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


* using log directory 'F:/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck'
* using R version 4.4.0 (2024-04-24 ucrt)
* using platform: x86_64-w64-mingw32
* R was compiled by
    gcc.exe (GCC) 13.2.0
    GNU Fortran (GCC) 13.2.0
* running under: Windows Server 2022 x64 (build 20348)
* using session charset: UTF-8
* using option '--no-vignettes'
* checking for file 'HPiP/DESCRIPTION' ... OK
* checking extension type ... Package
* this is package 'HPiP' version '1.10.0'
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking whether package 'HPiP' can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking 'build' directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
Package unavailable to check Rd xrefs: 'ftrCOOL'
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of 'data' directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in 'vignettes' ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
               user system elapsed
FSmethod      31.82   2.27   34.20
var_imp       32.08   1.18   33.27
corr_plot     30.98   2.05   33.04
pred_ensembel 13.74   0.50   10.33
enrichfindP    0.55   0.16   13.72
* checking for unstated dependencies in 'tests' ... OK
* checking tests ...
  Running 'runTests.R'
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

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

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


* installing to library 'F:/biocbuild/bbs-3.19-bioc/R/library'
* installing *source* package 'HPiP' ...
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R version 4.4.0 (2024-04-24 ucrt) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64

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

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

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

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

# weights:  103
initial  value 95.688798 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.360170 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.135167 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.507399 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.987676 
iter  10 value 91.494794
iter  20 value 86.471631
iter  20 value 86.471631
iter  20 value 86.471631
final  value 86.471631 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.762304 
iter  10 value 94.047425
final  value 94.043243 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.796684 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.853766 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.947335 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.225169 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.625532 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.255039 
iter  10 value 91.901272
iter  20 value 88.399081
iter  30 value 86.850589
iter  40 value 86.469265
iter  50 value 86.186804
iter  60 value 86.185196
final  value 86.183675 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.612094 
final  value 94.043243 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.663947 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.474885 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 116.738948 
iter  10 value 93.683733
iter  20 value 92.985552
iter  30 value 91.944474
iter  40 value 91.889017
iter  50 value 90.512752
iter  60 value 89.589565
iter  70 value 89.561562
iter  80 value 89.555442
final  value 89.554045 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.127748 
iter  10 value 93.985356
iter  20 value 90.800578
iter  30 value 89.337475
iter  40 value 88.944742
iter  50 value 82.892965
iter  60 value 81.705106
iter  70 value 81.336098
iter  80 value 81.108742
iter  90 value 81.029923
iter 100 value 80.250124
final  value 80.250124 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 99.634688 
iter  10 value 94.030269
iter  20 value 90.479648
iter  30 value 88.798715
iter  40 value 88.493145
iter  50 value 88.487676
final  value 88.487671 
converged
Fitting Repeat 4 

# weights:  103
initial  value 109.764931 
iter  10 value 94.079564
iter  20 value 94.016164
iter  30 value 89.971997
iter  40 value 87.262304
iter  50 value 86.144382
iter  60 value 85.137405
iter  70 value 84.796382
iter  80 value 84.782330
iter  90 value 84.776353
final  value 84.776283 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.235911 
iter  10 value 94.027136
iter  20 value 93.712076
iter  30 value 93.640206
iter  40 value 93.559661
iter  50 value 93.461580
iter  60 value 89.493560
iter  70 value 86.642173
iter  80 value 85.426482
iter  90 value 84.889043
iter 100 value 84.008397
final  value 84.008397 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 108.595129 
iter  10 value 94.044268
iter  20 value 91.139372
iter  30 value 88.607341
iter  40 value 87.112248
iter  50 value 86.649377
iter  60 value 85.124144
iter  70 value 84.701765
iter  80 value 82.731072
iter  90 value 81.103682
iter 100 value 80.632753
final  value 80.632753 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.761727 
iter  10 value 94.051672
iter  20 value 93.487331
iter  30 value 90.452317
iter  40 value 85.876314
iter  50 value 83.460036
iter  60 value 83.078324
iter  70 value 82.444061
iter  80 value 82.011762
iter  90 value 81.653361
iter 100 value 81.267625
final  value 81.267625 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 110.605593 
iter  10 value 93.735616
iter  20 value 93.320367
iter  30 value 87.493096
iter  40 value 86.334451
iter  50 value 81.818998
iter  60 value 80.973676
iter  70 value 80.158159
iter  80 value 79.884839
iter  90 value 79.715567
iter 100 value 79.621076
final  value 79.621076 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.366381 
iter  10 value 93.471856
iter  20 value 87.681601
iter  30 value 84.929847
iter  40 value 84.385569
iter  50 value 83.780124
iter  60 value 81.523247
iter  70 value 81.033869
iter  80 value 80.662225
iter  90 value 79.999135
iter 100 value 79.446018
final  value 79.446018 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.194306 
iter  10 value 93.910954
iter  20 value 90.496717
iter  30 value 86.576608
iter  40 value 86.191662
iter  50 value 86.009108
iter  60 value 85.614619
iter  70 value 85.265079
iter  80 value 84.082627
iter  90 value 81.846261
iter 100 value 81.566548
final  value 81.566548 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 114.267497 
iter  10 value 96.832994
iter  20 value 87.397720
iter  30 value 84.820559
iter  40 value 84.287091
iter  50 value 83.005228
iter  60 value 82.261243
iter  70 value 81.591333
iter  80 value 81.529977
iter  90 value 81.379855
iter 100 value 81.061233
final  value 81.061233 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.372072 
iter  10 value 96.557468
iter  20 value 84.660982
iter  30 value 81.809796
iter  40 value 81.085447
iter  50 value 80.637482
iter  60 value 80.311640
iter  70 value 80.174197
iter  80 value 79.999025
iter  90 value 79.392146
iter 100 value 78.799662
final  value 78.799662 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.320814 
iter  10 value 93.931558
iter  20 value 89.638757
iter  30 value 89.326951
iter  40 value 87.303628
iter  50 value 84.991390
iter  60 value 84.313464
iter  70 value 81.698859
iter  80 value 80.931342
iter  90 value 80.334653
iter 100 value 80.069479
final  value 80.069479 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 130.159021 
iter  10 value 94.221505
iter  20 value 91.960483
iter  30 value 89.640759
iter  40 value 89.508807
iter  50 value 89.104516
iter  60 value 88.695800
iter  70 value 88.329208
iter  80 value 88.237270
iter  90 value 88.129883
iter 100 value 87.282594
final  value 87.282594 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.033733 
iter  10 value 93.622820
iter  20 value 88.800278
iter  30 value 86.209717
iter  40 value 85.684411
iter  50 value 85.154118
iter  60 value 84.953251
iter  70 value 83.247847
iter  80 value 80.307302
iter  90 value 79.324355
iter 100 value 79.139769
final  value 79.139769 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.406661 
iter  10 value 94.054514
iter  20 value 94.051793
iter  30 value 93.125418
iter  40 value 93.069177
final  value 93.069157 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.621133 
final  value 94.054634 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.614611 
iter  10 value 93.986796
iter  20 value 93.184538
iter  30 value 93.095289
iter  40 value 92.830985
iter  50 value 90.888361
iter  60 value 86.467782
final  value 86.463414 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.409592 
iter  10 value 93.466291
iter  20 value 93.441519
iter  30 value 90.108206
iter  40 value 89.611457
iter  50 value 89.567921
iter  60 value 89.561539
iter  70 value 89.560854
iter  80 value 89.560554
iter  90 value 89.560019
iter 100 value 89.536664
final  value 89.536664 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 98.307456 
iter  10 value 91.837673
iter  20 value 91.754429
final  value 91.753902 
converged
Fitting Repeat 1 

