##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings HPiP_1.12.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck’
* using R version 4.4.2 (2024-10-31)
* using platform: aarch64-unknown-linux-gnu
* R was compiled by
    aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0
    GNU Fortran (GCC) 12.3.1 (openEuler 12.3.1-36.oe2403)
* running under: openEuler 24.03 (LTS)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.12.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
var_imp       35.804  0.355  36.250
corr_plot     34.086  0.252  34.418
FSmethod      34.021  0.263  34.362
pred_ensembel 17.489  0.348  16.631
enrichfindP    0.498  0.019  21.931
getFASTA       0.124  0.024   6.209
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

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

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/R/R-4.4.2/site-library’
* installing *source* package ‘HPiP’ ...
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R version 4.4.2 (2024-10-31) -- "Pile of Leaves"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-unknown-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 94.558135 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.214340 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 111.747267 
final  value 94.305882 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.197391 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.765017 
iter  10 value 94.088257
iter  20 value 94.002158
iter  20 value 94.002158
iter  20 value 94.002158
final  value 94.002158 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.717349 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.361030 
iter  10 value 94.275365
final  value 94.275362 
converged
Fitting Repeat 3 

# weights:  305
initial  value 108.032774 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.346367 
iter  10 value 93.701685
final  value 93.701657 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.179223 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 132.131505 
iter  10 value 91.967391
iter  20 value 86.524842
iter  30 value 86.495791
final  value 86.495642 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.423996 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.756529 
final  value 94.275362 
converged
Fitting Repeat 4 

# weights:  507
initial  value 111.684449 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.704653 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.186888 
iter  10 value 94.496140
iter  20 value 94.377591
iter  30 value 94.121283
iter  40 value 87.723022
iter  50 value 87.129821
iter  60 value 87.061505
iter  70 value 86.857684
iter  80 value 85.887621
iter  90 value 85.522131
iter 100 value 85.502478
final  value 85.502478 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 103.793546 
iter  10 value 94.474523
iter  20 value 94.016210
iter  30 value 92.826920
iter  40 value 87.671113
iter  50 value 85.370719
iter  60 value 84.663046
iter  70 value 83.935204
iter  80 value 82.989633
iter  90 value 82.878603
iter 100 value 82.852796
final  value 82.852796 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 102.724181 
iter  10 value 94.483841
iter  20 value 87.449049
iter  30 value 85.658976
iter  40 value 85.108812
iter  50 value 85.023509
iter  60 value 84.977680
iter  70 value 84.698466
iter  80 value 84.564659
iter  90 value 84.562559
final  value 84.562558 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.054363 
iter  10 value 94.454973
iter  20 value 90.799324
iter  30 value 87.314496
iter  40 value 87.081432
iter  50 value 86.439208
iter  60 value 86.085157
iter  70 value 85.552467
iter  80 value 85.336127
final  value 85.336116 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.540817 
iter  10 value 94.497619
iter  20 value 94.135216
iter  30 value 92.461025
iter  40 value 89.980664
iter  50 value 87.751835
iter  60 value 83.691066
iter  70 value 83.190791
iter  80 value 83.106804
iter  90 value 82.924797
iter 100 value 82.862349
final  value 82.862349 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 106.449501 
iter  10 value 94.741025
iter  20 value 93.257007
iter  30 value 92.607462
iter  40 value 87.562776
iter  50 value 86.086798
iter  60 value 85.068484
iter  70 value 85.005872
iter  80 value 84.832021
iter  90 value 84.616304
iter 100 value 83.706938
final  value 83.706938 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 98.505116 
iter  10 value 93.277110
iter  20 value 89.031898
iter  30 value 86.160686
iter  40 value 85.573957
iter  50 value 84.313528
iter  60 value 82.794141
iter  70 value 82.503424
iter  80 value 82.095143
iter  90 value 81.981810
iter 100 value 81.907405
final  value 81.907405 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.795035 
iter  10 value 94.418794
iter  20 value 91.821668
iter  30 value 87.415197
iter  40 value 86.182019
iter  50 value 85.498484
iter  60 value 85.361160
iter  70 value 85.209025
iter  80 value 84.903906
iter  90 value 83.127940
iter 100 value 81.578002
final  value 81.578002 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.013337 
iter  10 value 94.478049
iter  20 value 88.373267
iter  30 value 84.143624
iter  40 value 83.737307
iter  50 value 83.542647
iter  60 value 82.417186
iter  70 value 81.986759
iter  80 value 81.890150
iter  90 value 81.749510
iter 100 value 81.607738
final  value 81.607738 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.775644 
iter  10 value 89.121022
iter  20 value 85.630727
iter  30 value 84.831146
iter  40 value 84.045009
iter  50 value 83.906175
iter  60 value 83.561820
iter  70 value 83.398740
iter  80 value 82.975550
iter  90 value 82.146702
iter 100 value 81.874086
final  value 81.874086 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.206457 
iter  10 value 94.541959
iter  20 value 91.180456
iter  30 value 87.378260
iter  40 value 86.907761
iter  50 value 85.446835
iter  60 value 84.906529
iter  70 value 84.824667
iter  80 value 82.630624
iter  90 value 81.841701
iter 100 value 81.674709
final  value 81.674709 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.077117 
iter  10 value 94.790691
iter  20 value 90.364788
iter  30 value 88.944886
iter  40 value 86.267196
iter  50 value 84.604563
iter  60 value 84.093377
iter  70 value 83.913058
iter  80 value 83.473363
iter  90 value 82.550995
iter 100 value 81.384045
final  value 81.384045 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 127.829163 
iter  10 value 95.407628
iter  20 value 94.723393
iter  30 value 93.616151
iter  40 value 91.518041
iter  50 value 85.672639
iter  60 value 84.569868
iter  70 value 83.275566
iter  80 value 83.072807
iter  90 value 82.759705
iter 100 value 82.601511
final  value 82.601511 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.196351 
iter  10 value 94.565219
iter  20 value 92.585628
iter  30 value 86.950648
iter  40 value 86.610850
iter  50 value 85.907882
iter  60 value 85.751508
iter  70 value 85.435759
iter  80 value 84.833449
iter  90 value 82.359946
iter 100 value 81.985986
final  value 81.985986 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.090730 
iter  10 value 94.831930
iter  20 value 94.163357
iter  30 value 87.257930
iter  40 value 86.960160
iter  50 value 85.941179
iter  60 value 83.370835
iter  70 value 83.036624
iter  80 value 82.493431
iter  90 value 81.501995
iter 100 value 81.333727
final  value 81.333727 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.244096 
final  value 94.485797 
converged
Fitting Repeat 2 

