##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.19-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.19-bioc/R/site-library --timings HPiP_1.10.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck’
* using R version 4.4.0 (2024-04-24)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
    GNU Fortran (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
* running under: Ubuntu 22.04.4 LTS
* using session charset: UTF-8
* 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 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 loading without being on the library search path ... 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       37.031  1.032  38.065
FSmethod      35.325  0.587  35.914
corr_plot     35.212  0.315  35.531
pred_ensembel 13.679  0.385  10.785
enrichfindP    0.538  0.020   9.280
* 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 re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE

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

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.19-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.19-bioc/R/site-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) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

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 97.750180 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.892827 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.344494 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.143385 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.391749 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.345953 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.724959 
iter  10 value 93.870291
iter  20 value 93.469443
iter  30 value 93.324058
iter  40 value 93.322894
iter  40 value 93.322893
iter  40 value 93.322893
final  value 93.322893 
converged
Fitting Repeat 3 

# weights:  305
initial  value 121.664983 
final  value 93.582418 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.523816 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.719064 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.094752 
final  value 93.582418 
converged
Fitting Repeat 2 

# weights:  507
initial  value 94.998140 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 116.136230 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.815526 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.941288 
iter  10 value 93.276344
iter  20 value 93.193062
iter  20 value 93.193062
iter  20 value 93.193062
final  value 93.193062 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.704268 
iter  10 value 94.077283
iter  20 value 94.054900
iter  30 value 92.787561
iter  40 value 86.840936
iter  50 value 86.490940
iter  60 value 84.923420
iter  70 value 84.376927
iter  80 value 84.221889
iter  90 value 84.046403
iter 100 value 83.953735
final  value 83.953735 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 105.903391 
iter  10 value 94.056898
iter  20 value 94.003434
iter  30 value 93.687996
iter  40 value 93.683831
iter  50 value 93.598857
iter  60 value 90.308152
iter  70 value 86.473190
iter  80 value 84.414025
iter  90 value 84.312186
iter 100 value 84.228233
final  value 84.228233 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.633985 
iter  10 value 94.067162
iter  20 value 94.045447
iter  30 value 93.775255
iter  40 value 93.773073
iter  50 value 93.715273
iter  60 value 87.903156
iter  70 value 86.647954
iter  80 value 86.252581
iter  90 value 85.302348
iter 100 value 83.912335
final  value 83.912335 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 98.162342 
iter  10 value 93.802488
iter  20 value 89.719998
iter  30 value 87.663838
iter  40 value 86.144260
iter  50 value 86.026110
iter  60 value 85.044145
iter  70 value 84.769523
iter  80 value 84.618556
iter  90 value 84.420122
iter 100 value 84.393631
final  value 84.393631 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 102.675597 
iter  10 value 94.052586
iter  20 value 93.965278
iter  30 value 93.881756
iter  40 value 93.770684
iter  50 value 92.883030
iter  60 value 87.399951
iter  70 value 86.396441
iter  80 value 86.232747
iter  90 value 85.350023
iter 100 value 83.409627
final  value 83.409627 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 121.378573 
iter  10 value 94.429475
iter  20 value 94.059536
iter  30 value 93.787118
iter  40 value 92.823595
iter  50 value 87.818809
iter  60 value 86.596644
iter  70 value 85.995894
iter  80 value 83.505874
iter  90 value 82.177954
iter 100 value 81.982136
final  value 81.982136 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.225097 
iter  10 value 87.762740
iter  20 value 84.952660
iter  30 value 84.367471
iter  40 value 83.648558
iter  50 value 83.455862
iter  60 value 82.147451
iter  70 value 80.924675
iter  80 value 80.401756
iter  90 value 80.325833
iter 100 value 80.067007
final  value 80.067007 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 117.767019 
iter  10 value 95.534971
iter  20 value 93.444237
iter  30 value 92.572965
iter  40 value 89.256023
iter  50 value 84.769577
iter  60 value 84.175193
iter  70 value 83.134541
iter  80 value 82.687487
iter  90 value 82.019316
iter 100 value 81.335431
final  value 81.335431 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.819353 
iter  10 value 94.066350
iter  20 value 91.256018
iter  30 value 86.118547
iter  40 value 84.423570
iter  50 value 83.136749
iter  60 value 82.859977
iter  70 value 82.424391
iter  80 value 81.981679
iter  90 value 81.203895
iter 100 value 80.763695
final  value 80.763695 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 126.889361 
iter  10 value 96.108106
iter  20 value 93.835939
iter  30 value 88.917387
iter  40 value 83.168769
iter  50 value 82.580909
iter  60 value 82.153982
iter  70 value 81.474397
iter  80 value 80.805390
iter  90 value 80.639735
iter 100 value 80.628752
final  value 80.628752 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 122.626463 
iter  10 value 94.640330
iter  20 value 93.835157
iter  30 value 92.043648
iter  40 value 85.903914
iter  50 value 84.185847
iter  60 value 83.329478
iter  70 value 81.466011
iter  80 value 80.470555
iter  90 value 80.000889
iter 100 value 79.931317
final  value 79.931317 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.274717 
iter  10 value 95.259393
iter  20 value 94.697680
iter  30 value 94.243366
iter  40 value 89.386244
iter  50 value 88.165336
iter  60 value 86.849686
iter  70 value 86.276718
iter  80 value 86.118390
iter  90 value 85.656196
iter 100 value 85.048610
final  value 85.048610 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.692960 
iter  10 value 94.059331
iter  20 value 93.430054
iter  30 value 87.551063
iter  40 value 83.571533
iter  50 value 82.012379
iter  60 value 81.273197
iter  70 value 80.520749
iter  80 value 80.375387
iter  90 value 80.196385
iter 100 value 80.146405
final  value 80.146405 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.204635 
iter  10 value 94.154097
iter  20 value 90.929543
iter  30 value 87.912890
iter  40 value 82.603768
iter  50 value 81.264585
iter  60 value 80.867173
iter  70 value 80.707303
iter  80 value 80.424229
iter  90 value 80.226543
iter 100 value 80.181862
final  value 80.181862 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 123.390036 
iter  10 value 98.318661
iter  20 value 87.942813
iter  30 value 85.725062
iter  40 value 84.122388
iter  50 value 83.257632
iter  60 value 83.026433
iter  70 value 82.975792
iter  80 value 81.929172
iter  90 value 81.103553
iter 100 value 80.291126
final  value 80.291126 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.824311 
iter  10 value 94.054906
iter  20 value 93.895680
final  value 93.582756 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.099950 
iter  10 value 94.054695
iter  20 value 94.043709
iter  30 value 89.255465
iter  40 value 84.989471
iter  50 value 84.853070
iter  60 value 84.784446
iter  70 value 84.776158
iter  80 value 84.764810
iter  90 value 84.763312
iter 100 value 84.762373
final  value 84.762373 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 95.773147 
final  value 93.630139 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.661212 
final  value 94.054700 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.587473 
final  value 94.054536 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.841279 
iter  10 value 94.057219
iter  20 value 93.605416
final  value 93.582705 
converged
Fitting Repeat 2 

