##############################################################################
##############################################################################
###
### 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 4.4.3 (2025-02-28)
* using platform: aarch64-unknown-linux-gnu
* R was compiled by
    aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0
    GNU Fortran (GCC) 14.2.0
* 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       35.299  0.304  35.755
corr_plot     34.820  0.164  35.043
FSmethod      33.976  0.251  34.292
pred_ensembel 17.756  0.791  17.420
enrichfindP    0.515  0.024  23.024
getFASTA       0.128  0.007   5.812
* 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-4.4.3/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 4.4.3 (2025-02-28) -- "Trophy Case"
Copyright (C) 2025 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 97.624854 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.356508 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.097113 
iter  10 value 94.209303
iter  10 value 94.209302
iter  10 value 94.209302
final  value 94.209302 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.513234 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.202302 
iter  10 value 93.930732
final  value 93.930686 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.230365 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.523939 
iter  10 value 94.436793
iter  10 value 94.436793
iter  10 value 94.436792
final  value 94.436792 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.332374 
iter  10 value 93.834118
iter  20 value 93.625093
iter  30 value 93.623580
final  value 93.623578 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.091566 
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.709682 
final  value 94.275363 
converged
Fitting Repeat 1 

# weights:  507
initial  value 111.391379 
final  value 94.275362 
converged
Fitting Repeat 2 

# weights:  507
initial  value 121.115320 
final  value 94.484210 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.761557 
final  value 94.275362 
converged
Fitting Repeat 4 

# weights:  507
initial  value 112.892776 
iter  10 value 94.484248
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.885449 
final  value 94.275362 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.646915 
iter  10 value 94.502589
iter  20 value 94.486441
iter  30 value 90.019384
iter  40 value 89.245640
iter  50 value 86.900783
iter  60 value 85.755696
iter  70 value 85.540311
iter  80 value 84.172302
iter  90 value 81.022818
iter 100 value 80.698870
final  value 80.698870 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 102.789302 
iter  10 value 94.479111
iter  20 value 90.843888
iter  30 value 86.622190
iter  40 value 86.174578
iter  50 value 84.803362
iter  60 value 83.979924
iter  70 value 81.557690
iter  80 value 80.529288
iter  90 value 80.454707
iter 100 value 80.446701
final  value 80.446701 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.688369 
iter  10 value 94.514732
iter  20 value 88.473243
iter  30 value 87.571503
final  value 87.569714 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.426771 
iter  10 value 93.846653
iter  20 value 93.470270
iter  30 value 89.171088
iter  40 value 84.841335
iter  50 value 84.069863
iter  60 value 83.968428
iter  70 value 83.771742
iter  80 value 83.739669
iter  90 value 83.523602
iter 100 value 81.685906
final  value 81.685906 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 100.160042 
iter  10 value 94.488550
iter  20 value 94.121740
iter  30 value 93.414958
iter  40 value 90.206719
iter  50 value 82.686049
iter  60 value 81.174770
iter  70 value 80.530943
iter  80 value 80.373891
iter  90 value 80.337638
iter 100 value 80.314510
final  value 80.314510 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 112.879014 
iter  10 value 93.945166
iter  20 value 85.798566
iter  30 value 85.491681
iter  40 value 82.660339
iter  50 value 81.782949
iter  60 value 81.138611
iter  70 value 80.919794
iter  80 value 80.810938
iter  90 value 80.718869
iter 100 value 80.251551
final  value 80.251551 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.862101 
iter  10 value 94.733551
iter  20 value 93.641363
iter  30 value 93.368562
iter  40 value 93.263414
iter  50 value 85.387597
iter  60 value 85.048145
iter  70 value 82.898482
iter  80 value 81.512338
iter  90 value 80.625765
iter 100 value 80.443443
final  value 80.443443 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.407395 
iter  10 value 93.395711
iter  20 value 90.118422
iter  30 value 88.565794
iter  40 value 83.297794
iter  50 value 81.461515
iter  60 value 80.591921
iter  70 value 79.938605
iter  80 value 79.204822
iter  90 value 78.652599
iter 100 value 78.490302
final  value 78.490302 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 117.882371 
iter  10 value 95.202280
iter  20 value 93.250570
iter  30 value 89.494581
iter  40 value 84.528362
iter  50 value 81.489381
iter  60 value 81.009256
iter  70 value 80.971443
iter  80 value 80.880071
iter  90 value 80.401986
iter 100 value 79.760077
final  value 79.760077 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 119.204299 
iter  10 value 94.228215
iter  20 value 88.238720
iter  30 value 83.648758
iter  40 value 81.547172
iter  50 value 81.220683
iter  60 value 81.048446
iter  70 value 80.719165
iter  80 value 80.631891
iter  90 value 80.594280
iter 100 value 80.431363
final  value 80.431363 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.899263 
iter  10 value 94.567966
iter  20 value 94.154129
iter  30 value 92.098597
iter  40 value 89.292448
iter  50 value 88.639858
iter  60 value 84.442198
iter  70 value 81.095131
iter  80 value 79.830534
iter  90 value 79.114712
iter 100 value 78.934794
final  value 78.934794 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 123.208342 
iter  10 value 94.857539
iter  20 value 94.195859
iter  30 value 93.695570
iter  40 value 92.467920
iter  50 value 91.755193
iter  60 value 91.447410
iter  70 value 84.938649
iter  80 value 84.259702
iter  90 value 82.403813
iter 100 value 81.032644
final  value 81.032644 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.995963 
iter  10 value 96.321930
iter  20 value 89.000112
iter  30 value 87.941515
iter  40 value 85.254551
iter  50 value 83.953054
iter  60 value 83.617357
iter  70 value 82.284530
iter  80 value 81.724446
iter  90 value 80.909812
iter 100 value 79.948114
final  value 79.948114 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.957343 
iter  10 value 95.521059
iter  20 value 94.969962
iter  30 value 94.398256
iter  40 value 86.946863
iter  50 value 82.793901
iter  60 value 82.438734
iter  70 value 82.081307
iter  80 value 81.617014
iter  90 value 80.202553
iter 100 value 79.585358
final  value 79.585358 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 118.225152 
iter  10 value 94.517939
iter  20 value 93.494480
iter  30 value 88.910803
iter  40 value 85.895580
iter  50 value 84.637054
iter  60 value 83.131455
iter  70 value 81.447754
iter  80 value 80.293044
iter  90 value 80.131032
iter 100 value 80.039126
final  value 80.039126 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.295524 
final  value 94.485818 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.567619 
final  value 94.485759 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.495446 
final  value 94.486025 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.596882 
final  value 94.485973 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.362693 
final  value 94.485886 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.398468 
iter  10 value 94.280522
iter  20 value 94.276863
iter  30 value 93.697791
final  value 93.688574 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.616343 
iter  10 value 94.352853
iter  20 value 94.346556
iter  30 value 94.269591
iter  40 value 93.730623
iter  50 value 93.633832
iter  60 value 93.625058
iter  70 value 88.611647
iter  80 value 82.025597
iter  90 value 81.655331
iter 100 value 81.641020
final  value 81.641020 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 96.083584 
iter  10 value 94.488778
iter  20 value 94.484297
final  value 94.484285 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.169457 
iter  10 value 94.489068
iter  20 value 94.378385
iter  30 value 93.689760
iter  40 value 93.689128
final  value 93.689032 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.825955 
iter  10 value 94.487226
iter  20 value 94.351160
iter  30 value 93.628402
iter  40 value 90.140942
iter  50 value 89.407813
iter  60 value 89.334758
final  value 89.299868 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.805974 
iter  10 value 94.491431
iter  20 value 93.481254
iter  30 value 93.309042
final  value 93.299853 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.885541 
iter  10 value 94.490013
iter  20 value 94.277173
final  value 94.275605 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.580593 
iter  10 value 94.283712
iter  20 value 94.277265
iter  30 value 90.058023
iter  40 value 87.134837
iter  50 value 85.031488
iter  60 value 84.981963
iter  70 value 84.974554
iter  80 value 84.973224
iter  90 value 84.972760
final  value 84.972365 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.806802 
iter  10 value 94.284187
iter  20 value 94.278839
iter  30 value 94.277763
iter  40 value 93.998109
iter  50 value 92.506091
iter  60 value 90.565877
iter  70 value 90.522023
final  value 90.522008 
converged
Fitting Repeat 5 

