##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:HPiP.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings HPiP_1.11.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.20-bioc-mac-arm64/meat/HPiP.Rcheck’
* using R version 4.4.0 Patched (2024-04-24 r86482)
* using platform: aarch64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 12.2.0
* running under: macOS Ventura 13.6.6
* 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 for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
var_imp       55.527  1.899  57.480
FSmethod      52.974  1.887  54.904
corr_plot     52.807  1.963  54.849
pred_ensembel 15.204  0.317  12.766
enrichfindP    0.502  0.077  13.985
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 3 NOTEs
See
  ‘/Users/biocbuild/bbs-3.20-bioc-mac-arm64/meat/HPiP.Rcheck/00check.log’
for details.

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


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/library’
* installing *source* package ‘HPiP’ ...
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R version 4.4.0 Patched (2024-04-24 r86482) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20

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

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

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

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

# weights:  103
initial  value 102.978081 
final  value 94.038251 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.979041 
iter  10 value 94.052079
iter  20 value 94.038319
final  value 94.038251 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.061968 
final  value 93.671508 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.624299 
final  value 94.038251 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.802180 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.645781 
final  value 94.038251 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.858683 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.436642 
iter  10 value 94.052910
iter  10 value 94.052910
iter  10 value 94.052910
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.494967 
iter  10 value 93.405215
iter  20 value 92.357230
iter  30 value 91.645445
iter  40 value 91.213719
iter  50 value 91.147242
final  value 91.147239 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.563022 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 113.811059 
iter  10 value 93.656226
final  value 93.649711 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.196922 
final  value 94.038251 
converged
Fitting Repeat 3 

# weights:  507
initial  value 116.059000 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.922530 
iter  10 value 93.995513
final  value 93.995506 
converged
Fitting Repeat 5 

# weights:  507
initial  value 142.066124 
final  value 94.038251 
converged
Fitting Repeat 1 

# weights:  103
initial  value 108.802688 
iter  10 value 91.575046
iter  20 value 89.120123
iter  30 value 88.668054
iter  40 value 88.550574
iter  50 value 86.090444
iter  60 value 85.682010
iter  70 value 85.280326
iter  80 value 84.985997
iter  90 value 84.644633
final  value 84.586402 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.070128 
iter  10 value 94.070098
iter  20 value 94.056690
iter  30 value 88.929133
iter  40 value 87.926719
iter  50 value 86.458510
iter  60 value 85.386977
iter  70 value 85.367898
iter  80 value 85.355565
final  value 85.355308 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.355793 
iter  10 value 94.059259
iter  20 value 94.049422
iter  30 value 93.755483
iter  40 value 93.734109
iter  50 value 90.490916
iter  60 value 87.080662
iter  70 value 86.630075
iter  80 value 85.935708
iter  90 value 85.883512
iter 100 value 85.673881
final  value 85.673881 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.894041 
iter  10 value 87.565949
iter  20 value 86.352502
iter  30 value 86.195493
iter  40 value 85.693817
iter  50 value 84.935640
iter  60 value 84.827015
final  value 84.826083 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.288979 
iter  10 value 94.152528
iter  20 value 94.056615
iter  30 value 92.389201
iter  40 value 86.379707
iter  50 value 85.763911
iter  60 value 85.188827
iter  70 value 84.927220
iter  80 value 84.769732
iter  90 value 84.764283
iter 100 value 84.762514
final  value 84.762514 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 108.555372 
iter  10 value 93.981373
iter  20 value 90.842702
iter  30 value 90.217187
iter  40 value 88.687982
iter  50 value 86.998545
iter  60 value 85.628026
iter  70 value 85.360434
iter  80 value 85.156672
iter  90 value 84.721456
iter 100 value 83.654425
final  value 83.654425 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 127.920021 
iter  10 value 93.997110
iter  20 value 89.810154
iter  30 value 88.590940
iter  40 value 87.501438
iter  50 value 85.753108
iter  60 value 84.257542
iter  70 value 84.134519
iter  80 value 83.556209
iter  90 value 83.327168
iter 100 value 82.965902
final  value 82.965902 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.682170 
iter  10 value 94.023650
iter  20 value 88.098228
iter  30 value 85.956886
iter  40 value 85.692841
iter  50 value 85.330003
iter  60 value 84.956561
iter  70 value 84.321327
iter  80 value 83.765367
iter  90 value 83.132647
iter 100 value 82.912499
final  value 82.912499 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.951736 
iter  10 value 93.718870
iter  20 value 91.682500
iter  30 value 89.756803
iter  40 value 88.938786
iter  50 value 87.030844
iter  60 value 85.525949
iter  70 value 84.368535
iter  80 value 83.960345
iter  90 value 83.681769
iter 100 value 83.477744
final  value 83.477744 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.028242 
iter  10 value 94.341983
iter  20 value 93.482223
iter  30 value 88.229621
iter  40 value 86.561832
iter  50 value 85.997685
iter  60 value 85.554900
iter  70 value 84.979365
iter  80 value 84.888060
iter  90 value 84.154998
iter 100 value 83.740693
final  value 83.740693 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 120.280864 
iter  10 value 94.553809
iter  20 value 94.161304
iter  30 value 94.066559
iter  40 value 93.962874
iter  50 value 89.523751
iter  60 value 84.821040
iter  70 value 84.606805
iter  80 value 84.040859
iter  90 value 83.919494
iter 100 value 83.514726
final  value 83.514726 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 116.224802 
iter  10 value 94.084355
iter  20 value 93.992005
iter  30 value 90.304656
iter  40 value 88.463648
iter  50 value 86.750258
iter  60 value 85.470149
iter  70 value 84.999977
iter  80 value 84.950779
iter  90 value 84.764723
iter 100 value 84.564146
final  value 84.564146 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 119.170922 
iter  10 value 94.603483
iter  20 value 93.998731
iter  30 value 89.008174
iter  40 value 88.634762
iter  50 value 88.257180
iter  60 value 86.678756
iter  70 value 84.420046
iter  80 value 84.092264
iter  90 value 83.518084
iter 100 value 83.405567
final  value 83.405567 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.728736 
iter  10 value 94.121033
iter  20 value 93.021898
iter  30 value 90.455091
iter  40 value 89.565451
iter  50 value 86.791230
iter  60 value 85.664071
iter  70 value 84.280693
iter  80 value 83.970564
iter  90 value 83.955879
iter 100 value 83.913967
final  value 83.913967 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.321561 
iter  10 value 94.649441
iter  20 value 92.854005
iter  30 value 89.290467
iter  40 value 88.891229
iter  50 value 86.319636
iter  60 value 85.603918
iter  70 value 85.044780
iter  80 value 84.224065
iter  90 value 83.162664
iter 100 value 82.931447
final  value 82.931447 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.350802 
final  value 94.054350 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.044209 
final  value 94.054632 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.442198 
final  value 94.054704 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.998706 
iter  10 value 94.054610
iter  20 value 94.052989
iter  20 value 94.052988
iter  20 value 94.052988
final  value 94.052988 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.562941 
final  value 94.054634 
converged
Fitting Repeat 1 