# weights:  305
initial  value 119.769922 
iter  10 value 94.058851
iter  20 value 94.046373
iter  30 value 93.605658
iter  40 value 91.459314
iter  50 value 84.235915
iter  60 value 83.327361
iter  70 value 83.318009
iter  80 value 83.317290
iter  90 value 83.316325
final  value 83.316324 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.850043 
iter  10 value 93.587672
iter  20 value 93.583830
iter  30 value 93.469006
iter  40 value 87.841184
final  value 87.763408 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.560374 
iter  10 value 93.633367
iter  20 value 87.457565
iter  30 value 87.398151
iter  40 value 87.151890
iter  50 value 87.079387
final  value 87.079308 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.177803 
iter  10 value 94.057782
iter  20 value 94.038406
iter  30 value 93.585255
iter  40 value 93.583657
iter  50 value 93.575566
iter  60 value 87.960680
iter  70 value 85.858288
iter  80 value 85.851629
iter  90 value 85.600163
iter 100 value 85.474589
final  value 85.474589 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 114.257278 
iter  10 value 92.343209
iter  20 value 91.557459
iter  30 value 91.556950
iter  40 value 91.531174
iter  50 value 91.443212
iter  60 value 91.356561
iter  70 value 91.353905
iter  80 value 91.348817
iter  90 value 89.486746
iter 100 value 82.940992
final  value 82.940992 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 99.134003 
iter  10 value 93.337935
iter  20 value 93.337234
iter  30 value 93.329591
iter  40 value 93.326182
iter  50 value 92.330791
iter  60 value 92.221798
iter  70 value 92.221036
iter  70 value 92.221035
final  value 92.221032 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.489330 
iter  10 value 93.634664
iter  20 value 93.590428
iter  30 value 93.565462
iter  40 value 89.608361
iter  50 value 88.902571
iter  60 value 88.901472
iter  70 value 88.900437
iter  80 value 87.094434
iter  90 value 87.025360
iter 100 value 86.973410
final  value 86.973410 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 100.632249 
iter  10 value 93.590882
iter  20 value 93.582944
iter  30 value 93.579305
final  value 93.579251 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.281769 
iter  10 value 93.590875
iter  20 value 93.532621
iter  30 value 87.201652
iter  40 value 86.637016
iter  50 value 86.620863
iter  60 value 86.618233
iter  70 value 86.616846
iter  80 value 86.396505
iter  90 value 86.317410
iter 100 value 86.143466
final  value 86.143466 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.834454 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.461766 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.527649 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.200100 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.983955 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 111.191523 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 108.213026 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 124.675253 
iter  10 value 94.484210
iter  10 value 94.484210
iter  10 value 94.484210
final  value 94.484210 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.921891 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.444843 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.993925 
iter  10 value 93.001892
iter  20 value 92.991351
final  value 92.991335 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.998623 
iter  10 value 91.737421
iter  20 value 87.890368
iter  30 value 86.314749
final  value 86.312634 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.171098 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.072569 
iter  10 value 91.867555
iter  20 value 85.125225
iter  30 value 84.878839
final  value 84.877158 
converged
Fitting Repeat 5 

# weights:  507
initial  value 120.449659 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.415528 
iter  10 value 93.728730
iter  20 value 88.242493
iter  30 value 86.946278
iter  40 value 85.747052
iter  50 value 85.568089
iter  60 value 85.542489
final  value 85.533591 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.085032 
iter  10 value 94.400308
iter  20 value 90.340468
iter  30 value 87.221874
iter  40 value 85.843954
iter  50 value 84.955935
iter  60 value 84.419628
iter  70 value 84.164224
final  value 84.163888 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.665232 
iter  10 value 94.451904
iter  20 value 94.272996
iter  30 value 94.233593
iter  40 value 88.508588
iter  50 value 87.299096
iter  60 value 86.827461
iter  70 value 86.407409
iter  80 value 85.852928
iter  90 value 85.813037
final  value 85.813030 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.455759 
iter  10 value 94.480138
iter  20 value 91.523056
iter  30 value 87.599822
iter  40 value 86.021740
iter  50 value 85.819263
final  value 85.813030 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.064030 
iter  10 value 94.440932
iter  20 value 90.842096
iter  30 value 90.044642
iter  40 value 88.494185
iter  50 value 87.027509
iter  60 value 86.901229
iter  70 value 86.691314
iter  80 value 86.448811
final  value 86.448741 
converged
Fitting Repeat 1 

