##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings HPiP_1.18.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck’
* using R version 4.6.0 RC (2026-04-17 r89917)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
    GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
* running under: Ubuntu 24.04.4 LTS
* using session charset: UTF-8
* current time: 2026-05-08 05:01:00 UTC
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.18.0’
* 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 ... INFO
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
FSmethod      34.791  0.533  35.382
corr_plot     34.719  0.366  35.150
var_imp       34.114  0.710  34.824
pred_ensembel 13.168  0.130  11.942
enrichfindP    0.548  0.031  14.885
* 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: 2 NOTEs
See
  ‘/home/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.23-bioc/R/site-library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.18.0’
** 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 4.6.0 RC (2026-04-17 r89917) -- "Because it was There"
Copyright (C) 2026 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
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 97.082439 
iter  10 value 94.053141
final  value 94.052911 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.484674 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.801918 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.666166 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.167017 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.151079 
final  value 93.164740 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.715428 
final  value 93.164740 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.018667 
iter  10 value 91.443527
iter  20 value 88.457399
iter  30 value 88.064464
iter  40 value 88.059055
final  value 88.059007 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.202368 
iter  10 value 88.686292
iter  20 value 87.595910
iter  30 value 87.594121
iter  40 value 87.171360
iter  50 value 87.133049
iter  60 value 87.111323
final  value 87.111314 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.581594 
final  value 93.915746 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.372259 
final  value 93.915746 
converged
Fitting Repeat 2 

# weights:  507
initial  value 123.399381 
final  value 93.915746 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.268193 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.843775 
iter  10 value 93.854576
iter  10 value 93.854576
iter  10 value 93.854576
final  value 93.854576 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.826111 
iter  10 value 88.595503
iter  20 value 83.055306
iter  30 value 83.016624
iter  40 value 83.008867
final  value 83.008707 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.607998 
iter  10 value 93.995621
iter  20 value 93.442673
iter  30 value 93.363212
iter  40 value 93.336751
iter  50 value 93.335383
iter  60 value 93.331868
iter  70 value 86.559402
iter  80 value 85.135420
iter  90 value 84.823018
iter 100 value 84.804918
final  value 84.804918 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 102.793096 
iter  10 value 94.047624
iter  20 value 89.320588
iter  30 value 84.826048
iter  40 value 84.065126
iter  50 value 80.709542
iter  60 value 80.192612
iter  70 value 80.184354
final  value 80.183190 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.352969 
iter  10 value 94.056928
iter  20 value 92.250799
iter  30 value 92.084518
iter  40 value 86.351670
iter  50 value 83.339587
iter  60 value 81.619374
iter  70 value 81.569731
iter  80 value 80.886630
iter  90 value 80.648596
final  value 80.644659 
converged
Fitting Repeat 4 