# weights:  305
initial  value 116.206447 
iter  10 value 94.057913
iter  20 value 93.989473
iter  30 value 93.601592
iter  30 value 93.601592
iter  30 value 93.601592
final  value 93.601592 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.978078 
iter  10 value 94.057509
iter  20 value 93.937791
final  value 93.465526 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.962218 
iter  10 value 94.057885
iter  20 value 91.012769
iter  30 value 85.878533
iter  40 value 81.548006
iter  50 value 80.887510
iter  60 value 80.884942
iter  70 value 80.884611
iter  80 value 80.076699
iter  90 value 79.845462
iter 100 value 79.844685
final  value 79.844685 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.814360 
iter  10 value 94.064391
iter  20 value 93.561969
iter  30 value 90.399113
iter  40 value 87.528659
iter  50 value 86.648271
iter  60 value 86.646744
iter  70 value 84.790547
iter  80 value 84.788881
iter  90 value 84.783383
iter 100 value 84.763954
final  value 84.763954 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.964674 
iter  10 value 94.058145
iter  20 value 93.537568
iter  30 value 86.424062
iter  40 value 86.155768
iter  50 value 86.151991
iter  60 value 86.150917
iter  70 value 85.945982
iter  80 value 85.889332
iter  90 value 85.878715
final  value 85.878591 
converged
Fitting Repeat 1 

