##############################################################################
##############################################################################
###
### 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_1.15.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.22-bioc/meat/HPiP.Rcheck’
* using R version 4.5.0 (2025-04-11)
* 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 ‘1.15.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... INFO
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
var_imp       35.806  0.391  36.544
corr_plot     34.193  0.311  34.563
FSmethod      33.440  0.599  34.094
pred_ensembel 17.995  0.630  17.435
enrichfindP    0.510  0.008  21.375
getFASTA       0.079  0.004   6.099
* 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: 2 NOTEs
See
  ‘/home/biocbuild/bbs-3.22-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-4.5.0/site-library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.15.0’
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R version 4.5.0 (2025-04-11) -- "How About a Twenty-Six"
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 98.578794 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.213910 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.324091 
iter  10 value 94.047879
final  value 94.026542 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.886102 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.870756 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.988649 
final  value 94.026542 
converged
Fitting Repeat 2 

# weights:  305
initial  value 113.354456 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.396342 
final  value 94.088889 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.097158 
final  value 94.026542 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.626093 
final  value 94.026542 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.446850 
iter  10 value 91.251364
iter  20 value 88.130119
final  value 88.126185 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.310173 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.371849 
final  value 94.026542 
converged
Fitting Repeat 4 

# weights:  507
initial  value 116.253715 
iter  10 value 93.992035
iter  20 value 85.316494
iter  30 value 85.244058
final  value 85.243423 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.697731 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.877837 
iter  10 value 94.487124
iter  20 value 93.721292
iter  30 value 88.159736
iter  40 value 85.799636
iter  50 value 84.706371
iter  60 value 84.487688
iter  70 value 83.269836
iter  80 value 82.342552
iter  90 value 82.105392
iter 100 value 82.073313
final  value 82.073313 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 102.912927 
iter  10 value 94.867745
iter  20 value 94.488122
iter  30 value 94.110258
iter  40 value 86.740175
iter  50 value 86.065765
iter  60 value 84.077089
iter  70 value 83.920101
iter  80 value 83.864468
iter  90 value 83.821728
iter 100 value 83.500417
final  value 83.500417 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 101.037592 
iter  10 value 94.683500
iter  20 value 94.486463
iter  30 value 94.051742
iter  40 value 93.789857
iter  50 value 86.775291
iter  60 value 85.723011
iter  70 value 85.636921
iter  80 value 85.611882
iter  90 value 85.590407
iter 100 value 85.454919
final  value 85.454919 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 109.697597 
iter  10 value 94.439068
iter  20 value 94.077670
iter  30 value 89.396701
iter  40 value 87.689582
iter  50 value 87.359588
iter  60 value 85.899584
iter  70 value 85.410572
iter  80 value 85.284519
iter  90 value 82.558218
iter 100 value 82.348294
final  value 82.348294 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 107.823078 
iter  10 value 94.454502
iter  20 value 94.372604
iter  30 value 92.923640
iter  40 value 92.753721
iter  50 value 92.446309
iter  60 value 92.061097
iter  70 value 92.020187
iter  80 value 91.585612
iter  90 value 91.283115
iter 100 value 91.266433
final  value 91.266433 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 113.410604 
iter  10 value 94.292693
iter  20 value 89.360945
iter  30 value 87.756279
iter  40 value 85.762983
iter  50 value 85.286310
iter  60 value 85.055061
iter  70 value 84.250039
iter  80 value 82.934373
iter  90 value 82.172710
iter 100 value 81.848423
final  value 81.848423 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 125.231977 
iter  10 value 94.717242
iter  20 value 94.080238
iter  30 value 87.885404
iter  40 value 86.019144
iter  50 value 85.787294
iter  60 value 85.715073
iter  70 value 84.848803
iter  80 value 83.105186
iter  90 value 82.816716
iter 100 value 82.781064
final  value 82.781064 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 117.470297 
iter  10 value 94.013091
iter  20 value 87.722344
iter  30 value 86.162414
iter  40 value 85.516928
iter  50 value 84.889150
iter  60 value 82.951162
iter  70 value 82.093497
iter  80 value 81.151530
iter  90 value 80.869448
iter 100 value 80.708563
final  value 80.708563 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 120.520719 
iter  10 value 94.903085
iter  20 value 92.969201
iter  30 value 90.977662
iter  40 value 85.667359
iter  50 value 84.447708
iter  60 value 84.095891
iter  70 value 83.289787
iter  80 value 82.335715
iter  90 value 81.763042
iter 100 value 81.641931
final  value 81.641931 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.712383 
iter  10 value 94.508753
iter  20 value 94.192738
iter  30 value 93.812406
iter  40 value 90.225338
iter  50 value 86.866744
iter  60 value 85.509408
iter  70 value 84.434296
iter  80 value 83.806070
iter  90 value 83.293094
iter 100 value 83.230016
final  value 83.230016 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 124.438649 
iter  10 value 100.162471
iter  20 value 87.759378
iter  30 value 85.192271
iter  40 value 84.039414
iter  50 value 82.487643
iter  60 value 81.720906
iter  70 value 81.352745
iter  80 value 81.108449
iter  90 value 80.931677
iter 100 value 80.779038
final  value 80.779038 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.903710 
iter  10 value 94.309939
iter  20 value 92.039584
iter  30 value 85.601090
iter  40 value 82.615497
iter  50 value 82.364338
iter  60 value 81.946681
iter  70 value 80.951460
iter  80 value 80.273283
iter  90 value 80.202727
iter 100 value 80.075875
final  value 80.075875 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 112.259458 
iter  10 value 96.855931
iter  20 value 92.617107
iter  30 value 89.351270
iter  40 value 87.553751
iter  50 value 85.482340
iter  60 value 83.311211
iter  70 value 82.473098
iter  80 value 81.933783
iter  90 value 81.607782
iter 100 value 81.531381
final  value 81.531381 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.856158 
iter  10 value 95.568613
iter  20 value 92.559377
iter  30 value 86.335446
iter  40 value 85.504939
iter  50 value 83.392876
iter  60 value 81.186988
iter  70 value 80.443565
iter  80 value 80.175694
iter  90 value 80.051901
iter 100 value 79.786983
final  value 79.786983 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 117.966006 
iter  10 value 94.217743
iter  20 value 88.956398
iter  30 value 86.555823
iter  40 value 86.359676
iter  50 value 83.444802
iter  60 value 82.834409
iter  70 value 82.630559
iter  80 value 82.136673
iter  90 value 81.719540
iter 100 value 81.423302
final  value 81.423302 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.139813 
final  value 94.485611 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.956162 
final  value 94.485877 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.373795 
final  value 94.485761 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.076368 
final  value 94.485941 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.235720 
final  value 94.486006 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.839696 
iter  10 value 85.444838
iter  20 value 84.283009
iter  30 value 83.678560
iter  40 value 83.675597
iter  50 value 83.673588
final  value 83.672626 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.230743 
iter  10 value 94.031365
iter  20 value 88.965544
iter  30 value 86.897144
iter  40 value 86.618096
iter  50 value 86.617949
final  value 86.617882 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.786641 
iter  10 value 94.488893
iter  20 value 94.482263
iter  30 value 93.643670
iter  40 value 89.170055
iter  50 value 89.082927
iter  60 value 89.082732
iter  60 value 89.082731
iter  70 value 89.082458
iter  80 value 88.843254
iter  90 value 88.842787
iter 100 value 86.044615
final  value 86.044615 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 114.554000 
iter  10 value 94.107886
iter  20 value 87.162734
iter  30 value 85.914122
iter  40 value 83.743785
iter  50 value 83.552472
iter  60 value 83.549543
final  value 83.549099 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.549880 
iter  10 value 94.031701
iter  20 value 93.923056
iter  30 value 92.132664
iter  40 value 91.603981
iter  50 value 91.293403
iter  60 value 91.274349
iter  70 value 91.272013
iter  80 value 91.271531
final  value 91.271412 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.540694 
iter  10 value 94.491882
iter  20 value 94.483683
iter  30 value 94.028529
final  value 94.027391 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.598151 
iter  10 value 93.683434
iter  20 value 93.673457
iter  30 value 93.671182
iter  40 value 93.654330
iter  50 value 93.640002
iter  60 value 93.535804
iter  70 value 93.521259
iter  80 value 93.519010
iter  90 value 93.514452
iter 100 value 92.354896
final  value 92.354896 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.313834 
iter  10 value 94.035082
iter  20 value 93.985621
iter  30 value 93.971549
iter  40 value 89.803819
iter  50 value 86.679414
iter  60 value 86.084548
iter  70 value 86.016819
iter  80 value 86.015950
final  value 86.015919 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.339345 
iter  10 value 94.034467
iter  20 value 93.998864
final  value 93.969842 
converged
Fitting Repeat 5 