# weights:  103
initial  value 109.164166 
iter  10 value 94.006755
iter  20 value 83.522394
iter  30 value 82.680867
iter  40 value 82.387535
iter  50 value 80.925470
iter  60 value 80.673833
iter  70 value 80.660633
iter  80 value 80.656014
iter  90 value 80.647005
iter 100 value 80.646859
final  value 80.646859 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.206025 
iter  10 value 93.990325
iter  20 value 93.544271
iter  30 value 93.463837
iter  40 value 93.328333
iter  50 value 84.772624
iter  60 value 81.012334
iter  70 value 80.053024
iter  80 value 78.604359
iter  90 value 78.515687
iter 100 value 78.363156
final  value 78.363156 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 101.495449 
iter  10 value 94.035453
iter  20 value 91.683950
iter  30 value 85.888394
iter  40 value 84.873594
iter  50 value 84.191420
iter  60 value 81.568477
iter  70 value 79.537546
iter  80 value 78.584856
iter  90 value 78.027143
iter 100 value 77.154825
final  value 77.154825 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.689053 
iter  10 value 94.115245
iter  20 value 94.057572
iter  30 value 87.911284
iter  40 value 82.854799
iter  50 value 81.223273
iter  60 value 80.400253
iter  70 value 80.115164
iter  80 value 79.679871
iter  90 value 78.236026
iter 100 value 77.493839
final  value 77.493839 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.254902 
iter  10 value 93.778220
iter  20 value 84.124684
iter  30 value 83.208537
iter  40 value 81.001137
iter  50 value 79.682970
iter  60 value 78.824274
iter  70 value 78.232777
iter  80 value 77.857735
iter  90 value 77.695033
iter 100 value 77.401737
final  value 77.401737 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.790713 
iter  10 value 89.875284
iter  20 value 89.031152
iter  30 value 88.117457
iter  40 value 80.391588
iter  50 value 78.684107
iter  60 value 77.677624
iter  70 value 77.442772
iter  80 value 77.321567
iter  90 value 77.067360
iter 100 value 76.747047
final  value 76.747047 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.679224 
iter  10 value 93.924207
iter  20 value 85.054838
iter  30 value 81.948674
iter  40 value 81.177849
iter  50 value 80.009747
iter  60 value 79.676036
iter  70 value 79.610614
iter  80 value 79.593696
iter  90 value 79.509769
iter 100 value 78.847383
final  value 78.847383 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 111.593756 
iter  10 value 91.763020
iter  20 value 85.101907
iter  30 value 81.896334
iter  40 value 81.427748
iter  50 value 80.083611
iter  60 value 78.920378
iter  70 value 77.924200
iter  80 value 77.791903
iter  90 value 77.563235
iter 100 value 77.299166
final  value 77.299166 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.656971 
iter  10 value 95.539547
iter  20 value 92.322733
iter  30 value 86.600098
iter  40 value 84.514950
iter  50 value 84.289621
iter  60 value 83.241434
iter  70 value 82.675647
iter  80 value 82.525827
iter  90 value 82.505398
iter 100 value 80.902617
final  value 80.902617 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.082277 
iter  10 value 94.139274
iter  20 value 93.907423
iter  30 value 83.139758
iter  40 value 82.172182
iter  50 value 79.246549
iter  60 value 78.591571
iter  70 value 77.604002
iter  80 value 76.872430
iter  90 value 76.609041
iter 100 value 76.577887
final  value 76.577887 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.428538 
iter  10 value 94.090001
iter  20 value 93.337243
iter  30 value 83.039293
iter  40 value 80.806601
iter  50 value 80.262982
iter  60 value 80.153627
iter  70 value 80.029566
iter  80 value 78.795210
iter  90 value 78.200714
iter 100 value 77.378483
final  value 77.378483 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.768516 
iter  10 value 94.044342
iter  20 value 88.796012
iter  30 value 84.755827
iter  40 value 84.303175
iter  50 value 82.311938
iter  60 value 79.547536
iter  70 value 78.804500
iter  80 value 78.725293
iter  90 value 78.636175
iter 100 value 78.416611
final  value 78.416611 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.724364 
final  value 94.054496 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.717654 
final  value 94.054633 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.599621 
final  value 94.054805 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.688034 
final  value 93.917280 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.990003 
final  value 94.054498 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.691905 
iter  10 value 93.536390
iter  20 value 93.532889
iter  30 value 93.379119
iter  40 value 82.508510
iter  50 value 79.888578
iter  60 value 79.466782
iter  70 value 79.451928
iter  80 value 79.086674
iter  90 value 78.845142
final  value 78.845040 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.869570 
iter  10 value 94.057798
iter  20 value 94.052925
iter  30 value 89.523835
iter  40 value 84.861471
iter  50 value 80.797338
iter  60 value 80.793407
iter  70 value 80.793268
final  value 80.792894 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.378492 
iter  10 value 94.057646
iter  20 value 94.052972
final  value 94.052943 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.870200 
iter  10 value 94.058180
iter  20 value 94.045405
iter  30 value 86.167930
iter  40 value 83.650872
iter  50 value 83.612008
iter  60 value 82.172848
iter  70 value 79.369163
iter  80 value 79.337810
iter  90 value 78.191646
iter 100 value 78.025987
final  value 78.025987 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.599285 
iter  10 value 94.058776
iter  20 value 88.721316
iter  30 value 83.994914
iter  40 value 83.979774
iter  50 value 83.952545
iter  60 value 83.949749
iter  70 value 83.948201
final  value 83.947467 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.036053 
iter  10 value 93.782415
iter  20 value 93.699491
iter  30 value 93.206752
iter  40 value 92.982161
iter  50 value 83.411763
iter  60 value 83.405458
iter  70 value 82.030652
iter  80 value 80.770888
iter  90 value 79.831822
iter 100 value 79.826336
final  value 79.826336 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 97.081063 
iter  10 value 94.061001
iter  20 value 94.049957
iter  30 value 93.367683
iter  40 value 81.302484
iter  50 value 79.783509
iter  60 value 79.372194
iter  70 value 78.877608
iter  80 value 78.760393
iter  90 value 78.739562
iter 100 value 78.738760
final  value 78.738760 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.743652 
iter  10 value 94.060730
iter  20 value 93.380178
iter  30 value 83.570648
iter  40 value 81.709678
iter  50 value 81.673735
final  value 81.673586 
converged
Fitting Repeat 4 