# weights:  103
initial  value 110.547778 
final  value 94.485892 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.529526 
final  value 94.485866 
converged
Fitting Repeat 4 

# weights:  103
initial  value 116.584126 
final  value 94.486724 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.886135 
final  value 94.485794 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.495986 
iter  10 value 94.488838
iter  20 value 94.458937
iter  30 value 94.113896
iter  40 value 94.112828
final  value 94.112800 
converged
Fitting Repeat 2 

# weights:  305
initial  value 113.924118 
iter  10 value 94.489075
iter  20 value 94.106354
final  value 93.995587 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.869078 
iter  10 value 94.488966
iter  20 value 91.442281
iter  30 value 88.383238
iter  40 value 86.556937
iter  50 value 86.429421
iter  60 value 86.386483
iter  70 value 86.326117
iter  80 value 84.296232
iter  90 value 84.173400
iter 100 value 84.155522
final  value 84.155522 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 123.878332 
iter  10 value 94.488780
iter  20 value 94.484252
iter  30 value 93.998522
iter  40 value 87.627846
iter  50 value 84.875346
iter  60 value 84.415625
iter  70 value 80.875453
iter  80 value 80.660026
iter  90 value 80.620514
iter 100 value 80.125056
final  value 80.125056 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.907451 
iter  10 value 94.280708
iter  20 value 94.275888
iter  30 value 86.493693
iter  40 value 86.493167
final  value 86.493110 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.093960 
iter  10 value 94.283216
iter  20 value 94.275942
iter  30 value 94.141636
final  value 94.052842 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.449739 
iter  10 value 94.491879
iter  20 value 94.484260
iter  30 value 92.769821
iter  40 value 88.332053
iter  50 value 85.393682
iter  60 value 82.391189
iter  70 value 82.247025
iter  80 value 82.222765
iter  90 value 82.143492
iter 100 value 82.139918
final  value 82.139918 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 98.203464 
iter  10 value 94.283732
iter  20 value 94.270503
iter  30 value 93.770176
iter  40 value 87.540695
iter  50 value 87.178140
iter  60 value 87.173869
iter  70 value 87.163274
final  value 87.163221 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.296643 
iter  10 value 94.494669
iter  20 value 94.486501
iter  30 value 91.555198
iter  40 value 89.678479
final  value 89.429674 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.633460 
iter  10 value 94.491901
iter  20 value 94.144494
iter  30 value 87.743624
iter  40 value 85.466183
iter  50 value 85.465817
final  value 85.465791 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.726503 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.321909 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.093014 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.471545 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.415594 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.983260 
final  value 94.035941 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.010601 
iter  10 value 94.036958
iter  20 value 94.008795
final  value 94.008696 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.593418 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.742121 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.107123 
iter  10 value 93.100811
iter  20 value 93.093218
final  value 93.093198 
converged
Fitting Repeat 1 

# weights:  507
initial  value 111.057009 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.658125 
final  value 94.038251 
converged
Fitting Repeat 3 