# weights:  507
initial  value 126.521408 
iter  10 value 94.485029
iter  20 value 92.138114
iter  30 value 87.991589
iter  40 value 87.698342
iter  50 value 86.075198
iter  60 value 83.695115
iter  70 value 82.217531
iter  80 value 81.987320
iter  90 value 81.904763
final  value 81.904342 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.839157 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 109.401311 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.693776 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 109.679607 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.928004 
iter  10 value 93.900827
final  value 93.900011 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.283652 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.316147 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.411345 
final  value 93.869755 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.506009 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 109.311983 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 119.213151 
iter  10 value 89.651443
iter  20 value 83.422980
iter  30 value 82.443130
iter  40 value 82.404533
iter  50 value 82.325798
final  value 82.325732 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.141616 
iter  10 value 84.012009
iter  20 value 83.964864
iter  30 value 82.100897
final  value 82.021773 
converged
Fitting Repeat 3 

# weights:  507
initial  value 113.756164 
final  value 94.038251 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.306797 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.589625 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.262929 
iter  10 value 94.056269
iter  20 value 90.826967
iter  30 value 85.971177
iter  40 value 83.545387
iter  50 value 83.383060
iter  60 value 82.815770
iter  70 value 81.567897
iter  80 value 81.527626
final  value 81.527575 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.863826 
iter  10 value 93.687024
iter  20 value 93.368339
iter  30 value 84.287078
iter  40 value 83.871130
iter  50 value 83.307826
iter  60 value 81.802577
iter  70 value 81.530575
iter  80 value 81.527770
iter  90 value 81.527576
final  value 81.527574 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.884890 
iter  10 value 94.001021
iter  20 value 90.573684
iter  30 value 87.719311
iter  40 value 83.025003
iter  50 value 81.145955
iter  60 value 81.029617
iter  70 value 80.700959
iter  80 value 80.477990
iter  90 value 80.437474
final  value 80.437472 
converged
Fitting Repeat 4 

# weights:  103
initial  value 109.205123 
iter  10 value 94.058371
iter  20 value 87.314210
iter  30 value 84.059212
iter  40 value 81.956217
iter  50 value 81.539356
iter  60 value 81.529201
final  value 81.527575 
converged
Fitting Repeat 5 