# weights:  305
initial  value 123.851119 
iter  10 value 95.515500
iter  20 value 92.697753
iter  30 value 88.179932
iter  40 value 86.820171
iter  50 value 84.940509
iter  60 value 84.102550
iter  70 value 83.359220
iter  80 value 83.207912
iter  90 value 83.150951
iter 100 value 83.125450
final  value 83.125450 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.187643 
iter  10 value 94.483235
iter  20 value 89.270230
iter  30 value 88.771080
iter  40 value 88.464916
iter  50 value 87.277232
iter  60 value 86.751445
iter  70 value 86.336312
iter  80 value 84.273064
iter  90 value 84.042191
iter 100 value 83.025358
final  value 83.025358 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.703259 
iter  10 value 94.495805
iter  20 value 93.894345
iter  30 value 92.964406
iter  40 value 91.189443
iter  50 value 88.869796
iter  60 value 84.569405
iter  70 value 84.471259
iter  80 value 83.783560
iter  90 value 83.226962
iter 100 value 83.019283
final  value 83.019283 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.378458 
iter  10 value 94.516735
iter  20 value 94.129803
iter  30 value 92.691748
iter  40 value 89.814670
iter  50 value 85.476734
iter  60 value 83.619235
iter  70 value 83.054649
iter  80 value 82.877815
iter  90 value 82.692745
iter 100 value 82.656717
final  value 82.656717 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.313181 
iter  10 value 94.593660
iter  20 value 93.477500
iter  30 value 90.457184
iter  40 value 87.273074
iter  50 value 85.595523
iter  60 value 85.288963
iter  70 value 85.036627
iter  80 value 85.007550
iter  90 value 84.860347
iter 100 value 84.333579
final  value 84.333579 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 119.692478 
iter  10 value 94.592687
iter  20 value 90.143741
iter  30 value 86.582045
iter  40 value 86.310268
iter  50 value 85.543129
iter  60 value 85.429304
iter  70 value 85.282404
iter  80 value 84.310960
iter  90 value 83.414773
iter 100 value 83.235699
final  value 83.235699 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.551592 
iter  10 value 93.106684
iter  20 value 92.516676
iter  30 value 90.655642
iter  40 value 89.511475
iter  50 value 84.219786
iter  60 value 83.354375
iter  70 value 82.764981
iter  80 value 82.529306
iter  90 value 82.306795
iter 100 value 82.276449
final  value 82.276449 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 122.185781 
iter  10 value 98.316597
iter  20 value 96.998695
iter  30 value 93.280233
iter  40 value 90.174735
iter  50 value 87.067732
iter  60 value 86.526952
iter  70 value 86.041828
iter  80 value 85.677794
iter  90 value 85.073223
iter 100 value 83.723913
final  value 83.723913 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 117.408742 
iter  10 value 94.492295
iter  20 value 92.247574
iter  30 value 91.018685
iter  40 value 87.199948
iter  50 value 85.582159
iter  60 value 85.512635
iter  70 value 85.407111
iter  80 value 84.403311
iter  90 value 83.737381
iter 100 value 83.296856
final  value 83.296856 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.976137 
iter  10 value 96.565221
iter  20 value 96.099498
iter  30 value 92.266594
iter  40 value 87.237058
iter  50 value 86.195742
iter  60 value 85.467127
iter  70 value 84.903561
iter  80 value 84.620270
iter  90 value 84.232772
iter 100 value 83.419230
final  value 83.419230 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 112.502512 
final  value 94.468181 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.132377 
final  value 94.486002 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.561614 
iter  10 value 94.485683
iter  20 value 92.724846
iter  30 value 87.545280
iter  40 value 87.544635
iter  50 value 87.462009
iter  60 value 87.213219
iter  70 value 87.213025
iter  70 value 87.213024
iter  70 value 87.213024
final  value 87.213024 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.864171 
final  value 94.468281 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.372959 
iter  10 value 94.321725
iter  20 value 94.229142
iter  30 value 89.041534
iter  40 value 86.508863
iter  50 value 85.918444
iter  60 value 85.849292
iter  70 value 85.849030
iter  80 value 85.424393
iter  90 value 85.099416
final  value 85.087146 
converged
Fitting Repeat 1 

# weights:  305
initial  value 114.883577 
iter  10 value 94.471368
iter  20 value 94.376803
iter  30 value 87.624904
iter  40 value 86.148338
iter  50 value 86.147801
iter  60 value 85.686187
final  value 85.395579 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.088106 
iter  10 value 94.489064
iter  20 value 92.673872
iter  30 value 88.393168
iter  40 value 88.084838
iter  50 value 88.034836
iter  60 value 85.816351
iter  70 value 85.011731
iter  80 value 85.002593
iter  90 value 85.002082
final  value 85.001647 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.362141 
iter  10 value 94.471485
iter  20 value 94.303501
iter  30 value 88.510769
iter  40 value 87.471354
final  value 87.033264 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.609336 
iter  10 value 92.611859
iter  20 value 84.889813
iter  30 value 84.880172
iter  40 value 84.778176
iter  50 value 84.746173
final  value 84.746150 
converged
Fitting Repeat 5 

