##############################################################################
##############################################################################
###
### 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_1.17.2.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2026-03-05 r89546)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
    GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
* running under: Ubuntu 24.04.4 LTS
* using session charset: UTF-8
* current time: 2026-03-12 04:17:44 UTC
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.17.2’
* 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
corr_plot     33.732  0.319  34.052
var_imp       33.240  0.473  33.715
FSmethod      32.654  0.630  33.288
pred_ensembel 12.567  0.111  11.373
enrichfindP    0.562  0.050  12.569
* 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 ‘1.17.2’
** 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 Under development (unstable) (2026-03-05 r89546) -- "Unsuffered Consequences"
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
avNNet
Loading required package: ggplot2
Loading required package: lattice
Fitting Repeat 1 

# weights:  103
initial  value 99.704923 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.313157 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.810481 
iter  10 value 94.443275
final  value 94.443243 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.123160 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.174300 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.997437 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 106.892079 
iter  10 value 94.483605
iter  20 value 86.685397
final  value 86.520651 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.083810 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.681826 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.262358 
iter  10 value 93.733931
iter  20 value 93.650026
final  value 93.649861 
converged
Fitting Repeat 1 

# weights:  507
initial  value 110.927976 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 119.483429 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.306463 
final  value 94.443243 
converged
Fitting Repeat 4 

# weights:  507
initial  value 107.220076 
final  value 94.443243 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.999484 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 107.303077 
iter  10 value 94.467284
iter  20 value 94.149973
iter  30 value 90.343640
iter  40 value 89.726382
iter  50 value 89.663636
iter  60 value 89.651834
iter  70 value 89.648661
iter  80 value 89.643433
final  value 89.643299 
converged
Fitting Repeat 2 

# weights:  103
initial  value 120.775670 
iter  10 value 93.675631
iter  20 value 85.401746
iter  30 value 84.726316
iter  40 value 83.392771
iter  50 value 82.375834
iter  60 value 82.319299
iter  70 value 82.291980
final  value 82.291761 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.721108 
iter  10 value 94.397064
iter  20 value 91.241889
iter  30 value 90.689511
iter  40 value 90.079555
iter  50 value 89.693744
iter  60 value 89.643223
final  value 89.643213 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.292026 
iter  10 value 94.292947
iter  20 value 86.819973
iter  30 value 83.330441
iter  40 value 82.850148
iter  50 value 82.025711
iter  60 value 81.774070
iter  70 value 81.684935
final  value 81.684843 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.391111 
iter  10 value 94.444605
iter  20 value 90.604244
iter  30 value 87.791488
iter  40 value 83.476857
iter  50 value 83.402069
iter  60 value 82.968797
iter  70 value 82.694818
iter  80 value 82.692400
iter  90 value 82.673839
iter 100 value 82.659583
final  value 82.659583 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 113.670153 
iter  10 value 90.869895
iter  20 value 83.401677
iter  30 value 82.471233
iter  40 value 82.146600
iter  50 value 81.835841
iter  60 value 81.790957
iter  70 value 81.755544
iter  80 value 81.719970
iter  90 value 81.662913
iter 100 value 81.323462
final  value 81.323462 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 111.411351 
iter  10 value 94.523228
iter  20 value 90.612106
iter  30 value 86.784300
iter  40 value 86.422958
iter  50 value 85.057228
iter  60 value 81.570660
iter  70 value 80.491512
iter  80 value 80.076763
iter  90 value 79.986179
iter 100 value 79.831378
final  value 79.831378 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.075513 
iter  10 value 94.497220
iter  20 value 94.262034
iter  30 value 87.471935
iter  40 value 83.916253
iter  50 value 83.321694
iter  60 value 82.920978
iter  70 value 80.612106
iter  80 value 80.452835
iter  90 value 80.105742
iter 100 value 79.499273
final  value 79.499273 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 118.792721 
iter  10 value 94.543201
iter  20 value 94.427346
iter  30 value 92.070422
iter  40 value 88.929330
iter  50 value 82.649240
iter  60 value 81.590053
iter  70 value 81.273139
iter  80 value 80.671524
iter  90 value 80.269314
iter 100 value 80.215796
final  value 80.215796 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 115.365315 
iter  10 value 94.485688
iter  20 value 94.160752
iter  30 value 90.773100
iter  40 value 85.497515
iter  50 value 84.689288
iter  60 value 82.815765
iter  70 value 82.587870
iter  80 value 82.457672
iter  90 value 81.804261
iter 100 value 80.644937
final  value 80.644937 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 116.047344 
iter  10 value 96.012718
iter  20 value 90.247487
iter  30 value 85.529278
iter  40 value 84.758231
iter  50 value 83.502781
iter  60 value 81.375671
iter  70 value 81.262487
iter  80 value 81.073650
iter  90 value 80.276962
iter 100 value 79.862160
final  value 79.862160 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.171579 
iter  10 value 94.440016
iter  20 value 92.586283
iter  30 value 86.794865
iter  40 value 85.530934
iter  50 value 81.754772
iter  60 value 80.571383
iter  70 value 80.077520
iter  80 value 79.765910
iter  90 value 79.548392
iter 100 value 79.248256
final  value 79.248256 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 116.649507 
iter  10 value 94.195734
iter  20 value 92.013091
iter  30 value 85.283319
iter  40 value 82.290858
iter  50 value 81.746142
iter  60 value 81.147177
iter  70 value 80.545136
iter  80 value 80.369543
iter  90 value 80.014929
iter 100 value 79.944209
final  value 79.944209 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.845976 
iter  10 value 94.399134
iter  20 value 88.453522
iter  30 value 81.820583
iter  40 value 80.932532
iter  50 value 80.271454
iter  60 value 79.827185
iter  70 value 79.633867
iter  80 value 79.302457
iter  90 value 79.118690
iter 100 value 79.085285
final  value 79.085285 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.007070 
iter  10 value 91.041353
iter  20 value 87.643523
iter  30 value 86.004996
iter  40 value 84.240251
iter  50 value 83.133496
iter  60 value 82.432064
iter  70 value 80.196535
iter  80 value 79.590415
iter  90 value 79.324158
iter 100 value 79.230539
final  value 79.230539 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 108.232040 
final  value 94.485874 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.266062 
final  value 94.488084 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.496918 
final  value 94.486072 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.266036 
final  value 94.485962 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.028859 
final  value 94.485774 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.852722 
iter  10 value 94.331230
iter  20 value 94.326617
iter  30 value 94.326267
final  value 94.326245 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.164375 
iter  10 value 94.488339
iter  20 value 93.838248
iter  30 value 91.962955
iter  40 value 91.959266
iter  50 value 91.958359
iter  60 value 90.480610
iter  70 value 82.828264
iter  80 value 81.941840
iter  90 value 81.924735
iter 100 value 81.921134
final  value 81.921134 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 112.139496 
iter  10 value 87.510579
iter  20 value 82.633073
iter  30 value 82.619826
final  value 82.329981 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.140663 
iter  10 value 94.488339
iter  20 value 93.629928
iter  30 value 87.167980
iter  40 value 86.732225
iter  50 value 86.731995
iter  60 value 86.731671
iter  70 value 84.249451
iter  80 value 84.185476
iter  90 value 83.780211
iter 100 value 83.620973
final  value 83.620973 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 126.974951 
iter  10 value 93.913173
iter  20 value 83.927766
iter  30 value 82.735267
iter  40 value 81.524679
iter  50 value 81.486920
iter  60 value 81.484012
iter  70 value 79.735727
iter  80 value 79.563590
iter  90 value 79.517848
iter 100 value 79.473120
final  value 79.473120 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.049069 
iter  10 value 94.452104
iter  20 value 94.445742
iter  30 value 94.444872
iter  40 value 93.103115
iter  50 value 82.852249
iter  60 value 82.804711
iter  70 value 82.333380
iter  80 value 82.238268
iter  90 value 82.196179
iter 100 value 82.196030
final  value 82.196030 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 94.837858 
iter  10 value 94.451317
iter  20 value 94.375880
iter  30 value 92.126200
iter  40 value 91.932655
iter  50 value 85.440372
iter  60 value 81.679463
iter  70 value 81.630771
iter  80 value 81.629968
iter  90 value 81.629329
final  value 81.629234 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.956847 
iter  10 value 94.334042
iter  20 value 93.751610
iter  30 value 93.612576
iter  40 value 91.921957
iter  50 value 91.199293
iter  60 value 91.081632
final  value 91.079591 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.788814 
iter  10 value 94.148096
iter  20 value 94.145685
iter  30 value 93.950928
iter  40 value 93.948482
iter  50 value 93.943503
iter  60 value 93.069079
iter  70 value 91.498225
iter  80 value 90.840341
final  value 90.800339 
converged
Fitting Repeat 5 