# weights:  507
initial  value 121.488692 
iter  10 value 89.631447
iter  20 value 87.847367
iter  30 value 87.838721
iter  40 value 87.835977
iter  50 value 84.215733
iter  60 value 83.981868
iter  70 value 83.865278
iter  80 value 82.525120
iter  90 value 81.820698
iter 100 value 81.816811
final  value 81.816811 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 98.552642 
iter  10 value 93.667142
iter  20 value 90.561367
iter  30 value 90.253975
iter  40 value 88.517054
iter  50 value 87.875938
iter  60 value 87.872411
iter  70 value 87.853651
iter  70 value 87.853651
iter  80 value 87.851383
iter  90 value 87.848820
final  value 87.847692 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.909016 
iter  10 value 94.055164
iter  20 value 94.049711
final  value 93.602057 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.934241 
iter  10 value 94.054528
iter  20 value 91.088946
iter  30 value 90.621303
iter  40 value 90.619306
iter  50 value 89.435530
iter  60 value 88.621424
iter  70 value 81.407155
iter  80 value 81.165064
iter  90 value 80.908682
iter 100 value 80.681365
final  value 80.681365 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 96.946307 
iter  10 value 85.371169
iter  20 value 84.983801
iter  30 value 84.918258
iter  40 value 84.916326
iter  50 value 84.467863
iter  60 value 84.466131
iter  70 value 83.914016
iter  80 value 83.686185
iter  90 value 83.684210
iter 100 value 83.681729
final  value 83.681729 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.767713 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.130347 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.865312 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 113.904288 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.913782 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.475076 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.644199 
final  value 94.105263 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.504508 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 125.258140 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 113.495768 
iter  10 value 94.216962
iter  20 value 87.031775
iter  30 value 86.580427
final  value 86.580087 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.342511 
final  value 94.142589 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.005272 
iter  10 value 93.724465
final  value 93.708658 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.703134 
iter  10 value 94.026566
final  value 94.026542 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.281772 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 123.115694 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 116.210609 
iter  10 value 94.417323
iter  20 value 93.443496
iter  30 value 86.477587
iter  40 value 85.924213
iter  50 value 84.011647
iter  60 value 81.170495
iter  70 value 80.532356
iter  80 value 80.272028
iter  90 value 80.084306
final  value 80.081497 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.798790 
iter  10 value 94.595467
iter  20 value 94.483707
iter  30 value 94.156680
iter  40 value 94.125959
iter  50 value 93.889635
iter  60 value 89.619952
iter  70 value 85.472774
iter  80 value 83.647658
iter  90 value 83.504315
iter 100 value 82.631473
final  value 82.631473 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 106.152364 
iter  10 value 94.373886
iter  20 value 93.890146
iter  30 value 92.530136
iter  40 value 85.728049
iter  50 value 85.431770
iter  60 value 85.063120
iter  70 value 84.108870
iter  80 value 83.125965
iter  90 value 82.907338
iter 100 value 82.883306
final  value 82.883306 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 104.834827 
iter  10 value 94.384970
iter  20 value 92.827622
iter  30 value 92.544945
iter  40 value 92.440677
iter  50 value 86.961075
iter  60 value 81.158505
iter  70 value 80.909393
iter  80 value 80.218127
iter  90 value 80.204381
iter 100 value 80.190351
final  value 80.190351 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.896606 
iter  10 value 93.895824
iter  20 value 93.817273
iter  30 value 92.208414
iter  40 value 89.011473
iter  50 value 87.030774
iter  60 value 84.698032
iter  70 value 84.609511
iter  80 value 84.476690
iter  90 value 82.985220
iter 100 value 82.883287
final  value 82.883287 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 122.490809 
iter  10 value 93.064906
iter  20 value 85.905438
iter  30 value 85.309073
iter  40 value 81.800571
iter  50 value 80.733171
iter  60 value 80.564448
iter  70 value 80.540753
iter  80 value 80.499681
iter  90 value 80.436713
iter 100 value 80.080428
final  value 80.080428 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 120.886107 
iter  10 value 93.564426
iter  20 value 86.069776
iter  30 value 84.992288
iter  40 value 83.330815
iter  50 value 82.611300
iter  60 value 82.431436
iter  70 value 82.291220
iter  80 value 82.155389
iter  90 value 81.104179
iter 100 value 80.124016
final  value 80.124016 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 112.005903 
iter  10 value 94.457651
iter  20 value 91.750213
iter  30 value 91.251740
iter  40 value 91.226262
iter  50 value 88.593763
iter  60 value 83.185081
iter  70 value 82.209826
iter  80 value 81.733532
iter  90 value 80.573338
iter 100 value 80.188791
final  value 80.188791 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.006763 
iter  10 value 94.620061
iter  20 value 94.138164
iter  30 value 93.952087
iter  40 value 86.083281
iter  50 value 83.357222
iter  60 value 81.347261
iter  70 value 80.145481
iter  80 value 79.811267
iter  90 value 79.647883
iter 100 value 79.534195
final  value 79.534195 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.212659 
iter  10 value 94.721552
iter  20 value 93.818499
iter  30 value 93.801922
iter  40 value 87.233736
iter  50 value 84.408839
iter  60 value 81.548107
iter  70 value 80.872475
iter  80 value 79.879378
iter  90 value 79.590918
iter 100 value 79.508483
final  value 79.508483 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 131.443423 
iter  10 value 94.482311
iter  20 value 92.724287
iter  30 value 92.554361
iter  40 value 90.026930
iter  50 value 82.610168
iter  60 value 81.978772
iter  70 value 80.042762
iter  80 value 79.462631
iter  90 value 78.787913
iter 100 value 78.701321
final  value 78.701321 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.019542 
iter  10 value 93.861590
iter  20 value 89.326060
iter  30 value 86.537000
iter  40 value 84.698915
iter  50 value 83.945966
iter  60 value 82.419367
iter  70 value 82.007939
iter  80 value 80.922568
iter  90 value 80.462535
iter 100 value 80.062466
final  value 80.062466 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.636132 
iter  10 value 95.017065
iter  20 value 87.040423
iter  30 value 84.360745
iter  40 value 81.851870
iter  50 value 80.023503
iter  60 value 78.938199
iter  70 value 78.561548
iter  80 value 78.377841
iter  90 value 78.235088
iter 100 value 78.179704
final  value 78.179704 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.664431 
iter  10 value 93.994424
iter  20 value 88.448920
iter  30 value 83.997713
iter  40 value 83.477078
iter  50 value 82.282280
iter  60 value 81.319174
iter  70 value 80.143730
iter  80 value 78.980302
iter  90 value 78.836089
iter 100 value 78.752401
final  value 78.752401 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.322867 
iter  10 value 94.808781
iter  20 value 83.844817
iter  30 value 82.700166
iter  40 value 82.025977
iter  50 value 80.314937
iter  60 value 79.725990
iter  70 value 79.414935
iter  80 value 79.133098
iter  90 value 79.002995
iter 100 value 78.917674
final  value 78.917674 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 108.220092 
iter  10 value 94.028254
iter  20 value 94.027203
iter  30 value 92.807982
iter  40 value 81.736385
iter  50 value 81.024046
iter  60 value 81.013874
iter  70 value 80.798920
iter  80 value 80.639755
final  value 80.631283 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.905005 
final  value 94.485895 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.058226 
final  value 94.485945 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.152602 
final  value 94.485624 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.951532 
final  value 94.485903 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.779411 
iter  10 value 94.489002
iter  20 value 94.435740
iter  30 value 94.301295
iter  40 value 94.292995
iter  50 value 94.279911
iter  60 value 94.279324
iter  70 value 94.278935
iter  80 value 94.240182
iter  90 value 93.803582
final  value 93.796794 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.449937 
iter  10 value 94.488960
iter  20 value 94.484261
iter  30 value 94.026633
iter  40 value 92.718425
final  value 92.715225 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.449725 
iter  10 value 94.488838
iter  20 value 94.253900
iter  30 value 93.852638
iter  40 value 93.849513
final  value 93.849502 
converged
Fitting Repeat 4 

