##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:HPiP.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings HPiP_1.10.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck’
* using R version 4.4.0 (2024-04-24)
* using platform: x86_64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 12.2.0
* running under: macOS Monterey 12.7.1
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.10.0’
* 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 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       36.623  1.925  38.968
corr_plot     33.885  1.678  35.685
FSmethod      33.754  1.714  35.594
pred_ensembel 13.811  0.552  10.227
enrichfindP    0.495  0.066   8.623
* 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
  ‘/Users/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/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 4.4.0 (2024-04-24) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20

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 100.613360 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.799212 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.275354 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.695307 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.667828 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.296399 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.553993 
iter  10 value 94.052910
iter  10 value 94.052910
iter  10 value 94.052910
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.052874 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.292149 
iter  10 value 93.392069
iter  20 value 93.391581
iter  30 value 93.157336
iter  40 value 92.933622
final  value 92.933616 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.847506 
iter  10 value 90.516550
iter  20 value 89.861553
final  value 89.861550 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.168102 
final  value 94.052911 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.367842 
final  value 93.535112 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.001263 
iter  10 value 92.138796
iter  20 value 89.790206
iter  30 value 89.786770
iter  30 value 89.786770
final  value 89.786770 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.119158 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 114.347522 
iter  10 value 94.052910
iter  10 value 94.052910
iter  10 value 94.052910
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.532749 
iter  10 value 94.056729
iter  20 value 94.012514
iter  30 value 93.168638
iter  40 value 92.879012
iter  50 value 92.777164
iter  60 value 87.810429
iter  70 value 86.007623
iter  80 value 84.753408
iter  90 value 84.719590
iter 100 value 84.711462
final  value 84.711462 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.479029 
iter  10 value 93.975522
iter  20 value 83.863184
iter  30 value 83.629957
iter  40 value 83.402041
iter  50 value 83.317190
iter  60 value 83.315483
final  value 83.315482 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.436163 
iter  10 value 93.820907
iter  20 value 88.039074
iter  30 value 87.839409
iter  40 value 83.633845
iter  50 value 83.196104
iter  60 value 83.142014
iter  70 value 83.132541
iter  70 value 83.132540
iter  70 value 83.132540
final  value 83.132540 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.616898 
iter  10 value 94.056500
iter  20 value 93.603786
iter  30 value 93.437929
iter  40 value 92.833710
iter  50 value 92.741517
iter  60 value 85.560626
iter  70 value 85.230504
iter  80 value 83.764223
iter  90 value 82.128743
iter 100 value 80.501324
final  value 80.501324 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.060560 
iter  10 value 93.537394
iter  20 value 88.402434
iter  30 value 87.495891
iter  40 value 84.998301
iter  50 value 84.067928
iter  60 value 82.936455
iter  70 value 82.738146
iter  80 value 82.715618
final  value 82.713945 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.609473 
iter  10 value 94.409802
iter  20 value 94.067287
iter  30 value 94.020716
iter  40 value 85.098426
iter  50 value 84.149997
iter  60 value 83.972714
iter  70 value 82.875247
iter  80 value 80.064904
iter  90 value 78.858796
iter 100 value 78.723512
final  value 78.723512 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.922561 
iter  10 value 94.081555
iter  20 value 85.517175
iter  30 value 83.818064
iter  40 value 83.237467
iter  50 value 83.016931
iter  60 value 82.902546
iter  70 value 82.694277
iter  80 value 81.066095
iter  90 value 80.018051
iter 100 value 78.605110
final  value 78.605110 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 113.311500 
iter  10 value 94.011317
iter  20 value 88.051869
iter  30 value 87.705623
iter  40 value 84.907840
iter  50 value 82.556916
iter  60 value 81.684168
iter  70 value 80.915487
iter  80 value 80.710262
iter  90 value 80.463356
iter 100 value 80.434447
final  value 80.434447 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.231925 
iter  10 value 94.187506
iter  20 value 93.888788
iter  30 value 83.630306
iter  40 value 82.987828
iter  50 value 82.362753
iter  60 value 81.738767
iter  70 value 80.301120
iter  80 value 79.091948
iter  90 value 78.846998
iter 100 value 78.638756
final  value 78.638756 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.007002 
iter  10 value 94.680371
iter  20 value 85.963388
iter  30 value 84.503368
iter  40 value 84.165149