# weights:  305
initial  value 117.642053 
iter  10 value 94.057814
iter  20 value 93.997214
iter  30 value 93.883386
iter  40 value 89.985571
iter  50 value 89.575298
iter  60 value 89.344532
iter  70 value 88.076326
iter  80 value 85.666166
iter  90 value 83.370016
iter 100 value 83.309030
final  value 83.309030 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.288339 
iter  10 value 94.057580
iter  20 value 94.052949
iter  30 value 91.520256
iter  40 value 90.461006
iter  50 value 90.460413
iter  60 value 88.231655
iter  70 value 88.215631
iter  80 value 88.207177
iter  90 value 85.751793
iter 100 value 85.749573
final  value 85.749573 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 94.302990 
iter  10 value 94.057691
iter  20 value 92.568689
iter  30 value 85.751188
final  value 85.751185 
converged
Fitting Repeat 4 

# weights:  305
initial  value 122.240691 
iter  10 value 94.043123
iter  20 value 94.038972
iter  30 value 94.013191
iter  40 value 88.110176
iter  50 value 84.226388
iter  60 value 83.711964
iter  70 value 83.673152
iter  80 value 83.616109
iter  90 value 83.615601
final  value 83.615559 
converged
Fitting Repeat 5 

# weights:  305
initial  value 113.299310 
iter  10 value 93.959391
iter  20 value 93.956613
iter  30 value 93.786566
iter  40 value 93.724418
final  value 93.724393 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.325344 
iter  10 value 94.066355
iter  20 value 94.009654
iter  30 value 91.396379
iter  40 value 89.981518
iter  50 value 88.261771
iter  60 value 86.058332
iter  70 value 85.090851
iter  80 value 84.129576
iter  90 value 82.432138
iter 100 value 81.599735
final  value 81.599735 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.153496 
iter  10 value 91.697681
iter  20 value 91.694152
iter  30 value 91.665451
iter  40 value 91.653591
iter  50 value 91.633914
iter  60 value 91.623321
iter  70 value 91.578734
iter  80 value 91.576654
iter  90 value 91.576179
iter 100 value 91.575951
final  value 91.575951 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 115.837263 
iter  10 value 94.061637
iter  20 value 93.195596
final  value 85.749313 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.423592 
iter  10 value 94.046693
iter  20 value 94.038656
iter  30 value 94.038264
iter  30 value 94.038263
final  value 94.038263 
converged
Fitting Repeat 5 