# weights:  507
initial  value 116.700480 
iter  10 value 91.864398
iter  20 value 79.900604
iter  30 value 79.488853
iter  40 value 79.484355
iter  50 value 79.479357
iter  60 value 79.465355
iter  70 value 79.463142
iter  80 value 78.865287
iter  90 value 78.864102
iter 100 value 78.857539
final  value 78.857539 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 94.789442 
iter  10 value 93.923667
iter  20 value 93.917835
iter  30 value 93.916801
iter  40 value 93.287382
iter  50 value 79.984355
iter  60 value 79.854796
iter  70 value 79.834571
iter  80 value 79.800932
iter  90 value 79.466976
iter 100 value 77.935709
final  value 77.935709 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.734216 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.122360 
final  value 93.915746 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.656347 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.755141 
iter  10 value 89.917702
final  value 89.917698 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.333960 
final  value 93.697740 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.394387 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.708457 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.924592 
iter  10 value 89.731552
iter  20 value 89.622200
iter  30 value 86.925582
final  value 86.924138 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.452847 
final  value 93.583334 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.565042 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 113.375000 
iter  10 value 89.262373
iter  20 value 88.363272
iter  30 value 87.738369
iter  40 value 87.737275
final  value 87.737273 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.184134 
final  value 93.491108 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.270786 
iter  10 value 93.367620
iter  20 value 92.698129
iter  30 value 92.542245
iter  40 value 92.529492
final  value 92.529490 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.186044 
final  value 93.867391 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.355677 
iter  10 value 93.868061
final  value 93.867391 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.621482 
iter  10 value 94.096353
iter  20 value 89.182485
iter  30 value 87.315619
iter  40 value 86.119994
iter  50 value 85.925484
iter  60 value 85.668568
iter  70 value 84.542188
iter  80 value 84.467690
iter  90 value 84.465898
final  value 84.465849 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.556998 
iter  10 value 94.046561
iter  20 value 89.521953
iter  30 value 88.533989
iter  40 value 87.620742
iter  50 value 84.714733
iter  60 value 84.466264
final  value 84.465850 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.424068 
iter  10 value 93.454826
iter  20 value 91.680263
iter  30 value 91.434221
iter  40 value 89.981299
iter  50 value 85.011388
iter  60 value 84.671351
iter  70 value 83.331947
iter  80 value 83.058299
iter  90 value 82.204787
iter 100 value 81.755411
final  value 81.755411 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.885557 
iter  10 value 94.055668
iter  20 value 93.152722
iter  30 value 88.864626
iter  40 value 88.209624
iter  50 value 86.911538
iter  60 value 86.234747
iter  70 value 83.368895
iter  80 value 82.630099
iter  90 value 82.470202
iter 100 value 82.376664
final  value 82.376664 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 102.921539 
iter  10 value 94.107889
iter  20 value 93.579331
iter  30 value 87.537905
iter  40 value 86.347692
iter  50 value 86.146465
iter  60 value 85.484785
iter  70 value 83.858132
iter  80 value 82.893499
iter  90 value 81.969902
iter 100 value 81.685242
final  value 81.685242 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 105.466251 
iter  10 value 93.811924
iter  20 value 92.433537
iter  30 value 91.496995
iter  40 value 91.381133
iter  50 value 91.310363
iter  60 value 91.214177
iter  70 value 87.430195
iter  80 value 85.451429
iter  90 value 84.182185
iter 100 value 84.039902
final  value 84.039902 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 119.403306 
iter  10 value 94.252560
iter  20 value 93.930769
iter  30 value 91.487028
iter  40 value 83.662213
iter  50 value 82.476955
iter  60 value 81.195988
iter  70 value 81.053433
iter  80 value 80.711382
iter  90 value 80.524505
iter 100 value 80.426050
final  value 80.426050 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.866601 
iter  10 value 93.905801
iter  20 value 89.031402
iter  30 value 88.082359
iter  40 value 86.514774
iter  50 value 85.473004
iter  60 value 84.725809
iter  70 value 83.785586
iter  80 value 82.223689
iter  90 value 81.767656
iter 100 value 80.899857
final  value 80.899857 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.688796 
iter  10 value 94.217140
iter  20 value 89.047270
iter  30 value 86.617222
iter  40 value 84.471092
iter  50 value 83.724000
iter  60 value 82.013757
iter  70 value 80.965210
iter  80 value 80.809496
iter  90 value 80.679776
iter 100 value 80.566440
final  value 80.566440 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.146526 
iter  10 value 93.779713
iter  20 value 90.044243
iter  30 value 89.689789
iter  40 value 85.502306
iter  50 value 84.991432
iter  60 value 83.671469
iter  70 value 82.276433
iter  80 value 81.093241
iter  90 value 80.957465
iter 100 value 80.813732
final  value 80.813732 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.004178 
iter  10 value 92.425252
iter  20 value 85.567765
iter  30 value 84.882218
iter  40 value 84.620780
iter  50 value 83.342343
iter  60 value 81.131258
iter  70 value 80.562845
iter  80 value 80.362178
iter  90 value 80.274017
iter 100 value 80.247185
final  value 80.247185 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 116.496796 
iter  10 value 93.860637
iter  20 value 92.239262
iter  30 value 87.112381
iter  40 value 84.642523
iter  50 value 83.461856
iter  60 value 82.003765
iter  70 value 81.226600
iter  80 value 81.022546
iter  90 value 80.799850
iter 100 value 80.695442
final  value 80.695442 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.895650 
iter  10 value 94.169983
iter  20 value 91.956573
iter  30 value 90.459969
iter  40 value 85.963838
iter  50 value 84.011230
iter  60 value 82.217939
iter  70 value 81.489009
iter  80 value 81.202733
iter  90 value 80.832557
iter 100 value 80.534447
final  value 80.534447 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 116.323749 
iter  10 value 96.578645
iter  20 value 87.365069
iter  30 value 83.507091
iter  40 value 81.415064
iter  50 value 80.738278
iter  60 value 80.460238
iter  70 value 80.338175
iter  80 value 80.132878
iter  90 value 80.046586
iter 100 value 80.009959
final  value 80.009959 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 142.065694 
iter  10 value 94.005991
iter  20 value 88.198616
iter  30 value 85.779711
iter  40 value 84.756380
iter  50 value 84.307584
iter  60 value 82.485721
iter  70 value 81.774436
iter  80 value 81.125829
iter  90 value 80.401078
iter 100 value 80.238334
final  value 80.238334 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.557747 
final  value 94.054543 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.016687 
final  value 94.054564 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.273201 
final  value 94.054604 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.656535 
final  value 94.054270 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.726052 
final  value 94.054675 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.772843 
iter  10 value 94.057567
iter  20 value 93.538459
iter  30 value 91.651579
iter  40 value 90.961165
iter  50 value 86.540747
iter  60 value 85.877031
iter  70 value 84.370399
iter  80 value 81.876031
iter  90 value 81.775508
iter 100 value 81.774380
final  value 81.774380 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 97.412805 
iter  10 value 94.058304
iter  20 value 94.053327
iter  30 value 86.682230
final  value 86.682148 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.655718 
iter  10 value 94.057557
iter  20 value 94.008911
final  value 93.492354 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.338799 
iter  10 value 93.920644
iter  20 value 93.631438
iter  30 value 91.165313
iter  40 value 85.210490
iter  50 value 85.107875
iter  60 value 85.106948
iter  70 value 85.105694
final  value 85.105434 
converged
Fitting Repeat 5 