# weights:  305
initial  value 111.465205 
iter  10 value 94.488483
iter  20 value 94.476560
iter  30 value 87.399247
iter  40 value 86.464727
iter  50 value 86.265162
iter  60 value 86.124485
iter  70 value 86.120912
iter  80 value 86.097651
iter  90 value 86.090208
iter 100 value 85.391206
final  value 85.391206 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.870371 
iter  10 value 94.492247
iter  20 value 94.454513
iter  30 value 87.209474
iter  40 value 87.159808
iter  50 value 87.159085
iter  60 value 87.156590
iter  70 value 86.784547
final  value 86.729180 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.922677 
iter  10 value 94.474695
iter  20 value 93.923973
iter  30 value 87.513559
iter  40 value 87.513279
iter  50 value 86.007710
iter  60 value 86.006778
iter  70 value 85.702321
iter  80 value 83.927559
iter  90 value 83.030752
iter 100 value 82.578815
final  value 82.578815 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 121.237006 
iter  10 value 94.474990
iter  20 value 94.315619
final  value 94.313455 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.725741 
iter  10 value 90.679645
iter  20 value 88.420329
iter  30 value 88.309404
iter  40 value 87.576877
iter  50 value 86.770738
iter  60 value 86.259601
iter  70 value 85.073110
iter  80 value 85.068053
final  value 85.067120 
converged
Fitting Repeat 5 

# weights:  507
initial  value 139.753668 
iter  10 value 94.492931
iter  20 value 94.413683
iter  30 value 93.000756
iter  40 value 92.157635
iter  50 value 92.157188
final  value 92.156848 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.248039 
iter  10 value 94.484212
iter  10 value 94.484211
iter  10 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.910627 
final  value 94.165117 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.008604 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.829194 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.455480 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.263101 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.303294 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.514554 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 111.311291 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.093136 
final  value 94.165116 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.309312 
iter  10 value 94.286492
iter  20 value 93.721415
iter  30 value 93.369511
iter  40 value 85.520844
iter  50 value 82.992218
iter  60 value 82.617806
iter  70 value 82.509755
iter  80 value 82.506876
final  value 82.506856 
converged
Fitting Repeat 2 

# weights:  507
initial  value 113.037401 
iter  10 value 93.860656
final  value 92.376405 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.875252 
iter  10 value 84.025224
iter  20 value 81.674869
iter  30 value 80.150541
iter  40 value 79.912187
iter  50 value 79.715592
iter  60 value 79.644492
iter  70 value 79.442439
iter  80 value 79.430922
iter  90 value 79.429954
iter 100 value 79.429860
final  value 79.429860 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 100.727267 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.182133 
final  value 94.275362 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.859563 
iter  10 value 94.488577
final  value 94.488559 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.758736 
iter  10 value 94.079835
iter  20 value 89.587798
iter  30 value 89.278502
iter  40 value 88.585090
iter  50 value 88.556502
final  value 88.556487 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.164136 
iter  10 value 94.488789
iter  20 value 94.329712
iter  30 value 94.329185
iter  40 value 94.210003
iter  50 value 93.696995
iter  60 value 90.096367
iter  70 value 89.562595
iter  80 value 88.882351
iter  90 value 88.801302
final  value 88.801280 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.988477 
iter  10 value 91.892490
iter  20 value 89.810468
iter  30 value 89.699621
iter  40 value 88.803737
iter  50 value 88.801488
final  value 88.801270 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.351950 
iter  10 value 94.016166
iter  20 value 83.478780
iter  30 value 81.220280
iter  40 value 80.836079
iter  50 value 79.810623
iter  60 value 79.542757
iter  70 value 79.428608
iter  80 value 79.304886
iter  90 value 79.196320
final  value 79.184095 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.849246 
iter  10 value 94.114869
iter  20 value 82.230670
iter  30 value 81.540424
iter  40 value 79.762450
iter  50 value 78.792648
iter  60 value 78.603173
iter  70 value 78.264160
iter  80 value 78.010658
iter  90 value 77.867441
iter 100 value 77.812132
final  value 77.812132 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.562244 
iter  10 value 94.336813
iter  20 value 85.294587
iter  30 value 82.249829
iter  40 value 80.343786
iter  50 value 79.809758
iter  60 value 79.466246
iter  70 value 79.149568
iter  80 value 78.124074
iter  90 value 77.842133
iter 100 value 77.695456
final  value 77.695456 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 112.662163 
iter  10 value 93.283624
iter  20 value 91.386640
iter  30 value 89.323745
iter  40 value 82.787821
iter  50 value 80.616569
iter  60 value 79.742216
iter  70 value 79.129859
iter  80 value 78.181759
iter  90 value 78.088119
iter 100 value 78.067543
final  value 78.067543 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 116.232525 
iter  10 value 98.730524
iter  20 value 87.986767
iter  30 value 87.094891
iter  40 value 86.537015
iter  50 value 83.787724
iter  60 value 80.025349
iter  70 value 78.726560
iter  80 value 78.420255
iter  90 value 78.168768
iter 100 value 78.087111
final  value 78.087111 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.904755 
iter  10 value 94.598437
iter  20 value 94.155871
iter  30 value 89.602599
iter  40 value 86.639186
iter  50 value 84.418595
iter  60 value 80.762625
iter  70 value 80.509815
iter  80 value 80.461264
iter  90 value 80.178526
iter 100 value 79.479941
final  value 79.479941 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 119.069914 
iter  10 value 94.208132
iter  20 value 88.421003
iter  30 value 81.950530
iter  40 value 80.692291
iter  50 value 80.574670
iter  60 value 80.224986
iter  70 value 79.956652
iter  80 value 79.796848
iter  90 value 79.744359
iter 100 value 79.457572
final  value 79.457572 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 121.660758 
iter  10 value 94.052871
iter  20 value 88.680953
iter  30 value 83.743318
iter  40 value 81.141307
iter  50 value 79.666649
iter  60 value 79.168478
iter  70 value 79.048230
iter  80 value 78.814065
iter  90 value 78.009611
iter 100 value 77.675135
final  value 77.675135 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.283906 
iter  10 value 94.406766
iter  20 value 90.311306
iter  30 value 87.819445
iter  40 value 80.026355
iter  50 value 79.326867
iter  60 value 78.806152
iter  70 value 78.663592
iter  80 value 78.499095
iter  90 value 78.379073
iter 100 value 78.281814
final  value 78.281814 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 122.623510 
iter  10 value 95.700245
iter  20 value 94.707880
iter  30 value 93.136754
iter  40 value 83.972266
iter  50 value 82.470859
iter  60 value 82.036053
iter  70 value 81.213991
iter  80 value 80.184577
iter  90 value 78.912137
iter 100 value 78.579427
final  value 78.579427 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.657892 
iter  10 value 96.311809
iter  20 value 94.274962
iter  30 value 92.511559
iter  40 value 83.483337
iter  50 value 81.548979
iter  60 value 79.581152
iter  70 value 78.483340
iter  80 value 78.362894
iter  90 value 78.202875
iter 100 value 78.141218
final  value 78.141218 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.292505 
final  value 94.485908 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.294969 
final  value 94.485927 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.491933 
iter  10 value 94.485833
iter  20 value 94.484203
iter  30 value 93.786379
iter  40 value 91.501590
iter  50 value 89.436124
iter  60 value 89.434467
iter  70 value 87.335578
iter  80 value 87.334409
final  value 87.334170 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.616307 
final  value 94.485859 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.410998 
final  value 94.485455 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.865029 
iter  10 value 94.488494
iter  20 value 94.332557
iter  30 value 80.880607
iter  40 value 80.678099
iter  50 value 80.677368
iter  60 value 80.675327
iter  70 value 80.672598
iter  80 value 80.667833
iter  90 value 80.027351
final  value 80.010955 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.418829 
iter  10 value 94.171163
iter  20 value 94.145641
iter  30 value 94.094260
final  value 94.094182 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.800114 
iter  10 value 94.488183
iter  20 value 94.460057
iter  30 value 83.583155
iter  40 value 83.537585
iter  50 value 83.531039
iter  60 value 82.772874
iter  70 value 82.723416
iter  80 value 82.722434
final  value 82.722375 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.377366 
iter  10 value 94.488652
iter  20 value 94.410951
final  value 94.275606 
converged
Fitting Repeat 5 