# weights:  507
initial  value 121.163050 
iter  10 value 89.014789
iter  20 value 88.589351
iter  30 value 87.859022
iter  40 value 87.553408
iter  50 value 87.372269
iter  60 value 87.366911
iter  70 value 87.363918
final  value 87.363513 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.771838 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.869685 
final  value 93.915746 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.724367 
iter  10 value 91.824626
iter  20 value 91.804329
final  value 91.804173 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.480478 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.141611 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.624036 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 109.869776 
iter  10 value 93.705405
iter  20 value 93.598177
iter  30 value 93.415474
iter  40 value 93.414026
final  value 93.414007 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.851871 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 116.876038 
final  value 93.915746 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.809664 
final  value 93.915746 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.467328 
final  value 93.288889 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.385451 
final  value 93.915746 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.526350 
iter  10 value 83.153373
iter  20 value 83.034525
iter  30 value 83.033142
final  value 83.033139 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.403614 
iter  10 value 93.389002
iter  20 value 90.697474
iter  30 value 90.693495
final  value 90.693126 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.399449 
iter  10 value 93.010560
final  value 93.008017 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.618565 
iter  10 value 94.057068
iter  20 value 93.804563
iter  30 value 93.646869
iter  40 value 93.411826
iter  50 value 85.788431
iter  60 value 83.952491
iter  70 value 83.307719
iter  80 value 83.291788
final  value 83.291126 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.286809 
iter  10 value 93.878522
iter  20 value 90.513455
iter  30 value 87.747156
iter  40 value 87.111215
iter  50 value 85.687994
iter  60 value 85.339594
iter  70 value 82.877489
iter  80 value 82.156071
iter  90 value 81.921555
iter 100 value 81.736780
final  value 81.736780 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.600432 
iter  10 value 94.055480
iter  20 value 93.648728
iter  30 value 93.641983
iter  40 value 93.638581
iter  50 value 92.823279
iter  60 value 87.279956
iter  70 value 84.188673
iter  80 value 83.706131
iter  90 value 83.636628
iter 100 value 83.608411
final  value 83.608411 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 118.366298 
iter  10 value 94.055563
iter  20 value 89.454044
iter  30 value 88.014288
iter  40 value 87.869796
iter  50 value 86.558986
iter  60 value 84.620510
iter  70 value 82.803745
iter  80 value 82.146127
iter  90 value 81.692743
final  value 81.691393 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.782343 
iter  10 value 94.055189
iter  20 value 93.707600
iter  30 value 93.639820
iter  40 value 93.639469
iter  50 value 93.638990
iter  60 value 91.394287
iter  70 value 87.114195
iter  80 value 86.761885
iter  90 value 86.220230
iter 100 value 83.759607
final  value 83.759607 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 105.904309 
iter  10 value 94.072589
iter  20 value 93.632271
iter  30 value 87.435419
iter  40 value 84.824909
iter  50 value 81.604905
iter  60 value 81.226434
iter  70 value 80.989767
iter  80 value 80.870306
iter  90 value 80.754765
iter 100 value 80.706870
final  value 80.706870 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.329367 
iter  10 value 94.097988
iter  20 value 93.716764
iter  30 value 90.486126
iter  40 value 88.962623
iter  50 value 85.890351
iter  60 value 83.009331
iter  70 value 82.130422
iter  80 value 81.288540
iter  90 value 80.643844
iter 100 value 80.351799
final  value 80.351799 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 113.219256 
iter  10 value 94.054154
iter  20 value 90.322992
iter  30 value 87.704472
iter  40 value 87.491925
iter  50 value 82.726931
iter  60 value 81.560305
iter  70 value 81.307409
iter  80 value 81.094590
iter  90 value 80.647709
iter 100 value 80.556674
final  value 80.556674 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.317909 
iter  10 value 94.179923
iter  20 value 92.640022
iter  30 value 91.834676
iter  40 value 90.106511
iter  50 value 86.433513
iter  60 value 82.544508
iter  70 value 82.119738
iter  80 value 81.482404
iter  90 value 80.588621
iter 100 value 80.425194
final  value 80.425194 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.259984 
iter  10 value 93.430307
iter  20 value 84.636202
iter  30 value 83.820312
iter  40 value 83.634103
iter  50 value 83.578066
iter  60 value 83.497889
iter  70 value 83.391060
iter  80 value 82.338963
iter  90 value 82.038089
iter 100 value 81.847106
final  value 81.847106 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.207778 
iter  10 value 94.190331
iter  20 value 91.974670
iter  30 value 89.475193
iter  40 value 89.070331
iter  50 value 86.968797
iter  60 value 86.102794
iter  70 value 84.253127
iter  80 value 83.894827
iter  90 value 83.687544
iter 100 value 83.398722
final  value 83.398722 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.183473 
iter  10 value 96.363294
iter  20 value 84.594896
iter  30 value 83.553379
iter  40 value 83.067225
iter  50 value 82.981008
iter  60 value 82.897257
iter  70 value 82.323504
iter  80 value 81.358651
iter  90 value 80.822735
iter 100 value 80.684662
final  value 80.684662 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 140.064831 
iter  10 value 94.565721
iter  20 value 87.666748
iter  30 value 86.681073
iter  40 value 84.500894
iter  50 value 83.423990
iter  60 value 82.008898
iter  70 value 80.915192
iter  80 value 80.249656
iter  90 value 80.083392
iter 100 value 80.049283
final  value 80.049283 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.972961 
iter  10 value 92.826335
iter  20 value 83.561568
iter  30 value 83.309586
iter  40 value 82.409517
iter  50 value 82.306512
iter  60 value 82.066608
iter  70 value 81.123027
iter  80 value 80.778615
iter  90 value 80.694784
iter 100 value 80.678670
final  value 80.678670 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.013660 
iter  10 value 96.952663
iter  20 value 86.365167
iter  30 value 84.010333
iter  40 value 83.517604
iter  50 value 83.225470
iter  60 value 81.474111
iter  70 value 80.824187
iter  80 value 80.623130
iter  90 value 80.512350
iter 100 value 80.446233
final  value 80.446233 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.820185 
final  value 94.054764 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.978577 
final  value 94.054585 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.776183 
final  value 94.054584 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.125861 
final  value 94.054737 
converged
Fitting Repeat 5 

# weights:  103
initial  value 111.152286 
iter  10 value 94.054590
iter  20 value 94.052930
final  value 94.052913 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.830585 
iter  10 value 94.057554
iter  20 value 93.751753
iter  30 value 93.601751
iter  30 value 93.601750
iter  30 value 93.601750
final  value 93.601750 
converged
Fitting Repeat 2 