# weights:  305
initial  value 114.960100 
iter  10 value 94.036275
iter  20 value 94.025391
iter  30 value 93.736134
iter  40 value 93.713255
iter  50 value 93.709308
iter  60 value 93.266427
iter  70 value 91.469559
iter  80 value 89.151293
iter  90 value 81.053040
iter 100 value 80.393454
final  value 80.393454 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 115.316581 
iter  10 value 94.031948
iter  20 value 93.976650
iter  30 value 93.953977
iter  40 value 93.910122
iter  50 value 93.713564
final  value 93.708955 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.219724 
iter  10 value 85.607580
iter  20 value 81.971856
iter  30 value 81.712106
iter  40 value 81.710116
iter  50 value 81.499338
iter  60 value 79.358947
iter  70 value 79.332770
iter  80 value 79.331077
iter  80 value 79.331077
final  value 79.331077 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.177044 
iter  10 value 94.495529
iter  20 value 94.443910
iter  30 value 91.658825
iter  40 value 88.925947
iter  50 value 88.906039
iter  60 value 88.900570
iter  70 value 87.587005
iter  80 value 85.743492
iter  90 value 84.450460
iter 100 value 84.380071
final  value 84.380071 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 98.367518 
iter  10 value 93.751955
iter  20 value 93.730295
iter  30 value 93.713256
iter  40 value 93.694344
iter  50 value 93.093038
iter  60 value 84.098126
iter  70 value 79.647351
iter  80 value 78.631000
iter  90 value 77.955887
iter 100 value 77.700763
final  value 77.700763 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 117.555151 
iter  10 value 94.007994
iter  20 value 93.962168
iter  30 value 93.954373
iter  40 value 90.127110
iter  50 value 87.673350
iter  60 value 83.674955
iter  70 value 83.256734
iter  80 value 83.009082
iter  90 value 79.485666
iter 100 value 79.071518
final  value 79.071518 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 97.762805 
iter  10 value 94.492283
iter  20 value 94.193781
iter  30 value 93.711919
final  value 93.709490 
converged
Fitting Repeat 1 

# weights:  103
initial  value 94.542048 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.355485 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.863167 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.204398 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.834858 
final  value 94.449438 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.682023 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.693505 
final  value 94.312038 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.281897 
iter  10 value 94.357495
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  305
initial  value 108.370219 
final  value 94.354396 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.293018 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 112.466243 
iter  10 value 87.590374
iter  20 value 86.630465
iter  30 value 84.914851
final  value 84.914835 
converged
Fitting Repeat 2 

# weights:  507
initial  value 117.652013 
iter  10 value 94.356193
final  value 94.354396 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.846604 
iter  10 value 91.465516
iter  20 value 83.552092
iter  30 value 83.310570
iter  40 value 82.908375
final  value 82.814574 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.998846 
iter  10 value 86.698071
iter  20 value 86.622127
iter  20 value 86.622126
iter  20 value 86.622126
final  value 86.622126 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.603392 
iter  10 value 94.487801
final  value 94.476471 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.411280 
iter  10 value 94.488645
iter  20 value 88.471871
iter  30 value 86.560577
iter  40 value 86.143242
iter  50 value 85.614339
iter  60 value 80.877798
iter  70 value 80.427177
iter  80 value 80.314806
iter  90 value 80.174671
iter 100 value 80.154339
final  value 80.154339 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.952471 
iter  10 value 93.235219
iter  20 value 83.460800
iter  30 value 82.601832
iter  40 value 82.351230
iter  50 value 82.271635
iter  60 value 81.750790
iter  70 value 81.531617
iter  80 value 81.428714
final  value 81.428535 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.883684 
iter  10 value 94.490660
iter  20 value 94.439999
iter  30 value 91.292026
iter  40 value 90.349899
iter  50 value 90.056552
iter  60 value 88.563915
iter  70 value 85.598628
iter  80 value 84.917675
iter  90 value 82.743238
iter 100 value 82.228711
final  value 82.228711 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 105.760694 
iter  10 value 94.486445
iter  20 value 90.656374
iter  30 value 88.509164
iter  40 value 85.351046
iter  50 value 84.964016
iter  60 value 84.452314
iter  70 value 81.742568
iter  80 value 80.772283
iter  90 value 80.404752
iter 100 value 80.179262
final  value 80.179262 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 98.966176 
iter  10 value 94.380660
iter  20 value 94.349069
iter  30 value 85.203493
iter  40 value 84.597057
iter  50 value 84.401558
iter  60 value 83.836037
iter  70 value 83.393524
iter  80 value 83.299828
iter  90 value 83.293062
final  value 83.291947 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.271565 
iter  10 value 93.831532
iter  20 value 90.326058
iter  30 value 89.955407
iter  40 value 85.223527
iter  50 value 80.733977
iter  60 value 79.152525
iter  70 value 78.964410
iter  80 value 78.737898
iter  90 value 78.652116
iter 100 value 78.643917
final  value 78.643917 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.751746 
iter  10 value 94.593654
iter  20 value 93.631729
iter  30 value 86.557093
iter  40 value 84.619408
iter  50 value 81.994402
iter  60 value 81.259129
iter  70 value 80.728654
iter  80 value 79.272071
iter  90 value 79.041811
iter 100 value 78.914316
final  value 78.914316 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 121.943671 
iter  10 value 94.347143
iter  20 value 87.512254
iter  30 value 86.137061
iter  40 value 84.736247
iter  50 value 84.146633
iter  60 value 83.513981
iter  70 value 81.781582
iter  80 value 80.215233
iter  90 value 79.531071
iter 100 value 79.230336
final  value 79.230336 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.833933 
iter  10 value 94.362494
iter  20 value 90.415978
iter  30 value 86.248519
iter  40 value 84.055708
iter  50 value 83.699982
iter  60 value 83.419751
iter  70 value 83.309296
iter  80 value 83.133065
iter  90 value 82.139859
iter 100 value 81.469996
final  value 81.469996 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.669904 
iter  10 value 93.145371
iter  20 value 87.752707
iter  30 value 85.851192
iter  40 value 82.171828
iter  50 value 81.088329
iter  60 value 80.316444
iter  70 value 79.282787
iter  80 value 78.390114
iter  90 value 78.097636
iter 100 value 78.055197
final  value 78.055197 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 116.704256 
iter  10 value 93.423275
iter  20 value 87.621173
iter  30 value 85.234505
iter  40 value 83.502155
iter  50 value 80.690649
iter  60 value 80.127953
iter  70 value 78.950387
iter  80 value 78.580048
iter  90 value 78.502152
iter 100 value 78.322016
final  value 78.322016 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.654310 
iter  10 value 93.425213
iter  20 value 83.580006
iter  30 value 81.768400
iter  40 value 80.745865
iter  50 value 80.436958
iter  60 value 80.189139
iter  70 value 80.040448
iter  80 value 79.720820
iter  90 value 79.216099
iter 100 value 78.964297
final  value 78.964297 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 124.861450 
iter  10 value 93.952838
iter  20 value 89.455639
iter  30 value 87.880243
iter  40 value 87.591123
iter  50 value 87.008559
iter  60 value 84.431599
iter  70 value 83.931916
iter  80 value 80.000778
iter  90 value 79.116175
iter 100 value 78.777393
final  value 78.777393 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.090597 
iter  10 value 94.603055
iter  20 value 85.881284
iter  30 value 84.301649
iter  40 value 81.987407
iter  50 value 80.015361
iter  60 value 79.438945
iter  70 value 79.352612
iter  80 value 79.036989
iter  90 value 78.531402
iter 100 value 78.449464
final  value 78.449464 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.264386 
iter  10 value 95.719539
iter  20 value 93.613008
iter  30 value 93.039817
iter  40 value 85.638336
iter  50 value 84.626149
iter  60 value 84.279488
iter  70 value 83.744720
iter  80 value 83.400085
iter  90 value 83.371747
iter 100 value 83.344689
final  value 83.344689 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.441722 
final  value 94.485771 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.336451 
final  value 94.486141 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.700644 
final  value 94.485687 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.714005 
final  value 94.485823 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.882072 
iter  10 value 88.352831
iter  20 value 88.350854
iter  30 value 85.348867
final  value 85.231398 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.105876 
iter  10 value 94.488486
iter  20 value 94.484325
iter  30 value 91.764764
iter  40 value 87.987355
iter  50 value 87.980091
iter  60 value 87.826767
iter  70 value 84.883412
iter  80 value 84.420327
iter  90 value 84.309065
iter 100 value 84.045012
final  value 84.045012 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.159753 
iter  10 value 94.359162
iter  20 value 94.355128
iter  30 value 94.354463
iter  40 value 93.793690
iter  50 value 82.114484
iter  60 value 81.854875
iter  70 value 81.831672
iter  80 value 81.800600
final  value 81.800352 
converged
Fitting Repeat 3 