# weights:  507
initial  value 121.160102 
iter  10 value 94.294164
iter  20 value 94.260882
iter  30 value 94.255923
iter  40 value 94.229927
final  value 94.229923 
converged
Fitting Repeat 1 

# weights:  103
initial  value 94.082791 
iter  10 value 83.835820
final  value 83.783302 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.432788 
final  value 94.354396 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.446148 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.656295 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.588067 
final  value 94.484214 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.896265 
final  value 94.323810 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.605249 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.450876 
iter  10 value 93.037881
final  value 93.037879 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.821931 
final  value 94.354396 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.733416 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.800226 
iter  10 value 94.338745
iter  10 value 94.338745
iter  10 value 94.338745
final  value 94.338745 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.032476 
final  value 94.354396 
converged
Fitting Repeat 3 

# weights:  507
initial  value 92.617052 
iter  10 value 82.422853
iter  20 value 82.370900
iter  30 value 82.366698
iter  40 value 82.366640
iter  40 value 82.366639
iter  40 value 82.366639
final  value 82.366639 
converged
Fitting Repeat 4 

# weights:  507
initial  value 127.887073 
iter  10 value 95.127765
iter  20 value 93.439467
final  value 93.439442 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.157841 
iter  10 value 94.167835
iter  20 value 86.082223
iter  30 value 82.374501
iter  40 value 82.017580
iter  50 value 81.310875
iter  60 value 80.539450
iter  70 value 80.505258
iter  80 value 80.505046
iter  80 value 80.505046
iter  80 value 80.505046
final  value 80.505046 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.993510 
iter  10 value 94.486538
iter  20 value 92.971351
iter  30 value 92.445387
iter  40 value 92.340884
iter  50 value 92.329537
iter  60 value 92.328373
iter  70 value 92.328191
iter  80 value 86.665096
iter  90 value 84.324740
iter 100 value 83.575469
final  value 83.575469 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 103.590044 
iter  10 value 94.486599
iter  20 value 94.290307
iter  30 value 94.193797
iter  40 value 94.139968
iter  50 value 90.219226
iter  60 value 87.173613
iter  70 value 82.448284
iter  80 value 81.533451
iter  90 value 80.885774
iter 100 value 79.500713
final  value 79.500713 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 101.284031 
iter  10 value 94.348478
iter  20 value 86.175068
iter  30 value 85.531022
iter  40 value 84.051055
iter  50 value 83.452065
iter  60 value 83.093749
iter  70 value 82.925381
final  value 82.925363 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.869695 
iter  10 value 94.434237
iter  20 value 87.888604
iter  30 value 84.851424
iter  40 value 83.422916
iter  50 value 83.254073
iter  60 value 83.044438
iter  70 value 82.935958
final  value 82.925363 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.337712 
iter  10 value 94.464466
iter  20 value 88.897826
iter  30 value 87.674570
iter  40 value 85.524095
iter  50 value 83.567248
iter  60 value 83.351260
final  value 83.345310 
converged
Fitting Repeat 1 