# weights:  507
initial  value 110.194811 
iter  10 value 94.273438
iter  20 value 94.217721
iter  30 value 94.213141
iter  40 value 94.209461
final  value 94.209424 
converged
Fitting Repeat 1 

# weights:  103
initial  value 113.663503 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.148969 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 111.501703 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.191314 
final  value 94.026542 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.697413 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.860262 
iter  10 value 94.473770
final  value 94.473684 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.680581 
iter  10 value 91.558304
final  value 91.556378 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.077677 
iter  10 value 94.118631
final  value 94.026542 
converged
Fitting Repeat 4 

# weights:  305
initial  value 115.805598 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.745621 
final  value 94.026542 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.281364 
iter  10 value 87.408887
iter  20 value 86.881808
iter  30 value 86.880177
final  value 86.880173 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.602975 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.413166 
iter  10 value 85.408503
iter  20 value 85.351353
final  value 85.348401 
converged
Fitting Repeat 4 

# weights:  507
initial  value 125.281631 
iter  10 value 93.701658
iter  10 value 93.701657
iter  10 value 93.701657
final  value 93.701657 
converged
Fitting Repeat 5 

# weights:  507
initial  value 121.759252 
final  value 94.443182 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.791629 
iter  10 value 88.842758
iter  20 value 87.008275
iter  30 value 86.908106
iter  40 value 86.296271
iter  50 value 85.839466
iter  60 value 85.469822
iter  70 value 85.366055
final  value 85.364438 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.637513 
iter  10 value 94.473977
iter  20 value 93.923512
iter  30 value 93.904147
iter  40 value 93.900121
iter  50 value 93.899932
iter  60 value 93.899865
iter  70 value 93.760171
iter  80 value 89.504646
iter  90 value 88.979278
iter 100 value 88.715664
final  value 88.715664 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 100.133182 
iter  10 value 94.025405
iter  20 value 88.969046
iter  30 value 88.273902
iter  40 value 84.499730
iter  50 value 83.551394
iter  60 value 83.181505
iter  70 value 83.061454
iter  80 value 83.026007
final  value 83.025834 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.545044 
iter  10 value 94.112827
iter  20 value 93.842349
iter  30 value 93.265516
iter  40 value 87.855293
iter  50 value 86.366571
iter  60 value 84.131896
iter  70 value 83.754649
iter  80 value 83.569948
iter  90 value 83.258824
iter 100 value 83.131202
final  value 83.131202 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 103.713433 
iter  10 value 94.431879
iter  20 value 92.319557
iter  30 value 91.658649
iter  40 value 90.032011
iter  50 value 84.030275
iter  60 value 83.123217
iter  70 value 82.932978
iter  80 value 82.860976
iter  90 value 82.790969
iter 100 value 82.631850
final  value 82.631850 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 121.858988 
iter  10 value 94.483367
iter  20 value 92.979788
iter  30 value 85.198918
iter  40 value 84.229735
iter  50 value 83.086463
iter  60 value 82.612260
iter  70 value 82.207653
iter  80 value 82.119511
iter  90 value 82.071384
iter 100 value 81.768513
final  value 81.768513 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.159698 
iter  10 value 94.595601
iter  20 value 93.814703
iter  30 value 86.793772
iter  40 value 84.914190
iter  50 value 84.268990
iter  60 value 84.165911
iter  70 value 83.553951
iter  80 value 83.097900
iter  90 value 82.714358
iter 100 value 82.597209
final  value 82.597209 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 113.170145 
iter  10 value 95.461783
iter  20 value 93.654033
iter  30 value 86.150545
iter  40 value 84.134919
iter  50 value 83.389470
iter  60 value 82.775975
iter  70 value 82.623404
iter  80 value 82.101341
iter  90 value 81.799905
iter 100 value 81.698723
final  value 81.698723 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 111.560829 
iter  10 value 94.381980
iter  20 value 92.534974
iter  30 value 92.203404
iter  40 value 91.980223
iter  50 value 85.118500
iter  60 value 83.821022
iter  70 value 83.253460
iter  80 value 82.613333
iter  90 value 81.982987
iter 100 value 81.858424
final  value 81.858424 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.423137 
iter  10 value 94.624209
iter  20 value 94.296529
iter  30 value 86.481762
iter  40 value 85.013766
iter  50 value 84.597287
iter  60 value 84.279910
iter  70 value 83.341168
iter  80 value 82.414640
iter  90 value 81.902805
iter 100 value 81.804784
final  value 81.804784 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 121.324976 
iter  10 value 98.996960
iter  20 value 95.442110
iter  30 value 90.814652
iter  40 value 86.926284
iter  50 value 84.244980
iter  60 value 83.186930
iter  70 value 82.153522
iter  80 value 81.898611
iter  90 value 81.710262
iter 100 value 81.686632