# weights:  305
initial  value 122.361475 
iter  10 value 93.872123
iter  20 value 93.869579
iter  30 value 93.869364
iter  40 value 93.861251
iter  50 value 89.886997
iter  60 value 86.260274
iter  70 value 85.525216
iter  80 value 85.072306
final  value 85.067231 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.947811 
iter  10 value 90.450040
iter  20 value 84.668096
iter  30 value 84.449076
iter  40 value 83.968703
iter  50 value 83.965753
iter  60 value 83.616844
iter  70 value 83.563211
iter  80 value 83.562249
iter  90 value 83.474346
iter 100 value 81.841258
final  value 81.841258 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.523323 
iter  10 value 93.852581
iter  20 value 93.849786
final  value 93.849760 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.546515 
iter  10 value 94.059824
iter  20 value 93.921089
iter  30 value 89.664390
iter  40 value 88.966725
iter  50 value 85.526663
iter  60 value 84.146817
iter  70 value 83.888310
iter  80 value 83.875329
iter  90 value 82.487880
iter 100 value 81.939799
final  value 81.939799 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 100.214743 
iter  10 value 93.447321
iter  20 value 93.339909
iter  30 value 93.334270
iter  40 value 93.249213
iter  50 value 92.795970
iter  60 value 92.752088
iter  70 value 92.751063
final  value 92.751041 
converged
Fitting Repeat 5 

# weights:  507
initial  value 128.464938 
iter  10 value 92.258779
iter  20 value 92.248791
iter  30 value 91.993618
iter  40 value 89.054532
iter  50 value 82.672947
iter  60 value 81.376470
iter  70 value 80.885392
iter  80 value 80.748264
iter  90 value 80.616203
iter 100 value 80.546659
final  value 80.546659 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 106.633711 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.771691 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.739126 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.759331 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.600738 
final  value 93.922222 
converged
Fitting Repeat 1 

# weights:  305
initial  value 119.292503 
iter  10 value 93.773010
final  value 93.772973 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.282657 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.121452 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 117.608772 
iter  10 value 89.093309
iter  20 value 85.912433
final  value 85.851232 
converged
Fitting Repeat 5 

# weights:  305
initial  value 120.165608 
iter  10 value 93.772975
final  value 93.772973 
converged
Fitting Repeat 1 

# weights:  507
initial  value 116.553711 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 113.383372 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 118.911362 
iter  10 value 94.484211
iter  10 value 94.484211
iter  10 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.980456 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 109.416734 
iter  10 value 93.563707
iter  20 value 89.057925
iter  30 value 83.127624
iter  40 value 83.124957
iter  50 value 83.124454
final  value 83.124406 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.012412 
iter  10 value 94.732493
iter  20 value 94.478791
iter  30 value 86.557348
iter  40 value 83.983254
iter  50 value 83.072955
iter  60 value 82.474913
iter  70 value 82.245299
iter  80 value 82.063127
iter  90 value 82.019402
final  value 82.015718 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.271398 
iter  10 value 94.491212
iter  20 value 91.654037
iter  30 value 88.749730
iter  40 value 86.922145
iter  50 value 85.360407
iter  60 value 84.133199
iter  70 value 83.239124
iter  80 value 82.941199
iter  90 value 82.920671
iter 100 value 82.233502
final  value 82.233502 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 101.839493 
iter  10 value 94.487724
iter  20 value 94.267271
iter  30 value 94.114654
iter  40 value 93.968065
iter  50 value 93.829339
iter  60 value 93.824397
iter  70 value 87.872050
iter  80 value 85.735768
iter  90 value 84.686425
iter 100 value 84.167601
final  value 84.167601 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 121.881962 
iter  10 value 94.385201
iter  20 value 85.016217
iter  30 value 84.473889
iter  40 value 83.901412
iter  50 value 83.674226
iter  60 value 83.628243
iter  70 value 83.600837
iter  80 value 83.591758
final  value 83.591756 
converged
Fitting Repeat 5 