# weights:  305
initial  value 116.219283 
iter  10 value 94.057505
iter  20 value 94.052913
iter  30 value 94.015234
iter  40 value 90.879944
iter  50 value 90.571576
iter  60 value 84.861240
iter  70 value 83.399254
iter  80 value 83.394482
iter  90 value 83.391960
iter 100 value 82.633252
final  value 82.633252 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 114.872452 
iter  10 value 93.718736
iter  20 value 93.602238
iter  30 value 93.600252
iter  40 value 93.437592
iter  50 value 93.169092
iter  60 value 93.167984
iter  70 value 93.167834
iter  80 value 93.167328
final  value 93.167190 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.412327 
iter  10 value 94.057227
iter  20 value 93.011560
iter  30 value 86.444535
iter  40 value 84.018180
iter  50 value 82.963797
iter  60 value 82.460433
iter  70 value 82.108110
iter  80 value 82.107426
iter  90 value 82.020724
iter 100 value 80.127133
final  value 80.127133 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.482081 
iter  10 value 93.726479
iter  20 value 93.717838
iter  30 value 93.594919
iter  40 value 93.343195
iter  50 value 83.834295
iter  60 value 82.247760
iter  70 value 81.766787
iter  80 value 81.661995
final  value 81.657931 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.703313 
iter  10 value 93.893706
iter  20 value 93.721980
iter  30 value 93.608496
iter  40 value 93.589499
final  value 93.589496 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.899710 
iter  10 value 93.721689
iter  20 value 93.720642
iter  30 value 93.714021
iter  40 value 93.678052
iter  50 value 86.170653
iter  60 value 83.094301
iter  70 value 83.073085
iter  80 value 83.066953
iter  90 value 83.064635
iter 100 value 83.059031
final  value 83.059031 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 98.870343 
iter  10 value 93.923823
iter  20 value 93.327694
iter  30 value 93.155966
iter  40 value 85.627067
iter  50 value 83.673438
iter  60 value 83.548275
iter  70 value 83.530839
iter  80 value 83.521326
iter  90 value 82.520916
iter 100 value 82.360889
final  value 82.360889 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 98.001587 
iter  10 value 90.473049
iter  20 value 88.095127
iter  30 value 87.283022
iter  40 value 87.263054
iter  50 value 86.810049
iter  60 value 86.435689
iter  70 value 86.412043
iter  80 value 86.410178
iter  90 value 86.105957
iter 100 value 84.338299
final  value 84.338299 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 102.096184 
iter  10 value 94.061005
iter  20 value 93.945309
iter  30 value 91.656286
iter  40 value 89.521658
iter  50 value 89.493616
iter  60 value 89.492552
iter  70 value 89.487906
iter  80 value 89.486247
iter  90 value 89.482654
iter 100 value 89.424879
final  value 89.424879 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.950725 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.566824 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.370822 
iter  10 value 94.275363
iter  10 value 94.275362
iter  10 value 94.275362
final  value 94.275362 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.659286 
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.126415 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.317948 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 124.194893 
iter  10 value 89.132777
iter  20 value 87.093892
iter  30 value 86.688110
iter  40 value 86.683625
iter  50 value 86.683469
final  value 86.683460 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.622663 
final  value 94.275363 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.971387 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.927356 
iter  10 value 94.234285
iter  20 value 93.769673
iter  30 value 93.149301
iter  40 value 93.119716
iter  50 value 89.720153
iter  60 value 83.907518
iter  70 value 83.621353
iter  80 value 83.587631
iter  90 value 82.849367
iter 100 value 82.843470
final  value 82.843470 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 127.256248 
iter  10 value 94.275380
final  value 94.275362 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.555351 
final  value 94.275362 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.493037 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.247301 
iter  10 value 93.383119
iter  20 value 92.860381
final  value 92.860100 
converged
Fitting Repeat 5 

# weights:  507
initial  value 116.769722 
final  value 94.275362 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.175590 
iter  10 value 94.564365
iter  20 value 94.481655
iter  30 value 87.223839
iter  40 value 85.484721
iter  50 value 85.158107
iter  60 value 83.038903
iter  70 value 82.476078
final  value 82.472251 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.499138 
iter  10 value 94.610192
iter  20 value 94.485029
iter  30 value 93.021388
iter  40 value 90.573922
iter  50 value 87.055573
iter  60 value 86.654380
iter  70 value 86.295822
iter  80 value 84.802613
iter  90 value 83.279872
iter 100 value 82.496774
final  value 82.496774 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.020650 
iter  10 value 94.489187
iter  20 value 90.793301
iter  30 value 86.432487
iter  40 value 84.977025
iter  50 value 83.597323
iter  60 value 82.871933
iter  70 value 82.622770
iter  80 value 82.417419
iter  90 value 82.235227
final  value 82.192731 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.287930 
iter  10 value 94.490210
iter  20 value 94.439057
iter  30 value 94.327633
iter  40 value 94.327471
iter  50 value 91.470374
iter  60 value 87.872999
iter  70 value 87.102324
iter  80 value 85.834264
iter  90 value 85.496906
iter 100 value 85.483598
final  value 85.483598 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 96.978074 
iter  10 value 94.487078
iter  20 value 91.685933
iter  30 value 87.520963
iter  40 value 87.339891
iter  50 value 87.100724
iter  60 value 87.053685
iter  70 value 87.002914
iter  80 value 86.245361
iter  90 value 85.532475
iter 100 value 85.483033
final  value 85.483033 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 107.900198 
iter  10 value 94.444136
iter  20 value 90.430156
iter  30 value 89.070726
iter  40 value 86.095125
iter  50 value 84.774190
iter  60 value 83.440319
iter  70 value 82.499223
iter  80 value 82.056923
iter  90 value 81.839729
iter 100 value 81.644402
final  value 81.644402 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.571356 
iter  10 value 94.499040
iter  20 value 88.715112
iter  30 value 86.802709
iter  40 value 85.697756
iter  50 value 84.285366
iter  60 value 83.455799
iter  70 value 83.299617
iter  80 value 83.184519
iter  90 value 83.115433
iter 100 value 82.923087
final  value 82.923087 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.666937 
iter  10 value 94.300585
iter  20 value 93.356115
iter  30 value 89.409795
iter  40 value 87.734606
iter  50 value 84.268361
iter  60 value 82.715717
iter  70 value 81.408891
iter  80 value 80.846624
iter  90 value 80.739978
iter 100 value 80.625364
final  value 80.625364 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.593911 
iter  10 value 94.235662
iter  20 value 88.667824
iter  30 value 86.823299
iter  40 value 83.480075
iter  50 value 82.958723
iter  60 value 82.514069
iter  70 value 82.335455
iter  80 value 81.815619
iter  90 value 81.782253
iter 100 value 81.772015
final  value 81.772015 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 114.638309 
iter  10 value 95.198761
iter  20 value 91.365379
iter  30 value 84.115182
iter  40 value 82.804756
iter  50 value 82.074872
iter  60 value 81.758608
iter  70 value 81.684532
iter  80 value 81.375547
iter  90 value 81.131544
iter 100 value 80.973096
final  value 80.973096 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.345074 
iter  10 value 95.025931
iter  20 value 93.381757
iter  30 value 92.899605
iter  40 value 91.435358
iter  50 value 85.509863
iter  60 value 85.140229
iter  70 value 84.738569
iter  80 value 84.456813
iter  90 value 84.175651
iter 100 value 83.831134
final  value 83.831134 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.646173 
iter  10 value 96.846756
iter  20 value 94.268928
iter  30 value 91.405851
iter  40 value 87.138055
iter  50 value 83.452341
iter  60 value 82.302221
iter  70 value 81.531992
iter  80 value 81.338597
iter  90 value 81.127398
iter 100 value 81.034304
final  value 81.034304 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 135.315991 
iter  10 value 101.015113
iter  20 value 93.693820
iter  30 value 91.922153
iter  40 value 86.955577
iter  50 value 86.263765
iter  60 value 83.068071
iter  70 value 82.550528
iter  80 value 82.334037
iter  90 value 82.214218
iter 100 value 82.135981
final  value 82.135981 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 116.312410 
iter  10 value 94.657109
iter  20 value 94.253442
iter  30 value 92.794922
iter  40 value 89.462519
iter  50 value 86.405416
iter  60 value 85.358633
iter  70 value 83.947635
iter  80 value 83.693461
iter  90 value 82.628216
iter 100 value 81.149296
final  value 81.149296 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.814216 
iter  10 value 94.470593
iter  20 value 88.517208
iter  30 value 87.982802
iter  40 value 87.349067
iter  50 value 86.102848
iter  60 value 84.663035
iter  70 value 83.855228
iter  80 value 82.769282
iter  90 value 81.681953
iter 100 value 81.252685
final  value 81.252685 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.616859 
final  value 94.485985 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.869483 
final  value 94.485848 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.348209 
final  value 94.486039 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.943480 
final  value 94.486026 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.403306 
final  value 94.485754 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.599067 
iter  10 value 94.490002
iter  20 value 94.480369
iter  30 value 94.253967
final  value 94.229762 
converged
Fitting Repeat 2 

