  305
initial  value 122.945137 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.546189 
iter  10 value 93.631799
iter  20 value 86.821424
iter  30 value 86.649603
final  value 86.649574 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.421329 
iter  10 value 87.419530
iter  20 value 85.963834
iter  30 value 85.959981
final  value 85.959979 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.807848 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.576075 
final  value 93.551913 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.438660 
final  value 93.601516 
converged
Fitting Repeat 2 

# weights:  507
initial  value 114.773483 
final  value 93.915747 
converged
Fitting Repeat 3 

# weights:  507
initial  value 117.799133 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.744765 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.785017 
final  value 93.781016 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.062760 
iter  10 value 94.026082
iter  20 value 90.944646
iter  30 value 90.322424
iter  40 value 84.761106
iter  50 value 84.523594
iter  60 value 82.500286
iter  70 value 81.863632
iter  80 value 81.237007
iter  90 value 80.889398
iter 100 value 80.814083
final  value 80.814083 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.770992 
iter  10 value 93.920694
iter  20 value 85.821448
iter  30 value 84.405166
iter  40 value 84.197140
iter  50 value 83.281773
iter  60 value 82.865301
iter  70 value 82.658352
iter  80 value 82.633937
final  value 82.627761 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.070973 
iter  10 value 87.388505
iter  20 value 85.003866
iter  30 value 84.712967
iter  40 value 84.499306
iter  50 value 82.790270
iter  60 value 82.138011
iter  70 value 82.050684
final  value 82.050682 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.794335 
iter  10 value 94.054689
iter  20 value 93.955865
iter  30 value 93.952182
iter  40 value 92.736142
iter  50 value 87.241865
iter  60 value 86.786895
iter  70 value 86.156844
iter  80 value 83.937809
iter  90 value 83.376719
iter 100 value 82.596238
final  value 82.596238 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 96.547895 
iter  10 value 94.072229
iter  20 value 85.725350
iter  30 value 84.640790
iter  40 value 83.626297
iter  50 value 82.139026
iter  60 value 81.687424
iter  70 value 80.891221
iter  80 value 80.640258
final  value 80.638443 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.060709 
iter  10 value 94.054217
iter  20 value 85.898470
iter  30 value 85.266250
iter  40 value 83.934184
iter  50 value 82.921611
iter  60 value 80.955085
iter  70 value 80.344923
iter  80 value 79.594840
iter  90 value 79.384548
iter 100 value 79.258927
final  value 79.258927 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 118.709930 
iter  10 value 96.641752
iter  20 value 95.735474
iter  30 value 88.311370
iter  40 value 84.887415
iter  50 value 84.623354
iter  60 value 83.938724
iter  70 value 83.092558
iter  80 value 82.183438
iter  90 value 81.266337
iter 100 value 80.359371
final  value 80.359371 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.484962 
iter  10 value 94.308544
iter  20 value 93.870129
iter  30 value 87.086923
iter  40 value 85.114592
iter  50 value 84.888457
iter  60 value 84.552434
iter  70 value 81.968877
iter  80 value 79.808149
iter  90 value 79.562141
iter 100 value 79.475655
final  value 79.475655 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 111.918576 
iter  10 value 94.241025
iter  20 value 86.057195
iter  30 value 85.687869
iter  40 value 83.340315
iter  50 value 82.840389
iter  60 value 82.559860
iter  70 value 82.495205
iter  80 value 82.406281
iter  90 value 81.466518
iter 100 value 81.244018
final  value 81.244018 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.898976 
iter  10 value 94.215525
iter  20 value 92.535292
iter  30 value 91.068276
iter  40 value 90.053153
iter  50 value 84.050399
iter  60 value 81.668572
iter  70 value 80.257144
iter  80 value 79.694846
iter  90 value 79.453943
iter 100 value 79.288877
final  value 79.288877 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.879385 
iter  10 value 94.060196
iter  20 value 93.260312
iter  30 value 88.297089
iter  40 value 86.719091
iter  50 value 85.820675
iter  60 value 83.725451
iter  70 value 82.309304
iter  80 value 80.311186
iter  90 value 79.721598
iter 100 value 79.450367
final  value 79.450367 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.957551 
iter  10 value 93.563412
iter  20 value 83.676442
iter  30 value 80.770761
iter  40 value 80.244461
iter  50 value 79.479538
iter  60 value 79.316812
iter  70 value 79.276080
iter  80 value 79.122716
iter  90 value 79.099987
iter 100 value 79.012453
final  value 79.012453 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 116.224595 
iter  10 value 93.971775
iter  20 value 90.655096
iter  30 value 87.605361
iter  40 value 84.349582
iter  50 value 82.097542
iter  60 value 81.835140
iter  70 value 81.538180
iter  80 value 81.406453
iter  90 value 81.211508
iter 100 value 79.874651
final  value 79.874651 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 119.199090 
iter  10 value 94.330945
iter  20 value 93.136296
iter  30 value 87.062773
iter  40 value 86.727803
iter  50 value 84.491988
iter  60 value 83.501207
iter  70 value 82.684723
iter  80 value 81.946948
iter  90 value 81.244918
iter 100 value 80.216469
final  value 80.216469 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.929739 
iter  10 value 93.788189
iter  20 value 90.486100
iter  30 value 87.372157
iter  40 value 84.349311
iter  50 value 84.057016
iter  60 value 83.513295
iter  70 value 82.305793
iter  80 value 82.049835
iter  90 value 81.880847
iter 100 value 81.414096
final  value 81.414096 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.173862 
final  value 94.054148 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.530163 
final  value 94.054489 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.766774 
final  value 94.054368 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.713474 
final  value 94.054588 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.693905 
final  value 94.054432 
converged
Fitting Repeat 1 