final  value 81.686632 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.521471 
iter  10 value 95.505600
iter  20 value 94.049315
iter  30 value 86.750352
iter  40 value 84.942012
iter  50 value 83.969730
iter  60 value 83.006595
iter  70 value 82.860493
iter  80 value 82.526064
iter  90 value 82.139467
iter 100 value 81.946946
final  value 81.946946 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.535529 
iter  10 value 94.460985
iter  20 value 92.285835
iter  30 value 85.636096
iter  40 value 83.036272
iter  50 value 82.003912
iter  60 value 81.841775
iter  70 value 81.528024
iter  80 value 81.451551
iter  90 value 81.411206
iter 100 value 81.224806
final  value 81.224806 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.397671 
iter  10 value 94.689800
iter  20 value 94.466968
iter  30 value 88.816037
iter  40 value 86.774392
iter  50 value 85.839648
iter  60 value 84.236171
iter  70 value 83.358975
iter  80 value 82.467620
iter  90 value 82.151487
iter 100 value 82.008488
final  value 82.008488 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.383354 
iter  10 value 91.177158
iter  20 value 90.326240
iter  30 value 88.850351
iter  40 value 85.672085
iter  50 value 83.682443
iter  60 value 83.095403
iter  70 value 82.845254
iter  80 value 82.497882
iter  90 value 81.943376
iter 100 value 81.794685
final  value 81.794685 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.231771 
iter  10 value 94.457959
iter  20 value 88.400550
iter  30 value 88.393285
iter  40 value 88.392972
iter  50 value 86.463475
iter  60 value 86.456962
final  value 86.454847 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.871288 
final  value 94.485556 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.136391 
iter  10 value 93.807606
final  value 93.796924 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.837337 
final  value 94.485779 
converged
Fitting Repeat 5 

# weights:  103
initial  value 111.417854 
final  value 94.485862 
converged
Fitting Repeat 1 

# weights:  305
initial  value 125.352951 
iter  10 value 94.034291
iter  20 value 94.030715
iter  30 value 93.928434
iter  40 value 93.799794
iter  50 value 93.797458
iter  60 value 93.764729
iter  70 value 86.349941
iter  80 value 83.776879
iter  90 value 83.564469
iter 100 value 83.558677
final  value 83.558677 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.069531 
iter  10 value 94.448107
iter  20 value 93.771822
iter  30 value 92.885598
iter  40 value 92.877716
iter  50 value 90.321984
iter  60 value 90.305548
iter  70 value 90.304729
iter  80 value 88.543916
iter  90 value 83.303433
iter 100 value 81.670984
final  value 81.670984 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.354179 
iter  10 value 94.488650
iter  20 value 94.034084
final  value 94.026689 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.934597 
iter  10 value 91.405972
iter  20 value 89.392672
iter  30 value 89.368515
iter  40 value 89.356646
iter  50 value 87.228788
iter  60 value 87.218663
final  value 87.218449 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.147600 
iter  10 value 94.032052
iter  20 value 94.030775
iter  30 value 94.026898
final  value 94.026772 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.432529 
iter  10 value 94.493183
iter  20 value 94.484692
iter  30 value 93.944625
iter  40 value 85.879225
iter  50 value 85.202032
iter  60 value 83.972369
iter  70 value 83.083668
iter  80 value 81.284678
iter  90 value 80.790271
iter 100 value 80.458396
final  value 80.458396 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.227084 
iter  10 value 93.115450
iter  20 value 84.153451
iter  30 value 83.992823
iter  40 value 83.887880
iter  50 value 83.358443
iter  60 value 83.300125
iter  70 value 83.296163
iter  80 value 83.248983
iter  90 value 83.174902
iter 100 value 83.170008
final  value 83.170008 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 123.717205 
iter  10 value 94.492271
iter  20 value 94.484250
iter  30 value 94.385818
iter  40 value 93.802746
iter  50 value 93.753132
final  value 93.752998 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.672214 
iter  10 value 94.485788
iter  20 value 93.855790
iter  30 value 87.256981
iter  40 value 85.550102
iter  50 value 85.450799
iter  60 value 85.450007
iter  70 value 85.265051
iter  80 value 85.182147
iter  90 value 83.607403
iter 100 value 82.616041
final  value 82.616041 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 102.731482 
iter  10 value 94.492263
iter  20 value 94.471502
iter  30 value 86.863125
iter  40 value 86.452590
iter  50 value 86.399904
iter  60 value 86.393220
final  value 86.393212 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.333372 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.501364 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.146658 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.704391 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 112.488096 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.742704 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.937142 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.129533 
iter  10 value 94.008705
final  value 94.008696 
converged
Fitting Repeat 4 