# weights:  305
initial  value 121.648205 
iter  10 value 94.494534
iter  20 value 94.397657
iter  30 value 90.786232
iter  40 value 85.005058
iter  50 value 80.239002
iter  60 value 77.615298
iter  70 value 76.566433
iter  80 value 76.063233
iter  90 value 76.023083
iter 100 value 75.888651
final  value 75.888651 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 125.146731 
iter  10 value 94.372604
iter  20 value 92.261684
iter  30 value 87.072504
iter  40 value 84.350777
iter  50 value 83.063194
iter  60 value 80.531403
iter  70 value 78.793555
iter  80 value 76.787597
iter  90 value 76.135374
iter 100 value 75.461239
final  value 75.461239 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.306566 
iter  10 value 91.373286
iter  20 value 86.054799
iter  30 value 83.867639
iter  40 value 82.533932
iter  50 value 82.193252
iter  60 value 82.134454
iter  70 value 82.079850
iter  80 value 82.005252
iter  90 value 81.666656
iter 100 value 79.049664
final  value 79.049664 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.193790 
iter  10 value 94.484072
iter  20 value 88.297059
iter  30 value 83.147526
iter  40 value 82.785550
iter  50 value 82.480229
iter  60 value 81.795746
iter  70 value 81.726525
final  value 81.725714 
converged
Fitting Repeat 5 

# weights:  305
initial  value 109.268450 
iter  10 value 95.702273
iter  20 value 87.651630
iter  30 value 85.595350
iter  40 value 85.271111
iter  50 value 84.063605
iter  60 value 79.823621
iter  70 value 77.390443
iter  80 value 76.750487
iter  90 value 76.705918
iter 100 value 76.586935
final  value 76.586935 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.525889 
iter  10 value 94.766866
iter  20 value 94.047178
iter  30 value 83.602922
iter  40 value 80.678087
iter  50 value 79.886091
iter  60 value 78.279538
iter  70 value 77.478515
iter  80 value 76.805148
iter  90 value 76.677059
iter 100 value 76.450827
final  value 76.450827 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.755551 
iter  10 value 94.762756
iter  20 value 93.951726
iter  30 value 85.189069
iter  40 value 83.695772
iter  50 value 81.664928
iter  60 value 81.383753
iter  70 value 79.422963
iter  80 value 78.936355
iter  90 value 78.187477
iter 100 value 77.685193
final  value 77.685193 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 123.865572 
iter  10 value 94.612633
iter  20 value 93.825739
iter  30 value 91.142379
iter  40 value 87.984603
iter  50 value 84.257709
iter  60 value 81.398142
iter  70 value 77.903698
iter  80 value 76.423139
iter  90 value 75.552221
iter 100 value 75.294989
final  value 75.294989 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 116.379148 
iter  10 value 94.789247
iter  20 value 93.301309
iter  30 value 91.816532
iter  40 value 88.208442
iter  50 value 83.772979
iter  60 value 83.174528
iter  70 value 81.618687
iter  80 value 80.100039
iter  90 value 79.802140
iter 100 value 78.383735
final  value 78.383735 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 118.222993 
iter  10 value 94.526683
iter  20 value 94.422382
iter  30 value 94.241138
iter  40 value 88.212695
iter  50 value 85.708863
iter  60 value 85.571464
iter  70 value 80.165634
iter  80 value 79.629559
iter  90 value 78.219368
iter 100 value 76.498946
final  value 76.498946 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.084847 
final  value 94.355941 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.923077 
final  value 94.486055 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.805831 
iter  10 value 94.486043
iter  20 value 94.483806
iter  30 value 86.565718
iter  30 value 86.565718
iter  30 value 86.565718
final  value 86.565718 
converged
Fitting Repeat 4 

# weights:  103
initial  value 109.402878 
final  value 94.485926 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.676153 
iter  10 value 94.356234
iter  20 value 94.355027
iter  30 value 94.354615
final  value 94.354610 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.011702 
iter  10 value 94.359294
iter  20 value 94.355438
iter  30 value 94.139695
iter  40 value 83.794280
iter  50 value 83.788043
iter  60 value 83.779527
iter  70 value 83.778614
iter  80 value 83.777677
iter  90 value 83.682789
iter 100 value 83.508918
final  value 83.508918 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 112.789718 
iter  10 value 93.706665
iter  20 value 93.702632
final  value 93.702172 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.456721 
iter  10 value 94.488946
iter  20 value 94.484283
final  value 94.484271 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.568172 
iter  10 value 94.359608
iter  20 value 94.354695
final  value 94.354503 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.966848 
iter  10 value 94.358503
iter  20 value 94.355009
iter  30 value 94.314399
iter  40 value 82.662146
iter  50 value 82.630915
iter  60 value 82.311019
iter  70 value 82.308260
iter  80 value 82.306553
final  value 82.306393 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.422850 
iter  10 value 94.493267
iter  20 value 94.413941
iter  30 value 86.854237
iter  40 value 79.644278
iter  50 value 78.852837
iter  60 value 78.123059
iter  70 value 77.618863
iter  80 value 77.554493
final  value 77.544325 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.641299 
iter  10 value 94.492108
iter  20 value 93.999266
iter  30 value 86.389060
iter  40 value 83.685728
iter  50 value 80.106378
iter  60 value 78.878269
iter  70 value 76.588382
iter  80 value 76.278129
iter  90 value 76.126551
iter 100 value 75.713280
final  value 75.713280 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 100.035416 
iter  10 value 94.346762
iter  20 value 94.334300
iter  30 value 94.314051
iter  40 value 94.311466
iter  50 value 84.630169
iter  60 value 83.025007
iter  70 value 83.024433
iter  80 value 82.920665
iter  90 value 81.874208
iter 100 value 81.647455
final  value 81.647455 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 100.636099 
iter  10 value 82.670946
iter  20 value 81.284970
final  value 81.274005 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.649062 
iter  10 value 93.722415
iter  20 value 93.700774
iter  30 value 93.694294
iter  40 value 93.693331
iter  40 value 93.693330
final  value 93.693326 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.478848 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.097727 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.390181 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.282736 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.699388 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.973242 
iter  10 value 92.966636
iter  20 value 87.951730
final  value 87.951515 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.869767 
iter  10 value 88.883352
iter  20 value 88.644228
iter  30 value 88.644140
iter  30 value 88.644139
iter  30 value 88.644139
final  value 88.644139 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.263997 
iter  10 value 94.437144
iter  20 value 94.436658
iter  30 value 91.637730
iter  40 value 89.388684
iter  50 value 89.318274
final  value 89.315530 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.262136 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 111.859265 
final  value 94.338745 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.603405 
iter  10 value 89.260974
final  value 87.951515 
converged
Fitting Repeat 2 