# weights:  305
initial  value 109.502724 
iter  10 value 94.485690
iter  20 value 94.177824
iter  30 value 90.058741
iter  40 value 89.688209
iter  50 value 89.666906
iter  60 value 88.039764
iter  70 value 87.336470
iter  80 value 86.180561
iter  90 value 80.892664
iter 100 value 80.467044
final  value 80.467044 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 102.713797 
iter  10 value 91.211785
iter  20 value 91.184703
iter  30 value 89.999126
iter  40 value 89.985055
iter  50 value 89.888950
iter  60 value 85.268718
iter  70 value 79.596050
iter  80 value 79.579112
iter  90 value 78.219435
iter 100 value 78.187826
final  value 78.187826 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 95.719033 
iter  10 value 94.486238
iter  20 value 93.974330
iter  30 value 89.795015
iter  40 value 89.792996
iter  50 value 89.792759
iter  60 value 89.791994
iter  70 value 89.791505
iter  80 value 89.528448
iter  90 value 88.592261
iter 100 value 88.591918
final  value 88.591918 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.077830 
iter  10 value 94.493363
iter  20 value 94.469726
iter  30 value 89.540251
iter  40 value 87.349212
iter  50 value 87.334658
final  value 87.334632 
converged
Fitting Repeat 4 

# weights:  507
initial  value 122.169568 
iter  10 value 94.492628
iter  20 value 94.422213
iter  30 value 90.542461
iter  40 value 88.865258
iter  50 value 88.684798
final  value 88.684792 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.596688 
iter  10 value 94.274478
iter  20 value 94.241181
iter  30 value 94.101667
iter  40 value 94.094447
iter  50 value 94.094194
final  value 94.094192 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.786783 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.841275 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.775447 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.240174 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.763107 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 118.153238 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.772583 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.741804 
iter  10 value 94.006931
iter  20 value 93.975536
final  value 93.963025 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.634479 
iter  10 value 93.963025
iter  10 value 93.963025
iter  10 value 93.963025
final  value 93.963025 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.891355 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.718608 
final  value 93.969040 
converged
Fitting Repeat 2 

# weights:  507
initial  value 111.578584 
iter  10 value 91.988505
iter  20 value 90.874960
final  value 90.874747 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.544382 
final  value 94.008696 
converged
Fitting Repeat 4 