iter  50 value 83.230407
iter  60 value 81.525530
iter  70 value 80.644316
iter  80 value 80.242179
iter  90 value 79.941672
iter 100 value 79.790732
final  value 79.790732 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 116.181885 
iter  10 value 90.810343
iter  20 value 84.496846
iter  30 value 83.212736
iter  40 value 82.229617
iter  50 value 80.640407
iter  60 value 79.139261
iter  70 value 78.838199
iter  80 value 78.632669
iter  90 value 78.517624
iter 100 value 78.489935
final  value 78.489935 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 114.792788 
iter  10 value 94.783617
iter  20 value 92.631814
iter  30 value 89.459833
iter  40 value 86.155107
iter  50 value 83.143057
iter  60 value 81.268791
iter  70 value 80.343309
iter  80 value 79.797076
iter  90 value 79.486732
iter 100 value 79.450579
final  value 79.450579 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.866777 
iter  10 value 94.068093
iter  20 value 93.643662
iter  30 value 93.598647
iter  40 value 90.994093
iter  50 value 83.202477
iter  60 value 81.059625
iter  70 value 80.626818
iter  80 value 80.077423
iter  90 value 79.062033
iter 100 value 78.651293
final  value 78.651293 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.684795 
iter  10 value 93.249545
iter  20 value 89.287519
iter  30 value 83.610694
iter  40 value 83.166768
iter  50 value 81.082230
iter  60 value 79.307833
iter  70 value 78.707167
iter  80 value 78.470271
iter  90 value 78.228087
iter 100 value 78.083093
final  value 78.083093 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 117.472882 
iter  10 value 91.340000
iter  20 value 84.147285
iter  30 value 82.899863
iter  40 value 81.462763
iter  50 value 80.915064
iter  60 value 79.639344
iter  70 value 78.773804
iter  80 value 78.621588
iter  90 value 78.373006
iter 100 value 78.134047
final  value 78.134047 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.480432 
final  value 94.054616 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.999665 
iter  10 value 93.469954
final  value 93.358335 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.763385 
final  value 94.054349 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.093127 
final  value 94.054761 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.978880 
iter  10 value 94.054463
iter  20 value 84.310549
iter  30 value 83.371143
iter  40 value 83.286372
final  value 83.286370 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.401699 
iter  10 value 94.049358
iter  20 value 93.339714
iter  30 value 86.642342
iter  40 value 86.620710
iter  50 value 85.585387
final  value 85.585344 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.714077 
iter  10 value 93.397450
iter  20 value 93.394108
iter  30 value 93.392261
iter  40 value 92.210890
iter  50 value 92.018886
iter  60 value 90.992320
iter  70 value 87.419560
iter  80 value 87.334222
iter  90 value 87.020293
iter 100 value 86.891528
final  value 86.891528 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.461771 
iter  10 value 94.057754
iter  20 value 94.053113
iter  30 value 93.762433
iter  40 value 86.639400
iter  50 value 84.511120
iter  60 value 84.500243
final  value 84.500086 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.272025 
iter  10 value 94.057533
iter  20 value 93.977699
iter  30 value 92.145350
iter  40 value 91.991816
iter  50 value 91.989795
iter  60 value 91.989120
iter  70 value 84.667857
iter  80 value 82.722883
iter  90 value 82.685290
iter 100 value 82.574553
final  value 82.574553 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.159772 
iter  10 value 93.396804
iter  20 value 93.391004
iter  30 value 90.860800
iter  40 value 83.787517
iter  50 value 83.366674
iter  60 value 83.242638
iter  70 value 83.239793
final  value 83.239744 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.100083 
iter  10 value 89.420177
iter  20 value 88.823643
iter  30 value 88.423747
iter  40 value 88.420269
iter  50 value 86.844209
iter  60 value 86.735443
iter  70 value 86.734741
iter  80 value 86.734137
iter  80 value 86.734136
final  value 86.734136 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.717618 
iter  10 value 93.400862
iter  20 value 93.394350
iter  30 value 86.565147
iter  40 value 85.717709
iter  50 value 85.702652
final  value 85.702633 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.365256 
iter  10 value 94.061547
iter  20 value 93.991577
final  value 93.357811 
converged
Fitting Repeat 4 

# weights:  507
initial  value 117.110106 
iter  10 value 94.052997
iter  20 value 93.964659
iter  30 value 93.329416
iter  40 value 92.701627
final  value 92.701282 
converged
Fitting Repeat 5 

# weights:  507
initial  value 114.678400 
iter  10 value 91.736444
iter  20 value 91.727194
iter  30 value 91.623684
iter  40 value 91.615278
final  value 91.614743 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.123368 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  103
initial  value 126.083411 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.977805 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.477568 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.145499 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 118.784969 
iter  10 value 94.354484