# weights:  507
initial  value 108.620226 
final  value 94.038252 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.237539 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 113.205318 
final  value 94.038251 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.015694 
iter  10 value 94.061784
iter  20 value 93.240171
iter  30 value 88.610952
iter  40 value 86.307877
iter  50 value 84.396041
iter  60 value 83.059116
iter  70 value 82.821282
iter  80 value 82.689145
iter  90 value 82.464437
iter 100 value 82.403718
final  value 82.403718 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 106.155445 
iter  10 value 94.048879
iter  20 value 86.968648
iter  30 value 85.012368
iter  40 value 84.757783
iter  50 value 84.148583
iter  60 value 83.445102
iter  70 value 83.194520
final  value 83.194365 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.735618 
iter  10 value 94.062051
iter  20 value 88.882935
iter  30 value 86.259020
iter  40 value 83.714230
iter  50 value 83.267044
iter  60 value 83.194476
final  value 83.194364 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.802596 
iter  10 value 94.129761
iter  20 value 94.055203
iter  30 value 91.980123
iter  40 value 89.560044
iter  50 value 86.128667
iter  60 value 85.814123
iter  70 value 85.717885
iter  80 value 85.136462
iter  90 value 83.615534
iter 100 value 83.194438
final  value 83.194438 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 95.899088 
iter  10 value 94.027750
iter  20 value 92.956139
iter  30 value 90.226355
iter  40 value 85.117972
iter  50 value 84.440076
iter  60 value 84.002512
iter  70 value 83.365903
iter  80 value 81.980406
iter  90 value 81.801873
final  value 81.801541 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.737139 
iter  10 value 94.066750
iter  20 value 92.805303
iter  30 value 85.531961
iter  40 value 83.597389
iter  50 value 82.923056
iter  60 value 82.832885
iter  70 value 82.618649
iter  80 value 82.347427
iter  90 value 82.226873
iter 100 value 82.192149
final  value 82.192149 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.146421 
iter  10 value 93.875683
iter  20 value 91.380449
iter  30 value 87.243017
iter  40 value 84.477723
iter  50 value 83.851307
iter  60 value 81.140457
iter  70 value 80.662760
iter  80 value 80.307437
iter  90 value 80.258636
iter 100 value 80.122124
final  value 80.122124 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 136.165825 
iter  10 value 93.932677
iter  20 value 90.764676
iter  30 value 85.566122
iter  40 value 84.311730
iter  50 value 83.799815
iter  60 value 82.997256
iter  70 value 82.532862
iter  80 value 82.422285
iter  90 value 82.409647
iter 100 value 82.274129
final  value 82.274129 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.019823 
iter  10 value 93.840431
iter  20 value 88.220815
iter  30 value 84.542373
iter  40 value 82.644623
iter  50 value 82.035200
iter  60 value 81.305779
iter  70 value 80.826941
iter  80 value 80.675313
iter  90 value 80.615084
iter 100 value 80.334981
final  value 80.334981 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.918667 
iter  10 value 94.066291
iter  20 value 88.497841
iter  30 value 88.293592
iter  40 value 87.761641
iter  50 value 84.861459
iter  60 value 83.189045
iter  70 value 81.560871
iter  80 value 80.641373
iter  90 value 80.394944
iter 100 value 80.260370
final  value 80.260370 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.355898 
iter  10 value 94.093604
iter  20 value 85.227520
iter  30 value 84.832638
iter  40 value 83.055787
iter  50 value 82.320322
iter  60 value 82.211723
iter  70 value 82.081796
iter  80 value 82.034610
iter  90 value 81.594672
iter 100 value 80.877950
final  value 80.877950 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.114053 
iter  10 value 94.093169
iter  20 value 94.056186
iter  30 value 93.845137
iter  40 value 86.284290
iter  50 value 84.708260
iter  60 value 84.475315
iter  70 value 83.714945
iter  80 value 82.851918
iter  90 value 81.595335
iter 100 value 81.334564
final  value 81.334564 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.093222 
iter  10 value 92.647201
iter  20 value 86.124471
iter  30 value 85.566371
iter  40 value 84.357691
iter  50 value 82.624508
iter  60 value 81.791570
iter  70 value 80.739476
iter  80 value 80.523953
iter  90 value 79.958903
iter 100 value 79.816896
final  value 79.816896 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.231159 
iter  10 value 94.073312
iter  20 value 85.045762
iter  30 value 83.934788
iter  40 value 82.106979
iter  50 value 81.539334
iter  60 value 80.945657
iter  70 value 80.214482
iter  80 value 79.902733
iter  90 value 79.859293
iter 100 value 79.799446
final  value 79.799446 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 124.693187 
iter  10 value 94.463559
iter  20 value 94.123403
iter  30 value 87.018946
iter  40 value 84.882997
iter  50 value 83.172124
iter  60 value 82.908551
iter  70 value 82.529228
iter  80 value 81.577290
iter  90 value 80.699692
iter 100 value 80.309755
final  value 80.309755 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 107.733039 
iter  10 value 94.054482
iter  20 value 93.677708
iter  30 value 84.911561
final  value 84.894532 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.230531 
iter  10 value 94.054497
iter  20 value 94.046676
iter  30 value 85.580070
iter  40 value 85.482508
iter  50 value 84.199709
iter  60 value 84.152876
iter  70 value 84.144783
iter  80 value 84.142087
iter  90 value 84.109578
iter 100 value 84.106530
final  value 84.106530 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 95.902774 
final  value 94.054643 
converged
Fitting Repeat 4 

# weights:  103
initial  value 110.575586 
iter  10 value 88.782336
final  value 88.778868 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.713359 
final  value 94.054494 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.902086 
iter  10 value 94.056769
iter  20 value 93.878716
final  value 92.359381 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.553317 
iter  10 value 94.043123
iter  20 value 93.909069
iter  30 value 92.536898
iter  40 value 84.652220
iter  50 value 84.267896
iter  60 value 84.267308
final  value 84.267257 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.606774 
iter  10 value 94.057251
iter  20 value 89.131804
iter  30 value 82.754369
iter  40 value 82.738767
iter  50 value 82.113324
iter  60 value 82.087681
iter  70 value 82.086859
iter  80 value 81.952470
final  value 81.952041 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.476054 
iter  10 value 94.054836
iter  20 value 93.988250
iter  30 value 92.658115
iter  40 value 92.654295
iter  50 value 92.654116
iter  60 value 92.653743
iter  70 value 92.567132
iter  80 value 92.123039
iter  90 value 85.990002
iter 100 value 81.654389
final  value 81.654389 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 96.285627 
iter  10 value 94.057094
iter  20 value 93.891811
iter  30 value 84.356113
iter  40 value 83.652301
iter  50 value 83.575889
iter  60 value 83.544308
iter  70 value 83.476311
iter  80 value 83.362139
iter  90 value 83.361166
final  value 83.361152 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.631752 
iter  10 value 94.061795
iter  20 value 94.040269
iter  30 value 93.597821
iter  40 value 83.434238
iter  50 value 82.908927
iter  60 value 81.565946
iter  70 value 81.200319
iter  80 value 80.394980
iter  90 value 80.388104
iter 100 value 80.387793
final  value 80.387793 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 102.047109 
iter  10 value 90.135121
iter  20 value 87.528375
iter  30 value 85.845764
iter  40 value 85.219581
iter  50 value 85.216681
iter  60 value 85.097248
iter  70 value 85.091853
iter  80 value 83.284602
iter  90 value 83.151954
iter 100 value 83.134060
final  value 83.134060 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.521814 
iter  10 value 92.836079
iter  20 value 85.117706
iter  30 value 82.955784
iter  40 value 82.898315
final  value 82.894455 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.121098 
iter  10 value 86.438442
iter  20 value 86.392864
iter  30 value 85.176988
iter  40 value 84.508202
iter  50 value 84.339562
iter  60 value 82.194770
iter  70 value 82.194028
iter  80 value 82.193888
iter  90 value 82.187828
iter 100 value 82.173260
final  value 82.173260 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 94.921493 
iter  10 value 94.058822
iter  20 value 87.414552
iter  30 value 85.970813
iter  40 value 82.722199
iter  50 value 81.134704
iter  60 value 80.996272
iter  70 value 80.901296
iter  80 value 80.608375
iter  90 value 80.296209
iter 100 value 79.950665
final  value 79.950665 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 108.118569 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.372333 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.075087 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.340015 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.155871 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.623824 
final  value 94.052448 
converged
Fitting Repeat 2 