# weights:  305
initial  value 109.696324 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.214417 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 128.701397 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.765374 
iter  10 value 92.723927
final  value 92.723810 
converged
Fitting Repeat 3 

# weights:  507
initial  value 111.094614 
iter  10 value 94.053115
final  value 94.052911 
converged
Fitting Repeat 4 

# weights:  507
initial  value 111.076550 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 113.543208 
final  value 94.008696 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.508238 
iter  10 value 94.078615
final  value 94.056802 
converged
Fitting Repeat 2 

# weights:  103
initial  value 115.341746 
iter  10 value 93.985226
iter  20 value 93.198871
iter  30 value 92.457461
iter  40 value 83.213283
iter  50 value 82.785410
iter  60 value 82.471570
iter  70 value 82.445277
iter  80 value 82.357081
iter  90 value 82.285416
final  value 82.284861 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.539538 
iter  10 value 92.230129
iter  20 value 87.913874
iter  30 value 85.405050
iter  40 value 84.779723
iter  50 value 84.612844
iter  60 value 84.229514
iter  70 value 84.122855
iter  80 value 83.898429
iter  90 value 82.289654
iter 100 value 82.167967
final  value 82.167967 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 104.267143 
iter  10 value 92.968545
iter  20 value 85.796859
iter  30 value 84.729435
iter  40 value 84.411680
iter  50 value 82.532801
iter  60 value 82.320560
iter  70 value 82.246145
iter  80 value 82.164819
final  value 82.159659 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.260403 
iter  10 value 94.956478
iter  20 value 94.054202
iter  30 value 87.816133
iter  40 value 83.680557
iter  50 value 83.125058
iter  60 value 82.570380
iter  70 value 82.300706
iter  80 value 82.176555
iter  90 value 82.159664
final  value 82.159659 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.099228 
iter  10 value 92.656083
iter  20 value 84.460848
iter  30 value 83.889649
iter  40 value 82.627409
iter  50 value 82.006754
iter  60 value 81.279860
iter  70 value 79.967442
iter  80 value 79.696040
iter  90 value 79.638647
iter 100 value 79.598294
final  value 79.598294 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.873702 
iter  10 value 93.646127
iter  20 value 91.209482
iter  30 value 88.132225
iter  40 value 86.256392
iter  50 value 82.345568
iter  60 value 81.555113
iter  70 value 80.811821
iter  80 value 79.720383
iter  90 value 79.527489
iter 100 value 79.483526
final  value 79.483526 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 98.716255 
iter  10 value 93.978174
iter  20 value 93.618179
iter  30 value 92.340183
iter  40 value 85.234742
iter  50 value 82.966739
iter  60 value 82.456149
iter  70 value 82.100308
iter  80 value 82.062546
iter  90 value 81.851205
iter 100 value 81.076251
final  value 81.076251 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 116.659090 
iter  10 value 95.305927
iter  20 value 91.640605
iter  30 value 88.316082
iter  40 value 85.993971
iter  50 value 83.143147
iter  60 value 81.949557
iter  70 value 81.154309
iter  80 value 80.849567
iter  90 value 80.106123
iter 100 value 79.814072
final  value 79.814072 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.782219 
iter  10 value 94.148508
iter  20 value 93.433934
iter  30 value 88.277066
iter  40 value 83.475607
iter  50 value 82.363522
iter  60 value 81.909852
iter  70 value 81.709032
iter  80 value 81.677845
iter  90 value 81.634147
iter 100 value 81.258860
final  value 81.258860 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 149.176956 
iter  10 value 98.447962
iter  20 value 95.539807
iter  30 value 89.450634
iter  40 value 87.204725
iter  50 value 86.820227
iter  60 value 84.983493
iter  70 value 83.076020
iter  80 value 81.598007
iter  90 value 81.279873
iter 100 value 80.901359
final  value 80.901359 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.797386 
iter  10 value 93.957830
iter  20 value 85.731228
iter  30 value 85.268646
iter  40 value 84.089102
iter  50 value 81.249370
iter  60 value 80.076410
iter  70 value 79.810810
iter  80 value 79.731910
iter  90 value 79.662568
iter 100 value 79.584454
final  value 79.584454 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 121.270260 
iter  10 value 93.864687
iter  20 value 91.775524
iter  30 value 87.183170
iter  40 value 84.656273
iter  50 value 84.290142
iter  60 value 82.524339
iter  70 value 82.244724
iter  80 value 81.656230
iter  90 value 81.281610
iter 100 value 81.143068
final  value 81.143068 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.474711 
iter  10 value 94.328313
iter  20 value 93.670570
iter  30 value 93.617599
iter  40 value 91.881338
iter  50 value 84.166972
iter  60 value 82.800957
iter  70 value 81.211164
iter  80 value 80.226994
iter  90 value 79.828806
iter 100 value 79.507450
final  value 79.507450 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 115.857898 
iter  10 value 93.799170
iter  20 value 86.999346
iter  30 value 84.235599
iter  40 value 84.046281
iter  50 value 82.725467
iter  60 value 81.377769
iter  70 value 80.526017
iter  80 value 79.587127
iter  90 value 79.316224
iter 100 value 79.264187
final  value 79.264187 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.991717 
iter  10 value 94.054737
iter  20 value 94.052929
final  value 94.052918 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.511411 
iter  10 value 94.054556
iter  20 value 94.052978
final  value 94.052915 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.143047 
iter  10 value 94.045305
final  value 94.044809 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.282098 
final  value 94.054500 
converged
Fitting Repeat 5 