# weights:  507
initial  value 112.523051 
iter  10 value 94.311474
final  value 94.309524 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.303851 
iter  10 value 88.613642
iter  20 value 86.233655
iter  30 value 85.958078
iter  40 value 85.923637
final  value 85.923622 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.025800 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.870025 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 108.413042 
iter  10 value 94.448594
iter  20 value 92.171347
iter  30 value 87.780690
iter  40 value 86.791935
iter  50 value 84.691615
iter  60 value 83.773091
iter  70 value 83.757974
iter  80 value 83.756837
iter  90 value 83.755748
final  value 83.755628 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.915095 
iter  10 value 94.491115
iter  20 value 93.929879
iter  30 value 88.589796
iter  40 value 86.554901
iter  50 value 84.993865
iter  60 value 83.675493
iter  70 value 83.353918
iter  80 value 83.338581
final  value 83.338577 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.755571 
iter  10 value 94.488229
iter  20 value 94.388297
iter  30 value 91.149176
iter  40 value 86.805201
iter  50 value 86.125424
iter  60 value 85.624611
iter  70 value 85.460288
iter  80 value 85.101611
iter  90 value 84.744081
iter 100 value 84.307435
final  value 84.307435 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 102.701923 
iter  10 value 94.462758
iter  20 value 90.007064
iter  30 value 88.554770
iter  40 value 87.121224
iter  50 value 86.341278
iter  60 value 83.836192
iter  70 value 83.370479
iter  80 value 83.331163
final  value 83.330323 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.553596 
iter  10 value 94.455579
iter  20 value 90.797005
iter  30 value 88.424687
iter  40 value 85.403142
iter  50 value 85.248986
iter  60 value 85.017904
final  value 85.002703 
converged
Fitting Repeat 1 

# weights:  305
initial  value 111.675467 
iter  10 value 94.834679
iter  20 value 85.705086
iter  30 value 85.518455
iter  40 value 84.119913
iter  50 value 82.177467
iter  60 value 81.560535
iter  70 value 81.199375
iter  80 value 80.962556
iter  90 value 80.931273
iter 100 value 80.882373
final  value 80.882373 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.673536 
iter  10 value 94.430312
iter  20 value 87.669628
iter  30 value 86.226909
iter  40 value 85.727219
iter  50 value 83.982939
iter  60 value 82.266685
iter  70 value 81.580808
iter  80 value 81.299875
iter  90 value 81.221508
iter 100 value 81.201250
final  value 81.201250 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 109.072382 
iter  10 value 94.487578
iter  20 value 94.474880
iter  30 value 92.299219
iter  40 value 85.981440
iter  50 value 84.935204
iter  60 value 84.045937
iter  70 value 83.764025
iter  80 value 83.653199
iter  90 value 83.536468
iter 100 value 83.526519
final  value 83.526519 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.842387 
iter  10 value 94.573194
iter  20 value 94.290755
iter  30 value 89.761384
iter  40 value 88.700319
iter  50 value 87.056388
iter  60 value 84.373086
iter  70 value 83.337654
iter  80 value 81.951342
iter  90 value 81.429462
iter 100 value 81.184651
final  value 81.184651 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.045512 
iter  10 value 94.387229
iter  20 value 86.890005
iter  30 value 84.763625
iter  40 value 84.471066
iter  50 value 84.209229
iter  60 value 82.059429
iter  70 value 81.619271
iter  80 value 81.563560
iter  90 value 81.494315
iter 100 value 81.455642
final  value 81.455642 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 111.032549 
iter  10 value 95.200942
iter  20 value 94.609194
iter  30 value 87.013185
iter  40 value 85.154305
iter  50 value 84.303938
iter  60 value 84.068640
iter  70 value 83.859580
iter  80 value 83.512136
iter  90 value 82.970930
iter 100 value 82.679352
final  value 82.679352 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.697122 
iter  10 value 94.223611
iter  20 value 89.745645
iter  30 value 86.660586
iter  40 value 84.648400
iter  50 value 84.420954
iter  60 value 83.820811
iter  70 value 83.530321
iter  80 value 82.953823
iter  90 value 81.833189
iter 100 value 81.252312
final  value 81.252312 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 121.708443 
iter  10 value 94.278366
iter  20 value 88.368187
iter  30 value 85.511470
iter  40 value 84.045862
iter  50 value 83.957187
iter  60 value 83.790993
iter  70 value 83.718997
iter  80 value 83.652881
iter  90 value 81.771748
iter 100 value 81.356985
final  value 81.356985 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.703844 
iter  10 value 91.444663
iter  20 value 84.434175
iter  30 value 83.799125
iter  40 value 83.446974
iter  50 value 83.294794
iter  60 value 83.180638
iter  70 value 83.169014
iter  80 value 82.569783
iter  90 value 81.729343
iter 100 value 81.488953
final  value 81.488953 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.002508 
iter  10 value 94.467294
iter  20 value 88.616504
iter  30 value 85.810026
iter  40 value 84.167485
iter  50 value 83.877439
iter  60 value 83.514269
iter  70 value 83.159398
iter  80 value 82.399161
iter  90 value 81.531241
iter 100 value 81.366698
final  value 81.366698 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.948931 
final  value 94.485781 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.421152 
iter  10 value 94.485612
final  value 94.484526 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.665652 
iter  10 value 94.485842
iter  20 value 94.370076
iter  30 value 91.762387
iter  40 value 91.740079
final  value 91.739940 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.036028 
final  value 94.485964 
converged
Fitting Repeat 5 