# weights:  103
initial  value 116.612181 
iter  10 value 94.487789
iter  20 value 94.212073
iter  30 value 94.042131
iter  40 value 93.875579
iter  50 value 93.835004
iter  60 value 89.347235
iter  70 value 86.419917
iter  80 value 84.605281
iter  90 value 84.489108
iter 100 value 84.315854
final  value 84.315854 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 103.387680 
iter  10 value 96.353664
iter  20 value 90.168183
iter  30 value 83.290655
iter  40 value 82.700725
iter  50 value 82.419452
iter  60 value 82.235675
iter  70 value 82.098290
iter  80 value 81.797672
iter  90 value 81.444391
iter 100 value 81.369002
final  value 81.369002 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.085698 
iter  10 value 94.508064
iter  20 value 93.956315
iter  30 value 88.180488
iter  40 value 87.197626
iter  50 value 86.674301
iter  60 value 85.011650
iter  70 value 83.307399
iter  80 value 81.794017
iter  90 value 81.343470
iter 100 value 81.268080
final  value 81.268080 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.997075 
iter  10 value 94.349835
iter  20 value 93.021888
iter  30 value 88.038646
iter  40 value 86.508203
iter  50 value 84.519726
iter  60 value 82.799303
iter  70 value 82.483171
iter  80 value 82.141878
iter  90 value 82.017758
iter 100 value 81.960138
final  value 81.960138 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.116677 
iter  10 value 94.480492
iter  20 value 91.542478
iter  30 value 88.008667
iter  40 value 85.596059
iter  50 value 83.815700
iter  60 value 83.476663
iter  70 value 82.774269
iter  80 value 82.478142
iter  90 value 81.972922
iter 100 value 81.302243
final  value 81.302243 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 112.600066 
iter  10 value 93.962973
iter  20 value 90.236923
iter  30 value 85.477824
iter  40 value 82.676687
iter  50 value 82.225818
iter  60 value 81.953237
iter  70 value 81.759609
iter  80 value 81.607835
iter  90 value 81.454713
iter 100 value 81.411115
final  value 81.411115 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.993430 
iter  10 value 94.599866
iter  20 value 91.324774
iter  30 value 88.382974
iter  40 value 87.057029
iter  50 value 86.270861
iter  60 value 84.431997
iter  70 value 82.345742
iter  80 value 81.982433
iter  90 value 81.573831
iter 100 value 81.091647
final  value 81.091647 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 131.151419 
iter  10 value 94.888139
iter  20 value 91.542331
iter  30 value 84.797917
iter  40 value 84.152147
iter  50 value 83.725280
iter  60 value 83.415852
iter  70 value 83.225898
iter  80 value 83.056483
iter  90 value 82.368937
iter 100 value 81.345209
final  value 81.345209 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.056491 
iter  10 value 95.376028
iter  20 value 93.963133
iter  30 value 93.385915
iter  40 value 88.425560
iter  50 value 87.962748
iter  60 value 84.933212
iter  70 value 83.841819
iter  80 value 83.462493
iter  90 value 83.239738
iter 100 value 82.039553
final  value 82.039553 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.125022 
iter  10 value 94.440560
iter  20 value 91.953341
iter  30 value 88.069515
iter  40 value 85.108367
iter  50 value 83.554664
iter  60 value 83.254738
iter  70 value 82.949975
iter  80 value 82.880054
iter  90 value 82.766167
iter 100 value 82.437341
final  value 82.437341 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 128.567296 
iter  10 value 95.419369
iter  20 value 89.838407
iter  30 value 85.511209
iter  40 value 84.229616
iter  50 value 83.672337
iter  60 value 83.294550
iter  70 value 83.217981
iter  80 value 83.206754
iter  90 value 83.106653
iter 100 value 82.747910
final  value 82.747910 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 116.282239 
iter  10 value 93.775390
iter  20 value 93.774964
iter  30 value 93.715448
iter  40 value 93.666380
iter  50 value 93.665123
iter  50 value 93.665122
iter  50 value 93.665122
final  value 93.665122 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.193240 
final  value 94.486191 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.473186 
final  value 94.486391 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.989740 
final  value 94.486499 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.940104 
final  value 94.485859 
converged
Fitting Repeat 1 

# weights:  305
initial  value 117.079603 
iter  10 value 93.501659
iter  20 value 92.642879
iter  30 value 92.128878
iter  40 value 92.054608
iter  50 value 92.039989
iter  60 value 92.036908
iter  70 value 92.020749
iter  80 value 91.995167
iter  90 value 86.882542
iter 100 value 86.204053
final  value 86.204053 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 95.910019 
iter  10 value 94.489921
iter  20 value 94.485318
final  value 94.485272 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.788179 
iter  10 value 93.836295
iter  20 value 93.829625
iter  30 value 93.162035
iter  40 value 84.084127
iter  50 value 83.886938
iter  60 value 83.851945
iter  70 value 83.143688
iter  80 value 83.136237
iter  90 value 83.103240
iter 100 value 83.094699
final  value 83.094699 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 96.998961 
iter  10 value 94.087246
iter  20 value 93.772973
iter  30 value 93.669805
iter  40 value 93.669121
iter  50 value 93.665155
final  value 93.664975 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.753995 
iter  10 value 94.488780
iter  20 value 94.484233
final  value 94.484210 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.482768 
iter  10 value 94.492503
iter  20 value 94.300312
iter  30 value 84.300950
iter  40 value 82.680584
iter  50 value 80.985356
iter  60 value 80.797899
iter  70 value 80.559469
iter  80 value 80.519149
iter  90 value 80.367535
iter 100 value 80.362755
final  value 80.362755 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.275189 
iter  10 value 94.495415
iter  20 value 93.735280
iter  30 value 88.809457
iter  40 value 86.477207
iter  50 value 86.339198
iter  60 value 86.338040
iter  70 value 86.337489
final  value 86.337445 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.281907 
iter  10 value 94.480628
iter  20 value 94.473419
iter  30 value 89.967437
iter  40 value 88.888469
iter  50 value 87.062448
iter  60 value 86.520872
iter  70 value 86.327387
iter  80 value 85.445597
iter  90 value 83.276964
iter 100 value 83.180897
final  value 83.180897 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 117.939285 
iter  10 value 94.492679
iter  20 value 94.454322
iter  30 value 84.229910
iter  40 value 84.195033
iter  50 value 83.937923
iter  60 value 83.922213
final  value 83.922162 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.365218 
iter  10 value 93.967209
iter  20 value 93.729154
iter  30 value 93.725417
iter  40 value 93.724770
iter  50 value 93.722171
iter  60 value 93.671475
final  value 93.665862 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.900042 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.918413 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.886827 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 108.738654 
final  value 94.252920 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.806347 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.136686 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.130130 
final  value 94.455556 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.303380 
iter  10 value 86.817366
iter  20 value 84.762311
iter  30 value 84.152961
iter  40 value 84.096666
iter  50 value 83.318705
iter  60 value 83.149516
iter  70 value 83.108997
iter  80 value 83.040500
iter  90 value 82.958478
iter 100 value 82.951614
final  value 82.951614 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 97.723812 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.256195 
iter  10 value 90.884298
iter  20 value 90.842139
final  value 90.842081 
converged
Fitting Repeat 1 