# weights:  103
initial  value 107.124362 
iter  10 value 93.992932
iter  20 value 92.717866
iter  30 value 91.388694
iter  40 value 90.913480
iter  50 value 90.030209
iter  60 value 84.122540
iter  70 value 81.996214
iter  80 value 81.592601
iter  90 value 81.528011
final  value 81.527574 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.021010 
iter  10 value 94.193576
iter  20 value 83.882356
iter  30 value 81.543816
iter  40 value 81.199382
iter  50 value 80.300165
iter  60 value 79.725867
iter  70 value 79.577954
iter  80 value 79.284376
iter  90 value 79.202514
iter 100 value 79.176684
final  value 79.176684 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 117.894775 
iter  10 value 94.043198
iter  20 value 91.961326
iter  30 value 87.134692
iter  40 value 83.452673
iter  50 value 83.138732
iter  60 value 80.709135
iter  70 value 80.330523
iter  80 value 79.947274
iter  90 value 79.824335
iter 100 value 79.317902
final  value 79.317902 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.141608 
iter  10 value 95.615436
iter  20 value 91.654218
iter  30 value 84.672488
iter  40 value 83.112555
iter  50 value 81.260220
iter  60 value 81.139362
iter  70 value 80.897785
iter  80 value 79.894808
iter  90 value 79.036803
iter 100 value 78.791038
final  value 78.791038 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.160422 
iter  10 value 93.671757
iter  20 value 90.885945
iter  30 value 85.057600
iter  40 value 82.513034
iter  50 value 80.265148
iter  60 value 79.892824
iter  70 value 79.535980
iter  80 value 79.384458
iter  90 value 79.374450
iter 100 value 79.286779
final  value 79.286779 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.672432 
iter  10 value 94.228446
iter  20 value 83.957808
iter  30 value 81.837119
iter  40 value 81.546710
iter  50 value 81.524581
iter  60 value 81.299155
iter  70 value 81.284476
iter  80 value 81.095192
iter  90 value 80.538363
iter 100 value 80.290025
final  value 80.290025 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 135.416270 
iter  10 value 94.431045
iter  20 value 89.211511
iter  30 value 83.781003
iter  40 value 81.849716
iter  50 value 81.590399
iter  60 value 80.793754
iter  70 value 79.767247
iter  80 value 79.569057
iter  90 value 79.370159
iter 100 value 79.308768
final  value 79.308768 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.827668 
iter  10 value 94.061955
iter  20 value 86.302416
iter  30 value 84.796948
iter  40 value 82.520703
iter  50 value 81.515329
iter  60 value 80.951757
iter  70 value 80.775329
iter  80 value 80.636264
iter  90 value 80.001142
iter 100 value 79.663169
final  value 79.663169 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.872457 
iter  10 value 93.655845
iter  20 value 84.439802
iter  30 value 82.166479
iter  40 value 81.593754
iter  50 value 81.303980
iter  60 value 81.283671
final  value 81.281297 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.583823 
iter  10 value 94.102722
iter  20 value 91.453659
iter  30 value 85.852548
iter  40 value 80.937460
iter  50 value 80.308956
iter  60 value 79.983082
iter  70 value 79.925869
iter  80 value 79.680886
iter  90 value 79.427298
iter 100 value 79.125773
final  value 79.125773 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.765964 
iter  10 value 98.311234
iter  20 value 90.379010
iter  30 value 85.480343
iter  40 value 82.885518
iter  50 value 81.229040
iter  60 value 81.037681
iter  70 value 81.015593
iter  80 value 80.906315
iter  90 value 79.443591
iter 100 value 79.030945
final  value 79.030945 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.286690 
final  value 94.054335 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.585581 
iter  10 value 94.054641
iter  20 value 94.052638
iter  30 value 94.035354
iter  40 value 93.257189
iter  50 value 93.246289
iter  60 value 84.178826
final  value 82.159278 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.350074 
iter  10 value 94.054746
iter  20 value 94.052230
iter  30 value 82.709977
iter  40 value 82.544368
iter  50 value 82.448405
iter  60 value 82.446874
final  value 82.446626 
converged
Fitting Repeat 4 

# weights:  103
initial  value 115.455851 
final  value 94.054699 
converged
Fitting Repeat 5 

# weights:  103
initial  value 116.251748 
iter  10 value 94.054465
iter  20 value 93.758074
iter  30 value 83.572566
iter  40 value 82.267050
iter  50 value 81.432491
iter  60 value 81.343077
iter  70 value 81.342814
iter  70 value 81.342813
iter  70 value 81.342813
final  value 81.342813 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.325141 
iter  10 value 94.057649
iter  20 value 92.784814
iter  30 value 82.162729
iter  40 value 82.161305
iter  50 value 81.507773
iter  60 value 80.157117
iter  70 value 80.133754
iter  80 value 79.517051
iter  90 value 78.970735
iter 100 value 78.820578
final  value 78.820578 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.104786 
iter  10 value 94.042943
iter  20 value 94.041912
iter  30 value 94.038515
final  value 94.038489 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.386870 
iter  10 value 94.056117
iter  20 value 94.041981
iter  30 value 94.041256
iter  40 value 93.880459
iter  50 value 82.185419
iter  60 value 82.163692
iter  70 value 81.972490
iter  80 value 81.923432
iter  90 value 81.729101
iter 100 value 81.725334
final  value 81.725334 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.730148 
iter  10 value 94.057777
iter  20 value 93.877774
iter  30 value 93.805535
iter  40 value 92.223667
final  value 91.254286 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.457319 
iter  10 value 94.058014
iter  20 value 94.053091
iter  30 value 93.552284
iter  40 value 83.861945
final  value 83.535494 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.593600 
iter  10 value 85.019481
iter  20 value 83.632190
iter  30 value 83.629645
iter  40 value 83.628249
iter  50 value 81.628351
iter  60 value 81.555560
iter  70 value 81.555198
iter  80 value 81.554277
final  value 81.554216 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.790409 
iter  10 value 93.833452
iter  20 value 93.828185
iter  30 value 93.826183
iter  30 value 93.826182
iter  30 value 93.826182
final  value 93.826182 
converged
Fitting Repeat 3 