# weights:  103
initial  value 113.058563 
final  value 94.485888 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.377639 
iter  10 value 94.359343
iter  20 value 94.355056
iter  30 value 94.349421
iter  40 value 92.663838
iter  50 value 89.436538
iter  60 value 89.336445
iter  70 value 85.552870
iter  80 value 84.820157
iter  90 value 82.839425
iter 100 value 80.740444
final  value 80.740444 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 96.433322 
iter  10 value 94.359166
iter  20 value 93.004660
iter  30 value 92.302869
iter  40 value 92.302206
iter  40 value 92.302206
final  value 92.302206 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.173853 
iter  10 value 94.358909
iter  20 value 88.853720
iter  30 value 87.145309
iter  40 value 86.557881
iter  50 value 86.339577
final  value 86.338616 
converged
Fitting Repeat 4 

# weights:  305
initial  value 115.025248 
iter  10 value 94.488874
iter  20 value 94.484314
iter  30 value 92.438727
final  value 92.403731 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.582490 
iter  10 value 94.489429
iter  20 value 94.481479
iter  30 value 94.320079
final  value 94.308476 
converged
Fitting Repeat 1 

# weights:  507
initial  value 111.332340 
iter  10 value 94.491829
iter  20 value 93.820164
iter  30 value 86.871703
iter  40 value 85.788188
iter  50 value 85.782853
iter  60 value 85.741580
iter  70 value 85.739891
iter  80 value 85.527329
iter  90 value 84.927523
iter 100 value 84.653888
final  value 84.653888 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 98.753527 
iter  10 value 94.317763
iter  20 value 94.028325
iter  30 value 86.085165
iter  40 value 86.078104
iter  50 value 85.856282
iter  60 value 82.556382
iter  70 value 81.103223
iter  80 value 81.099892
iter  90 value 81.086744
iter 100 value 80.950328
final  value 80.950328 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 118.976118 
iter  10 value 88.644384
iter  20 value 87.057566
iter  30 value 86.908345
iter  40 value 86.899740
final  value 86.899606 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.043348 
iter  10 value 93.410297
iter  20 value 92.574359
iter  30 value 92.572378
iter  40 value 92.564199
iter  50 value 92.269406
iter  60 value 91.869753
iter  70 value 91.656780
iter  80 value 91.606385
iter  90 value 91.589403
iter 100 value 91.589000
final  value 91.589000 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 100.218009 
iter  10 value 89.061042
iter  20 value 87.952295
iter  30 value 87.946819
iter  40 value 87.185906
iter  50 value 85.948578
iter  60 value 85.775298
iter  70 value 83.895691
iter  80 value 83.416253
iter  90 value 83.401962
iter 100 value 83.401578
final  value 83.401578 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.538360 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.173723 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.747210 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.587284 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.199813 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.309281 
final  value 93.671508 
converged
Fitting Repeat 2 

# weights:  305
initial  value 116.409016 
iter  10 value 94.052910
iter  10 value 94.052910
iter  10 value 94.052910
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 108.219971 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.548633 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.945227 
final  value 94.008696 
converged
Fitting Repeat 1 