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.849284 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.544946 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.349253 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.450585 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.970495 
iter  10 value 91.976488
final  value 91.976472 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.148276 
final  value 94.354396 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.198452 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.033001 
final  value 94.354396 
converged
Fitting Repeat 5 

# weights:  507
initial  value 112.411545 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.027096 
iter  10 value 94.436996
iter  20 value 93.641562
iter  30 value 93.535093
iter  40 value 93.526980
iter  50 value 93.131258
iter  60 value 91.146474
iter  70 value 91.032727
iter  80 value 91.031609
final  value 91.031605 
converged
Fitting Repeat 2 

# weights:  103
initial  value 106.527042 
iter  10 value 94.363562
iter  20 value 93.757046
iter  30 value 93.672143
iter  40 value 93.660361
iter  50 value 86.856390
iter  60 value 81.957163
iter  70 value 81.600515
iter  80 value 81.014475
iter  90 value 80.900564
iter 100 value 80.556782
final  value 80.556782 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.806048 
iter  10 value 94.488553
iter  20 value 94.186998
iter  30 value 87.930236
iter  40 value 84.429560
iter  50 value 82.712188
iter  60 value 82.539851
iter  70 value 81.571737
iter  80 value 81.083588
iter  90 value 80.801570
iter 100 value 80.498369
final  value 80.498369 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.639401 
iter  10 value 94.120163
iter  20 value 93.726857
iter  30 value 89.662430
iter  40 value 85.332566
iter  50 value 84.293530
iter  60 value 82.190264
iter  70 value 82.038206
iter  80 value 82.023435
iter  90 value 82.022949
iter 100 value 82.022606
final  value 82.022606 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 96.656529 
iter  10 value 94.413075
iter  20 value 84.544269
iter  30 value 83.771081
iter  40 value 82.866796
iter  50 value 82.588940
iter  60 value 82.566998
final  value 82.566505 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.179394 
iter  10 value 94.479236
iter  20 value 93.896634
iter  30 value 83.718347
iter  40 value 83.432087
iter  50 value 83.209627
iter  60 value 82.630318
iter  70 value 81.623846
iter  80 value 80.271408
iter  90 value 80.084604
iter 100 value 80.016101
final  value 80.016101 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 113.278169 
iter  10 value 94.549556
iter  20 value 91.742890
iter  30 value 86.701658
iter  40 value 86.197071
iter  50 value 86.072345
iter  60 value 85.938630
iter  70 value 85.459860
iter  80 value 80.026941
iter  90 value 78.897595
iter 100 value 78.648652
final  value 78.648652 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.799932 
iter  10 value 93.839645
iter  20 value 83.777603
iter  30 value 82.848354
iter  40 value 80.884779
iter  50 value 80.078713
iter  60 value 79.478241
iter  70 value 79.378447
iter  80 value 78.926459
iter  90 value 78.295115
iter 100 value 78.115999
final  value 78.115999 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 124.312870 
iter  10 value 94.538437
iter  20 value 93.785733
iter  30 value 85.043481
iter  40 value 83.842149
iter  50 value 82.873571
iter  60 value 82.730439
iter  70 value 82.691180
iter  80 value 82.604343
iter  90 value 81.964930
iter 100 value 80.281560
final  value 80.281560 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.605238 
iter  10 value 95.746532
iter  20 value 89.904133
iter  30 value 85.321564
iter  40 value 84.504609
iter  50 value 82.328399
iter  60 value 81.499831
iter  70 value 80.723092
iter  80 value 80.283214
iter  90 value 80.106377
iter 100 value 79.975970
final  value 79.975970 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 131.024212 
iter  10 value 92.312080
iter  20 value 88.557134
iter  30 value 81.708482
iter  40 value 80.554040
iter  50 value 78.771639
iter  60 value 78.514343
iter  70 value 78.273105
iter  80 value 78.206855
iter  90 value 78.072245
iter 100 value 78.057062
final  value 78.057062 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 117.087011 
iter  10 value 94.537078
iter  20 value 91.898909
iter  30 value 82.774835
iter  40 value 82.047293
iter  50 value 80.496959
iter  60 value 79.310888
iter  70 value 79.023021
iter  80 value 78.800747
iter  90 value 78.653886
iter 100 value 78.465759
final  value 78.465759 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.495298 
iter  10 value 95.695676
iter  20 value 90.626956
iter  30 value 88.204133
iter  40 value 84.344161
iter  50 value 83.066505
iter  60 value 80.617151
iter  70 value 79.265158
iter  80 value 78.705734
iter  90 value 78.142943
iter 100 value 78.100688
final  value 78.100688 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 131.205210 
iter  10 value 94.989681
iter  20 value 94.242585
iter  30 value 88.039383
iter  40 value 83.014997
iter  50 value 81.855861
iter  60 value 81.707019
iter  70 value 80.643001
iter  80 value 80.312790
iter  90 value 80.164534
iter 100 value 80.081137
final  value 80.081137 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.191069 
iter  10 value 96.901448
iter  20 value 91.924870
iter  30 value 88.204017
iter  40 value 85.131263
iter  50 value 81.987933
iter  60 value 80.816921
iter  70 value 79.442751
iter  80 value 78.369610
iter  90 value 78.148094