# weights:  305
initial  value 106.326778 
iter  10 value 94.489437
iter  20 value 88.125692
iter  30 value 86.745223
iter  40 value 86.108432
iter  50 value 86.105991
iter  60 value 86.027657
final  value 86.027619 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.663031 
iter  10 value 94.488577
iter  20 value 94.483947
iter  30 value 86.356852
final  value 85.954546 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.788861 
iter  10 value 94.488980
iter  20 value 94.484451
final  value 94.484254 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.016958 
iter  10 value 94.489005
iter  20 value 94.484329
iter  30 value 91.769718
iter  40 value 90.346163
iter  50 value 90.345209
iter  60 value 90.343259
iter  70 value 90.342836
iter  80 value 88.517304
iter  90 value 87.372740
iter 100 value 87.371093
final  value 87.371093 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.249870 
iter  10 value 94.492239
iter  20 value 94.424377
iter  30 value 94.232085
final  value 94.229772 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.795406 
iter  10 value 94.493245
iter  20 value 93.699435
iter  30 value 87.383224
iter  40 value 87.375362
iter  50 value 87.191189
iter  60 value 85.630992
iter  70 value 84.183726
iter  80 value 83.102537
iter  90 value 81.258212
iter 100 value 80.259554
final  value 80.259554 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 100.099712 
iter  10 value 94.492169
iter  20 value 94.482939
iter  30 value 93.644692
iter  40 value 88.342564
iter  50 value 83.320037
iter  60 value 81.171690
iter  70 value 81.118229
iter  80 value 81.116743
iter  90 value 80.419172
iter 100 value 80.157347
final  value 80.157347 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.823483 
iter  10 value 94.492140
iter  20 value 94.446550
iter  30 value 87.639844
iter  40 value 85.320154
iter  50 value 84.899414
iter  60 value 84.898726
final  value 84.898607 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.784603 
iter  10 value 93.358435
iter  20 value 92.851793
iter  30 value 92.587045
final  value 92.585831 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.279036 
iter  10 value 93.551691
iter  20 value 93.477434
final  value 93.477395 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.798848 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.871057 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.477999 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 110.939128 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.521230 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 106.305045 
iter  10 value 93.394928
iter  10 value 93.394928
iter  10 value 93.394928
final  value 93.394928 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.298635 
iter  10 value 93.394931
final  value 93.394928 
converged
Fitting Repeat 4 

# weights:  305
initial  value 119.934821 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.891453 
iter  10 value 93.394945
final  value 93.394928 
converged
Fitting Repeat 1 

# weights:  507
initial  value 121.169476 
iter  10 value 92.025542
iter  20 value 92.021611
final  value 92.021513 
converged
Fitting Repeat 2 