# weights:  305
initial  value 109.951736 
iter  10 value 94.496109
iter  20 value 94.380885
iter  30 value 91.869207
iter  40 value 91.868085
iter  50 value 91.867430
iter  60 value 91.867107
iter  70 value 91.847356
iter  80 value 91.827465
iter  90 value 91.826918
iter 100 value 91.826729
final  value 91.826729 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 94.503577 
iter  10 value 94.248347
iter  20 value 94.238521
iter  30 value 94.238047
iter  40 value 94.237484
iter  50 value 94.236704
iter  60 value 92.925298
iter  70 value 83.569737
iter  80 value 83.208333
iter  90 value 83.195902
iter 100 value 83.193439
final  value 83.193439 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 94.085237 
iter  10 value 93.210756
iter  20 value 93.207279
iter  30 value 93.027606
iter  40 value 90.159166
iter  50 value 84.143270
iter  60 value 84.023675
iter  70 value 84.023113
iter  80 value 82.692220
iter  90 value 82.611437
iter 100 value 82.501914
final  value 82.501914 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 115.895060 
iter  10 value 94.362927
iter  20 value 94.355161
final  value 94.355137 
converged
Fitting Repeat 2 

# weights:  507
initial  value 110.383624 
iter  10 value 94.492626
iter  20 value 94.443880
iter  30 value 91.873321
iter  40 value 91.819705
iter  50 value 91.796660
iter  60 value 91.794993
iter  70 value 91.586403
iter  80 value 83.969748
iter  90 value 83.460603
iter 100 value 83.441196
final  value 83.441196 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.771832 
iter  10 value 94.320702
iter  20 value 94.315514
iter  30 value 94.311245
iter  40 value 87.938056
iter  50 value 84.983445
iter  60 value 84.939855
final  value 84.939567 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.272796 
iter  10 value 94.490320
iter  20 value 90.177029
iter  30 value 84.631514
iter  40 value 84.546295
iter  50 value 84.545477
iter  60 value 84.544185
final  value 84.543657 
converged
Fitting Repeat 5 

# weights:  507
initial  value 109.180290 
iter  10 value 94.492683
iter  20 value 94.484618
iter  30 value 94.359857
iter  40 value 94.008489
iter  50 value 92.103256
iter  60 value 87.345941
iter  70 value 87.168980
iter  80 value 87.021041
iter  90 value 86.618541
iter 100 value 86.548314
final  value 86.548314 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.371060 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 111.274667 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.167651 
iter  10 value 93.358251
iter  20 value 84.544606
final  value 84.454545 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.444002 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.801575 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.980650 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.055529 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.870411 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.503051 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.504980 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 115.390229 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.940441 
iter  10 value 94.367369
final  value 94.366483 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.700334 
final  value 94.467391 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.825518 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 120.540728 
iter  10 value 94.483463
final  value 94.483333 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.188513 
iter  10 value 94.413557
iter  20 value 86.958094
iter  30 value 85.617992
iter  40 value 85.341577
iter  50 value 85.270514
final  value 85.269172 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.384037 
iter  10 value 94.468992
iter  20 value 93.605765
iter  30 value 93.267667
iter  40 value 92.768848
iter  50 value 85.974868
iter  60 value 84.896185
final  value 84.891535 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.994261 
iter  10 value 94.487883
iter  20 value 94.271418
iter  30 value 90.398643
iter  40 value 89.423465
iter  50 value 87.073479
iter  60 value 85.178518
iter  70 value 84.310938
iter  80 value 83.785465
iter  90 value 83.772155
iter 100 value 83.753365
final  value 83.753365 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.609784 
iter  10 value 94.484730
iter  20 value 88.319683
iter  30 value 85.043535
iter  40 value 84.435215
iter  50 value 83.944677
iter  60 value 83.909078
iter  70 value 83.765205
iter  80 value 83.738542
iter  90 value 83.734415
final  value 83.733671 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.353792 
iter  10 value 94.472050
iter  20 value 87.638965
iter  30 value 86.475522
iter  40 value 86.214841
iter  50 value 85.585985
iter  60 value 85.270859
iter  70 value 85.269201
final  value 85.269171 
converged
Fitting Repeat 1 