# weights:  103
initial  value 107.609030 
final  value 94.054426 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.357909 
iter  10 value 94.056523
final  value 94.052929 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.457694 
iter  10 value 93.609677
iter  20 value 93.605185
final  value 93.604854 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.984010 
iter  10 value 93.583523
iter  20 value 93.579140
iter  30 value 93.558960
iter  40 value 93.500969
iter  50 value 85.689985
iter  60 value 83.469238
final  value 83.469237 
converged
Fitting Repeat 4 

# weights:  305
initial  value 116.643497 
iter  10 value 94.057810
iter  20 value 94.052989
iter  30 value 94.007190
iter  40 value 93.579629
iter  50 value 93.578952
final  value 93.578948 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.398756 
iter  10 value 94.057382
iter  20 value 92.525445
iter  30 value 86.475810
iter  40 value 86.469285
iter  50 value 86.469116
iter  60 value 86.468424
iter  70 value 85.753285
iter  80 value 82.760504
iter  90 value 82.630717
iter 100 value 82.344748
final  value 82.344748 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 95.716808 
iter  10 value 83.833145
iter  20 value 83.819432
iter  30 value 83.525067
iter  40 value 83.482541
iter  50 value 83.077962
iter  60 value 81.430598
iter  70 value 80.371565
iter  80 value 80.092353
final  value 80.092002 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.754436 
iter  10 value 94.017280
iter  20 value 94.009101
final  value 94.008892 
converged
Fitting Repeat 3 

# weights:  507
initial  value 113.715379 
iter  10 value 85.103408
iter  20 value 82.812278
iter  30 value 82.811567
iter  40 value 82.805623
iter  50 value 82.805498
final  value 82.804505 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.768326 
iter  10 value 94.016869
iter  20 value 93.505558
iter  30 value 87.969178
iter  40 value 87.930131
iter  50 value 87.929296
iter  60 value 84.559022
iter  70 value 81.967570
iter  80 value 79.524208
iter  90 value 79.131004
iter 100 value 79.128432
final  value 79.128432 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.012291 
iter  10 value 94.016896
iter  20 value 94.009793
iter  30 value 91.246860
iter  40 value 85.653985
iter  50 value 83.882000
iter  60 value 83.366536
iter  70 value 80.705588
iter  80 value 80.024472
iter  90 value 79.933742
final  value 79.933426 
converged
Fitting Repeat 1 

# weights:  103
initial  value 111.935885 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.309877 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.841181 
iter  10 value 94.303447
final  value 94.289216 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.094744 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.077717 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.428824 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.816882 
final  value 94.484215 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.556845 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.350166 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 114.261625 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 113.901022 
iter  10 value 94.484211
iter  10 value 94.484211
iter  10 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.953996 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.687017 
iter  10 value 93.330739
iter  20 value 90.434047
iter  30 value 87.486114
iter  40 value 87.481202
final  value 87.481074 
converged
Fitting Repeat 4 

# weights:  507
initial  value 108.961745 
final  value 93.701657 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.044175 
final  value 94.428839 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.599943 
iter  10 value 93.342808
iter  20 value 88.305532
iter  30 value 88.117862
iter  40 value 85.198689
iter  50 value 84.781833
iter  60 value 84.693653
iter  70 value 83.804579
iter  80 value 83.546096
iter  90 value 83.339191
iter 100 value 83.257597
final  value 83.257597 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 98.783727 
iter  10 value 94.383360
iter  20 value 94.381924
iter  30 value 91.099134
iter  40 value 88.334596
iter  50 value 87.093627
iter  60 value 86.817948
iter  70 value 85.959575
iter  80 value 84.869704
iter  90 value 83.578815
iter 100 value 83.265243
final  value 83.265243 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 99.617978 
iter  10 value 94.463150
iter  20 value 92.833262
iter  30 value 91.431064
iter  40 value 91.229446
iter  50 value 91.097267
iter  60 value 91.090474
final  value 91.090431 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.435973 
iter  10 value 94.486687
iter  20 value 94.220196
iter  30 value 94.118855
iter  40 value 94.115020
iter  50 value 94.113766
iter  60 value 94.113001
final  value 94.112594 
converged
Fitting Repeat 5 