# weights:  507
initial  value 110.957627 
iter  10 value 94.008697
iter  10 value 94.008696
iter  10 value 94.008696
final  value 94.008696 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.236226 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.236753 
iter  10 value 94.040549
iter  20 value 90.339506
iter  30 value 85.446727
iter  40 value 84.438599
iter  50 value 83.322885
iter  60 value 83.175048
iter  70 value 82.367890
iter  80 value 82.240573
iter  90 value 82.031395
final  value 82.031165 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.738405 
iter  10 value 94.119298
iter  20 value 94.056180
iter  30 value 93.747403
iter  40 value 87.963373
iter  50 value 85.721618
iter  60 value 85.607406
iter  70 value 85.591082
iter  80 value 85.589764
final  value 85.589673 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.409236 
iter  10 value 94.036749
iter  20 value 89.063634
iter  30 value 88.406540
iter  40 value 85.870585
iter  50 value 84.894765
iter  60 value 84.531116
iter  70 value 84.369502
final  value 84.369359 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.914350 
iter  10 value 93.574860
iter  20 value 91.520574
iter  30 value 86.057517
iter  40 value 85.576821
iter  50 value 85.091457
iter  60 value 85.075016
final  value 85.068155 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.361425 
iter  10 value 94.054892
iter  20 value 93.763465
iter  30 value 93.325175
iter  40 value 92.493516
iter  50 value 84.335605
iter  60 value 83.547448
iter  70 value 83.161106
iter  80 value 83.014436
iter  90 value 82.862116
iter 100 value 82.642266
final  value 82.642266 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 99.575589 
iter  10 value 94.140548
iter  20 value 93.987370
iter  30 value 93.036954
iter  40 value 85.885526
iter  50 value 85.569536
iter  60 value 85.376251
iter  70 value 85.280790
iter  80 value 84.024263
iter  90 value 82.669490
iter 100 value 81.733078
final  value 81.733078 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.280045 
iter  10 value 94.023203
iter  20 value 92.703163
iter  30 value 91.992696
iter  40 value 90.004987
iter  50 value 85.533656
iter  60 value 85.237236
iter  70 value 85.101690
iter  80 value 84.206530
iter  90 value 82.978103
iter 100 value 82.354854
final  value 82.354854 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.260640 
iter  10 value 93.974831
iter  20 value 86.054292
iter  30 value 85.768130
iter  40 value 83.601160
iter  50 value 82.649760
iter  60 value 82.391055
iter  70 value 82.249133
iter  80 value 82.191423
iter  90 value 82.189926
iter 100 value 82.185458
final  value 82.185458 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.787351 
iter  10 value 93.689974
iter  20 value 85.906634
iter  30 value 85.484897
iter  40 value 84.820410
iter  50 value 83.190874
iter  60 value 82.828134
iter  70 value 82.608868
iter  80 value 82.407647
iter  90 value 82.298802
iter 100 value 82.222897
final  value 82.222897 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 122.184584 
iter  10 value 94.061783
iter  20 value 91.238527
iter  30 value 89.513116
iter  40 value 87.426381
iter  50 value 86.773266
iter  60 value 86.057159
iter  70 value 84.645317
iter  80 value 84.259040
iter  90 value 83.970888
iter 100 value 83.061868
final  value 83.061868 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 111.137798 
iter  10 value 95.240272
iter  20 value 93.861954
iter  30 value 87.736135
iter  40 value 87.064305
iter  50 value 85.900970
iter  60 value 84.888901
iter  70 value 84.204950
iter  80 value 82.512564
iter  90 value 81.105859
iter 100 value 80.784302
final  value 80.784302 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.269691 
iter  10 value 94.178882
iter  20 value 91.113284
iter  30 value 88.188369
iter  40 value 85.488793
iter  50 value 85.369906
iter  60 value 85.235185
iter  70 value 84.996785
iter  80 value 82.670102
iter  90 value 82.173337
iter 100 value 81.788546
final  value 81.788546 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.835703 
iter  10 value 94.738702
iter  20 value 91.117309
iter  30 value 89.078748
iter  40 value 87.557662
iter  50 value 87.071775
iter  60 value 86.880152
iter  70 value 84.357606
iter  80 value 83.240319
iter  90 value 82.587326
iter 100 value 82.263310
final  value 82.263310 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.934406 
iter  10 value 93.953421
iter  20 value 86.341792
iter  30 value 84.970076
iter  40 value 82.929406
iter  50 value 82.287965
iter  60 value 81.994947
iter  70 value 81.005643
iter  80 value 80.857579
iter  90 value 80.740325
iter 100 value 80.679233
final  value 80.679233 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 115.983863 
iter  10 value 94.052633
iter  20 value 92.469261
iter  30 value 87.054278
iter  40 value 85.754116
iter  50 value 85.072995
iter  60 value 84.636967
iter  70 value 83.810461
iter  80 value 82.033760
iter  90 value 81.529625
iter 100 value 81.247058
final  value 81.247058 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.231041 
iter  10 value 93.672691
iter  20 value 93.665973
final  value 93.665212 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.312000 
final  value 94.054627 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.363381 
iter  10 value 93.724088
iter  20 value 93.666150
iter  30 value 93.664745
iter  40 value 93.501909
iter  50 value 92.156902
iter  60 value 84.804508
iter  70 value 83.504832
iter  80 value 83.489290
iter  90 value 83.474644
iter 100 value 83.474295
final  value 83.474295 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 102.655927 
final  value 94.054585 
converged
Fitting Repeat 5 

# weights:  103
initial  value 107.691767 
final  value 94.054498 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.005908 
iter  10 value 94.057287
iter  20 value 93.725195
iter  30 value 84.783377
iter  40 value 84.753473
final  value 84.753416 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.065242 
iter  10 value 94.057672
iter  20 value 94.052942
iter  20 value 94.052942
iter  20 value 94.052942
final  value 94.052942 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.864811 
iter  10 value 94.057963
iter  20 value 94.010664
iter  30 value 87.285124
iter  40 value 87.248520
final  value 87.248393 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.150439 
iter  10 value 89.491012
iter  20 value 87.253179
iter  30 value 87.247364
iter  40 value 85.883785
iter  50 value 84.255228
iter  60 value 84.250110
iter  70 value 84.236323
iter  80 value 84.233164
final  value 84.232701 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.433348 
iter  10 value 94.058390
iter  20 value 93.625691
iter  30 value 90.872478
iter  40 value 86.365426
iter  50 value 83.687239
iter  60 value 81.295285
iter  70 value 80.470495
iter  80 value 80.457625
iter  90 value 80.456648
iter 100 value 80.455804
final  value 80.455804 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 101.792141 
iter  10 value 93.972236
iter  20 value 93.970303
iter  30 value 93.322764
iter  40 value 87.949188
iter  50 value 87.873417
final  value 87.873131 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.741889 
iter  10 value 93.970708
iter  20 value 93.964982
iter  30 value 93.963213
iter  40 value 93.505665
final  value 93.496021 
converged
Fitting Repeat 3 