# weights:  305
initial  value 119.187446 
iter  10 value 94.485385
iter  20 value 91.973372
iter  30 value 90.410349
iter  40 value 90.099773
iter  50 value 89.586163
iter  60 value 87.764224
iter  70 value 83.966299
iter  80 value 83.157712
iter  90 value 82.984663
iter 100 value 82.624081
final  value 82.624081 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.602388 
iter  10 value 95.545014
iter  20 value 92.673526
iter  30 value 88.235432
iter  40 value 87.034396
iter  50 value 84.561356
iter  60 value 83.811014
iter  70 value 83.083734
iter  80 value 82.626446
iter  90 value 82.551354
iter 100 value 82.285699
final  value 82.285699 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 109.646285 
iter  10 value 94.601159
iter  20 value 94.494221
iter  30 value 94.204972
iter  40 value 88.651526
iter  50 value 86.216134
iter  60 value 85.215449
iter  70 value 83.735805
iter  80 value 82.707325
iter  90 value 82.497569
iter 100 value 82.279279
final  value 82.279279 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.156216 
iter  10 value 94.480847
iter  20 value 93.491645
iter  30 value 90.444425
iter  40 value 87.826286
iter  50 value 86.200750
iter  60 value 85.968616
iter  70 value 85.619655
iter  80 value 85.072079
iter  90 value 83.193735
iter 100 value 82.737835
final  value 82.737835 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.419692 
iter  10 value 92.381735
iter  20 value 88.560706
iter  30 value 86.649434
iter  40 value 84.047220
iter  50 value 84.010508
iter  60 value 83.993029
iter  70 value 83.980288
iter  80 value 83.973411
iter  90 value 83.944852
iter 100 value 83.276087
final  value 83.276087 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 102.880924 
iter  10 value 94.434156
iter  20 value 86.212039
iter  30 value 85.489003
iter  40 value 85.209529
iter  50 value 84.049522
iter  60 value 82.980122
iter  70 value 82.319962
iter  80 value 82.127130
iter  90 value 82.030314
iter 100 value 81.952384
final  value 81.952384 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.207207 
iter  10 value 94.754207
iter  20 value 94.135421
iter  30 value 87.239778
iter  40 value 84.448481
iter  50 value 83.289794
iter  60 value 82.756605
iter  70 value 82.537408
iter  80 value 82.480557
iter  90 value 82.340094
iter 100 value 82.208683
final  value 82.208683 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 115.717263 
iter  10 value 94.499639
iter  20 value 90.376823
iter  30 value 86.117624
iter  40 value 85.777208
iter  50 value 84.974461
iter  60 value 84.071878
iter  70 value 83.685624
iter  80 value 83.636952
iter  90 value 83.625136
iter 100 value 83.402412
final  value 83.402412 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 116.886666 
iter  10 value 94.596948
iter  20 value 93.583913
iter  30 value 91.142619
iter  40 value 89.177422
iter  50 value 85.017098
iter  60 value 82.946939
iter  70 value 82.538440
iter  80 value 82.356070
iter  90 value 82.169047
iter 100 value 82.053539
final  value 82.053539 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.748625 
iter  10 value 95.625067
iter  20 value 90.902775
iter  30 value 88.290573
iter  40 value 87.132373
iter  50 value 85.896161
iter  60 value 85.233123
iter  70 value 84.807962
iter  80 value 84.193262
iter  90 value 84.123542
iter 100 value 83.893484
final  value 83.893484 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.995009 
final  value 94.485724 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.070579 
iter  10 value 94.469199
iter  20 value 94.467443
final  value 94.467407 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.105563 
final  value 94.485848 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.440268 
iter  10 value 94.486241
iter  20 value 87.663210
iter  30 value 87.604503
iter  40 value 86.959422
iter  50 value 86.957725
iter  60 value 86.845472
iter  70 value 85.107393
iter  80 value 85.104320
iter  80 value 85.104320
final  value 85.104307 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.746044 
final  value 94.485859 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.812045 
iter  10 value 94.484903
iter  20 value 94.483509
iter  30 value 94.467412
iter  30 value 94.467411
iter  30 value 94.467411
final  value 94.467411 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.905222 
iter  10 value 94.487900
iter  20 value 93.514330
iter  30 value 87.940517
iter  40 value 87.932908
iter  50 value 87.930757
iter  60 value 87.172391
iter  70 value 86.957702
final  value 86.957100 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.560950 
iter  10 value 94.472396
iter  20 value 94.465780
iter  30 value 93.389490
iter  40 value 93.141871
iter  50 value 93.139030
iter  50 value 93.139030
final  value 93.139030 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.223916 
iter  10 value 94.306660
iter  20 value 94.303526
iter  30 value 94.302011
final  value 94.302008 
converged
Fitting Repeat 5 