# weights:  507
initial  value 110.216077 
iter  10 value 94.060854
iter  20 value 93.915841
iter  30 value 82.741497
iter  40 value 82.405205
iter  50 value 80.967420
iter  60 value 80.934963
iter  70 value 80.214992
iter  80 value 79.735194
iter  90 value 79.734661
iter 100 value 79.728396
final  value 79.728396 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 97.446301 
iter  10 value 94.046009
iter  20 value 94.038509
final  value 94.038392 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.250249 
iter  10 value 84.155119
iter  20 value 80.482623
iter  30 value 80.280891
final  value 80.278633 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.700775 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.275174 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.598488 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.486893 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.439098 
final  value 94.050000 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.791223 
iter  10 value 93.990542
final  value 93.988095 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.508374 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.475798 
iter  10 value 85.006556
iter  20 value 84.940721
iter  30 value 84.926930
iter  40 value 84.895868
iter  50 value 84.827218
iter  50 value 84.827218
iter  50 value 84.827217
final  value 84.827217 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.771025 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.199997 
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.263440 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 117.459741 
iter  10 value 91.618225
iter  20 value 84.668264
iter  30 value 84.618295
iter  40 value 84.426597
iter  50 value 84.279948
final  value 84.272860 
converged
Fitting Repeat 3 

# weights:  507
initial  value 113.732667 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 110.894733 
final  value 93.988095 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.532854 
iter  10 value 94.045163
iter  20 value 94.032973
final  value 94.032968 
converged
Fitting Repeat 1 

# weights:  103
initial  value 115.558367 
iter  10 value 94.042428
iter  20 value 88.819459
iter  30 value 87.985558
iter  40 value 87.739342
iter  50 value 85.125737
iter  60 value 83.599370
iter  70 value 82.867118
iter  80 value 82.616297
iter  90 value 82.579395
final  value 82.579320 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.629060 
iter  10 value 94.062868
iter  20 value 94.055379
iter  30 value 89.638419
iter  40 value 84.679095
iter  50 value 84.347479
iter  60 value 84.219396
iter  70 value 83.988884
iter  80 value 82.831444
iter  90 value 82.450858
iter 100 value 82.406259
final  value 82.406259 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 99.768575 
iter  10 value 93.417536
iter  20 value 88.318554
iter  30 value 84.392243
iter  40 value 84.082736
iter  50 value 83.793525
iter  60 value 83.087335
iter  70 value 82.517158
iter  80 value 81.194827
iter  90 value 80.958073
final  value 80.922627 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.020000 
iter  10 value 93.810689
iter  20 value 88.727859
iter  30 value 86.550201
iter  40 value 86.493775
iter  50 value 83.261471
iter  60 value 82.965915
iter  70 value 82.760872
iter  80 value 81.887951
iter  90 value 81.512465
iter 100 value 81.417690
final  value 81.417690 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 98.473357 
iter  10 value 94.052711
iter  20 value 94.002704
iter  30 value 88.643001
iter  40 value 85.223452
iter  50 value 84.319094
iter  60 value 84.059705
iter  70 value 83.417778
iter  80 value 82.919023
iter  90 value 82.657288
iter 100 value 82.626107
final  value 82.626107 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 117.407008 
iter  10 value 94.102650
iter  20 value 90.634107
iter  30 value 84.523868
iter  40 value 84.171612
iter  50 value 83.677477
iter  60 value 81.397744
iter  70 value 80.986252
iter  80 value 80.042158
iter  90 value 79.883294
iter 100 value 79.694985
final  value 79.694985 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.556275 
iter  10 value 93.494615
iter  20 value 88.712798
iter  30 value 84.516557
iter  40 value 83.716845
iter  50 value 82.889027
iter  60 value 82.057151
iter  70 value 80.718682
iter  80 value 79.868880
iter  90 value 79.478541
iter 100 value 79.102866
final  value 79.102866 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.369666 
iter  10 value 94.136147
iter  20 value 87.910636
iter  30 value 85.138750
iter  40 value 84.917390
iter  50 value 81.962803
iter  60 value 80.074611
iter  70 value 79.639657
iter  80 value 79.320754
iter  90 value 78.955062
iter 100 value 78.754033
final  value 78.754033 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.677705 
iter  10 value 93.914254
iter  20 value 88.365872
iter  30 value 86.634220
iter  40 value 86.205418
iter  50 value 86.028938
iter  60 value 85.879950
iter  70 value 83.272600
iter  80 value 82.368535
iter  90 value 81.961563
iter 100 value 80.182310
final  value 80.182310 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.160561 
iter  10 value 94.216734
iter  20 value 94.061385
iter  30 value 93.613465
iter  40 value 85.177521
iter  50 value 83.812893
iter  60 value 81.344457
iter  70 value 79.990105
iter  80 value 79.748402
iter  90 value 79.132451
iter 100 value 78.873981
final  value 78.873981 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.592135 
iter  10 value 94.058463
iter  20 value 91.066635
iter  30 value 84.778819
iter  40 value 81.638063
iter  50 value 80.355907
iter  60 value 79.256171
iter  70 value 78.728067
iter  80 value 78.240371
iter  90 value 78.146430
iter 100 value 78.099686
final  value 78.099686 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 130.840973 
iter  10 value 94.877901
iter  20 value 93.270075
iter  30 value 85.436983
iter  40 value 83.845438
iter  50 value 82.815731
iter  60 value 80.762347
iter  70 value 79.416455
iter  80 value 78.812495
iter  90 value 78.614644
iter 100 value 78.441463
final  value 78.441463 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.390275 
iter  10 value 96.607381
iter  20 value 96.253478
iter  30 value 94.086840
iter  40 value 87.342377
iter  50 value 85.519056
iter  60 value 84.839124
iter  70 value 82.588501
iter  80 value 81.137798
iter  90 value 81.037654
iter 100 value 80.866327
final  value 80.866327 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 128.365231 
iter  10 value 93.753173
iter  20 value 87.847263
iter  30 value 83.558345
iter  40 value 82.304036
iter  50 value 81.074390
iter  60 value 80.463420
iter  70 value 79.934061
iter  80 value 79.406710
iter  90 value 79.201290
iter 100 value 79.142357
final  value 79.142357 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.528152 
iter  10 value 98.403229
iter  20 value 93.646048
iter  30 value 92.680354
iter  40 value 89.730212
iter  50 value 85.632389
iter  60 value 84.401291
iter  70 value 83.587481
iter  80 value 82.332411
iter  90 value 80.475043
iter 100 value 79.213879
final  value 79.213879 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.989884 
final  value 94.054643 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.829977 
final  value 94.054411 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.399629 
final  value 94.054392 
converged
Fitting Repeat 4 