# weights:  507
initial  value 122.462622 
iter  10 value 92.380146
iter  20 value 88.537769
iter  30 value 87.437567
iter  40 value 87.237576
iter  50 value 87.229480
final  value 87.229377 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.993899 
iter  10 value 89.096392
iter  20 value 88.790152
final  value 88.789942 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.181636 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 114.194897 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.421222 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.571666 
iter  10 value 93.961440
iter  20 value 89.634605
iter  30 value 89.337418
iter  40 value 87.543791
iter  50 value 86.521667
iter  60 value 86.217024
iter  70 value 86.099462
iter  80 value 85.946294
iter  90 value 85.899068
iter 100 value 85.857978
final  value 85.857978 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 119.395435 
iter  10 value 94.041643
iter  20 value 91.573965
iter  30 value 89.383888
iter  40 value 87.843060
iter  50 value 87.262659
iter  60 value 86.126037
iter  70 value 85.865063
iter  80 value 85.575388
iter  90 value 85.451316
final  value 85.451271 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.818401 
iter  10 value 93.758183
iter  20 value 89.839419
iter  30 value 88.326691
iter  40 value 88.195774
iter  50 value 87.939408
iter  60 value 87.756597
iter  70 value 87.368928
iter  80 value 87.337322
final  value 87.337266 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.062586 
iter  10 value 94.042136
iter  20 value 90.808762
iter  30 value 88.666425
iter  40 value 87.939916
iter  50 value 87.164742
iter  60 value 86.981483
final  value 86.978357 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.266512 
iter  10 value 94.056488
iter  20 value 89.494609
iter  30 value 88.622986
iter  40 value 87.533680
iter  50 value 87.374034
iter  60 value 87.352940
final  value 87.349203 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.580861 
iter  10 value 94.093799
iter  20 value 94.050977
iter  30 value 93.882783
iter  40 value 92.562220
iter  50 value 92.160199
iter  60 value 90.666923
iter  70 value 86.624712
iter  80 value 85.226022
iter  90 value 85.070075
iter 100 value 84.641435
final  value 84.641435 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 109.146714 
iter  10 value 94.142140
iter  20 value 89.254958
iter  30 value 88.413204
iter  40 value 87.996649
iter  50 value 87.366354
iter  60 value 86.318468
iter  70 value 86.165407
iter  80 value 85.649432
iter  90 value 84.809388
iter 100 value 84.269340
final  value 84.269340 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.294668 
iter  10 value 94.090059
iter  20 value 93.980679
iter  30 value 91.356010
iter  40 value 88.637013
iter  50 value 86.338773
iter  60 value 85.716954
iter  70 value 85.118507
iter  80 value 84.880269
iter  90 value 84.734231
iter 100 value 84.665561
final  value 84.665561 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 111.491389 
iter  10 value 94.820590
iter  20 value 94.341797
iter  30 value 94.053663
iter  40 value 93.984022
iter  50 value 93.594571
iter  60 value 91.702395
iter  70 value 91.488176
iter  80 value 89.046031
iter  90 value 87.425346
iter 100 value 87.295208
final  value 87.295208 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.610195 
iter  10 value 94.842513
iter  20 value 91.850596
iter  30 value 87.726517
iter  40 value 85.684861
iter  50 value 84.741043
iter  60 value 84.573806
iter  70 value 84.547402
iter  80 value 84.473197
iter  90 value 84.413229
iter 100 value 84.393030
final  value 84.393030 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 138.103421 
iter  10 value 93.601647
iter  20 value 89.756662
iter  30 value 88.551709
iter  40 value 86.411126
iter  50 value 84.976586
iter  60 value 84.265132
iter  70 value 84.160540
iter  80 value 84.070272
iter  90 value 84.052730
iter 100 value 84.036677
final  value 84.036677 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 115.696910 
iter  10 value 94.249975
iter  20 value 93.936406
iter  30 value 89.707337
iter  40 value 89.069870
iter  50 value 88.314326
iter  60 value 86.179767
iter  70 value 85.885534
iter  80 value 85.800351
iter  90 value 85.679079
iter 100 value 85.238562
final  value 85.238562 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 124.345900 
iter  10 value 94.224865
iter  20 value 93.753220
iter  30 value 88.082885
iter  40 value 87.153918
iter  50 value 85.963865
iter  60 value 85.166386
iter  70 value 84.749770
iter  80 value 84.445678
iter  90 value 84.118544
iter 100 value 83.834845
final  value 83.834845 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 117.914043 
iter  10 value 91.240845
iter  20 value 89.820273
iter  30 value 89.372238
iter  40 value 88.472001
iter  50 value 87.742449
iter  60 value 87.547524
iter  70 value 87.459490
iter  80 value 87.344156
iter  90 value 87.003457
iter 100 value 86.091213
final  value 86.091213 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 112.821006 
iter  10 value 95.851166
iter  20 value 92.563215
iter  30 value 89.939838
iter  40 value 88.448476
iter  50 value 86.631528
iter  60 value 85.029782
iter  70 value 84.674005
iter  80 value 84.537644
iter  90 value 84.494676
iter 100 value 84.403542
final  value 84.403542 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.040583 
final  value 94.054783 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.010100 
final  value 94.051739 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.532526 
iter  10 value 94.054483
iter  20 value 94.052859
iter  30 value 92.154329
iter  40 value 89.408631
final  value 89.408212 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.956263 
iter  10 value 94.054632
iter  20 value 94.052915
iter  30 value 93.855661
final  value 93.854833 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.928454 
final  value 94.054543 
converged
Fitting Repeat 1 

# weights:  305
initial  value 114.209848 
iter  10 value 94.057685
iter  20 value 94.034264
iter  30 value 91.524687
iter  40 value 90.522206
iter  50 value 88.905904
iter  60 value 84.586243
iter  70 value 83.899340
iter  80 value 83.784478
iter  90 value 83.675179
iter 100 value 83.653086
final  value 83.653086 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 95.403841 
iter  10 value 94.057826
iter  20 value 94.053095
iter  30 value 94.030999
iter  40 value 88.541528
iter  50 value 88.469809
iter  60 value 88.234119
iter  70 value 86.933967
iter  80 value 86.534637
iter  90 value 86.516922
iter 100 value 86.499765
final  value 86.499765 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 94.408698 
iter  10 value 94.013696
iter  20 value 94.009302
iter  30 value 94.008690
iter  40 value 89.924854
iter  50 value 88.213188
iter  60 value 88.061009
iter  70 value 85.082222
iter  80 value 84.677694
iter  90 value 84.330096
iter 100 value 84.326978
final  value 84.326978 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.839218 
iter  10 value 94.057719
iter  20 value 91.726319
iter  30 value 91.286890
iter  40 value 88.675381
iter  50 value 88.509133
final  value 88.509116 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.505207 
iter  10 value 94.057704
iter  20 value 93.838854
iter  30 value 89.198859
iter  40 value 88.938320
iter  50 value 88.776588
iter  60 value 88.709173
iter  70 value 88.110796
iter  80 value 86.288804
iter  90 value 86.266618
final  value 86.265846 
converged
Fitting Repeat 1 