# weights:  305
initial  value 116.420748 
iter  10 value 94.489185
iter  20 value 94.481467
iter  30 value 94.348620
iter  40 value 94.323861
iter  50 value 87.338242
iter  60 value 86.529416
iter  70 value 86.400175
iter  80 value 84.508192
iter  90 value 84.352871
iter 100 value 84.297794
final  value 84.297794 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.601939 
iter  10 value 94.475823
iter  20 value 94.474884
iter  30 value 94.458826
iter  40 value 94.421779
iter  50 value 94.412795
iter  60 value 92.057814
iter  70 value 84.448569
iter  80 value 84.024257
iter  90 value 83.889499
iter 100 value 83.885461
final  value 83.885461 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.659742 
iter  10 value 94.492441
iter  20 value 94.279053
iter  30 value 88.500915
iter  40 value 85.344131
iter  50 value 84.685317
iter  60 value 84.295411
iter  70 value 84.188532
iter  80 value 84.124969
iter  90 value 83.998967
iter 100 value 83.997384
final  value 83.997384 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 116.209864 
iter  10 value 94.423474
iter  20 value 94.418841
iter  30 value 94.414997
iter  40 value 91.170327
iter  50 value 87.051570
iter  60 value 85.476170
iter  70 value 85.217174
iter  80 value 83.846765
iter  90 value 83.004420
iter 100 value 83.002179
final  value 83.002179 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 100.641379 
iter  10 value 94.475698
iter  20 value 94.468261
iter  30 value 94.435839
iter  40 value 85.743929
iter  50 value 84.347827
iter  60 value 83.839562
iter  70 value 83.829642
iter  80 value 83.825805
iter  90 value 83.820423
iter 100 value 83.819527
final  value 83.819527 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.393541 
iter  10 value 94.331213
iter  20 value 93.248233
iter  30 value 93.166198
iter  40 value 92.918559
iter  50 value 92.903207
iter  60 value 92.794978
iter  70 value 92.664682
iter  80 value 92.584510
final  value 92.584323 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.728847 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.735976 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.004381 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.934489 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.734913 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.600025 
final  value 94.052448 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.998612 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.840124 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.253219 
iter  10 value 93.582418
iter  10 value 93.582418
iter  10 value 93.582418
final  value 93.582418 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.761808 
iter  10 value 90.642588
iter  20 value 87.624853
iter  30 value 85.149714
iter  40 value 82.628319
iter  50 value 82.536752
iter  60 value 82.441284
iter  70 value 82.438388
final  value 82.438368 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.284795 
final  value 93.582418 
converged
Fitting Repeat 2 

# weights:  507
initial  value 94.773127 
final  value 93.582417 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.131732 
iter  10 value 93.805694
iter  20 value 93.804881
final  value 93.804879 
converged
Fitting Repeat 4 

# weights:  507
initial  value 126.360729 
final  value 93.860355 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.604914 
iter  10 value 93.130583
iter  20 value 88.133566
iter  30 value 85.570874
iter  40 value 84.866402
final  value 84.865718 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.922062 
iter  10 value 94.044214
iter  20 value 88.398643
iter  30 value 87.813250
iter  40 value 86.693955
iter  50 value 84.686570
iter  60 value 84.502195
iter  70 value 84.207825
iter  80 value 83.093473
iter  90 value 82.942497
iter 100 value 82.919458
final  value 82.919458 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 108.638089 
iter  10 value 93.883208
iter  20 value 87.182112
iter  30 value 85.862467
iter  40 value 83.958441
iter  50 value 83.342488
iter  60 value 82.951961
iter  70 value 82.927087
final  value 82.917702 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.903265 
iter  10 value 93.973538
iter  20 value 88.876707
iter  30 value 87.641641
iter  40 value 87.008320
iter  50 value 86.411579
iter  60 value 85.423478
iter  70 value 83.851299
iter  80 value 83.548789
iter  90 value 83.533506
iter 100 value 83.272367
final  value 83.272367 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.849989 
iter  10 value 94.056471
iter  20 value 93.942091
iter  30 value 90.241492
iter  40 value 86.983452
iter  50 value 85.750015
iter  60 value 85.547929
iter  70 value 85.455753
final  value 85.454215 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.536704 
iter  10 value 94.057104
iter  20 value 90.129832
iter  30 value 86.740289
iter  40 value 85.281053
iter  50 value 85.042329
iter  60 value 84.748702
iter  70 value 84.533585
iter  80 value 84.495385
iter  90 value 83.775150
iter 100 value 82.943436
final  value 82.943436 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 100.224233 
iter  10 value 94.058246
iter  20 value 92.202978
iter  30 value 91.463601
iter  40 value 89.430620
iter  50 value 84.544534
iter  60 value 82.948068
iter  70 value 81.754495
iter  80 value 81.662130
iter  90 value 81.583257
iter 100 value 81.557473
final  value 81.557473 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.306282 
iter  10 value 92.698640
iter  20 value 89.387477
iter  30 value 88.487872
iter  40 value 87.089760
iter  50 value 85.571259
iter  60 value 84.626992
iter  70 value 84.203474
iter  80 value 83.856082
iter  90 value 83.357843
iter 100 value 81.927473
final  value 81.927473 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.687165 
iter  10 value 91.636560
iter  20 value 88.776133
iter  30 value 87.710202
iter  40 value 84.095161
iter  50 value 82.724605
iter  60 value 82.331773
iter  70 value 81.775889
iter  80 value 81.640463
iter  90 value 81.265627
iter 100 value 81.065476
final  value 81.065476 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.792621 
iter  10 value 96.228219
iter  20 value 93.784447
iter  30 value 92.435673
iter  40 value 90.108685
iter  50 value 86.786385
iter  60 value 84.107752
iter  70 value 82.742330
iter  80 value 82.273443
iter  90 value 82.223401
iter 100 value 82.166043
final  value 82.166043 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.444971 
iter  10 value 94.096621
iter  20 value 92.951085
iter  30 value 88.693216
iter  40 value 87.362968
iter  50 value 86.517695
iter  60 value 86.300955
iter  70 value 82.945692
iter  80 value 81.902011
iter  90 value 81.507869
iter 100 value 81.388383
final  value 81.388383 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.322121 
iter  10 value 93.707089
iter  20 value 89.525148
iter  30 value 86.772357
iter  40 value 85.153111
iter  50 value 84.290483
iter  60 value 83.492749
iter  70 value 82.576860
iter  80 value 82.259544
iter  90 value 81.978219
iter 100 value 81.670194
final  value 81.670194 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 117.456348 
iter  10 value 94.444143
iter  20 value 93.539329
iter  30 value 89.314619
iter  40 value 88.966814
iter  50 value 88.572318
iter  60 value 87.294287
iter  70 value 85.117267
iter  80 value 84.247435
iter  90 value 83.990884
iter 100 value 82.622627
final  value 82.622627 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.311493 
iter  10 value 94.056085
iter  20 value 92.834119
iter  30 value 90.251058
iter  40 value 88.946760
iter  50 value 88.439840
iter  60 value 85.061342
iter  70 value 83.346838
iter  80 value 82.899443
iter  90 value 82.096537
iter 100 value 82.029147
final  value 82.029147 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.373241 
iter  10 value 94.227398
iter  20 value 91.635233
iter  30 value 88.912063
iter  40 value 85.737249
iter  50 value 83.236538
iter  60 value 82.753385
iter  70 value 82.228044
iter  80 value 81.766481
iter  90 value 81.407288
iter 100 value 81.308010
final  value 81.308010 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.223688 
iter  10 value 94.096426
iter  20 value 91.639886
iter  30 value 87.822315
iter  40 value 83.610749
iter  50 value 82.400702
iter  60 value 82.274689
iter  70 value 81.958851
iter  80 value 81.646567
iter  90 value 81.412190
iter 100 value 81.126786
final  value 81.126786 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.780598 
iter  10 value 94.054694
iter  20 value 93.828165
iter  30 value 93.599984
final  value 93.599880 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.877374 
final  value 94.054750 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.012980 
final  value 94.054587 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.512766 
final  value 94.054444 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.445410 
final  value 94.057497 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.076886 
iter  10 value 93.588251
iter  20 value 93.586928
iter  30 value 93.454405
iter  40 value 90.642488
iter  50 value 90.053567
iter  60 value 89.800431
iter  70 value 89.694986
final  value 89.694910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.338388 
iter  10 value 94.057428
iter  20 value 94.052919
iter  20 value 94.052918
iter  20 value 94.052918
final  value 94.052918 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.739504 
iter  10 value 94.055459
iter  20 value 93.906840
iter  30 value 93.579455
final  value 93.579363 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.327482 
iter  10 value 94.058172
iter  20 value 94.052868
iter  30 value 93.583154
final  value 93.582773 
converged
Fitting Repeat 5 