# weights:  507
initial  value 127.672457 
iter  10 value 93.394980
final  value 93.394928 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.667784 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.452773 
iter  10 value 91.054244
iter  20 value 90.805433
final  value 90.805195 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.423151 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.124307 
iter  10 value 94.480300
iter  20 value 93.479983
iter  30 value 93.026323
iter  40 value 80.719082
iter  50 value 78.270554
iter  60 value 77.926513
iter  70 value 77.814036
iter  80 value 77.626601
iter  90 value 77.150430
iter 100 value 77.066949
final  value 77.066949 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 100.191552 
iter  10 value 94.455778
iter  20 value 93.380728
iter  30 value 93.245860
iter  40 value 86.758248
iter  50 value 82.191688
iter  60 value 79.983835
iter  70 value 78.347185
iter  80 value 77.649086
iter  90 value 77.549549
iter 100 value 77.316549
final  value 77.316549 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.306649 
iter  10 value 93.480399
iter  20 value 89.533489
iter  30 value 83.873215
iter  40 value 79.459355
iter  50 value 79.044250
iter  60 value 78.980759
iter  70 value 78.846871
iter  80 value 78.780688
iter  90 value 77.501663
iter 100 value 77.283069
final  value 77.283069 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.664188 
iter  10 value 94.057777
iter  20 value 93.238411
iter  30 value 92.853535
iter  40 value 83.150620
iter  50 value 82.616997
iter  60 value 82.283588
iter  70 value 82.234808
iter  80 value 82.232403
final  value 82.232341 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.066922 
iter  10 value 94.455328
iter  20 value 89.579964
iter  30 value 88.344831
iter  40 value 82.030358
iter  50 value 81.359328
iter  60 value 80.991658
iter  70 value 80.865782
final  value 80.865780 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.403304 
iter  10 value 93.514832
iter  20 value 84.317175
iter  30 value 82.566174
iter  40 value 79.868406
iter  50 value 78.627007
iter  60 value 78.343476
iter  70 value 78.182041
iter  80 value 78.017151
iter  90 value 77.499847
iter 100 value 76.455279
final  value 76.455279 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 109.221494 
iter  10 value 93.803894
iter  20 value 93.511187
iter  30 value 86.482033
iter  40 value 82.435375
iter  50 value 82.028121
iter  60 value 81.429586
iter  70 value 80.262769
iter  80 value 79.011905
iter  90 value 77.284809
iter 100 value 76.429469
final  value 76.429469 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.003940 
iter  10 value 94.894602
iter  20 value 82.821178
iter  30 value 79.794019
iter  40 value 78.677217
iter  50 value 78.501656
iter  60 value 78.334725
iter  70 value 77.482244
iter  80 value 76.947917
iter  90 value 76.739759
iter 100 value 76.410779
final  value 76.410779 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.643437 
iter  10 value 92.922903
iter  20 value 89.648351
iter  30 value 89.071627
iter  40 value 87.459586
iter  50 value 84.125326
iter  60 value 83.468018
iter  70 value 80.856522
iter  80 value 79.797984
iter  90 value 78.276819
iter 100 value 77.895873
final  value 77.895873 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.964521 
iter  10 value 93.920264
iter  20 value 87.628783
iter  30 value 80.424710
iter  40 value 78.827415
iter  50 value 77.573066
iter  60 value 76.921128
iter  70 value 76.708487
iter  80 value 76.585040
iter  90 value 76.528035
iter 100 value 76.429188
final  value 76.429188 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.812251 
iter  10 value 94.812026
iter  20 value 92.956134
iter  30 value 79.933561
iter  40 value 79.045684
iter  50 value 78.618250
iter  60 value 77.156347
iter  70 value 76.666248
iter  80 value 76.267973
iter  90 value 75.842496
iter 100 value 75.503371
final  value 75.503371 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.373527 
iter  10 value 89.215218
iter  20 value 81.838657
iter  30 value 78.525917
iter  40 value 76.551821
iter  50 value 76.311649
iter  60 value 75.750603
iter  70 value 75.610110
iter  80 value 75.521585
iter  90 value 75.481460
iter 100 value 75.371577
final  value 75.371577 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.284158 
iter  10 value 95.695281
iter  20 value 85.999811
iter  30 value 83.206690
iter  40 value 82.261371
iter  50 value 81.431652
iter  60 value 78.639083
iter  70 value 77.771108
iter  80 value 77.341291
iter  90 value 77.115418
iter 100 value 76.777060
final  value 76.777060 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 130.983963 
iter  10 value 94.007362
iter  20 value 93.223905
iter  30 value 90.281557
iter  40 value 87.272171
iter  50 value 86.357956
iter  60 value 83.012604
iter  70 value 78.063656
iter  80 value 77.292019
iter  90 value 77.140288
iter 100 value 76.872837
final  value 76.872837 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 121.556452 
iter  10 value 94.178372
iter  20 value 93.270780
iter  30 value 92.431425
iter  40 value 87.192493
iter  50 value 82.350551
iter  60 value 80.627964
iter  70 value 79.323939
iter  80 value 78.806084
iter  90 value 78.605413
iter 100 value 78.190874
final  value 78.190874 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.264839 
final  value 94.485654 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.450243 
final  value 94.485539 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.034363 
iter  10 value 94.486015
final  value 94.484296 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.079654 
final  value 94.324776 
converged
Fitting Repeat 5 

# weights:  103
initial  value 114.535617 
final  value 94.485823 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.911823 
iter  10 value 94.491089
iter  20 value 89.125402
iter  30 value 82.989149
iter  40 value 82.221864
iter  50 value 81.314674
iter  60 value 81.304810
final  value 81.304208 
converged
Fitting Repeat 2 