# weights:  305
initial  value 110.460801 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.864529 
final  value 94.052448 
converged
Fitting Repeat 4 

# weights:  305
initial  value 92.056405 
iter  10 value 87.646156
iter  20 value 87.529649
final  value 87.526844 
converged
Fitting Repeat 5 

# weights:  305
initial  value 122.341159 
iter  10 value 93.943343
final  value 93.943263 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.843595 
final  value 94.032967 
converged
Fitting Repeat 2 

# weights:  507
initial  value 134.478968 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 113.096123 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.616180 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.019521 
final  value 93.900821 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.773126 
iter  10 value 94.057415
iter  20 value 93.990076
iter  30 value 93.373403
iter  40 value 89.870881
iter  50 value 87.188412
iter  60 value 86.718290
iter  70 value 86.546223
final  value 86.543141 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.210620 
iter  10 value 93.713864
iter  20 value 91.717370
iter  30 value 89.755269
iter  40 value 86.154061
iter  50 value 85.480641
iter  60 value 85.033921
iter  70 value 84.752795
iter  80 value 84.566611
iter  90 value 84.408788
iter 100 value 84.308830
final  value 84.308830 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.861967 
iter  10 value 94.056704
iter  20 value 92.262280
iter  30 value 89.943953
iter  40 value 88.839395
iter  50 value 87.767383
iter  60 value 85.750894
iter  70 value 85.309186
iter  80 value 84.953579
iter  90 value 84.643896
iter 100 value 84.283463
final  value 84.283463 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 101.066466 
iter  10 value 93.944253
iter  20 value 90.747543
iter  30 value 88.541417
iter  40 value 88.453038
iter  50 value 88.292409
iter  60 value 87.831025
iter  70 value 87.386333
iter  80 value 87.184760
final  value 87.184163 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.106158 
iter  10 value 93.957055
iter  20 value 91.440579
iter  30 value 88.775000
iter  40 value 86.685527
iter  50 value 86.562296
iter  60 value 86.505345
iter  70 value 86.050709
iter  80 value 85.930956
final  value 85.915457 
converged
Fitting Repeat 1 

# weights:  305
initial  value 117.218816 
iter  10 value 94.049862
iter  20 value 87.786321
iter  30 value 87.152919
iter  40 value 86.110651
iter  50 value 84.716727
iter  60 value 84.461144
iter  70 value 84.361752
iter  80 value 84.305868
iter  90 value 84.086248
iter 100 value 83.817651
final  value 83.817651 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.799747 
iter  10 value 93.958451
iter  20 value 92.873064
iter  30 value 88.475210
iter  40 value 88.097825
iter  50 value 86.346513
iter  60 value 85.913535
iter  70 value 84.735976
iter  80 value 84.191497
iter  90 value 83.737076
iter 100 value 83.455819
final  value 83.455819 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.277003 
iter  10 value 94.119809
iter  20 value 94.056947
iter  30 value 94.036383
iter  40 value 90.757153
iter  50 value 87.071786
iter  60 value 86.530273
iter  70 value 86.380883
iter  80 value 86.223635
iter  90 value 85.980595
iter 100 value 85.836691
final  value 85.836691 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 111.951048 
iter  10 value 94.430595
iter  20 value 91.802941
iter  30 value 90.986943
iter  40 value 86.696363
iter  50 value 85.536230
iter  60 value 84.376746
iter  70 value 84.030158
iter  80 value 83.946745
iter  90 value 83.884066
iter 100 value 83.862154
final  value 83.862154 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.607648 
iter  10 value 94.424811
iter  20 value 88.441889
iter  30 value 87.601044
iter  40 value 86.985904
iter  50 value 86.012137
iter  60 value 84.652274
iter  70 value 84.236554
iter  80 value 83.977589
iter  90 value 83.723526
iter 100 value 83.210492
final  value 83.210492 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.046923 
iter  10 value 94.161355
iter  20 value 87.877794
iter  30 value 86.829727
iter  40 value 86.459644
iter  50 value 84.856665
iter  60 value 84.593794
iter  70 value 83.989812
iter  80 value 83.285110
iter  90 value 83.172482
iter 100 value 83.138585
final  value 83.138585 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 115.224885 
iter  10 value 97.105404
iter  20 value 89.428160
iter  30 value 86.770590
iter  40 value 85.471568
iter  50 value 85.381919
iter  60 value 85.200889
iter  70 value 85.055076
iter  80 value 84.124910
iter  90 value 83.606471
iter 100 value 83.440720
final  value 83.440720 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.100133 
iter  10 value 94.474679
iter  20 value 87.875252
iter  30 value 85.359334
iter  40 value 84.695832
iter  50 value 83.688677
iter  60 value 83.230856
iter  70 value 83.196656
iter  80 value 83.113899
iter  90 value 83.070963
iter 100 value 82.989950
final  value 82.989950 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 122.600068 
iter  10 value 94.173168
iter  20 value 92.895942
iter  30 value 87.101920
iter  40 value 86.356328
iter  50 value 85.308933
iter  60 value 85.090058
iter  70 value 84.696308
iter  80 value 84.133928
iter  90 value 83.385051
iter 100 value 83.293867
final  value 83.293867 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 118.522414 
iter  10 value 94.125668
iter  20 value 88.688052
iter  30 value 87.055460
iter  40 value 86.723819
iter  50 value 85.173039
iter  60 value 84.787990
iter  70 value 84.526718
iter  80 value 84.438741
iter  90 value 84.275965
iter 100 value 84.024807
final  value 84.024807 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.258034 
final  value 94.067987 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.520402 
final  value 94.054411 
converged
Fitting Repeat 3 