# weights:  507
initial  value 117.321680 
iter  10 value 94.061831
iter  20 value 94.041545
iter  30 value 88.899377
iter  40 value 88.431398
iter  50 value 84.735060
iter  60 value 83.596545
iter  70 value 83.296516
iter  80 value 83.258069
final  value 83.257825 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.785731 
iter  10 value 93.751736
iter  20 value 92.995861
iter  30 value 92.988339
iter  40 value 92.479898
iter  50 value 92.341332
iter  60 value 91.896594
iter  70 value 91.881062
final  value 91.880477 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.815986 
iter  10 value 94.025622
iter  20 value 94.016400
iter  30 value 90.305552
final  value 88.786162 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.211832 
iter  10 value 94.019734
iter  20 value 93.882715
iter  30 value 93.698085
iter  40 value 93.659692
iter  50 value 93.657844
iter  60 value 93.656451
iter  70 value 93.655787
iter  80 value 93.655329
iter  90 value 93.654789
final  value 93.654547 
converged
Fitting Repeat 5 

# weights:  507
initial  value 121.938588 
iter  10 value 94.053503
iter  20 value 93.115546
iter  30 value 93.108011
iter  40 value 93.106334
iter  50 value 93.098333
iter  60 value 93.070786
iter  70 value 87.131771
iter  80 value 86.097482
iter  90 value 85.154842
iter 100 value 85.121897
final  value 85.121897 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 107.219584 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.288394 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.276295 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.911879 
final  value 93.836066 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.701557 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.062342 
iter  10 value 91.875332
iter  20 value 91.533496
iter  30 value 91.503719
final  value 91.503677 
converged
Fitting Repeat 2 

# weights:  305
initial  value 114.852916 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.343440 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.601745 
iter  10 value 92.933409
iter  20 value 92.933335
final  value 92.933333 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.780752 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.524894 
final  value 93.836066 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.564567 
iter  10 value 93.911535
iter  20 value 93.036404
iter  30 value 92.932160
final  value 92.925654 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.805346 
final  value 93.836066 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.003005 
iter  10 value 92.296643
iter  20 value 91.854452
final  value 91.854325 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.966921 
iter  10 value 93.183861
iter  10 value 93.183861
iter  10 value 93.183861
final  value 93.183861 
converged
Fitting Repeat 1 

# weights:  103
initial  value 107.884666 
iter  10 value 93.235765
iter  20 value 92.244398
iter  30 value 92.195654
iter  40 value 92.159337
iter  50 value 90.163826
iter  60 value 83.969864
iter  70 value 83.335458
iter  80 value 82.825792
iter  90 value 82.799080
final  value 82.799078 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.226726 
iter  10 value 94.076823
iter  20 value 93.972232
iter  30 value 87.986267
iter  40 value 83.747808
iter  50 value 83.370860
iter  60 value 82.493667
iter  70 value 82.433561
final  value 82.433523 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.676161 
iter  10 value 92.592711
iter  20 value 83.618621
iter  30 value 81.785820
iter  40 value 80.169977
iter  50 value 80.007228
iter  60 value 79.843511
iter  70 value 79.758190
final  value 79.757791 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.172200 
iter  10 value 94.075157
iter  20 value 94.048471
iter  30 value 93.433904
iter  40 value 90.165148
iter  50 value 89.376802
iter  60 value 83.956437
iter  70 value 83.036653
iter  80 value 82.182566
iter  90 value 81.998204
final  value 81.979454 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.958460 
iter  10 value 92.828267
iter  20 value 83.932920
iter  30 value 82.385495
iter  40 value 80.911298
iter  50 value 79.916720
iter  60 value 79.503529
final  value 79.442136 
converged
Fitting Repeat 1 