# weights:  305
initial  value 117.301189 
iter  10 value 94.060320
iter  20 value 94.027531
iter  30 value 92.863094
final  value 92.863074 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.916613 
iter  10 value 93.920609
iter  20 value 93.916544
iter  30 value 85.275992
iter  40 value 83.031395
iter  50 value 82.850983
final  value 82.850675 
converged
Fitting Repeat 3 

# weights:  305
initial  value 113.836919 
iter  10 value 94.059739
iter  20 value 94.054522
iter  30 value 89.002346
iter  40 value 84.707389
iter  50 value 83.974807
iter  60 value 83.421614
iter  70 value 83.416952
iter  80 value 82.835430
iter  90 value 82.728027
iter 100 value 82.396623
final  value 82.396623 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 93.698629 
iter  10 value 86.889914
iter  20 value 86.875028
iter  30 value 86.874630
iter  40 value 83.983864
iter  50 value 82.976966
iter  60 value 82.803764
iter  70 value 82.790642
iter  70 value 82.790642
final  value 82.790642 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.799680 
iter  10 value 94.054868
iter  20 value 92.964375
iter  30 value 92.861861
iter  40 value 92.857662
iter  50 value 86.593774
iter  60 value 83.108603
iter  70 value 82.903726
iter  80 value 82.857971
iter  90 value 82.857273
final  value 82.857249 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.278540 
iter  10 value 93.924078
iter  20 value 93.595050
iter  30 value 92.867191
iter  40 value 92.862070
final  value 92.862049 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.427840 
iter  10 value 94.060845
iter  20 value 93.976147
iter  30 value 92.862293
iter  30 value 92.862292
iter  30 value 92.862292
final  value 92.862292 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.050047 
iter  10 value 94.030641
iter  20 value 94.023360
iter  30 value 93.086541
iter  40 value 92.847463
iter  50 value 92.847097
final  value 92.847088 
converged
Fitting Repeat 4 

# weights:  507
initial  value 113.851958 
iter  10 value 93.924416
iter  20 value 93.915950
iter  30 value 93.915730
iter  40 value 83.356576
iter  50 value 82.511411
iter  60 value 81.796426
iter  70 value 78.954305
iter  80 value 78.786306
final  value 78.721140 
converged
Fitting Repeat 5 

# weights:  507
initial  value 109.744476 
iter  10 value 94.061172
iter  20 value 94.016589
iter  30 value 92.881806
iter  40 value 92.865627
iter  50 value 89.150815
iter  60 value 84.386813
iter  70 value 83.564289
iter  80 value 83.562173
iter  90 value 83.489343
iter 100 value 83.475228
final  value 83.475228 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.150028 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.358176 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.269627 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.700747 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.183102 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.789449 
final  value 93.582418 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.898791 
iter  10 value 93.992038
iter  10 value 93.992038
iter  10 value 93.992038
final  value 93.992038 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.400259 
iter  10 value 94.023310
iter  10 value 94.023310
iter  10 value 94.023310
final  value 94.023310 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.359118 
iter  10 value 93.357394
iter  20 value 93.356704
iter  30 value 93.306179
final  value 93.304777 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.853251 
iter  10 value 93.386501
final  value 93.356736 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.837158 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.732972 
final  value 93.582418 
converged
Fitting Repeat 3 