# weights:  103
initial  value 113.376668 
final  value 94.054545 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.895430 
final  value 94.054567 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.340563 
final  value 94.054369 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.123006 
iter  10 value 94.056909
iter  20 value 93.881235
final  value 93.672055 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.617932 
iter  10 value 94.060861
iter  20 value 94.057556
iter  30 value 93.951040
iter  40 value 90.872923
iter  50 value 87.385599
iter  60 value 87.366424
final  value 87.366227 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.121656 
iter  10 value 94.057491
iter  20 value 94.052174
iter  30 value 87.654196
iter  40 value 87.634917
iter  50 value 87.634082
iter  60 value 87.243526
iter  70 value 87.177221
iter  80 value 87.124993
iter  90 value 87.065896
iter 100 value 86.438784
final  value 86.438784 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 98.641376 
iter  10 value 89.449361
iter  20 value 89.195906
iter  30 value 88.776288
iter  40 value 88.773927
iter  50 value 88.636242
iter  60 value 88.631665
iter  70 value 88.631580
iter  80 value 88.629686
iter  80 value 88.629685
final  value 88.629685 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.432651 
iter  10 value 94.057610
iter  20 value 94.018715
iter  30 value 91.477096
iter  40 value 88.217361
final  value 88.212477 
converged
Fitting Repeat 1 

# weights:  507
initial  value 117.009638 
iter  10 value 94.041284
iter  20 value 94.039399
iter  30 value 93.764010
iter  40 value 88.876946
iter  50 value 88.791810
iter  60 value 87.616871
iter  70 value 87.360163
iter  80 value 87.282087
final  value 87.282079 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.391540 
iter  10 value 93.186268
iter  20 value 91.829995
iter  30 value 91.816697
iter  40 value 91.695054
iter  50 value 91.576655
iter  60 value 91.575362
iter  70 value 91.573174
iter  80 value 91.572148
iter  90 value 91.375716
iter 100 value 91.196366
final  value 91.196366 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.461562 
iter  10 value 90.054115
iter  20 value 87.880258
iter  30 value 87.852798
final  value 87.850883 
converged
Fitting Repeat 4 

# weights:  507
initial  value 113.290358 
iter  10 value 94.061217
iter  20 value 93.798511
iter  30 value 91.600040
iter  40 value 91.598149
iter  50 value 91.590170
iter  60 value 90.930612
iter  70 value 90.923076
final  value 90.922993 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.949886 
iter  10 value 94.061085
iter  20 value 94.000833
iter  30 value 93.083728
iter  30 value 93.083727
iter  30 value 93.083727
final  value 93.083727 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.523030 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.838784 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.879484 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.755979 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.950331 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.361674 
final  value 94.275362 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.111407 
final  value 94.275363 
converged
Fitting Repeat 3 

# weights:  305
initial  value 109.053659 
iter  10 value 93.924634
final  value 93.922222 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.483351 
iter  10 value 93.360526
iter  20 value 92.109567
iter  30 value 92.023971
final  value 92.017778 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.973017 
iter  10 value 93.991342
iter  10 value 93.991342
iter  10 value 93.991342
final  value 93.991342 
converged
Fitting Repeat 1 