# weights:  507
initial  value 120.604791 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 114.986412 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 129.254852 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.678583 
iter  10 value 94.201497
final  value 94.104067 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.218364 
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  103
initial  value 108.807373 
iter  10 value 94.513718
iter  20 value 94.486641
iter  30 value 92.081568
iter  40 value 89.628681
iter  50 value 88.026718
iter  60 value 85.659486
iter  70 value 85.532713
iter  80 value 85.531076
iter  90 value 85.523103
iter 100 value 85.521952
final  value 85.521952 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 101.254174 
iter  10 value 94.483210
iter  20 value 94.256687
iter  30 value 94.102250
iter  40 value 94.091567
iter  50 value 93.155529
iter  60 value 88.873319
iter  70 value 88.828530
iter  80 value 88.822749
iter  90 value 88.809401
iter 100 value 88.679829
final  value 88.679829 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 105.771986 
iter  10 value 94.395920
iter  20 value 92.820944
iter  30 value 90.553863
iter  40 value 90.407892
iter  50 value 90.361979
final  value 90.359841 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.548373 
iter  10 value 94.259513
iter  20 value 89.731320
iter  30 value 87.398245
iter  40 value 86.230554
iter  50 value 82.966543
iter  60 value 82.051665
iter  70 value 81.801499
iter  80 value 81.670919
final  value 81.669418 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.330493 
iter  10 value 93.542648
iter  20 value 90.943722
iter  30 value 86.489851
iter  40 value 86.438952
iter  50 value 85.619557
iter  60 value 85.094852
iter  70 value 84.904518
final  value 84.904098 
converged
Fitting Repeat 1 

# weights:  305
initial  value 111.907088 
iter  10 value 94.521457
iter  20 value 94.473138
iter  30 value 91.485681
iter  40 value 88.950374
iter  50 value 88.237826
iter  60 value 84.591483
iter  70 value 83.477987
iter  80 value 82.848860
iter  90 value 82.632005
iter 100 value 82.575789
final  value 82.575789 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.930385 
iter  10 value 94.739273
iter  20 value 94.304182
iter  30 value 92.702116
iter  40 value 87.947490
iter  50 value 87.141922
iter  60 value 84.990661
iter  70 value 84.039063
iter  80 value 83.896417
iter  90 value 83.444419
iter 100 value 81.251835
final  value 81.251835 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 110.104208 
iter  10 value 94.579899
iter  20 value 94.178612
iter  30 value 94.095250
iter  40 value 93.861552
iter  50 value 88.316334
iter  60 value 84.895199
iter  70 value 83.636002
iter  80 value 82.720548
iter  90 value 82.161252
iter 100 value 81.757661
final  value 81.757661 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.351819 
iter  10 value 93.833979
iter  20 value 92.830419
iter  30 value 90.220075
iter  40 value 89.937512
iter  50 value 89.880174
iter  60 value 89.059281
iter  70 value 86.377626
iter  80 value 83.846365
iter  90 value 82.236376
iter 100 value 81.859699
final  value 81.859699 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.996961 
iter  10 value 94.460429
iter  20 value 87.874532
iter  30 value 86.695200
iter  40 value 84.306583
iter  50 value 83.847453
iter  60 value 83.692889
iter  70 value 83.589582
iter  80 value 83.259711
iter  90 value 82.176603
iter 100 value 81.408187
final  value 81.408187 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.265319 
iter  10 value 94.371453
iter  20 value 93.777051
iter  30 value 89.584299
iter  40 value 87.212718
iter  50 value 85.480430
iter  60 value 83.431165
iter  70 value 82.228606
iter  80 value 81.127237
iter  90 value 80.802189
iter 100 value 80.569860
final  value 80.569860 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.761067 
iter  10 value 94.718713
iter  20 value 89.561789
iter  30 value 84.233449
iter  40 value 82.468630
iter  50 value 81.482906
iter  60 value 81.099170
iter  70 value 80.983476
iter  80 value 80.841936
iter  90 value 80.637534
iter 100 value 80.323331
final  value 80.323331 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.503403 
iter  10 value 94.523029
iter  20 value 89.210890
iter  30 value 85.995142
iter  40 value 83.763463
iter  50 value 82.221542
iter  60 value 82.138017
iter  70 value 82.060181
iter  80 value 81.217123
iter  90 value 81.017913
iter 100 value 80.572149
final  value 80.572149 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.772869 
iter  10 value 94.760630
iter  20 value 92.385212
iter  30 value 86.407174
iter  40 value 82.478777
iter  50 value 82.215843
iter  60 value 81.865858
iter  70 value 81.581025
iter  80 value 80.727560
iter  90 value 80.675857
iter 100 value 80.406925
final  value 80.406925 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.112516 
iter  10 value 94.662596
iter  20 value 92.879581
iter  30 value 88.076271
iter  40 value 83.347852
iter  50 value 82.634380
iter  60 value 82.245601
iter  70 value 81.334166
iter  80 value 81.131623
iter  90 value 80.875323
iter 100 value 80.834320
final  value 80.834320 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.049552 
final  value 94.485675 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.899174 
final  value 94.485830 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.187528 
final  value 94.485696 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.285894 
final  value 94.485710 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.489741 
final  value 94.485849 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.175190 
iter  10 value 94.488489
iter  20 value 94.288480
final  value 94.057389 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.239796 
iter  10 value 94.488931
iter  20 value 94.483959
iter  30 value 94.354807
final  value 94.354791 
converged
Fitting Repeat 3 

# weights:  305
initial  value 116.826468 
iter  10 value 94.489242
iter  20 value 93.100643
iter  30 value 87.287525
iter  40 value 87.286396
iter  50 value 87.285977
final  value 87.285943 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.766204 
iter  10 value 94.359102
iter  20 value 94.356960
iter  30 value 94.354496
iter  30 value 94.354495
iter  30 value 94.354495
final  value 94.354495 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.041647 
iter  10 value 94.485051
iter  20 value 94.456550
final  value 94.354744 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.382603 
iter  10 value 92.188488
iter  20 value 89.548019
iter  30 value 89.532445
final  value 89.531815 
converged
Fitting Repeat 2 