# weights:  103
initial  value 107.714481 
iter  10 value 94.488526
iter  20 value 94.251698
iter  30 value 92.359770
iter  40 value 88.831909
iter  50 value 86.622062
iter  60 value 85.287745
iter  70 value 83.286047
iter  80 value 81.904601
iter  90 value 81.590552
iter 100 value 81.490499
final  value 81.490499 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 101.646181 
iter  10 value 94.488412
iter  20 value 94.417275
iter  30 value 87.811700
iter  40 value 86.204553
iter  50 value 82.882463
iter  60 value 82.425156
iter  70 value 81.878600
iter  80 value 81.283531
iter  90 value 81.095175
iter 100 value 80.984316
final  value 80.984316 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.798683 
iter  10 value 94.715956
iter  20 value 91.225973
iter  30 value 86.857566
iter  40 value 84.579297
iter  50 value 83.368694
iter  60 value 83.284547
iter  70 value 83.065659
iter  80 value 82.992200
iter  90 value 82.337154
iter 100 value 81.755942
final  value 81.755942 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.322094 
iter  10 value 93.718915
iter  20 value 84.279247
iter  30 value 83.783613
iter  40 value 83.561823
iter  50 value 83.288483
iter  60 value 83.070183
iter  70 value 82.505880
iter  80 value 81.195304
iter  90 value 80.661961
iter 100 value 80.282491
final  value 80.282491 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.598948 
iter  10 value 94.374155
iter  20 value 88.179329
iter  30 value 84.374071
iter  40 value 83.728660
iter  50 value 82.622421
iter  60 value 82.427919
iter  70 value 82.276809
iter  80 value 82.265539
iter  90 value 82.261771
iter 100 value 82.236450
final  value 82.236450 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.316903 
iter  10 value 95.113519
iter  20 value 91.197065
iter  30 value 87.530678
iter  40 value 87.008493
iter  50 value 86.893929
iter  60 value 83.834816
iter  70 value 83.549096
iter  80 value 83.380629
iter  90 value 83.353183
iter 100 value 83.218847
final  value 83.218847 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 135.232859 
iter  10 value 94.417464
iter  20 value 89.972793
iter  30 value 87.075771
iter  40 value 85.177212
iter  50 value 81.062398
iter  60 value 80.717366
iter  70 value 80.190316
iter  80 value 80.101815
iter  90 value 79.894228
iter 100 value 79.843882
final  value 79.843882 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 159.369325 
iter  10 value 95.578432
iter  20 value 94.492970
iter  30 value 94.187569
iter  40 value 89.051065
iter  50 value 86.488435
iter  60 value 85.040211
iter  70 value 84.317184
iter  80 value 81.085467
iter  90 value 80.023541
iter 100 value 79.687884
final  value 79.687884 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 120.994439 
iter  10 value 94.645195
iter  20 value 86.205179
iter  30 value 84.979059
iter  40 value 84.775387
iter  50 value 84.518643
iter  60 value 83.550711
iter  70 value 82.992341
iter  80 value 81.626722
iter  90 value 81.342540
iter 100 value 80.901476
final  value 80.901476 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.153812 
iter  10 value 94.442326
iter  20 value 91.822982
iter  30 value 88.350518
iter  40 value 84.914888
iter  50 value 82.597940
iter  60 value 81.819231
iter  70 value 81.594369
iter  80 value 80.355220
iter  90 value 80.088622
iter 100 value 79.939788
final  value 79.939788 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.718383 
iter  10 value 93.239139
iter  20 value 87.273012
iter  30 value 83.736370
iter  40 value 82.376418
iter  50 value 80.442906
iter  60 value 79.746582
iter  70 value 79.331349
iter  80 value 79.232942
iter  90 value 79.125617
iter 100 value 79.048415
final  value 79.048415 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.717389 
iter  10 value 94.485992
iter  20 value 94.398199
iter  30 value 94.074091
final  value 94.066899 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.809802 
final  value 94.486093 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.707610 
final  value 94.485762 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.615125 
final  value 94.485941 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.597346 
iter  10 value 94.486223
final  value 94.484228 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.158558 
iter  10 value 94.358376
iter  20 value 94.338495
iter  30 value 87.679316
iter  40 value 81.744001
iter  50 value 81.438535
iter  60 value 81.166237
iter  70 value 81.131837
iter  80 value 81.008942
iter  90 value 80.980782
iter 100 value 80.979977
final  value 80.979977 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.273675 
iter  10 value 85.115265
iter  20 value 83.038862
iter  30 value 83.030890
iter  40 value 83.009065
iter  50 value 83.005500
iter  60 value 82.692549
iter  70 value 82.136785
iter  80 value 81.129565
iter  90 value 80.768280
iter 100 value 80.599709
final  value 80.599709 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.396590 
iter  10 value 94.359159
iter  20 value 94.357739
iter  20 value 94.357739
iter  20 value 94.357739
final  value 94.357739 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.527961 
iter  10 value 94.359366
iter  20 value 94.294468
iter  30 value 83.035425
iter  40 value 83.029259
iter  50 value 82.876400
iter  60 value 82.475638
iter  70 value 81.952281
iter  80 value 78.962608
iter  90 value 78.335234
iter 100 value 78.296924
final  value 78.296924 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.301624 
iter  10 value 94.488908
iter  20 value 94.484021
iter  30 value 94.112698
final  value 94.112616 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.802412 
iter  10 value 93.709508
iter  20 value 93.598627
iter  30 value 89.824597
iter  40 value 84.882170
iter  50 value 83.219291
iter  60 value 83.150833
iter  70 value 82.974259
iter  80 value 81.827299
final  value 81.825518 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.646013 
iter  10 value 94.491049
iter  20 value 88.781574
iter  30 value 86.316668
iter  40 value 86.300406
iter  50 value 86.300159
iter  60 value 86.297043
iter  70 value 86.115976
iter  80 value 85.700576
iter  90 value 82.454029
iter 100 value 81.789366
final  value 81.789366 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 99.933008 
iter  10 value 94.491183
iter  20 value 94.368435
iter  30 value 92.927196
iter  40 value 91.248632
iter  50 value 91.243074
iter  60 value 91.242650
iter  70 value 91.242017
iter  80 value 91.188147
iter  90 value 83.522604
iter 100 value 82.099974
final  value 82.099974 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 98.293565 
iter  10 value 94.492199
iter  20 value 94.484707
iter  30 value 94.258758
iter  40 value 85.260850
iter  50 value 85.040254
iter  60 value 85.040138
final  value 85.039957 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.718478 
iter  10 value 94.362565
iter  20 value 94.355803
iter  30 value 91.082883
iter  40 value 82.875989
iter  50 value 82.395838
iter  60 value 81.894931
iter  70 value 81.665077
iter  80 value 81.662746
final  value 81.662719 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.570709 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 111.849431 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.341200 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.316258 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.420057 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.988470 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.220679 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.460491 
iter  10 value 85.485890
iter  20 value 84.530857
iter  30 value 84.525372
final  value 84.525346 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.232483 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.669874 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 119.284605 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.930317 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.619811 
final  value 94.038251 
converged
Fitting Repeat 4 