# weights:  103
initial  value 111.721191 
final  value 94.034619 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.101666 
final  value 94.054543 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.130593 
iter  10 value 94.057471
iter  20 value 93.359029
iter  30 value 92.266206
iter  40 value 92.263181
iter  50 value 92.218669
iter  60 value 92.218557
iter  60 value 92.218556
iter  60 value 92.218556
final  value 92.218556 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.575004 
iter  10 value 94.056677
iter  20 value 94.047344
iter  30 value 84.618652
iter  40 value 83.032792
iter  50 value 82.944385
iter  60 value 82.943834
iter  70 value 82.637363
iter  80 value 82.593698
iter  90 value 82.593378
final  value 82.592869 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.424841 
iter  10 value 94.056006
iter  20 value 94.016584
iter  30 value 94.013310
iter  40 value 94.010749
iter  50 value 92.676690
iter  60 value 91.696427
iter  70 value 91.115854
iter  80 value 82.112907
iter  90 value 82.040106
iter 100 value 82.035612
final  value 82.035612 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.937843 
iter  10 value 94.057873
iter  20 value 94.053068
iter  30 value 84.921951
iter  40 value 84.347750
iter  50 value 82.787564
iter  60 value 79.737247
iter  70 value 79.551485
iter  80 value 78.225163
iter  90 value 78.152468
iter 100 value 78.151003
final  value 78.151003 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.429643 
iter  10 value 94.038304
iter  20 value 94.033876
iter  30 value 93.371782
iter  40 value 86.386669
iter  50 value 84.644427
iter  60 value 84.004880
iter  70 value 83.066905
iter  80 value 82.752113
iter  90 value 82.700620
iter 100 value 82.700209
final  value 82.700209 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 97.645396 
iter  10 value 94.041246
iter  20 value 94.038758
iter  30 value 93.895047
iter  40 value 91.251185
iter  50 value 84.533561
iter  60 value 84.430634
iter  70 value 84.429698
iter  80 value 84.428496
iter  90 value 84.428035
iter 100 value 84.426696
final  value 84.426696 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 102.800672 
iter  10 value 88.935641
iter  20 value 81.922833
iter  30 value 81.810937
iter  40 value 81.630638
iter  50 value 81.613840
iter  60 value 81.605759
final  value 81.595693 
converged
Fitting Repeat 3 

# weights:  507
initial  value 110.325590 
iter  10 value 94.041448
iter  20 value 92.035798
iter  30 value 84.919524
iter  40 value 84.840199
iter  40 value 84.840199
final  value 84.840199 
converged
Fitting Repeat 4 

# weights:  507
initial  value 122.659538 
iter  10 value 94.041431
iter  20 value 93.851791
iter  30 value 91.934382
iter  40 value 90.101459
iter  50 value 90.050456
iter  60 value 89.962029
iter  70 value 89.942956
iter  80 value 89.928916
iter  90 value 89.865622
iter 100 value 88.981234
final  value 88.981234 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 115.338101 
iter  10 value 94.060847
iter  20 value 94.036123
iter  30 value 91.823447
iter  40 value 89.089880
iter  50 value 83.441480
iter  60 value 81.282118
iter  70 value 81.069436
iter  80 value 81.023450
iter  90 value 80.982786
iter 100 value 80.925187
final  value 80.925187 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.306796 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.897224 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.420457 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 109.383495 
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.330564 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.755887 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.856619 
iter  10 value 93.772978
final  value 93.772973 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.654472 
iter  10 value 91.657934
iter  20 value 91.614755
iter  30 value 91.491610
final  value 91.491554 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.005168 
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.730219 
final  value 93.456972 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.139014 
iter  10 value 93.637379
iter  10 value 93.637379
iter  10 value 93.637379
final  value 93.637379 
converged
Fitting Repeat 2 

# weights:  507
initial  value 113.974192 
final  value 94.275362 
converged
Fitting Repeat 3 

# weights:  507
initial  value 118.722315 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.757888 
iter  10 value 94.047684
final  value 93.999229 
converged
Fitting Repeat 5 