# weights:  507
initial  value 113.446849 
iter  10 value 94.052910
iter  10 value 94.052910
iter  10 value 94.052910
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.544691 
iter  10 value 93.304778
final  value 93.304777 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.346596 
iter  10 value 93.307214
final  value 93.304783 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.278347 
iter  10 value 93.955054
iter  20 value 93.234162
iter  30 value 90.310346
iter  40 value 89.479310
iter  50 value 84.787441
iter  60 value 83.941777
iter  70 value 83.723651
iter  80 value 82.986474
iter  90 value 82.301204
iter 100 value 81.520444
final  value 81.520444 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 98.457822 
iter  10 value 94.055013
iter  20 value 93.987448
iter  30 value 93.552487
iter  40 value 93.400166
iter  50 value 92.266724
iter  60 value 86.921178
iter  70 value 85.409891
iter  80 value 84.363687
iter  90 value 84.018646
iter 100 value 83.038172
final  value 83.038172 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.650022 
iter  10 value 94.026105
iter  20 value 92.832233
iter  30 value 86.261361
iter  40 value 86.063772
iter  50 value 85.833991
iter  60 value 85.374194
iter  70 value 85.167566
iter  80 value 85.165644
iter  80 value 85.165643
iter  80 value 85.165643
final  value 85.165643 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.394965 
iter  10 value 94.055762
iter  20 value 93.500790
iter  30 value 93.431318
iter  40 value 93.413623
iter  50 value 92.687014
iter  60 value 86.553358
iter  70 value 86.454985
iter  80 value 86.361628
iter  90 value 85.418112
iter 100 value 85.266574
final  value 85.266574 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 101.601308 
iter  10 value 93.824463
iter  20 value 89.170850
iter  30 value 86.410822
iter  40 value 86.168164
iter  50 value 85.931033
iter  60 value 85.449616
iter  70 value 85.265185
final  value 85.264994 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.201857 
iter  10 value 94.327041
iter  20 value 94.098581
iter  30 value 93.601015
iter  40 value 93.425937
iter  50 value 93.288079
iter  60 value 86.736345
iter  70 value 83.620402
iter  80 value 82.294711
iter  90 value 81.534222
iter 100 value 80.689661
final  value 80.689661 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.052445 
iter  10 value 94.013001
iter  20 value 91.865742
iter  30 value 86.006287
iter  40 value 84.695280
iter  50 value 83.955542
iter  60 value 82.547988
iter  70 value 82.502407
iter  80 value 82.430972
iter  90 value 82.166914
iter 100 value 81.985962
final  value 81.985962 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.511180 
iter  10 value 94.251394
iter  20 value 90.012627
iter  30 value 84.735121
iter  40 value 84.178993
iter  50 value 83.420929
iter  60 value 82.659138
iter  70 value 82.381485
iter  80 value 81.976722
iter  90 value 81.798006
iter 100 value 81.520536
final  value 81.520536 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.908323 
iter  10 value 94.255525
iter  20 value 93.996439
iter  30 value 89.301856
iter  40 value 88.439007
iter  50 value 86.224118
iter  60 value 85.004884
iter  70 value 84.328121
iter  80 value 83.929690
iter  90 value 83.256246
iter 100 value 81.911982
final  value 81.911982 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 98.663332 
iter  10 value 89.740065
iter  20 value 87.547865
iter  30 value 84.049991
iter  40 value 82.959015
iter  50 value 82.380162
iter  60 value 82.250340
iter  70 value 81.576975
iter  80 value 80.944941
iter  90 value 80.620106
iter 100 value 80.585951
final  value 80.585951 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.052493 
iter  10 value 94.683067
iter  20 value 93.612643
iter  30 value 93.104914
iter  40 value 88.019058
iter  50 value 86.925330
iter  60 value 86.277286
iter  70 value 84.328674
iter  80 value 83.590044
iter  90 value 82.949366
iter 100 value 82.714416
final  value 82.714416 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 114.114914 
iter  10 value 93.847150
iter  20 value 88.943321
iter  30 value 86.095421
iter  40 value 85.149120
iter  50 value 84.290534
iter  60 value 82.456724
iter  70 value 82.007526
iter  80 value 81.772052
iter  90 value 81.518898
iter 100 value 80.906751
final  value 80.906751 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.471716 
iter  10 value 94.098493
iter  20 value 89.704589
iter  30 value 86.912212
iter  40 value 86.659914
iter  50 value 86.402870
iter  60 value 83.555145
iter  70 value 83.215346
iter  80 value 82.848209
iter  90 value 82.171205
iter 100 value 81.128749
final  value 81.128749 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.085393 
iter  10 value 94.375501
iter  20 value 87.362000
iter  30 value 85.913843
iter  40 value 85.045198
iter  50 value 84.808257
iter  60 value 84.372028
iter  70 value 82.948861
iter  80 value 81.876785
iter  90 value 81.667102
iter 100 value 81.549631
final  value 81.549631 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.990929 
iter  10 value 93.837337
iter  20 value 88.642138
iter  30 value 86.150844
iter  40 value 84.207285
iter  50 value 83.238889
iter  60 value 82.714764
iter  70 value 82.568904
iter  80 value 82.429139
iter  90 value 81.825466
iter 100 value 81.378633
final  value 81.378633 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.642019 
final  value 94.054836 
converged
Fitting Repeat 2 