# weights:  305
initial  value 106.058909 
iter  10 value 94.489378
iter  20 value 94.484533
iter  20 value 94.484533
final  value 94.484533 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.824987 
iter  10 value 94.487268
iter  20 value 92.954184
iter  30 value 79.886770
iter  40 value 78.438070
iter  50 value 78.224660
iter  60 value 78.159506
iter  70 value 78.088074
iter  70 value 78.088074
final  value 78.088074 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.453861 
iter  10 value 90.887743
iter  20 value 90.886829
iter  30 value 89.463668
iter  40 value 89.460414
iter  50 value 85.649494
iter  60 value 85.446851
iter  70 value 83.238934
iter  80 value 81.908705
iter  90 value 81.902582
final  value 81.902561 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.478284 
iter  10 value 94.488645
iter  20 value 94.068047
iter  30 value 86.613795
iter  40 value 86.085791
iter  50 value 85.863349
iter  60 value 85.652004
iter  70 value 84.165644
iter  80 value 82.887858
iter  90 value 82.885227
iter 100 value 81.314978
final  value 81.314978 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.470965 
iter  10 value 88.875587
iter  20 value 84.676795
iter  30 value 80.433809
iter  40 value 79.808011
iter  50 value 79.650134
iter  60 value 79.648391
iter  70 value 79.643342
iter  80 value 79.537065
iter  90 value 79.528138
iter 100 value 79.526867
final  value 79.526867 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 102.461390 
iter  10 value 94.492796
iter  20 value 94.457349
iter  30 value 93.592277
iter  40 value 91.083223
iter  50 value 91.050175
iter  60 value 89.733083
iter  70 value 87.141714
iter  80 value 81.581747
iter  90 value 76.898421
iter 100 value 76.093987
final  value 76.093987 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 96.730689 
iter  10 value 86.126124
iter  20 value 84.946545
iter  30 value 84.912141
iter  40 value 84.833273
iter  50 value 81.727851
iter  60 value 81.050483
iter  70 value 80.947207
iter  80 value 80.780921
iter  90 value 77.384308
iter 100 value 76.708346
final  value 76.708346 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 122.542212 
iter  10 value 93.736410
iter  20 value 93.439161
iter  30 value 93.404677
iter  40 value 93.396273
iter  50 value 93.137969
iter  60 value 90.522133
iter  70 value 83.648893
iter  80 value 82.035281
iter  90 value 82.000032
iter 100 value 81.996516
final  value 81.996516 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 102.568045 
iter  10 value 93.271021
iter  20 value 91.964499
iter  30 value 91.790678
iter  40 value 91.787520
iter  50 value 91.785127
iter  60 value 90.898075
iter  70 value 90.846274
iter  80 value 90.845870
iter  90 value 90.845828
iter 100 value 88.748079
final  value 88.748079 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.816253 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.967602 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.304822 
iter  10 value 94.430315
final  value 94.430234 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.549062 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.725279 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.751323 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.899521 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.670012 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 138.040324 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.306508 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.850088 
final  value 94.467391 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.072691 
final  value 94.467391 
converged
Fitting Repeat 3 

# weights:  507
initial  value 111.687731 
final  value 94.449438 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.707337 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 115.563390 
iter  10 value 94.431636
final  value 94.430233 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.088399 
iter  10 value 94.467568
iter  20 value 92.326574
iter  30 value 88.950090
iter  40 value 82.159790
iter  50 value 81.853882
iter  60 value 81.379446
iter  70 value 81.329324
final  value 81.328520 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.116516 
iter  10 value 93.384477
iter  20 value 84.882920
iter  30 value 83.484154
iter  40 value 83.022988
iter  50 value 82.272643
iter  60 value 81.905920
iter  70 value 80.710932
iter  80 value 80.244859
iter  90 value 80.020669
iter 100 value 79.711360
final  value 79.711360 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 102.357525 
iter  10 value 94.488174
iter  20 value 92.799496
iter  30 value 91.937403
iter  40 value 86.677975
iter  50 value 85.217069
iter  60 value 82.870226
iter  70 value 82.609557
iter  80 value 82.040617
iter  90 value 81.208726
iter 100 value 81.100363
final  value 81.100363 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 98.708191 
iter  10 value 94.194648
iter  20 value 90.076608
iter  30 value 83.030609
iter  40 value 82.068187
iter  50 value 81.365430
iter  60 value 81.111270
iter  70 value 81.099648
final  value 81.099648 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.244730 
iter  10 value 94.504056
iter  20 value 94.454623
iter  30 value 86.921233
iter  40 value 84.623432
iter  50 value 82.281007
iter  60 value 81.366405
iter  70 value 81.150703
iter  80 value 80.992214
iter  90 value 80.610501
iter 100 value 79.799499
final  value 79.799499 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 117.016115 
iter  10 value 94.752225
iter  20 value 94.502669
iter  30 value 92.206365
iter  40 value 86.837963
iter  50 value 85.567573
iter  60 value 80.452970
iter  70 value 79.267896
iter  80 value 78.836137
iter  90 value 78.666034
iter 100 value 78.559505
final  value 78.559505 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.775826 
iter  10 value 94.273795
iter  20 value 89.087118
iter  30 value 84.951922
iter  40 value 83.933739
iter  50 value 82.893416
iter  60 value 82.645464
iter  70 value 82.511650
iter  80 value 81.367278
iter  90 value 79.401422
iter 100 value 78.890360
final  value 78.890360 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.835169 
iter  10 value 94.578151
iter  20 value 93.731994
iter  30 value 91.989276
iter  40 value 87.702490
iter  50 value 87.179830
iter  60 value 87.035871
iter  70 value 85.280121
iter  80 value 84.231621
iter  90 value 83.455673
iter 100 value 82.838403
final  value 82.838403 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.995904 
iter  10 value 95.364375
iter  20 value 89.379385
iter  30 value 84.001198
iter  40 value 83.271832
iter  50 value 82.214673
iter  60 value 80.772218
iter  70 value 80.107406
iter  80 value 79.620268
iter  90 value 79.267750
iter 100 value 79.076343
final  value 79.076343 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.176006 
iter  10 value 94.499350
iter  20 value 88.417314
iter  30 value 84.529172
iter  40 value 79.968844
iter  50 value 79.579877
iter  60 value 79.356123
iter  70 value 78.929972
iter  80 value 78.733383
iter  90 value 78.692889
iter 100 value 78.614547
final  value 78.614547 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.203368 
iter  10 value 97.576825
iter  20 value 92.229551
iter  30 value 89.802590
iter  40 value 85.301428
iter  50 value 83.276470
iter  60 value 82.852239
iter  70 value 81.051593
iter  80 value 79.684617
iter  90 value 78.764302
iter 100 value 78.464473
final  value 78.464473 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 117.145441 
iter  10 value 94.430041
iter  20 value 86.132178
iter  30 value 83.171419
iter  40 value 82.433814
iter  50 value 82.260117
iter  60 value 81.589829
iter  70 value 80.672005
iter  80 value 80.467102
iter  90 value 79.856518
iter 100 value 79.128015
final  value 79.128015 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.898298 
iter  10 value 95.130377
iter  20 value 94.532850
iter  30 value 94.514113
iter  40 value 94.288539
iter  50 value 88.083362
iter  60 value 86.061467
iter  70 value 84.108565
iter  80 value 83.597680
iter  90 value 80.804890
iter 100 value 79.002611
final  value 79.002611 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 118.239093 
iter  10 value 94.585553
iter  20 value 94.455357
iter  30 value 89.007059
iter  40 value 87.734098
iter  50 value 87.369554
iter  60 value 84.944745
iter  70 value 82.639390
iter  80 value 82.197258
iter  90 value 80.251972
iter 100 value 79.352610
final  value 79.352610 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 123.183854 
iter  10 value 95.107158
iter  20 value 94.738613
iter  30 value 93.272373
iter  40 value 87.217892
iter  50 value 83.313661
iter  60 value 82.322953
iter  70 value 80.886836
iter  80 value 80.051636
iter  90 value 79.986602
iter 100 value 79.831623
final  value 79.831623 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.792590 
iter  10 value 94.499903
iter  20 value 94.469023
iter  30 value 94.467712
iter  40 value 93.184648
iter  50 value 93.156258
iter  60 value 89.279526
iter  70 value 83.596232
iter  80 value 83.086843
iter  90 value 83.070624
iter 100 value 83.043467
final  value 83.043467 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 95.478407 
final  value 94.485775 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.457796 
final  value 94.486963 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.255064 
final  value 94.486040 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.512224 
iter  10 value 94.486169
iter  20 value 94.484259
iter  30 value 94.317231
iter  40 value 89.355510
iter  50 value 89.320971
iter  60 value 84.130814
iter  70 value 84.128996
iter  80 value 84.127600
iter  90 value 84.127422
iter  90 value 84.127421
iter  90 value 84.127421
final  value 84.127421 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.595842 
iter  10 value 94.488862
iter  20 value 94.483368
iter  30 value 92.318715
iter  40 value 91.740278
iter  50 value 87.399752
iter  60 value 85.185323
iter  70 value 84.165104
iter  80 value 84.105230
iter  90 value 83.949461
iter 100 value 83.854934
final  value 83.854934 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.996381 
iter  10 value 92.645671
iter  20 value 92.643634
iter  30 value 92.597142
iter  40 value 91.855584
iter  50 value 91.131308
iter  60 value 90.871550
iter  70 value 90.834133
iter  80 value 90.833523
iter  90 value 90.790268
iter 100 value 90.732824
final  value 90.732824 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.662649 
iter  10 value 94.489416
iter  20 value 94.452924
iter  30 value 82.121169
iter  40 value 82.085009
iter  50 value 81.681700
iter  60 value 81.663295
iter  70 value 81.659417
final  value 81.659415 
converged
Fitting Repeat 4 