iter 100 value 77.935896
final  value 77.935896 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.849808 
final  value 94.485767 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.821723 
final  value 94.485810 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.250589 
iter  10 value 86.313424
iter  20 value 82.343415
iter  30 value 82.314409
iter  40 value 82.314146
iter  50 value 82.274786
final  value 82.274492 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.293968 
final  value 94.146199 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.176911 
final  value 94.485642 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.555999 
iter  10 value 94.359080
iter  20 value 94.354635
final  value 94.354467 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.195842 
iter  10 value 94.040779
iter  20 value 94.039141
iter  30 value 94.038671
iter  40 value 94.038235
iter  50 value 93.826334
iter  60 value 90.330553
iter  70 value 85.544791
iter  80 value 85.543481
iter  90 value 85.188270
iter 100 value 83.000766
final  value 83.000766 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 113.722529 
iter  10 value 94.492096
iter  20 value 94.396985
iter  30 value 84.472449
iter  40 value 84.437994
iter  50 value 84.436883
iter  60 value 84.275722
iter  70 value 84.158744
iter  80 value 83.792275
iter  90 value 80.841899
iter 100 value 80.693968
final  value 80.693968 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 114.389145 
iter  10 value 90.265797
iter  20 value 85.803357
iter  30 value 82.321220
iter  40 value 82.308632
iter  50 value 82.286972
final  value 82.286689 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.516537 
iter  10 value 94.337379
iter  20 value 94.024157
iter  30 value 83.814962
iter  40 value 82.277438
iter  50 value 82.275309
iter  60 value 82.274514
iter  70 value 82.262522
final  value 82.261203 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.930397 
iter  10 value 93.454973
iter  20 value 86.206955
iter  30 value 85.650415
iter  40 value 85.650109
iter  50 value 84.252854
iter  60 value 83.678337
iter  70 value 83.676871
iter  80 value 83.674398
iter  80 value 83.674398
iter  80 value 83.674398
final  value 83.674398 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.744392 
iter  10 value 94.215853
iter  20 value 94.131341
iter  30 value 93.861374
iter  40 value 93.658976
iter  50 value 93.448375
iter  60 value 93.445725
iter  70 value 92.005959
iter  80 value 83.019609
iter  90 value 81.661636
iter 100 value 80.268749
final  value 80.268749 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.341718 
iter  10 value 94.492163
iter  20 value 94.484234
iter  30 value 93.804808
iter  40 value 86.948877
iter  50 value 86.354005
iter  60 value 86.352457
iter  70 value 86.351393
iter  80 value 85.522648
iter  90 value 82.461129
iter 100 value 78.499856
final  value 78.499856 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 100.629298 
iter  10 value 94.334260
iter  20 value 94.052653
iter  30 value 94.035036
iter  40 value 93.682129
iter  50 value 86.289268
iter  60 value 80.358518
iter  70 value 80.306138
iter  80 value 80.300600
iter  90 value 80.197784
iter 100 value 80.191080
final  value 80.191080 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.919288 
iter  10 value 94.362210
iter  20 value 94.005065
iter  30 value 86.848785
iter  40 value 85.862485
iter  50 value 85.651954
iter  60 value 85.403742
iter  70 value 83.603809
iter  80 value 81.229596
iter  90 value 81.153216
iter 100 value 80.934494
final  value 80.934494 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.497665 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.035634 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.685822 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.084995 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.082269 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.531868 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 120.406592 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.030256 
final  value 94.473118 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.726290 
final  value 94.026542 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.593380 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.040884 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.682916 
iter  10 value 85.586644
iter  20 value 84.551058
final  value 84.533333 
converged
Fitting Repeat 3 

# weights:  507
initial  value 113.064869 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.793334 
iter  10 value 94.026542
iter  10 value 94.026542
iter  10 value 94.026542
final  value 94.026542 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.468597 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.669587 
iter  10 value 94.033731
iter  20 value 83.600350
iter  30 value 83.108953
iter  40 value 82.447436
iter  50 value 81.588555
iter  60 value 81.175134
iter  70 value 81.157029
final  value 81.157021 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.896025 
iter  10 value 94.450367
iter  20 value 91.905833
iter  30 value 91.635284
iter  40 value 91.611241
iter  50 value 91.545150
iter  60 value 90.307994
iter  70 value 82.921932
iter  80 value 82.300555
iter  90 value 82.122430
iter 100 value 81.829269
final  value 81.829269 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 100.067260 