# weights:  507
initial  value 113.299470 
iter  10 value 92.489681
iter  20 value 87.633157
iter  30 value 87.627362
iter  40 value 84.785387
iter  50 value 84.756131
iter  60 value 84.753831
final  value 84.752962 
converged
Fitting Repeat 4 

# weights:  507
initial  value 116.602268 
iter  10 value 94.060927
iter  20 value 93.573007
iter  30 value 85.831603
iter  40 value 82.406232
iter  50 value 79.794964
iter  60 value 79.668533
iter  70 value 79.594540
iter  80 value 79.526656
iter  90 value 79.523863
iter 100 value 79.521457
final  value 79.521457 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.087572 
iter  10 value 94.061035
final  value 94.053849 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.234322 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.523432 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.572801 
iter  10 value 93.474561
final  value 93.472243 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.344879 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 110.853454 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.027527 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  305
initial  value 108.998546 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.548095 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  305
initial  value 110.655473 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.086545 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.118885 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.590890 
iter  10 value 94.333577
final  value 94.253430 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.905715 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  507
initial  value 114.605053 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.892200 
iter  10 value 94.275362
iter  10 value 94.275362
iter  10 value 94.275362
final  value 94.275362 
converged
Fitting Repeat 1 

# weights:  103
initial  value 121.416491 
iter  10 value 94.489198
iter  20 value 94.428083
iter  30 value 87.116145
iter  40 value 85.928828
iter  50 value 85.636126
iter  60 value 83.106893
iter  70 value 83.001725
iter  80 value 82.979693
iter  90 value 82.780334
iter 100 value 82.679420
final  value 82.679420 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 100.069730 
iter  10 value 94.509256
iter  20 value 94.477837
iter  30 value 94.341468
iter  40 value 94.326218
iter  50 value 94.317718
iter  60 value 92.185763
iter  70 value 86.242168
iter  80 value 85.458411
iter  90 value 84.594212
iter 100 value 84.334670
final  value 84.334670 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 100.275804 
iter  10 value 89.076997
iter  20 value 85.773693
iter  30 value 84.444618
iter  40 value 83.476040
iter  50 value 83.198481
iter  60 value 83.171479
final  value 83.168007 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.258103 
iter  10 value 94.486766
iter  20 value 92.514551
iter  30 value 85.022249
iter  40 value 83.940787
iter  50 value 83.675015
iter  60 value 83.493495
final  value 83.490836 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.229803 
iter  10 value 94.537626
iter  20 value 94.488797
iter  30 value 94.419838
iter  40 value 87.184420
iter  50 value 83.456251
iter  60 value 82.728457
iter  70 value 82.641070
iter  80 value 82.525198
iter  90 value 82.416900
iter 100 value 81.425031
final  value 81.425031 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 125.892088 
iter  10 value 94.606099
iter  20 value 84.390005
iter  30 value 83.401703
iter  40 value 81.592155
iter  50 value 80.442246
iter  60 value 79.910855
iter  70 value 79.118913
iter  80 value 79.048675
iter  90 value 78.978952
iter 100 value 78.920571
final  value 78.920571 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.796050 
iter  10 value 94.404019
iter  20 value 87.902060
iter  30 value 83.922843
iter  40 value 81.709168
iter  50 value 80.451310
iter  60 value 79.667278
iter  70 value 79.510018
iter  80 value 79.326356
iter  90 value 79.239436
iter 100 value 79.186933
final  value 79.186933 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.823247 
iter  10 value 94.487855
iter  20 value 89.542672
iter  30 value 83.127817
iter  40 value 82.662482
iter  50 value 82.492256
iter  60 value 82.402712
iter  70 value 82.348271
iter  80 value 82.304182
iter  90 value 82.150930
iter 100 value 81.768778
final  value 81.768778 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 116.307736 
iter  10 value 94.977757
iter  20 value 94.530434
iter  30 value 94.500749
iter  40 value 86.668698
iter  50 value 85.474128
iter  60 value 83.024869
iter  70 value 82.394540
iter  80 value 80.784395
iter  90 value 79.702007
iter 100 value 79.245739
final  value 79.245739 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 126.036849 
iter  10 value 95.568349
iter  20 value 94.939431
iter  30 value 86.864747
iter  40 value 85.855648
iter  50 value 84.813244
iter  60 value 82.787580
iter  70 value 82.441975
iter  80 value 82.354607
iter  90 value 82.194272
iter 100 value 81.154262
final  value 81.154262 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.462120 
iter  10 value 94.861207
iter  20 value 92.972202
iter  30 value 85.849700
iter  40 value 83.573122
iter  50 value 81.852287
iter  60 value 80.244937
iter  70 value 79.430593
iter  80 value 79.061271
iter  90 value 79.014894
iter 100 value 79.004283
final  value 79.004283 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.053760 
iter  10 value 94.751569
iter  20 value 87.655024
iter  30 value 85.001385
iter  40 value 82.540701
iter  50 value 81.758357
iter  60 value 79.607030
iter  70 value 79.079374
iter  80 value 78.842926
iter  90 value 78.453229
iter 100 value 78.321264
final  value 78.321264 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 120.716808 
iter  10 value 96.157317
iter  20 value 87.823955
iter  30 value 85.716222
iter  40 value 83.732382
iter  50 value 81.771404
iter  60 value 81.468061
iter  70 value 81.275114
iter  80 value 81.091866
iter  90 value 79.665244
iter 100 value 79.123038
final  value 79.123038 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.597573 
iter  10 value 94.315611
iter  20 value 89.745518
iter  30 value 82.819404
iter  40 value 81.013697
iter  50 value 80.452120
iter  60 value 79.497565
iter  70 value 79.328432
iter  80 value 79.286362
iter  90 value 78.984333
iter 100 value 78.829867
final  value 78.829867 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 140.358479 
iter  10 value 94.140799
iter  20 value 85.958879
iter  30 value 82.887608
iter  40 value 82.392379
iter  50 value 81.923833
iter  60 value 81.099671
iter  70 value 80.134120
iter  80 value 79.908181
iter  90 value 79.669050
iter 100 value 79.094215
final  value 79.094215 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 108.039842 
iter  10 value 94.324463
iter  20 value 91.366571
iter  30 value 85.038459
iter  40 value 84.822409
iter  50 value 84.813067
final  value 84.813059 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.536002 
final  value 94.485922 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.171984 
final  value 94.485849 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.083449 
iter  10 value 94.485943
iter  20 value 94.484214
iter  30 value 93.707928
iter  40 value 93.222845
iter  50 value 93.221080
final  value 93.218189 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.286158 
final  value 94.485788 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.501627 
iter  10 value 94.108075
iter  20 value 92.918674
iter  30 value 88.062639
iter  40 value 84.851214
iter  50 value 83.143148
iter  60 value 83.112035
iter  70 value 83.104478
iter  80 value 83.096072
iter  90 value 83.094783
iter 100 value 83.093600
final  value 83.093600 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.435815 
iter  10 value 94.489253
iter  20 value 94.484313
iter  30 value 94.340519
iter  40 value 82.734047
iter  50 value 81.301408
iter  60 value 79.339635
iter  70 value 78.423184
iter  80 value 78.200686
iter  90 value 78.117402
iter 100 value 77.982952
final  value 77.982952 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.609368 
iter  10 value 94.488627
iter  20 value 94.484184
iter  30 value 93.564410
iter  40 value 92.241010
iter  50 value 92.212806
iter  60 value 91.862753
iter  70 value 91.855985
iter  80 value 91.828877
iter  90 value 91.820850
final  value 91.820821 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.920289 
iter  10 value 94.489226
iter  20 value 94.484540
iter  30 value 91.139986
iter  40 value 90.928034
iter  50 value 85.532066
iter  60 value 84.477901
iter  70 value 84.477579
iter  80 value 83.410110
iter  90 value 83.000740
final  value 83.000594 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.209861 
iter  10 value 94.488225
iter  20 value 94.460038
iter  30 value 90.015724
iter  40 value 85.522222
iter  50 value 85.023632
iter  60 value 85.010618
iter  70 value 85.006806
final  value 85.005849 
converged
Fitting Repeat 1 