# weights:  507
initial  value 113.412592 
iter  10 value 94.492865
iter  20 value 94.461838
iter  30 value 93.964099
iter  40 value 86.122582
iter  50 value 84.491288
iter  60 value 84.463602
iter  70 value 84.446998
iter  80 value 83.392464
final  value 83.382290 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.515995 
iter  10 value 94.492223
iter  20 value 94.408377
iter  30 value 86.942799
iter  40 value 84.221812
iter  50 value 84.152180
iter  60 value 84.112248
iter  70 value 84.084732
iter  80 value 83.981634
iter  90 value 83.577703
iter 100 value 82.611138
final  value 82.611138 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 101.814394 
iter  10 value 94.362832
iter  20 value 94.355007
iter  30 value 87.952430
final  value 86.943537 
converged
Fitting Repeat 5 

# weights:  507
initial  value 119.907425 
iter  10 value 94.320343
iter  20 value 94.315050
iter  30 value 94.311951
iter  40 value 93.950775
iter  50 value 91.669957
iter  60 value 89.448201
iter  70 value 84.846652
iter  80 value 84.758338
iter  90 value 83.890691
iter 100 value 83.829864
final  value 83.829864 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.548993 
final  value 94.101525 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.907029 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.331964 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.741360 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 109.003878 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.640641 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.315100 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.318057 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.180888 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 109.214862 
iter  10 value 94.275365
final  value 94.275362 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.450074 
iter  10 value 92.845774
iter  20 value 91.044407
iter  30 value 87.492907
iter  40 value 86.777663
iter  50 value 86.727362
iter  60 value 86.724552
final  value 86.724543 
converged
Fitting Repeat 2 

# weights:  507
initial  value 120.483238 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 108.796758 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.015354 
iter  10 value 94.228845
final  value 94.228678 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.150032 
iter  10 value 94.228678
iter  10 value 94.228678
iter  10 value 94.228678
final  value 94.228678 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.688645 
iter  10 value 95.374743
iter  20 value 94.491974
iter  30 value 88.325899
iter  40 value 85.240421
iter  50 value 84.099693
iter  60 value 83.568020
iter  70 value 83.429989
iter  80 value 83.267724
iter  90 value 83.229662
final  value 83.229658 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.826278 
iter  10 value 94.428986
iter  20 value 89.111569
iter  30 value 86.262645
iter  40 value 85.292729
iter  50 value 82.809617
iter  60 value 82.107754
iter  70 value 81.367588
iter  80 value 81.129447
final  value 81.071692 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.638237 
iter  10 value 94.311823
iter  20 value 92.890414
iter  30 value 90.611252
iter  40 value 88.216844
iter  50 value 85.270492
iter  60 value 84.302322
iter  70 value 81.867834
iter  80 value 81.466090
iter  90 value 81.286909
iter 100 value 81.134842
final  value 81.134842 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 103.811325 
iter  10 value 94.483937
iter  20 value 93.473337
iter  30 value 91.635313
iter  40 value 91.257475
iter  50 value 91.209579
iter  60 value 91.197655
iter  70 value 91.197153
final  value 91.197125 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.586211 
iter  10 value 94.618034
iter  20 value 94.026240
iter  30 value 93.003667
iter  40 value 84.185256
iter  50 value 83.933013
iter  60 value 83.843842
iter  70 value 83.750331
iter  80 value 83.593492
iter  90 value 83.445960
iter 100 value 83.384392
final  value 83.384392 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 103.422389 
iter  10 value 94.373696
iter  20 value 94.296801
iter  30 value 91.869986
iter  40 value 83.128945
iter  50 value 81.351343
iter  60 value 80.855719
iter  70 value 80.711913
iter  80 value 80.682771
iter  90 value 80.408709
iter 100 value 79.940089
final  value 79.940089 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.216079 
iter  10 value 94.382887
iter  20 value 89.972422
iter  30 value 85.461099
iter  40 value 84.046411
iter  50 value 83.650372
iter  60 value 83.348337
iter  70 value 82.724434
iter  80 value 80.982235
iter  90 value 80.417106
iter 100 value 80.357848
final  value 80.357848 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.812766 
iter  10 value 95.014936
iter  20 value 92.620558
iter  30 value 84.262911
iter  40 value 82.244640
iter  50 value 81.321655
iter  60 value 80.782015
iter  70 value 80.508968
iter  80 value 80.384865
iter  90 value 80.295965
iter 100 value 80.235050
final  value 80.235050 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.494427 
iter  10 value 85.902094
iter  20 value 83.979362
iter  30 value 83.376641
iter  40 value 83.258666
iter  50 value 83.166242
iter  60 value 82.944170
iter  70 value 82.521759
iter  80 value 81.066064
iter  90 value 80.702067
iter 100 value 80.584411
final  value 80.584411 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.115824 
iter  10 value 94.266863
iter  20 value 87.491977
iter  30 value 85.564276
iter  40 value 84.504680
iter  50 value 82.316674
iter  60 value 80.780607
iter  70 value 80.097993
iter  80 value 79.954431
iter  90 value 79.681013
iter 100 value 79.437325
final  value 79.437325 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.333637 
iter  10 value 96.906232
iter  20 value 94.340051
iter  30 value 92.586791
iter  40 value 86.088483
iter  50 value 84.209126
iter  60 value 83.594552
iter  70 value 82.769739
iter  80 value 81.079708
iter  90 value 80.224437
iter 100 value 79.947399
final  value 79.947399 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 116.644929 
iter  10 value 94.160848
iter  20 value 87.792456
iter  30 value 85.347560
iter  40 value 84.633064
iter  50 value 82.543321
iter  60 value 81.209412
iter  70 value 79.831981
iter  80 value 79.617735
iter  90 value 79.595616
iter 100 value 79.554804
final  value 79.554804 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.018866 
iter  10 value 94.709130
iter  20 value 89.789662
iter  30 value 88.230409
iter  40 value 85.164936
iter  50 value 84.384695
iter  60 value 83.288018
iter  70 value 82.429463
iter  80 value 81.914180
iter  90 value 80.713821
iter 100 value 79.765593
final  value 79.765593 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.556770 
iter  10 value 94.526476
iter  20 value 89.553263
iter  30 value 84.653107
iter  40 value 83.996258
iter  50 value 83.528016
iter  60 value 83.289706
iter  70 value 82.989898
iter  80 value 81.488167
iter  90 value 81.048873
iter 100 value 80.182165
final  value 80.182165 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 133.376429 
iter  10 value 98.232241
iter  20 value 84.849985
iter  30 value 83.865820
iter  40 value 83.461831
iter  50 value 82.463877
iter  60 value 81.687893
iter  70 value 81.186765
iter  80 value 81.094164
iter  90 value 80.885103
iter 100 value 80.403964
final  value 80.403964 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.723242 
final  value 94.485799 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.850528 
final  value 94.485714 
converged
Fitting Repeat 3 