# weights:  305
initial  value 110.567639 
iter  10 value 94.064768
iter  20 value 94.059377
iter  30 value 94.053917
iter  40 value 86.257605
iter  50 value 85.286135
iter  60 value 85.137219
iter  70 value 85.133037
final  value 85.132511 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.219495 
iter  10 value 91.689566
iter  20 value 85.836443
iter  30 value 84.527141
iter  40 value 84.505313
iter  50 value 84.500759
iter  60 value 84.459722
iter  70 value 84.304986
iter  80 value 84.132518
iter  90 value 84.125097
iter 100 value 84.124709
final  value 84.124709 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 124.294214 
iter  10 value 93.591343
iter  20 value 93.585849
iter  30 value 93.585098
iter  40 value 93.583067
iter  50 value 93.189870
iter  60 value 93.148274
iter  70 value 93.147396
iter  80 value 93.090306
iter  90 value 93.013642
iter 100 value 93.012952
final  value 93.012952 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.352380 
iter  10 value 94.056907
iter  20 value 93.593830
iter  30 value 93.583450
iter  40 value 93.583034
iter  50 value 93.523952
iter  60 value 89.518849
iter  70 value 87.279432
iter  80 value 87.261213
final  value 87.260997 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.991208 
iter  10 value 93.594327
iter  20 value 93.583272
iter  30 value 93.524860
iter  40 value 87.071991
iter  50 value 86.606478
iter  60 value 86.536104
iter  70 value 86.518514
iter  80 value 85.707209
iter  90 value 85.056270
iter 100 value 85.055741
final  value 85.055741 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 136.645690 
iter  10 value 94.046164
iter  20 value 94.026387
iter  30 value 92.830875
iter  40 value 92.805864
iter  50 value 92.805446
iter  60 value 92.705414
iter  70 value 92.320718
iter  80 value 88.837478
iter  90 value 87.587676
iter 100 value 87.584398
final  value 87.584398 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 128.584605 
iter  10 value 117.763721
iter  20 value 117.759055
iter  30 value 117.524592
iter  40 value 112.719158
final  value 108.528270 
converged
Fitting Repeat 2 

# weights:  305
initial  value 127.711511 
iter  10 value 117.895463
iter  20 value 117.890416
iter  30 value 117.876963
iter  40 value 116.574220
iter  50 value 110.551725
iter  60 value 109.700328
iter  70 value 109.696020
iter  80 value 109.694905
iter  90 value 109.669001
iter 100 value 109.313676
final  value 109.313676 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 123.191337 
iter  10 value 117.892513
iter  20 value 117.760815
final  value 117.758920 
converged
Fitting Repeat 4 

# weights:  305
initial  value 136.404133 
iter  10 value 117.895612
iter  20 value 117.889464
iter  30 value 116.703688
iter  40 value 114.747495
iter  50 value 114.727587
final  value 114.727026 
converged
Fitting Repeat 5 

# weights:  305
initial  value 132.582549 
iter  10 value 114.920539
iter  20 value 114.666357
iter  30 value 114.320863
iter  40 value 113.114543
iter  50 value 108.812478
iter  60 value 106.620359
iter  70 value 104.915435
iter  80 value 104.375654
iter  90 value 104.373720
iter 100 value 104.337965
final  value 104.337965 
stopped after 100 iterations
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Wed May 22 03:00:05 2024 
*********************************************** 
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 
Warning messages:
1: `repeats` has no meaning for this resampling method. 
2: executing %dopar% sequentially: no parallel backend registered 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
  45.04    1.37   47.26