# weights:  507
initial  value 119.523579 
iter  10 value 94.364435
iter  20 value 94.296975
iter  30 value 94.284638
iter  40 value 94.158057
iter  50 value 94.157529
final  value 94.157203 
converged
Fitting Repeat 2 

# weights:  507
initial  value 128.722825 
iter  10 value 94.474693
iter  20 value 94.170724
iter  30 value 84.584508
iter  40 value 83.763849
iter  50 value 83.284384
iter  60 value 83.276704
final  value 83.276700 
converged
Fitting Repeat 3 

# weights:  507
initial  value 110.500216 
iter  10 value 94.503712
iter  20 value 94.461710
iter  30 value 94.436616
iter  40 value 94.430150
iter  50 value 94.428351
iter  60 value 87.900984
iter  70 value 82.252711
iter  80 value 82.155329
iter  90 value 81.762097
iter 100 value 81.209074
final  value 81.209074 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.941830 
iter  10 value 92.650210
iter  20 value 91.971666
iter  30 value 91.720537
iter  40 value 91.674166
iter  50 value 91.672637
iter  60 value 91.671586
iter  70 value 91.661085
iter  80 value 91.633458
iter  90 value 91.595449
iter 100 value 91.594784
final  value 91.594784 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 99.089806 
iter  10 value 93.788029
iter  20 value 93.131014
iter  30 value 93.060980
iter  40 value 93.060137
iter  50 value 92.974092
iter  60 value 87.247057
iter  70 value 84.533044
iter  80 value 82.802292
iter  90 value 80.144737
iter 100 value 78.986962
final  value 78.986962 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 129.993858 
iter  10 value 117.898795
iter  20 value 117.841425
final  value 117.759849 
converged
Fitting Repeat 2 

# weights:  507
initial  value 141.386951 
iter  10 value 117.737179
iter  20 value 117.732662
iter  30 value 117.720983
iter  40 value 117.568485
iter  50 value 117.555005
final  value 117.554805 
converged
Fitting Repeat 3 

# weights:  507
initial  value 124.622697 
iter  10 value 117.723038
iter  20 value 117.026827
iter  30 value 115.010721
iter  40 value 114.919196
final  value 114.727694 
converged
Fitting Repeat 4 

# weights:  507
initial  value 138.967911 
iter  10 value 117.899678
iter  20 value 117.828581
iter  30 value 107.229427
iter  40 value 104.308506
iter  50 value 102.786015
iter  60 value 102.667874
iter  70 value 102.667040
final  value 102.666880 
converged
Fitting Repeat 5 

# weights:  507
initial  value 123.120448 
iter  10 value 117.553136
iter  20 value 117.545931
iter  30 value 117.005721
iter  40 value 109.078969
iter  50 value 107.497778
iter  60 value 107.369583
iter  70 value 107.368825
final  value 107.367620 
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 -- Thu Jun  6 00:02:47 2024 
*********************************************** 
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 
Warning messages:
1: `repeats` has no meaning for this resampling method. 
2: executing %dopar% sequentially: no parallel backend registered 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
 42.147   2.175  45.441