# weights:  507
initial  value 120.916155 
iter  10 value 92.275879
iter  20 value 92.081194
iter  30 value 90.720627
final  value 90.702385 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.140950 
iter  10 value 93.757693
iter  20 value 92.731596
final  value 92.731183 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.597640 
iter  10 value 93.972191
iter  20 value 88.222441
iter  30 value 87.915976
iter  40 value 87.622547
iter  50 value 87.426651
iter  60 value 85.257013
iter  70 value 84.976407
iter  80 value 84.418978
iter  90 value 84.303865
iter 100 value 84.233663
final  value 84.233663 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 110.627189 
iter  10 value 93.954608
iter  20 value 87.569856
iter  30 value 85.613478
iter  40 value 84.631104
iter  50 value 83.543213
iter  60 value 82.868629
iter  70 value 82.780672
final  value 82.780646 
converged
Fitting Repeat 3 

# weights:  103
initial  value 114.918455 
iter  10 value 94.061710
iter  20 value 92.231322
iter  30 value 89.005077
iter  40 value 87.177877
iter  50 value 86.920837
iter  60 value 84.903619
iter  70 value 83.754125
iter  80 value 83.337892
iter  90 value 81.897413
iter 100 value 80.764694
final  value 80.764694 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 100.850132 
iter  10 value 94.056688
iter  20 value 93.629297
iter  30 value 89.062993
iter  40 value 87.410277
iter  50 value 84.243494
iter  60 value 83.635949
iter  70 value 83.614834
final  value 83.614817 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.295478 
iter  10 value 93.874104
iter  20 value 86.830013
iter  30 value 84.700173
iter  40 value 83.603278
iter  50 value 82.979537
iter  60 value 82.243797
iter  70 value 81.197095
iter  80 value 80.954675
final  value 80.936416 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.889002 
iter  10 value 94.025629
iter  20 value 93.580480
iter  30 value 89.387749
iter  40 value 85.232766
iter  50 value 83.828440
iter  60 value 82.340980
iter  70 value 81.412756
iter  80 value 80.760477
iter  90 value 80.278476
iter 100 value 79.400563
final  value 79.400563 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.443714 
iter  10 value 94.066251
iter  20 value 93.594197
iter  30 value 92.696528
iter  40 value 91.043359
iter  50 value 89.047809
iter  60 value 87.990455
iter  70 value 84.267488
iter  80 value 83.894220
iter  90 value 82.672460
iter 100 value 81.930602
final  value 81.930602 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 112.357865 
iter  10 value 94.072030
iter  20 value 92.940753
iter  30 value 88.005808
iter  40 value 86.923688
iter  50 value 85.495880
iter  60 value 83.434598
iter  70 value 81.206164
iter  80 value 80.716392
iter  90 value 80.230568
iter 100 value 79.944655
final  value 79.944655 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.728339 
iter  10 value 94.142030
iter  20 value 88.251670
iter  30 value 86.237243
iter  40 value 84.978040
iter  50 value 81.965390
iter  60 value 80.320959
iter  70 value 79.423199
iter  80 value 79.171252
iter  90 value 79.130518
final  value 79.123916 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.687132 
iter  10 value 93.986093
iter  20 value 90.625377
iter  30 value 85.924587
iter  40 value 85.478896
iter  50 value 83.158576
iter  60 value 82.227263
iter  70 value 81.465258
iter  80 value 81.426422
iter  90 value 80.998742
iter 100 value 80.168264
final  value 80.168264 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.517083 
iter  10 value 97.200703
iter  20 value 91.882748
iter  30 value 90.182973
iter  40 value 87.856193
iter  50 value 84.846558
iter  60 value 81.709596
iter  70 value 81.159282
iter  80 value 79.847479
iter  90 value 79.557780
iter 100 value 79.414511
final  value 79.414511 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 114.638422 
iter  10 value 93.983613
iter  20 value 90.770458
iter  30 value 85.936695
iter  40 value 84.693381
iter  50 value 82.123230
iter  60 value 80.138743
iter  70 value 79.802458
iter  80 value 79.579991
iter  90 value 79.515268
iter 100 value 79.490371
final  value 79.490371 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 117.732720 
iter  10 value 94.060656
iter  20 value 86.876671
iter  30 value 85.586390
iter  40 value 85.028906
iter  50 value 82.695851
iter  60 value 81.481568
iter  70 value 81.175748
iter  80 value 79.778550
iter  90 value 79.410161
iter 100 value 79.263931
final  value 79.263931 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.987245 
iter  10 value 93.382668
iter  20 value 86.790292
iter  30 value 85.089131
iter  40 value 83.948878
iter  50 value 81.402658
iter  60 value 80.731753
iter  70 value 80.325301
iter  80 value 79.845135
iter  90 value 79.196406
iter 100 value 79.089035