# weights:  507
initial  value 112.586767 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.844895 
iter  10 value 93.971015
iter  10 value 93.971015
iter  10 value 93.971015
final  value 93.971015 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.826352 
final  value 94.275362 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.249460 
final  value 94.264859 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.098273 
iter  10 value 93.789504
final  value 93.788489 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.211965 
iter  10 value 94.488537
iter  20 value 87.762859
iter  30 value 86.319582
iter  40 value 83.859813
iter  50 value 82.603156
iter  60 value 82.339995
iter  70 value 82.215782
iter  70 value 82.215782
iter  70 value 82.215782
final  value 82.215782 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.570778 
iter  10 value 94.502486
iter  20 value 94.487581
iter  30 value 94.457859
iter  40 value 94.035345
iter  50 value 93.953575
iter  60 value 93.941535
iter  70 value 92.523705
iter  80 value 86.636136
iter  90 value 84.191134
iter 100 value 83.870230
final  value 83.870230 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 101.503662 
iter  10 value 93.757014
iter  20 value 89.068188
iter  30 value 88.046349
iter  40 value 87.416971
iter  50 value 86.958157
iter  60 value 85.707472
iter  70 value 85.048714
iter  80 value 84.982491
final  value 84.968163 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.307097 
iter  10 value 94.287328
iter  20 value 85.742521
iter  30 value 84.991712
iter  40 value 84.528158
iter  50 value 83.150779
iter  60 value 82.161655
iter  70 value 82.107811
iter  80 value 82.020742
final  value 82.011271 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.654408 
iter  10 value 94.475820
iter  20 value 92.821636
iter  30 value 86.563421
iter  40 value 84.978135
iter  50 value 84.653391
iter  60 value 84.514507
iter  70 value 84.440555
iter  80 value 84.417080
final  value 84.416968 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.464270 
iter  10 value 93.900980
iter  20 value 85.938583
iter  30 value 85.235701
iter  40 value 84.698811
iter  50 value 82.961266
iter  60 value 81.815376
iter  70 value 81.012802
iter  80 value 80.925679
iter  90 value 80.872018
iter 100 value 80.861773
final  value 80.861773 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.745929 
iter  10 value 94.332119
iter  20 value 88.505798
iter  30 value 86.129409
iter  40 value 83.991689
iter  50 value 83.370035
iter  60 value 82.695081
iter  70 value 82.630792
iter  80 value 82.497304
iter  90 value 81.603106
iter 100 value 80.940643
final  value 80.940643 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.807087 
iter  10 value 93.811090
iter  20 value 88.224059
iter  30 value 87.011708
iter  40 value 86.696443
iter  50 value 84.459047
iter  60 value 83.972928
iter  70 value 82.427160
iter  80 value 81.913751
iter  90 value 81.333198
iter 100 value 81.179844
final  value 81.179844 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 114.071087 
iter  10 value 94.080717
iter  20 value 91.912455
iter  30 value 86.465762
iter  40 value 86.007734
iter  50 value 85.675368
iter  60 value 85.379798
iter  70 value 85.185573
iter  80 value 85.013726
iter  90 value 84.996789
iter 100 value 84.963059
final  value 84.963059 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.191777 
iter  10 value 94.437893
iter  20 value 89.514798
iter  30 value 87.885189
iter  40 value 86.978402
iter  50 value 85.500771
iter  60 value 84.396745
iter  70 value 83.020498
iter  80 value 82.568671
iter  90 value 82.413823
iter 100 value 82.372417
final  value 82.372417 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 123.880097 
iter  10 value 93.353353
iter  20 value 87.217627
iter  30 value 84.645638
iter  40 value 82.276127
iter  50 value 82.105244
iter  60 value 81.620704
iter  70 value 81.269873
iter  80 value 81.160482
iter  90 value 81.059458
iter 100 value 80.902136
final  value 80.902136 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 122.147546 
iter  10 value 95.535479
iter  20 value 88.946242
iter  30 value 86.963873
iter  40 value 85.115532
iter  50 value 83.348393
iter  60 value 82.754682
iter  70 value 81.980012
iter  80 value 81.649720
iter  90 value 81.006101
iter 100 value 80.721105
final  value 80.721105 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.462037 
iter  10 value 95.041999
iter  20 value 94.124111
iter  30 value 88.569482
iter  40 value 87.449757
iter  50 value 85.963146
iter  60 value 85.343418
iter  70 value 84.332653
iter  80 value 81.912880
iter  90 value 81.160925
iter 100 value 80.929479
final  value 80.929479 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 116.082733 
iter  10 value 94.454486
iter  20 value 93.190432
iter  30 value 87.851402
iter  40 value 86.557805
iter  50 value 86.164398
iter  60 value 85.936812
iter  70 value 83.236249
iter  80 value 81.778074
iter  90 value 81.568556
iter 100 value 80.788781
final  value 80.788781 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.094061 
iter  10 value 94.547560
iter  20 value 94.165056
iter  30 value 93.931971
iter  40 value 87.658243
iter  50 value 86.363119
iter  60 value 86.123365
iter  70 value 85.096184
iter  80 value 84.719687
iter  90 value 84.620092
iter 100 value 84.350609
final  value 84.350609 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.919736 
final  value 94.485846 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.187024 
final  value 94.485745 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.644815 
final  value 94.485807 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.259791 
final  value 94.485945 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.176300 
final  value 94.485813 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.970779 
iter  10 value 94.280669
iter  20 value 94.276681
iter  30 value 92.121559
iter  40 value 92.113881
iter  50 value 89.377806
iter  60 value 87.545356
iter  70 value 87.157235
iter  80 value 84.661206
final  value 84.643631 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.187063 
iter  10 value 94.488898
iter  20 value 94.484230
final  value 94.484208 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.053691 
iter  10 value 94.488807
iter  20 value 94.423979
iter  30 value 85.746719
iter  40 value 85.516895
iter  50 value 85.392490
iter  60 value 84.165101
iter  70 value 83.726915
final  value 83.725942 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.702432 
iter  10 value 93.891056
iter  20 value 93.814797
iter  30 value 93.811946
iter  40 value 90.399774
iter  50 value 86.186508
iter  60 value 86.148778
iter  70 value 86.115603
iter  80 value 85.977373
final  value 85.976504 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.442172 
iter  10 value 94.489256
iter  20 value 93.950995
iter  30 value 88.376434
iter  40 value 87.196669
iter  50 value 86.021799
iter  60 value 85.981686
iter  70 value 85.881771
final  value 85.881755 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.615536 
iter  10 value 94.491909
iter  20 value 94.113147
iter  30 value 85.981607
iter  40 value 84.868212
iter  50 value 84.233085
iter  60 value 84.146032
final  value 84.145331 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.180230 
iter  10 value 94.492422
iter  20 value 93.084971
iter  30 value 84.984532
iter  40 value 84.501603
iter  50 value 84.437735
iter  60 value 84.415243
iter  70 value 84.369795
iter  80 value 84.360804
iter  90 value 84.224950
iter 100 value 82.853385
final  value 82.853385 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.853654 
iter  10 value 92.071605
iter  20 value 84.725594
iter  30 value 84.489195
iter  40 value 84.216878
iter  50 value 83.936682
iter  60 value 83.934996
iter  70 value 83.873140
iter  80 value 83.829503
iter  90 value 83.729809
iter 100 value 83.727942
final  value 83.727942 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 117.394557 
iter  10 value 93.979231
iter  20 value 93.919743
iter  30 value 93.785285
iter  40 value 93.743923
iter  50 value 93.733473
iter  60 value 93.733318
iter  60 value 93.733317
iter  60 value 93.733317
final  value 93.733317 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.064199 
iter  10 value 94.445666
iter  20 value 94.436632
iter  30 value 94.428807
iter  40 value 93.272320
iter  50 value 90.605329
iter  60 value 90.430655
iter  70 value 86.751259
iter  80 value 86.511607
iter  90 value 86.036554
iter 100 value 85.551115
final  value 85.551115 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.101669 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.914784 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.981143 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.954543 
iter  10 value 94.026546
final  value 94.026542 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.786034 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.765177 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.165008 
final  value 94.026542 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.300497 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.705743 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.732126 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.271351 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 122.341006 
iter  10 value 94.026543
final  value 94.026542 
converged
Fitting Repeat 3 