# weights:  103
initial  value 112.471984 
final  value 94.054397 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.773865 
iter  10 value 92.691389
iter  20 value 90.160063
iter  30 value 90.152709
final  value 90.151181 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.608533 
iter  10 value 94.054405
iter  20 value 93.472052
iter  30 value 93.356949
final  value 93.356852 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.319157 
final  value 94.054738 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.093775 
iter  10 value 94.057791
iter  20 value 94.052766
final  value 93.356824 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.604749 
iter  10 value 94.057592
iter  20 value 94.053203
iter  20 value 94.053203
iter  20 value 94.053203
final  value 94.053203 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.790943 
iter  10 value 93.314100
iter  20 value 93.244245
iter  30 value 93.126384
iter  40 value 92.999242
iter  50 value 92.998537
iter  60 value 92.996829
final  value 92.996805 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.863569 
iter  10 value 94.058496
iter  20 value 94.053335
iter  30 value 93.316176
iter  40 value 93.305308
final  value 93.305263 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.471677 
iter  10 value 93.789048
iter  20 value 93.586781
iter  30 value 92.963797
iter  40 value 86.389403
iter  50 value 86.140443
iter  60 value 86.081289
final  value 86.080519 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.299808 
iter  10 value 94.053770
iter  20 value 93.955251
iter  30 value 86.314940
iter  40 value 85.311979
iter  50 value 84.724281
iter  60 value 83.773726
iter  70 value 81.258083
iter  80 value 79.439760
iter  90 value 78.603894
iter 100 value 78.564178
final  value 78.564178 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.707892 
iter  10 value 93.591336
iter  20 value 93.583096
iter  30 value 92.462260
iter  40 value 90.507784
iter  50 value 90.501068
iter  60 value 90.462555
iter  70 value 90.460197
iter  80 value 90.460130
iter  90 value 90.459642
final  value 90.459473 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.188266 
iter  10 value 94.061129
iter  20 value 93.916171
iter  30 value 93.197168
iter  40 value 91.727362
iter  50 value 81.659932
iter  60 value 81.496316
iter  70 value 81.487748
iter  80 value 81.469353
iter  90 value 81.409507
iter 100 value 81.407657
final  value 81.407657 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 100.628373 
iter  10 value 94.061144
iter  20 value 94.048613
iter  30 value 86.876821
iter  40 value 86.230099
iter  50 value 86.229001
final  value 86.227955 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.146497 
iter  10 value 93.591082
iter  20 value 93.583303
final  value 93.582752 
converged
Fitting Repeat 1 

# weights:  507
initial  value 130.260805 
iter  10 value 116.541869
iter  20 value 108.973323
iter  30 value 108.437638
iter  40 value 107.068675
iter  50 value 103.450388
iter  60 value 100.971624
iter  70 value 100.533392
iter  80 value 100.339866
iter  90 value 100.254960
iter 100 value 100.195183
final  value 100.195183 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 159.624648 
iter  10 value 117.358151
iter  20 value 110.129964
iter  30 value 107.617373
iter  40 value 104.777728
iter  50 value 103.296134
iter  60 value 102.035571
iter  70 value 101.808451
iter  80 value 101.569359
iter  90 value 101.384830
iter 100 value 101.353397
final  value 101.353397 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 162.351896 
iter  10 value 118.105144
iter  20 value 112.094742
iter  30 value 107.778385
iter  40 value 105.788927
iter  50 value 104.532429
iter  60 value 103.775150
iter  70 value 102.941117
iter  80 value 102.457272
iter  90 value 102.116235
iter 100 value 101.746267
final  value 101.746267 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 143.266798 
iter  10 value 117.964338
iter  20 value 114.833642
iter  30 value 106.645522
iter  40 value 105.403721
iter  50 value 103.642649
iter  60 value 101.723253
iter  70 value 101.497573
iter  80 value 101.300430
iter  90 value 101.015211
iter 100 value 100.603576
final  value 100.603576 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 147.341608 
iter  10 value 118.003686
iter  20 value 116.283654
iter  30 value 114.652356
iter  40 value 106.356985
iter  50 value 104.794698
iter  60 value 104.289753
iter  70 value 103.373371
iter  80 value 102.414082
iter  90 value 102.128104
iter 100 value 102.033966
final  value 102.033966 
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 May 16 01:53:37 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 
  46.29    2.00   49.57