iter  10 value 93.466779
iter  20 value 83.565352
iter  30 value 82.558984
iter  40 value 81.997413
iter  50 value 81.858897
iter  60 value 81.435413
iter  70 value 81.162005
final  value 81.157021 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.574039 
iter  10 value 94.459149
iter  20 value 91.317881
iter  30 value 91.087326
iter  40 value 90.844148
iter  50 value 90.795355
final  value 90.795340 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.208364 
iter  10 value 85.457349
iter  20 value 83.777177
iter  30 value 82.573446
iter  40 value 82.300409
iter  50 value 82.007587
iter  60 value 81.657348
iter  70 value 80.867664
iter  80 value 80.556207
iter  90 value 80.524894
final  value 80.524837 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.587910 
iter  10 value 94.550704
iter  20 value 92.446441
iter  30 value 85.900704
iter  40 value 85.062350
iter  50 value 83.245372
iter  60 value 82.961829
iter  70 value 82.715683
iter  80 value 82.195168
iter  90 value 80.580218
iter 100 value 79.986149
final  value 79.986149 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 111.999325 
iter  10 value 90.044274
iter  20 value 83.811616
iter  30 value 82.958485
iter  40 value 82.130186
iter  50 value 80.836321
iter  60 value 80.107902
iter  70 value 79.774532
iter  80 value 79.640891
iter  90 value 79.414619
iter 100 value 79.248886
final  value 79.248886 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.415637 
iter  10 value 94.430740
iter  20 value 85.038803
iter  30 value 83.237399
iter  40 value 83.094906
iter  50 value 81.555387
iter  60 value 80.318026
iter  70 value 79.826253
iter  80 value 79.716565
iter  90 value 79.644416
iter 100 value 79.468208
final  value 79.468208 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 130.553938 
iter  10 value 94.500400
iter  20 value 92.837354
iter  30 value 87.165795
iter  40 value 84.077435
iter  50 value 81.342352
iter  60 value 80.486270
iter  70 value 79.992496
iter  80 value 79.776916
iter  90 value 79.614532
iter 100 value 79.452026
final  value 79.452026 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.172693 
iter  10 value 94.632438
iter  20 value 93.582731
iter  30 value 90.928325
iter  40 value 90.440667
iter  50 value 90.209274
iter  60 value 89.759870
iter  70 value 87.704317
iter  80 value 83.348370
iter  90 value 82.385360
iter 100 value 81.506591
final  value 81.506591 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.555799 
iter  10 value 93.527234
iter  20 value 88.134592
iter  30 value 86.718622
iter  40 value 85.633531
iter  50 value 82.940109
iter  60 value 81.666988
iter  70 value 81.199289
iter  80 value 80.859729
iter  90 value 80.376717
iter 100 value 80.165522
final  value 80.165522 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 110.364011 
iter  10 value 94.482577
iter  20 value 91.087311
iter  30 value 82.955449
iter  40 value 81.497237
iter  50 value 80.575558
iter  60 value 80.414542
iter  70 value 80.119328
iter  80 value 80.048940
iter  90 value 80.009472
iter 100 value 79.942658
final  value 79.942658 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.078723 
iter  10 value 93.505668
iter  20 value 84.599999
iter  30 value 82.644128
iter  40 value 82.360764
iter  50 value 82.196720
iter  60 value 81.212165
iter  70 value 80.213241
iter  80 value 79.824824
iter  90 value 79.713366
iter 100 value 79.682772
final  value 79.682772 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 117.978361 
iter  10 value 92.320535
iter  20 value 86.310950
iter  30 value 84.843100
iter  40 value 83.485926
iter  50 value 82.907952
iter  60 value 81.410459
iter  70 value 80.632407
iter  80 value 80.193285
iter  90 value 79.698709
iter 100 value 79.656977
final  value 79.656977 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 117.165786 
iter  10 value 94.170861
iter  20 value 87.575169
iter  30 value 84.818783
iter  40 value 84.266518
iter  50 value 83.668374
iter  60 value 82.205024
iter  70 value 80.581285
iter  80 value 79.821056
iter  90 value 79.392140
iter 100 value 79.218113
final  value 79.218113 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.241504 
final  value 94.486190 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.964465 
final  value 94.485893 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.677249 
final  value 94.485707 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.008874 
final  value 94.486071 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.905005 
final  value 94.485895 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.222849 
iter  10 value 94.032495
iter  20 value 94.027582
iter  30 value 94.026819
iter  40 value 94.026771
iter  50 value 93.611346
iter  60 value 82.701957
iter  70 value 81.145484
iter  80 value 80.288235
iter  90 value 80.020023
iter 100 value 79.708537
final  value 79.708537 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 96.918440 
iter  10 value 94.489438
iter  20 value 94.341760
iter  30 value 90.763335
iter  40 value 90.758939
iter  50 value 89.991673
final  value 89.980423 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.551656 
iter  10 value 94.489830
iter  20 value 86.010282
iter  30 value 84.502508
iter  40 value 84.451851
iter  50 value 82.906270
iter  60 value 82.369785
final  value 82.369753 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.949536 
iter  10 value 94.166533