# weights:  507
initial  value 110.498918 
iter  10 value 93.643864
final  value 93.637379 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.083878 
iter  10 value 94.467603
iter  20 value 88.573319
iter  30 value 86.415691
iter  40 value 84.561908
iter  50 value 84.292142
iter  60 value 84.286971
final  value 84.286880 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.301697 
iter  10 value 94.486566
iter  20 value 93.916888
iter  30 value 93.772000
iter  40 value 93.702507
iter  50 value 86.961544
iter  60 value 86.418876
iter  70 value 84.306582
iter  80 value 84.298824
iter  90 value 84.112987
iter 100 value 83.925864
final  value 83.925864 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 106.519309 
iter  10 value 94.574172
iter  20 value 94.446096
iter  30 value 87.779228
iter  40 value 85.655983
iter  50 value 84.453930
iter  60 value 84.325099
iter  70 value 84.300386
iter  80 value 84.286880
final  value 84.286879 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.011681 
iter  10 value 94.449309
iter  20 value 90.951697
iter  30 value 87.512372
iter  40 value 84.560620
iter  50 value 83.345506
iter  60 value 82.178996
iter  70 value 81.874368
iter  80 value 81.692629
iter  90 value 81.180975
final  value 81.180937 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.934156 
iter  10 value 88.844523
iter  20 value 85.775481
iter  30 value 84.806839
iter  40 value 84.102836
iter  50 value 83.194214
iter  60 value 83.135506
iter  70 value 81.792700
iter  80 value 81.078968
iter  90 value 80.964653
final  value 80.963846 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.427474 
iter  10 value 94.465730
iter  20 value 94.077836
iter  30 value 92.522019
iter  40 value 90.683052
iter  50 value 90.453743
iter  60 value 89.215186
iter  70 value 85.324288
iter  80 value 83.081061
iter  90 value 81.766661
iter 100 value 81.060676
final  value 81.060676 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.750490 
iter  10 value 94.431164
iter  20 value 93.959985
iter  30 value 88.189394
iter  40 value 85.530849
iter  50 value 84.566159
iter  60 value 83.487933
iter  70 value 83.344004
iter  80 value 83.266558
iter  90 value 81.719999
iter 100 value 80.535133
final  value 80.535133 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.306993 
iter  10 value 91.503600
iter  20 value 86.472186
iter  30 value 85.505544
iter  40 value 84.251934
iter  50 value 84.050814
iter  60 value 83.062433
iter  70 value 80.638479
iter  80 value 80.388059
iter  90 value 80.028635
iter 100 value 79.800462
final  value 79.800462 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.499157 
iter  10 value 93.569747
iter  20 value 86.935263
iter  30 value 83.602261
iter  40 value 82.994057
iter  50 value 82.896106
iter  60 value 82.463650
iter  70 value 81.773921
iter  80 value 81.176096
iter  90 value 80.901713
iter 100 value 80.310774
final  value 80.310774 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 114.847601 
iter  10 value 94.455805
iter  20 value 89.593654
iter  30 value 88.403021
iter  40 value 84.334598
iter  50 value 82.650204
iter  60 value 82.036215
iter  70 value 81.900487
iter  80 value 81.683478
iter  90 value 81.515502
iter 100 value 81.487586
final  value 81.487586 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 120.833128 
iter  10 value 91.406843
iter  20 value 85.731451
iter  30 value 83.275804
iter  40 value 82.113275
iter  50 value 82.001139
iter  60 value 81.917871
iter  70 value 81.555539
iter  80 value 81.308062
iter  90 value 80.936286
iter 100 value 79.925726
final  value 79.925726 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.779625 
iter  10 value 94.384372
iter  20 value 94.350892
iter  30 value 89.347087
iter  40 value 85.407315
iter  50 value 83.298290
iter  60 value 81.222256
iter  70 value 80.861417
iter  80 value 80.661042
iter  90 value 80.551297
iter 100 value 80.154952
final  value 80.154952 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.805003 
iter  10 value 94.602863
iter  20 value 91.455050
iter  30 value 87.345086
iter  40 value 85.844375
iter  50 value 82.525815
iter  60 value 81.251758
iter  70 value 81.118993
iter  80 value 80.925296
iter  90 value 80.843399
iter 100 value 80.316454
final  value 80.316454 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.334240 
iter  10 value 94.358526
iter  20 value 93.781515
iter  30 value 90.123051
iter  40 value 86.438502
iter  50 value 85.091578
iter  60 value 81.757562
iter  70 value 80.811055
iter  80 value 79.855456
iter  90 value 79.706083
iter 100 value 79.535818
final  value 79.535818 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.154809 
iter  10 value 94.553257
iter  20 value 90.678026
iter  30 value 84.798874
iter  40 value 84.215122
iter  50 value 82.676577
iter  60 value 82.249887
iter  70 value 81.725468
iter  80 value 81.212443
iter  90 value 80.465163
iter 100 value 80.006128
final  value 80.006128 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.164909 
final  value 94.486023 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.648015 
final  value 94.485755 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.618302 
final  value 94.485846 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.025882 
iter  10 value 93.639179
iter  20 value 93.638448
iter  30 value 85.304422
iter  40 value 84.039123
iter  50 value 84.000497
iter  60 value 83.678171
iter  70 value 82.855387
iter  80 value 82.579748
iter  90 value 82.153672
final  value 82.088903 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.294052 
final  value 94.485921 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.710903 
iter  10 value 94.489149
iter  20 value 88.329022
final  value 85.755525 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.640361 
iter  10 value 94.487763
iter  20 value 94.455968
iter  30 value 84.821522
iter  40 value 84.749713
final  value 84.736403 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.994010 
iter  10 value 94.489250
iter  20 value 94.408870
iter  30 value 84.076330
iter  40 value 84.055733
iter  50 value 84.052168
iter  60 value 84.039050
iter  70 value 84.038717
final  value 84.037909 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.348406 
iter  10 value 94.280252
iter  20 value 94.275438
iter  30 value 90.639706
iter  40 value 85.514514
iter  50 value 85.504087
iter  60 value 83.975712
iter  70 value 83.893312
iter  80 value 83.892642
final  value 83.892454 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.340345 
iter  10 value 94.489692
iter  20 value 94.352113
iter  30 value 91.870799
iter  40 value 91.865847
iter  50 value 91.769658
iter  60 value 91.621829
iter  70 value 86.350895
iter  80 value 83.773534
iter  90 value 83.005684
iter 100 value 82.661269
final  value 82.661269 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 122.825493 
iter  10 value 94.283273
iter  20 value 94.198797
iter  30 value 90.978092
iter  40 value 90.352881
iter  50 value 90.263501
iter  60 value 89.243434
iter  70 value 81.666960
iter  80 value 81.621803
iter  90 value 80.861022
iter 100 value 80.553134
final  value 80.553134 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 119.035163 
iter  10 value 94.492434
iter  20 value 94.281149
iter  30 value 84.182884
iter  40 value 84.068012
iter  50 value 83.958949
iter  60 value 79.934075
iter  70 value 79.057003
iter  80 value 78.867579
iter  90 value 78.656789
iter 100 value 78.603815
final  value 78.603815 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 100.726683 
iter  10 value 94.491100
iter  20 value 93.922757
iter  30 value 89.140817
iter  40 value 89.119628
iter  50 value 86.317290
iter  60 value 82.938650
iter  70 value 82.777078
iter  80 value 82.613641
iter  90 value 82.604289
iter 100 value 82.592913
final  value 82.592913 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.939205 
iter  10 value 90.077893
iter  20 value 87.009246
iter  30 value 87.007110
iter  40 value 86.905742
iter  50 value 83.959079
iter  60 value 81.938966
iter  70 value 81.916575
iter  80 value 81.307861
iter  90 value 81.298963
iter 100 value 81.282581
final  value 81.282581 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 97.420915 
iter  10 value 88.945952
iter  20 value 88.592050
iter  30 value 83.107394
iter  40 value 82.089931
iter  50 value 81.588180
iter  60 value 80.406731
iter  70 value 80.128166
iter  80 value 80.113392
iter  90 value 80.059932
iter 100 value 80.016208
final  value 80.016208 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.193068 
final  value 94.275362 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.870591 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.973091 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.069955 
iter  10 value 94.275363
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.553517 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.544072 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.734998 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.007337 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 114.517464 
final  value 94.105263 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.435943 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.580699 
final  value 94.275362 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.389873 
iter  10 value 94.275610
final  value 94.275362 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.424921 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.583593 
final  value 94.088889 
converged
Fitting Repeat 5 