# weights:  305
initial  value 117.529575 
iter  10 value 94.039966
iter  20 value 92.299640
iter  30 value 92.184072
iter  40 value 92.081499
iter  50 value 83.917105
iter  60 value 82.741954
iter  70 value 82.552670
iter  80 value 82.171377
iter  90 value 80.903100
iter 100 value 79.758536
final  value 79.758536 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.549012 
iter  10 value 92.038855
iter  20 value 89.191070
iter  30 value 84.323487
iter  40 value 82.843341
iter  50 value 81.382626
iter  60 value 80.891696
iter  70 value 80.810018
iter  80 value 80.094020
iter  90 value 78.902189
iter 100 value 78.503885
final  value 78.503885 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.269738 
iter  10 value 91.085126
iter  20 value 85.048411
iter  30 value 82.914082
iter  40 value 82.250132
iter  50 value 82.085621
iter  60 value 81.906266
iter  70 value 81.596290
iter  80 value 80.618009
iter  90 value 79.804403
iter 100 value 78.977747
final  value 78.977747 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.996227 
iter  10 value 93.983951
iter  20 value 92.190942
iter  30 value 85.830068
iter  40 value 82.655279
iter  50 value 79.809820
iter  60 value 79.004052
iter  70 value 78.375201
iter  80 value 78.041117
iter  90 value 77.999456
iter 100 value 77.949138
final  value 77.949138 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.997483 
iter  10 value 95.530660
iter  20 value 93.534524
iter  30 value 92.340361
iter  40 value 92.008260
iter  50 value 84.416426
iter  60 value 82.634051
iter  70 value 80.112686
iter  80 value 78.458825
iter  90 value 78.129015
iter 100 value 77.929605
final  value 77.929605 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 128.970695 
iter  10 value 92.511301
iter  20 value 84.543661
iter  30 value 81.351981
iter  40 value 80.367741
iter  50 value 79.828499
iter  60 value 79.146290
iter  70 value 78.756708
iter  80 value 78.396149
iter  90 value 78.056915
iter 100 value 77.941447
final  value 77.941447 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.067437 
iter  10 value 93.926005
iter  20 value 92.552814
iter  30 value 81.587080
iter  40 value 79.507194
iter  50 value 78.415292
iter  60 value 78.282393
iter  70 value 78.062689
iter  80 value 77.969142
iter  90 value 77.854268
iter 100 value 77.696641
final  value 77.696641 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.314464 
iter  10 value 93.862841
iter  20 value 90.188820
iter  30 value 89.781397
iter  40 value 88.442942
iter  50 value 86.067466
iter  60 value 82.975851
iter  70 value 81.948066
iter  80 value 81.426739
iter  90 value 79.505674
iter 100 value 78.638398
final  value 78.638398 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 116.377979 
iter  10 value 93.944887
iter  20 value 84.092249
iter  30 value 83.217190
iter  40 value 82.154347
iter  50 value 80.148562
iter  60 value 79.467819
iter  70 value 79.156811
iter  80 value 79.082245
iter  90 value 78.919790
iter 100 value 78.828520
final  value 78.828520 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.925463 
iter  10 value 93.394259
iter  20 value 87.829895
iter  30 value 85.296133
iter  40 value 85.073969
iter  50 value 82.647896
iter  60 value 80.969431
iter  70 value 80.595897
iter  80 value 80.272004
iter  90 value 80.180366
iter 100 value 79.562006
final  value 79.562006 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.045574 
final  value 94.054443 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.200157 
iter  10 value 93.838049
iter  20 value 93.519643
iter  30 value 92.083730
iter  40 value 86.581197
iter  50 value 80.997241
iter  60 value 79.079247
iter  70 value 79.038471
iter  80 value 79.034777
iter  90 value 79.034563
iter 100 value 79.032813
final  value 79.032813 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.612424 
final  value 94.054496 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.126921 
iter  10 value 90.811881
iter  20 value 84.072830
iter  30 value 82.123667
iter  40 value 82.004149
iter  50 value 81.289204
iter  60 value 81.266546
iter  70 value 81.239162
iter  80 value 81.180999
iter  90 value 81.167644
final  value 81.167294 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.978866 
final  value 94.054572 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.302637 
iter  10 value 90.564065
iter  20 value 84.390775
iter  30 value 81.280738
iter  40 value 81.271819
iter  50 value 81.265509
final  value 81.265191 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.531106 
iter  10 value 93.841390
iter  20 value 93.341431
iter  30 value 92.069031
final  value 91.974667 
converged
Fitting Repeat 3 

# weights:  305
initial  value 109.299193 
iter  10 value 94.057805
final  value 94.053159 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.386701 
iter  10 value 91.826343
iter  20 value 91.573999
iter  30 value 91.515921
iter  40 value 91.515300
final  value 91.510794 
converged
Fitting Repeat 5 

# weights:  305
initial  value 115.093940 
iter  10 value 94.057619
iter  20 value 93.188107
iter  30 value 91.973716
final  value 91.973688 
converged
Fitting Repeat 1 

# weights:  507
initial  value 110.582986 
iter  10 value 90.801955
iter  20 value 89.068552
iter  30 value 89.061505
iter  40 value 86.177790
iter  50 value 85.593222
iter  60 value 85.071976
iter  70 value 85.058869
final  value 85.058836 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.670230 
iter  10 value 93.844096
iter  20 value 93.782865
iter  30 value 92.453291
iter  40 value 91.352829
iter  50 value 89.731476
iter  60 value 83.412664
iter  70 value 83.360596
iter  80 value 83.360309
iter  90 value 81.397829
final  value 81.314169 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.914138 
iter  10 value 92.247472
iter  20 value 90.278103
iter  30 value 90.036968
iter  40 value 90.034369
iter  50 value 87.620468
iter  60 value 87.342786
iter  70 value 87.035714
final  value 87.034772 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.672614 
iter  10 value 93.551230
iter  20 value 92.986777
iter  30 value 81.042735
iter  40 value 78.179858
iter  50 value 77.854808
final  value 77.853689 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.438752 
iter  10 value 91.979500
iter  20 value 91.957018
iter  30 value 91.366385
iter  40 value 89.265581
iter  50 value 86.482887
iter  60 value 85.957268
iter  70 value 85.936616
iter  80 value 85.705254
iter  90 value 85.245234
iter 100 value 85.237275
final  value 85.237275 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 120.632118 
iter  10 value 117.605849
iter  20 value 117.592500
iter  30 value 117.542193
iter  40 value 117.504305
iter  50 value 117.503374
iter  60 value 117.501296
iter  70 value 117.499616
iter  80 value 116.149890
iter  90 value 109.495216
iter 100 value 109.491394
final  value 109.491394 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 134.507946 
iter  10 value 117.899343
iter  20 value 117.891607
iter  30 value 111.376850
iter  40 value 110.595468
iter  50 value 109.128730
iter  60 value 106.926316
iter  70 value 106.924861
iter  80 value 106.922897
iter  90 value 106.883997
iter 100 value 106.878011
final  value 106.878011 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 132.975824 
iter  10 value 117.768445
iter  20 value 117.761875
iter  30 value 117.760466
iter  40 value 117.695251
iter  50 value 108.303924
iter  60 value 108.259723
iter  70 value 108.256190
iter  80 value 105.590819
iter  90 value 105.300776
final  value 105.300116 
converged
Fitting Repeat 4 

# weights:  507
initial  value 125.887870 
iter  10 value 117.898119
iter  20 value 117.893955
iter  30 value 116.259071
iter  40 value 115.230335
iter  50 value 115.227763
iter  60 value 115.225101
iter  70 value 115.223747
iter  80 value 115.222863
iter  90 value 115.221283
iter 100 value 115.028290
final  value 115.028290 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 130.587625 
iter  10 value 117.766891
iter  20 value 117.539400
iter  30 value 117.511467
final  value 117.511441 
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 Mar 12 00:22:59 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 
 40.249   0.875  93.487