iter  20 value 92.234499
iter  30 value 92.233035
iter  40 value 90.704542
iter  50 value 89.370528
iter  60 value 89.333400
iter  70 value 89.333176
final  value 89.333030 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.441563 
iter  10 value 94.488804
iter  20 value 94.451537
iter  30 value 93.976474
final  value 93.976469 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.304215 
iter  10 value 94.492449
iter  20 value 94.478418
final  value 94.027142 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.554135 
iter  10 value 91.804736
iter  20 value 90.650214
iter  30 value 90.646202
iter  40 value 90.445461
iter  50 value 90.113238
iter  60 value 90.091215
iter  70 value 90.042697
iter  80 value 89.937856
iter  90 value 89.900751
iter 100 value 89.616069
final  value 89.616069 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 101.174946 
iter  10 value 94.492680
iter  20 value 94.461567
iter  30 value 90.964683
iter  40 value 90.609744
final  value 90.609715 
converged
Fitting Repeat 4 

# weights:  507
initial  value 117.550542 
iter  10 value 93.418421
iter  20 value 92.335901
iter  30 value 92.283847
iter  40 value 92.248804
iter  50 value 92.242375
iter  60 value 91.072476
iter  70 value 90.892328
iter  80 value 90.781203
iter  90 value 90.665844
iter 100 value 90.665580
final  value 90.665580 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 114.420528 
iter  10 value 93.628256
iter  20 value 85.383530
iter  30 value 84.571934
iter  40 value 84.519304
iter  50 value 84.239204
iter  60 value 83.365364
iter  70 value 83.192672
iter  80 value 83.192333
iter  90 value 83.192133
iter 100 value 83.191779
final  value 83.191779 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.347919 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.287389 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.601859 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.800857 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.433374 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.047502 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.758997 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.608425 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.094131 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 114.371582 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  507
initial  value 124.182610 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 122.151787 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.270756 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  507
initial  value 116.639712 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.967763 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.771434 
iter  10 value 95.858988
iter  20 value 94.490549
iter  30 value 93.076878
iter  40 value 86.724772
iter  50 value 85.896021
iter  60 value 85.656076
iter  70 value 85.329086
iter  80 value 85.174699
iter  90 value 85.124012
final  value 85.123936 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.518583 
iter  10 value 94.429314
iter  20 value 88.400950
iter  30 value 85.930627
iter  40 value 85.632923
iter  50 value 85.510476
iter  60 value 84.741130
iter  70 value 84.616169
iter  70 value 84.616168
iter  70 value 84.616168
final  value 84.616168 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.614339 
iter  10 value 94.374817
iter  20 value 90.224861
iter  30 value 87.175038
iter  40 value 86.789809
iter  50 value 86.147916
iter  60 value 86.028935
iter  70 value 85.910016
final  value 85.909998 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.612336 
iter  10 value 94.463368
iter  20 value 92.524976
iter  30 value 91.687629
iter  40 value 91.420199
iter  50 value 91.248645
iter  60 value 86.979134
iter  70 value 86.831204
iter  80 value 86.409759
iter  90 value 85.930544
iter 100 value 85.701772
final  value 85.701772 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 101.248661 
iter  10 value 94.484595
iter  20 value 94.481329
iter  30 value 88.444504
iter  40 value 88.212802
iter  50 value 87.684753
iter  60 value 87.478010
iter  70 value 87.257469
iter  80 value 87.092632
iter  90 value 86.535797
iter 100 value 85.799438
final  value 85.799438 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 100.621913 
iter  10 value 94.586238
iter  20 value 93.237677
iter  30 value 88.973114
iter  40 value 88.593564
iter  50 value 87.714086
iter  60 value 86.246021
iter  70 value 85.168010
iter  80 value 85.056721
iter  90 value 84.032681
iter 100 value 82.991815
final  value 82.991815 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.569427 
iter  10 value 94.081162
iter  20 value 87.766336
iter  30 value 87.390186
iter  40 value 86.067572
iter  50 value 84.667319
iter  60 value 83.584398
iter  70 value 82.598009
iter  80 value 82.035327
iter  90 value 81.905467
iter 100 value 81.853487
final  value 81.853487 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.190621 
iter  10 value 89.300677
iter  20 value 86.784068
iter  30 value 84.620797
iter  40 value 84.001664
iter  50 value 83.685608
iter  60 value 83.521272
iter  70 value 83.509912
iter  80 value 83.487190
iter  90 value 83.223614
iter 100 value 82.637693
final  value 82.637693 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.658450 
iter  10 value 94.488724
iter  20 value 92.566514
iter  30 value 86.250262
iter  40 value 85.989561
iter  50 value 85.200368