# weights:  507
initial  value 109.883326 
iter  10 value 93.065044
iter  20 value 92.310514
iter  30 value 92.039613
iter  40 value 91.915970
iter  50 value 91.914007
iter  60 value 90.489546
iter  70 value 90.442464
final  value 90.442036 
converged
Fitting Repeat 1 

# weights:  103
initial  value 109.652318 
iter  10 value 94.381065
iter  20 value 93.570247
iter  30 value 93.549090
iter  40 value 93.548698
iter  50 value 89.133801
iter  60 value 87.198392
iter  70 value 86.436845
iter  80 value 83.659860
iter  90 value 82.889751
iter 100 value 82.418746
final  value 82.418746 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 105.047438 
iter  10 value 94.434560
iter  20 value 90.747822
iter  30 value 89.337133
iter  40 value 89.011041
iter  50 value 84.005093
iter  60 value 82.827569
iter  70 value 82.356881
iter  80 value 82.299090
iter  90 value 82.252454
iter 100 value 82.215871
final  value 82.215871 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 102.497581 
iter  10 value 94.552610
iter  20 value 94.487816
iter  30 value 89.838420
iter  40 value 84.604613
iter  50 value 83.680149
iter  60 value 83.476848
iter  70 value 82.602686
iter  80 value 82.310463
iter  90 value 82.271028
iter 100 value 82.215865
final  value 82.215865 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 100.844881 
iter  10 value 93.509255
iter  20 value 87.410991
iter  30 value 86.073433
iter  40 value 85.725662
iter  50 value 85.452440
iter  60 value 85.300731
iter  70 value 85.221502
iter  80 value 85.151871
iter  90 value 85.134162
final  value 85.134157 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.888959 
iter  10 value 94.431329
iter  20 value 93.677652
iter  30 value 93.665589
iter  40 value 89.906577
iter  50 value 87.072581
iter  60 value 86.722927
iter  70 value 85.609033
iter  80 value 83.244194
iter  90 value 82.580873
iter 100 value 82.044010
final  value 82.044010 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 101.589927 
iter  10 value 94.214912
iter  20 value 90.973575
iter  30 value 87.736983
iter  40 value 87.112811
iter  50 value 86.253067
iter  60 value 84.253560
iter  70 value 82.540419
iter  80 value 81.598889
iter  90 value 81.250977
iter 100 value 81.220982
final  value 81.220982 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.483481 
iter  10 value 94.618400
iter  20 value 93.880082
iter  30 value 93.643573
iter  40 value 87.154821
iter  50 value 83.656586
iter  60 value 83.429248
iter  70 value 82.655007
iter  80 value 82.272647
iter  90 value 81.977909
iter 100 value 81.513356
final  value 81.513356 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.781639 
iter  10 value 94.501602
iter  20 value 93.804945
iter  30 value 91.595436
iter  40 value 90.704011
iter  50 value 84.278309
iter  60 value 83.579248
iter  70 value 83.012105
iter  80 value 82.491468
iter  90 value 82.010533
iter 100 value 81.794809
final  value 81.794809 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.953483 
iter  10 value 93.929093
iter  20 value 90.323295
iter  30 value 85.036945
iter  40 value 83.830205
iter  50 value 83.408304
iter  60 value 83.040069
iter  70 value 82.847323
iter  80 value 82.783504
iter  90 value 81.852322
iter 100 value 81.411018
final  value 81.411018 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.821223 
iter  10 value 94.655770
iter  20 value 87.201552
iter  30 value 84.073365
iter  40 value 82.087014
iter  50 value 81.789746
iter  60 value 81.346417
iter  70 value 81.245849
iter  80 value 81.209918
iter  90 value 81.208155
iter 100 value 81.204429
final  value 81.204429 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 131.818078 
iter  10 value 94.401777
iter  20 value 94.231231
iter  30 value 91.578395
iter  40 value 84.226712
iter  50 value 83.205531
iter  60 value 82.031555
iter  70 value 81.687386
iter  80 value 81.206775
iter  90 value 81.074536
iter 100 value 80.926801
final  value 80.926801 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.325260 
iter  10 value 96.603164
iter  20 value 86.475219
iter  30 value 83.412507
iter  40 value 82.620937
iter  50 value 81.986889
iter  60 value 81.433225
iter  70 value 81.304412
iter  80 value 81.138191
iter  90 value 80.952896
iter 100 value 80.799816
final  value 80.799816 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.521880 
iter  10 value 94.481521
iter  20 value 93.687388
iter  30 value 93.556128
iter  40 value 89.281291
iter  50 value 88.403712
iter  60 value 85.120075
iter  70 value 83.184257
iter  80 value 82.488262
iter  90 value 82.197298
iter 100 value 81.967532
final  value 81.967532 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.873252 
iter  10 value 94.061418
iter  20 value 89.037670
iter  30 value 87.537999
iter  40 value 87.155811
iter  50 value 84.417268
iter  60 value 83.200026
iter  70 value 82.825865
iter  80 value 82.010227
iter  90 value 81.806731
iter 100 value 81.552331
final  value 81.552331 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 117.232662 
iter  10 value 93.979109
iter  20 value 89.560884
iter  30 value 85.979998
iter  40 value 84.457285
iter  50 value 82.901074
iter  60 value 82.464667
iter  70 value 82.304556
iter  80 value 81.625027
iter  90 value 81.261500
iter 100 value 81.178607
final  value 81.178607 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.018505 
final  value 94.486019 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.442540 
final  value 94.485828 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.197035 
final  value 94.486088 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.940293 
iter  10 value 94.277099
iter  20 value 93.735108
iter  30 value 93.409714
iter  40 value 93.409480
final  value 93.409478 
converged
Fitting Repeat 5 