# weights:  305
initial  value 111.200734 
iter  10 value 94.489443
iter  20 value 94.440609
iter  30 value 82.196621
iter  40 value 81.590462
iter  50 value 80.773781
iter  60 value 78.686846
iter  70 value 78.643008
iter  80 value 78.640663
iter  90 value 78.640579
final  value 78.640528 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.718009 
iter  10 value 94.489131
iter  20 value 94.484322
iter  30 value 88.772829
iter  40 value 81.704757
iter  50 value 81.684044
final  value 81.683966 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.871789 
iter  10 value 94.490938
iter  20 value 94.468171
iter  30 value 87.760072
iter  40 value 87.724684
iter  50 value 81.200284
iter  60 value 80.867953
iter  70 value 80.863881
iter  80 value 80.863676
iter  90 value 80.863042
iter 100 value 80.706385
final  value 80.706385 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 131.274206 
iter  10 value 94.475575
iter  20 value 94.469608
iter  30 value 90.767819
iter  40 value 84.635476
iter  50 value 83.141973
iter  60 value 82.853154
iter  70 value 82.614686
iter  80 value 81.737263
iter  90 value 80.672225
iter 100 value 80.656530
final  value 80.656530 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 119.323220 
iter  10 value 94.097128
iter  20 value 94.089791
final  value 94.089453 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.317290 
iter  10 value 87.070420
iter  20 value 86.690631
iter  30 value 86.020911
iter  40 value 85.940859
iter  50 value 85.940265
iter  60 value 85.937168
iter  70 value 85.934438
iter  80 value 85.829854
iter  90 value 84.261492
iter 100 value 83.264657
final  value 83.264657 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 96.241505 
iter  10 value 94.491834
iter  20 value 94.475034
iter  30 value 93.771271
iter  40 value 89.380489
iter  50 value 85.854546
iter  60 value 84.706752
iter  70 value 84.456690
iter  80 value 82.995961
iter  90 value 82.508602
iter 100 value 82.319565
final  value 82.319565 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 145.300260 
iter  10 value 117.768008
iter  20 value 117.737743
iter  30 value 117.730815
final  value 117.729130 
converged
Fitting Repeat 2 

# weights:  507
initial  value 147.596449 
iter  10 value 117.898101
iter  20 value 117.864448
iter  30 value 117.521349
final  value 117.512166 
converged
Fitting Repeat 3 

# weights:  507
initial  value 146.545928 
iter  10 value 117.898873
iter  20 value 117.758369
iter  30 value 108.574215
iter  40 value 108.529877
iter  50 value 105.126492
iter  60 value 104.830892
iter  70 value 104.812269
iter  80 value 104.811850
iter  80 value 104.811850
iter  80 value 104.811850
final  value 104.811850 
converged
Fitting Repeat 4 

# weights:  507
initial  value 128.281412 
iter  10 value 117.898949
iter  20 value 117.510448
iter  30 value 112.517808
iter  40 value 109.724499
iter  50 value 109.125275
iter  60 value 108.832932
iter  70 value 108.814867
iter  80 value 107.896603
iter  90 value 106.955162
iter 100 value 105.075376
final  value 105.075376 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 147.722761 
iter  10 value 117.766662
iter  20 value 117.762124
iter  30 value 117.759764
final  value 117.207076 
converged
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 -- Sun May 19 16:17:04 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 
 47.979   1.234  52.040