iter  60 value 85.059278
iter  70 value 84.721493
iter  80 value 83.839817
iter  90 value 83.193518
iter 100 value 82.686552
final  value 82.686552 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.580532 
iter  10 value 94.053177
iter  20 value 88.229343
iter  30 value 85.972061
iter  40 value 85.525772
iter  50 value 83.824841
iter  60 value 83.406798
iter  70 value 82.961065
iter  80 value 82.813466
iter  90 value 82.736777
iter 100 value 82.543992
final  value 82.543992 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.324983 
iter  10 value 94.556557
iter  20 value 94.468888
iter  30 value 94.143333
iter  40 value 87.295798
iter  50 value 85.999176
iter  60 value 85.387120
iter  70 value 84.275273
iter  80 value 83.194369
iter  90 value 82.747065
iter 100 value 82.408864
final  value 82.408864 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.556732 
iter  10 value 94.608628
iter  20 value 88.881312
iter  30 value 86.289347
iter  40 value 84.531356
iter  50 value 82.617045
iter  60 value 82.137027
iter  70 value 82.059377
iter  80 value 81.939455
iter  90 value 81.834432
iter 100 value 81.718841
final  value 81.718841 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.450664 
iter  10 value 94.771081
iter  20 value 94.508183
iter  30 value 86.331346
iter  40 value 85.753000
iter  50 value 85.318991
iter  60 value 84.636746
iter  70 value 83.189296
iter  80 value 82.831907
iter  90 value 82.329190
iter 100 value 82.176122
final  value 82.176122 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 118.526133 
iter  10 value 96.834844
iter  20 value 94.346452
iter  30 value 90.176000
iter  40 value 87.634444
iter  50 value 86.462505
iter  60 value 85.940649
iter  70 value 85.675997
iter  80 value 84.496374
iter  90 value 84.194109
iter 100 value 84.018666
final  value 84.018666 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 122.967635 
iter  10 value 96.063078
iter  20 value 93.581953
iter  30 value 89.036171
iter  40 value 84.662961
iter  50 value 83.219448
iter  60 value 82.975911
iter  70 value 82.687449
iter  80 value 82.491944
iter  90 value 82.334057
iter 100 value 82.168099
final  value 82.168099 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.887060 
final  value 94.485723 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.097022 
final  value 94.485810 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.661232 
iter  10 value 94.147361
iter  20 value 94.065117
iter  30 value 92.058050
iter  40 value 92.008415
iter  50 value 92.008270
final  value 92.008232 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.098530 
final  value 94.485891 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.882692 
final  value 94.486311 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.044120 
iter  10 value 94.488938
iter  20 value 94.408884
iter  30 value 93.619682
iter  40 value 89.602950
iter  50 value 88.085339
iter  60 value 87.850159
iter  70 value 87.655856
iter  80 value 85.827362
final  value 85.524857 
converged
Fitting Repeat 2 

# weights:  305
initial  value 109.185444 
iter  10 value 93.225542
iter  20 value 93.200779
iter  30 value 92.916884
iter  40 value 89.067819
iter  50 value 87.860664
iter  60 value 87.860499
iter  70 value 87.859718
iter  80 value 87.859489
iter  90 value 85.650038
final  value 85.395666 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.036048 
iter  10 value 94.488540
iter  20 value 94.381191
iter  30 value 87.209328
iter  40 value 85.618571
iter  50 value 85.617042
final  value 85.616660 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.570672 
iter  10 value 94.497889
iter  20 value 94.487608
iter  30 value 94.475219
iter  40 value 94.227937
iter  50 value 88.896825
iter  60 value 86.789510
iter  70 value 86.716330
iter  80 value 86.679308
iter  90 value 86.679210
iter 100 value 86.316110
final  value 86.316110 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 95.444383 
iter  10 value 94.471143
iter  20 value 94.466924
iter  30 value 93.716093
iter  40 value 92.637925
iter  50 value 86.095226
iter  60 value 85.402885
iter  70 value 85.303273
final  value 85.299063 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.615798 
iter  10 value 94.492287
iter  20 value 94.480590
iter  30 value 88.121680
iter  40 value 85.526664
iter  50 value 85.523866
iter  60 value 85.331090
iter  70 value 85.311487
iter  80 value 83.318607
iter  90 value 83.034914
iter 100 value 83.002656
final  value 83.002656 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 95.513977 
iter  10 value 94.491303
iter  20 value 93.549737
iter  30 value 91.945077
iter  40 value 91.941984
iter  50 value 91.940803
iter  60 value 91.940693
final  value 91.940683 
converged
Fitting Repeat 3 

# weights:  507
initial  value 111.111386 
iter  10 value 94.437072
iter  20 value 94.429779
iter  30 value 94.308139
iter  40 value 88.321120
iter  50 value 87.541927
iter  60 value 86.813017
iter  70 value 86.803275
iter  80 value 86.682352
iter  90 value 86.581447
iter 100 value 84.811043
final  value 84.811043 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.183323 
iter  10 value 93.695562
iter  20 value 93.691794
iter  30 value 93.686658
iter  40 value 93.485557
iter  50 value 93.449882
iter  60 value 89.276554
iter  70 value 87.885376
iter  80 value 87.805833
iter  90 value 87.803763
iter 100 value 87.634306