# weights:  103
initial  value 108.470253 
iter  10 value 94.787417
iter  20 value 94.707847
iter  30 value 94.488042
final  value 94.484223 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.553530 
iter  10 value 94.093985
iter  20 value 93.977308
iter  30 value 88.251185
iter  40 value 88.245098
iter  50 value 88.244115
iter  60 value 88.243153
iter  70 value 88.182514
iter  80 value 87.433469
iter  90 value 87.367488
final  value 87.367465 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.394228 
iter  10 value 94.230915
iter  20 value 91.792191
iter  30 value 91.479422
iter  40 value 91.477904
iter  50 value 91.476365
iter  60 value 91.395357
iter  70 value 91.184462
final  value 91.184329 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.604090 
iter  10 value 94.488901
iter  20 value 94.484235
final  value 94.484214 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.326104 
iter  10 value 94.489052
iter  20 value 94.313303
final  value 93.559028 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.118672 
iter  10 value 94.094092
iter  20 value 93.864981
iter  30 value 88.452770
iter  40 value 86.234997
iter  50 value 86.205785
iter  60 value 85.538551
iter  70 value 83.702944
iter  80 value 83.558423
iter  90 value 83.556740
iter 100 value 83.556592
final  value 83.556592 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 96.291816 
iter  10 value 94.492498
iter  20 value 94.460066
iter  30 value 93.426052
iter  40 value 90.025108
iter  50 value 85.549826
iter  60 value 85.460658
iter  70 value 85.265087
iter  80 value 85.191623
iter  90 value 85.186706
iter 100 value 83.629084
final  value 83.629084 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 120.938210 
iter  10 value 94.477053
iter  20 value 94.436270
final  value 94.276578 
converged
Fitting Repeat 3 

# weights:  507
initial  value 116.104806 
iter  10 value 94.097187
iter  20 value 94.089809
iter  30 value 92.933813
iter  40 value 85.422665
iter  50 value 82.976920
iter  60 value 82.712045
iter  70 value 82.691457
iter  80 value 82.664031
iter  90 value 82.650171
iter 100 value 81.604649
final  value 81.604649 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.804476 
iter  10 value 94.656049
iter  20 value 94.638029
iter  30 value 93.502875
iter  40 value 87.429745
iter  50 value 87.371449
iter  60 value 87.342274
iter  70 value 84.624862
iter  80 value 83.450154
iter  90 value 82.312349
iter 100 value 81.322510
final  value 81.322510 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 98.886609 
iter  10 value 94.283442
iter  20 value 94.278065
final  value 94.276371 
converged
Fitting Repeat 1 

# weights:  103
initial  value 148.717623 
iter  10 value 117.829206
iter  20 value 117.103485
iter  30 value 116.405972
iter  40 value 115.395378
iter  50 value 107.508180
iter  60 value 105.998922
iter  70 value 105.372116
iter  80 value 105.367589
iter  90 value 105.359732
iter 100 value 105.312941
final  value 105.312941 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 126.852914 
iter  10 value 116.709472
iter  20 value 112.191035
iter  30 value 111.542587
iter  40 value 110.062208
iter  50 value 107.596296
iter  60 value 107.230677
iter  70 value 106.128032
iter  80 value 105.289506
iter  90 value 105.261476
iter 100 value 105.258334
final  value 105.258334 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 134.172616 
iter  10 value 117.854204
iter  20 value 116.569924
iter  30 value 111.679988
iter  40 value 111.035916
iter  50 value 107.401507
iter  60 value 107.288985
iter  70 value 106.805284
iter  80 value 105.949541
iter  90 value 105.733010
iter 100 value 105.517239
final  value 105.517239 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 119.940131 
iter  10 value 115.927395
iter  20 value 114.135975
iter  30 value 113.877093
iter  40 value 113.818400
iter  40 value 113.818399
iter  40 value 113.818399
final  value 113.818399 
converged
Fitting Repeat 5 

# weights:  103
initial  value 122.470864 
iter  10 value 117.776510
iter  20 value 113.070393
iter  30 value 109.732270
iter  40 value 109.170248
iter  50 value 106.050233
iter  60 value 105.361982
iter  70 value 105.261050
iter  80 value 105.258333
iter  80 value 105.258333
iter  80 value 105.258333
final  value 105.258333 
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 -- Tue Sep  9 07:55:18 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 
 51.685   1.686 132.386