# weights:  507
initial  value 110.153007 
final  value 94.482478 
converged
Fitting Repeat 4 

# weights:  507
initial  value 114.072765 
iter  10 value 94.026544
final  value 94.026542 
converged
Fitting Repeat 5 

# weights:  507
initial  value 112.585841 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 111.824516 
iter  10 value 96.834484
iter  20 value 94.487731
iter  30 value 90.958205
iter  40 value 90.296179
iter  50 value 89.880219
iter  60 value 87.962634
iter  70 value 87.679619
iter  80 value 78.698929
iter  90 value 77.427356
iter 100 value 77.147446
final  value 77.147446 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 98.800836 
iter  10 value 94.430650
iter  20 value 94.127768
iter  30 value 94.109662
iter  40 value 83.952648
iter  50 value 82.140509
iter  60 value 80.782355
iter  70 value 80.625161
iter  80 value 80.609311
iter  90 value 80.601983
final  value 80.600510 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.665426 
iter  10 value 94.408864
iter  20 value 94.133509
iter  30 value 82.878504
iter  40 value 78.402446
iter  50 value 77.874624
iter  60 value 77.456188
iter  70 value 77.214744
iter  80 value 77.186416
iter  90 value 77.185093
iter 100 value 77.183818
final  value 77.183818 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 98.380564 
iter  10 value 94.486433
iter  20 value 94.091341
iter  30 value 82.022276
iter  40 value 80.387792
iter  50 value 78.549984
iter  60 value 77.842657
iter  70 value 77.400842
iter  80 value 77.308857
iter  90 value 77.185058
final  value 77.183816 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.374255 
iter  10 value 94.454535
iter  20 value 90.680032
iter  30 value 90.422729
iter  40 value 90.278764
iter  50 value 82.293929
iter  60 value 81.694881
iter  70 value 81.460496
iter  80 value 81.333180
iter  90 value 81.323614
iter  90 value 81.323613
iter  90 value 81.323613
final  value 81.323613 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.846086 
iter  10 value 94.423500
iter  20 value 94.116672
iter  30 value 85.075080
iter  40 value 80.016897
iter  50 value 79.042084
iter  60 value 78.186358
iter  70 value 77.710632
iter  80 value 77.085927
iter  90 value 76.015029
iter 100 value 75.705629
final  value 75.705629 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 121.042531 
iter  10 value 94.445288
iter  20 value 93.464859
iter  30 value 86.029628
iter  40 value 83.536965
iter  50 value 79.895864
iter  60 value 79.584445
iter  70 value 78.994946
iter  80 value 76.734555
iter  90 value 75.917090
iter 100 value 75.348266
final  value 75.348266 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.102092 
iter  10 value 94.193399
iter  20 value 90.465370
iter  30 value 86.531293
iter  40 value 82.459310
iter  50 value 81.638114
iter  60 value 80.845356
iter  70 value 78.977814
iter  80 value 77.265058
iter  90 value 76.895263
iter 100 value 76.670178
final  value 76.670178 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.970379 
iter  10 value 94.356946
iter  20 value 87.617783
iter  30 value 83.276325
iter  40 value 82.395702
iter  50 value 82.015871
iter  60 value 79.147274
iter  70 value 77.517031
iter  80 value 77.208131
iter  90 value 77.143997
iter 100 value 77.101953
final  value 77.101953 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 112.356162 
iter  10 value 94.220026
iter  20 value 92.376066
iter  30 value 84.469107
iter  40 value 82.232206
iter  50 value 79.831381
iter  60 value 77.982512
iter  70 value 76.073568
iter  80 value 75.670892
iter  90 value 75.360883
iter 100 value 75.138850
final  value 75.138850 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.619125 
iter  10 value 94.514529
iter  20 value 93.175401
iter  30 value 87.634388
iter  40 value 82.871435
iter  50 value 79.684216
iter  60 value 77.474803
iter  70 value 76.926659
iter  80 value 76.687641
iter  90 value 76.373689
iter 100 value 76.156459
final  value 76.156459 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.835405 
iter  10 value 92.926012
iter  20 value 81.235919
iter  30 value 80.636118
iter  40 value 80.450249
iter  50 value 79.941704
iter  60 value 78.111816
iter  70 value 76.819963
iter  80 value 76.146168
iter  90 value 75.709686
iter 100 value 75.579555
final  value 75.579555 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.104994 
iter  10 value 95.862296
iter  20 value 94.496119
iter  30 value 89.909707
iter  40 value 81.751993
iter  50 value 80.800211
iter  60 value 79.872820
iter  70 value 78.206993
iter  80 value 76.852206
iter  90 value 76.712879
iter 100 value 76.459085
final  value 76.459085 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 153.000257 
iter  10 value 94.462458
iter  20 value 93.521452
iter  30 value 88.044895
iter  40 value 84.388442
iter  50 value 83.240152
iter  60 value 82.726960
iter  70 value 80.300579
iter  80 value 77.662063
iter  90 value 77.032345
iter 100 value 76.396178
final  value 76.396178 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 116.200492 
iter  10 value 94.492125
iter  20 value 82.097942
iter  30 value 81.177704
iter  40 value 79.881495
iter  50 value 76.704250
iter  60 value 76.092600
iter  70 value 75.351965
iter  80 value 75.247881
iter  90 value 75.038208
iter 100 value 74.996840
final  value 74.996840 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.349615 
final  value 94.485806 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.711536 
final  value 94.486040 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.629221 
iter  10 value 94.028551
iter  20 value 94.027102
final  value 94.026870 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.812497 
final  value 94.485942 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.699173 
final  value 94.485622 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.305951 
iter  10 value 94.488883
iter  20 value 94.484511
final  value 94.484503 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.132336 
iter  10 value 94.485669
iter  20 value 94.443842
iter  30 value 90.058931
iter  40 value 89.407930
iter  50 value 89.340073
final  value 89.325736 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.996188 
iter  10 value 94.037701
iter  20 value 94.031450
iter  30 value 94.028911
final  value 94.027374 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.674747 
iter  10 value 92.652909
iter  20 value 92.009797
iter  30 value 91.991414
iter  40 value 91.990830
iter  50 value 91.989768
iter  60 value 91.988449
iter  70 value 91.962134
iter  80 value 90.402993
iter  90 value 81.832599
iter 100 value 75.338024
final  value 75.338024 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.161320 
iter  10 value 94.031358
iter  20 value 91.344663
iter  30 value 80.896182
iter  40 value 80.445120
iter  50 value 80.438230
iter  60 value 80.438053
iter  70 value 80.437975
final  value 80.437846 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.948791 
iter  10 value 94.488122
iter  20 value 94.315099
iter  30 value 87.318851
iter  40 value 86.899686
iter  50 value 86.843999
iter  60 value 85.432690
iter  70 value 85.399925
iter  80 value 85.191417
iter  90 value 85.156169
final  value 85.156159 
converged
Fitting Repeat 2 