# weights:  103
initial  value 115.668214 
final  value 94.325608 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.096854 
final  value 94.486024 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.066839 
final  value 94.276664 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.211423 
iter  10 value 94.170787
iter  20 value 94.169849
iter  30 value 94.166194
final  value 94.166020 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.335503 
iter  10 value 94.488616
iter  20 value 94.407329
iter  30 value 88.066247
iter  40 value 86.654648
iter  50 value 86.148668
iter  60 value 86.144562
final  value 86.144483 
converged
Fitting Repeat 3 

# weights:  305
initial  value 113.434831 
iter  10 value 94.488991
iter  20 value 94.484550
final  value 94.484330 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.220356 
iter  10 value 94.225264
iter  20 value 92.448688
iter  30 value 92.446346
iter  40 value 92.445530
final  value 92.444759 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.099054 
iter  10 value 94.489591
iter  20 value 94.484376
iter  30 value 83.799604
iter  40 value 83.205257
iter  50 value 83.185889
iter  60 value 83.030739
iter  70 value 83.001676
iter  80 value 82.984720
iter  90 value 82.751652
iter 100 value 82.748252
final  value 82.748252 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 126.811222 
iter  10 value 92.636913
iter  20 value 92.537167
iter  30 value 92.535846
iter  40 value 92.534495
iter  50 value 92.520580
iter  60 value 92.518247
iter  70 value 92.517704
final  value 92.516890 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.020410 
iter  10 value 92.269649
iter  20 value 84.336593
iter  30 value 83.194124
iter  40 value 83.158437
iter  50 value 83.156802
final  value 83.151163 
converged
Fitting Repeat 3 

# weights:  507
initial  value 125.185916 
iter  10 value 94.283552
iter  20 value 94.276385
iter  30 value 87.065628
final  value 86.944701 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.853050 
iter  10 value 94.260680
iter  20 value 94.234708
iter  30 value 94.229213
iter  40 value 92.149720
iter  50 value 83.820911
iter  60 value 82.285474
iter  70 value 81.983514
iter  80 value 81.982203
iter  90 value 81.372669
iter 100 value 80.070480
final  value 80.070480 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 119.287590 
iter  10 value 94.489794
iter  20 value 91.780272
iter  30 value 86.228340
iter  40 value 85.758911
iter  50 value 84.553193
iter  60 value 82.494194
iter  70 value 82.386903
iter  80 value 82.367151
iter  90 value 82.366459
iter 100 value 81.953472
final  value 81.953472 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 129.352771 
iter  10 value 117.928440
iter  20 value 116.733890
iter  30 value 108.034520
iter  40 value 106.370355
iter  50 value 105.783856
iter  60 value 105.648069
iter  70 value 105.380134
iter  80 value 104.219334
iter  90 value 102.048611
iter 100 value 101.478136
final  value 101.478136 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 141.939102 
iter  10 value 117.630217
iter  20 value 110.967324
iter  30 value 108.054769
iter  40 value 106.933518
iter  50 value 102.889447
iter  60 value 102.177879
iter  70 value 101.187867
iter  80 value 100.974969
iter  90 value 100.875659
iter 100 value 100.820839
final  value 100.820839 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 125.800729 
iter  10 value 117.840095
iter  20 value 117.594609
iter  30 value 111.515684
iter  40 value 106.501550
iter  50 value 106.012443
iter  60 value 105.476870
iter  70 value 105.363925
iter  80 value 105.012928
iter  90 value 104.350859
iter 100 value 103.744010
final  value 103.744010 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 127.404056 
iter  10 value 118.117414
iter  20 value 110.644615
iter  30 value 109.330749
iter  40 value 108.344668
iter  50 value 105.045249
iter  60 value 103.981329
iter  70 value 103.864098
iter  80 value 103.369754
iter  90 value 102.502625
iter 100 value 101.763986
final  value 101.763986 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 128.220386 
iter  10 value 117.846122
iter  20 value 116.580445
iter  30 value 113.433139
iter  40 value 112.859874
iter  50 value 112.169357
iter  60 value 109.415314
iter  70 value 104.568428
iter  80 value 103.373678
iter  90 value 102.456197
iter 100 value 101.624551
final  value 101.624551 
stopped after 100 iterations
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Fri May  8 01:06:33 2026 
*********************************************** 
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 
 42.266   1.235 100.486