final  value 79.089035 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.033508 
iter  10 value 93.753163
iter  20 value 87.390679
iter  30 value 83.162490
iter  40 value 81.495354
iter  50 value 80.657503
iter  60 value 80.344314
iter  70 value 79.813758
iter  80 value 79.566450
iter  90 value 79.464629
iter 100 value 79.445187
final  value 79.445187 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.888670 
final  value 94.054515 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.609212 
iter  10 value 94.054678
iter  20 value 94.012945
iter  30 value 88.178620
iter  40 value 83.080164
iter  50 value 83.045701
iter  60 value 83.044616
iter  70 value 83.044216
iter  80 value 83.041709
iter  90 value 83.035208
iter 100 value 82.505654
final  value 82.505654 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.726794 
final  value 94.054560 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.861752 
final  value 94.054435 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.751080 
final  value 94.054418 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.801526 
iter  10 value 94.057734
iter  20 value 93.940509
iter  30 value 90.400769
iter  40 value 86.797336
iter  50 value 86.557345
final  value 86.544295 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.235462 
iter  10 value 94.057235
iter  20 value 94.051230
iter  30 value 91.074273
iter  40 value 90.863194
iter  50 value 90.859450
iter  60 value 90.858553
final  value 90.858268 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.838181 
iter  10 value 94.057842
iter  20 value 94.052995
iter  30 value 93.204763
iter  40 value 92.097714
final  value 92.096239 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.189012 
iter  10 value 94.057810
iter  20 value 89.129131
iter  30 value 85.275836
iter  40 value 85.113023
final  value 85.112213 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.742187 
iter  10 value 94.056964
iter  20 value 93.829151
iter  30 value 89.867846
iter  40 value 89.865701
iter  50 value 89.865181
iter  60 value 89.862411
iter  70 value 89.861827
iter  80 value 89.450758
iter  90 value 89.070113
final  value 89.069977 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.470825 
iter  10 value 94.059538
iter  20 value 93.859821
iter  30 value 84.736348
iter  40 value 84.488821
final  value 84.488629 
converged
Fitting Repeat 2 

# weights:  507
initial  value 115.266921 
iter  10 value 94.046656
iter  20 value 93.879606
iter  30 value 91.540317
iter  40 value 91.488330
iter  50 value 91.487669
iter  60 value 91.485434
iter  70 value 91.370471
iter  80 value 91.369348
iter  90 value 91.366372
iter 100 value 91.365423
final  value 91.365423 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.019878 
iter  10 value 94.047067
iter  20 value 94.041433
final  value 94.039476 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.015007 
iter  10 value 94.060418
iter  20 value 94.038425
iter  30 value 87.757084
iter  40 value 87.345508
iter  50 value 87.335847
final  value 87.335417 
converged
Fitting Repeat 5 

# weights:  507
initial  value 113.060891 
iter  10 value 94.060454
iter  20 value 94.053017
iter  30 value 88.537254
iter  40 value 84.976858
iter  50 value 84.972472
iter  60 value 84.963097
iter  70 value 84.817914
iter  80 value 84.106695
iter  90 value 79.430830
iter 100 value 78.851025
final  value 78.851025 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 133.677397 
iter  10 value 117.763515
iter  20 value 117.611564
iter  30 value 107.250782
iter  40 value 106.847975
iter  50 value 106.062245
iter  60 value 106.046572
iter  70 value 105.939893
final  value 105.932151 
converged
Fitting Repeat 2 

# weights:  305
initial  value 123.940004 
iter  10 value 117.871262
iter  20 value 117.648347
iter  30 value 106.415687
iter  40 value 104.505251
iter  50 value 104.453188
iter  60 value 104.452194
final  value 104.452024 
converged
Fitting Repeat 3 

# weights:  305
initial  value 123.990299 
iter  10 value 117.211103
iter  20 value 115.437301
iter  30 value 105.647370
iter  40 value 103.805461
iter  50 value 102.446684
iter  60 value 102.423421
iter  70 value 102.422836
iter  80 value 102.420938
iter  90 value 102.402334
iter 100 value 101.882878
final  value 101.882878 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 122.030847 
iter  10 value 117.894735
iter  20 value 113.041407
iter  30 value 108.777831
final  value 107.004015 
converged
Fitting Repeat 5 

# weights:  305
initial  value 132.354035 
iter  10 value 117.853587
iter  20 value 117.849145
iter  30 value 117.549878
iter  40 value 117.549825
iter  40 value 117.549825
final  value 117.549825 
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 -- Fri Mar 14 07:12:18 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 
 51.816   1.082 129.277