# weights:  507
initial  value 110.763943 
iter  10 value 94.492657
iter  20 value 93.827456
iter  30 value 92.561737
iter  40 value 91.403542
iter  50 value 91.201657
final  value 91.201558 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.002356 
iter  10 value 94.173759
iter  20 value 94.123638
iter  30 value 93.977171
iter  40 value 93.969269
iter  50 value 92.998555
iter  60 value 87.880489
iter  70 value 83.426451
iter  80 value 80.120544
iter  90 value 79.816631
iter 100 value 79.770987
final  value 79.770987 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.372734 
iter  10 value 90.563844
iter  20 value 83.290510
iter  30 value 80.479468
iter  40 value 80.396277
iter  50 value 80.395849
iter  60 value 80.394710
iter  70 value 79.802250
iter  80 value 79.750029
iter  90 value 79.413883
iter 100 value 79.408908
final  value 79.408908 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 98.932302 
iter  10 value 94.492762
iter  20 value 94.373953
iter  30 value 93.787983
iter  40 value 90.358686
iter  50 value 89.364258
iter  60 value 89.344130
iter  70 value 89.342977
iter  80 value 89.342232
iter  90 value 89.331877
iter 100 value 89.331771
final  value 89.331771 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 120.453894 
iter  10 value 117.908886
iter  20 value 117.810482
iter  30 value 117.792271
iter  40 value 114.835216
iter  50 value 107.076038
iter  60 value 106.167407
iter  70 value 105.964374
iter  80 value 105.306870
iter  90 value 105.259723
iter 100 value 105.258523
final  value 105.258523 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 124.167120 
iter  10 value 117.439633
iter  20 value 107.847291
iter  30 value 105.654150
iter  40 value 105.356273
iter  50 value 104.687462
iter  60 value 103.589326
iter  70 value 103.095869
iter  80 value 102.541774
iter  90 value 102.325418
final  value 102.325293 
converged
Fitting Repeat 3 

# weights:  103
initial  value 120.873422 
iter  10 value 117.894868
iter  20 value 112.407664
iter  30 value 108.134436
iter  40 value 107.787061
iter  50 value 106.820520
iter  60 value 106.254860
iter  70 value 105.628085
iter  80 value 105.615640
iter  80 value 105.615639
final  value 105.615639 
converged
Fitting Repeat 4 

# weights:  103
initial  value 119.242592 
iter  10 value 106.544213
iter  20 value 105.392085
iter  30 value 104.401993
iter  40 value 103.044215
iter  50 value 102.777512
iter  60 value 102.773380
iter  70 value 102.574428
iter  80 value 102.094913
final  value 102.094294 
converged
Fitting Repeat 5 

# weights:  103
initial  value 129.363721 
iter  10 value 117.551710
iter  20 value 115.493129
iter  30 value 113.169913
iter  40 value 112.251630
iter  50 value 111.827383
iter  60 value 110.480746
iter  70 value 103.879049
iter  80 value 103.259687
iter  90 value 102.994618
iter 100 value 102.644306
final  value 102.644306 
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 -- Tue Jan 21 07:58:40 2025 
*********************************************** 
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 
 51.147   1.230  89.476