final  value 87.634306 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 118.901273 
iter  10 value 93.673094
iter  20 value 93.667508
iter  30 value 88.142854
iter  40 value 83.769718
iter  50 value 83.697753
iter  60 value 83.695275
iter  70 value 83.694860
iter  80 value 83.693765
iter  90 value 83.219205
iter 100 value 82.914135
final  value 82.914135 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 106.315047 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.645626 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.111276 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.139037 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.327856 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.582788 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.492650 
final  value 92.945355 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.309626 
iter  10 value 92.945358
final  value 92.945355 
converged
Fitting Repeat 4 

# weights:  305
initial  value 126.623117 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.533943 
iter  10 value 92.166176
final  value 92.165543 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.115416 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.190216 
iter  10 value 87.690835
iter  20 value 86.434681
iter  30 value 85.683057
iter  40 value 85.151070
iter  50 value 85.150021
final  value 85.150013 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.669946 
iter  10 value 88.383697
iter  20 value 83.637428
iter  30 value 81.228882
iter  40 value 79.646721
iter  50 value 79.388102
iter  60 value 79.387031
final  value 79.387014 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.103366 
iter  10 value 91.178831
iter  20 value 89.650947
iter  30 value 89.538229
final  value 89.535184 
converged
Fitting Repeat 5 

# weights:  507
initial  value 109.382781 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.863641 
iter  10 value 93.933774
iter  20 value 87.866492
iter  30 value 85.655925
iter  40 value 84.856489
iter  50 value 83.172357
iter  60 value 82.862309
iter  70 value 82.375780
iter  80 value 82.369060
final  value 82.369043 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.742851 
iter  10 value 94.032671
iter  20 value 91.856038
iter  30 value 89.003502
iter  40 value 86.657251
iter  50 value 86.307487
iter  60 value 84.130174
iter  70 value 83.987360
iter  80 value 82.776615
iter  90 value 82.513140
iter 100 value 82.462960
final  value 82.462960 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 95.890043 
iter  10 value 94.051727
iter  20 value 86.422469
iter  30 value 85.304713
iter  40 value 83.514624
iter  50 value 83.258406
iter  60 value 82.456317
final  value 82.454494 
converged
Fitting Repeat 4 

# weights:  103
initial  value 112.727392 
iter  10 value 94.024940
iter  20 value 91.949575
iter  30 value 90.160799
iter  40 value 89.914767
iter  50 value 89.222365
iter  60 value 84.241890
iter  70 value 81.583874
iter  80 value 81.130981
iter  90 value 80.664772
iter 100 value 80.557273
final  value 80.557273 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.795496 
iter  10 value 94.018325
iter  20 value 93.465796
iter  30 value 93.420146
iter  40 value 86.576269
iter  50 value 83.352337
iter  60 value 82.673278
iter  70 value 82.260099
iter  80 value 82.239225
iter  90 value 82.231672
iter 100 value 82.211846
final  value 82.211846 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 112.734330 
iter  10 value 93.688173
iter  20 value 86.792159
iter  30 value 85.038503
iter  40 value 84.813086
iter  50 value 84.651856
iter  60 value 83.450136
iter  70 value 81.569996
iter  80 value 80.403019
iter  90 value 80.208325
iter 100 value 80.134100
final  value 80.134100 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.673742 
iter  10 value 91.562239
iter  20 value 84.935996
iter  30 value 83.676489
iter  40 value 83.064175
iter  50 value 82.901016
iter  60 value 82.781787
iter  70 value 82.044130
iter  80 value 80.210887
iter  90 value 79.874385
iter 100 value 79.754451
final  value 79.754451 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.471498 
iter  10 value 93.870074
iter  20 value 86.987986
iter  30 value 83.812395
iter  40 value 83.516565
iter  50 value 82.971433
iter  60 value 82.345305
iter  70 value 80.927127
iter  80 value 80.456726
iter  90 value 79.913502
iter 100 value 79.732928
final  value 79.732928 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 116.750106 
iter  10 value 94.032982
iter  20 value 91.812516
iter  30 value 89.430920
iter  40 value 87.893770
iter  50 value 83.341344
iter  60 value 81.673679
iter  70 value 81.235850
iter  80 value 80.806558
iter  90 value 80.381214
iter 100 value 80.168512
final  value 80.168512 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.369014 
iter  10 value 93.951235
iter  20 value 92.720851
iter  30 value 92.556009
iter  40 value 92.493811
iter  50 value 92.443450
iter  60 value 87.322365
iter  70 value 83.730222
iter  80 value 82.374724
iter  90 value 79.905206
iter 100 value 79.441424
final  value 79.441424 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 123.240345 
iter  10 value 93.858919
iter  20 value 89.187728
iter  30 value 85.296795
iter  40 value 81.596982
iter  50 value 80.285789
iter  60 value 79.626737
iter  70 value 79.127925
iter  80 value 78.848185
iter  90 value 78.661913
iter 100 value 78.585719
final  value 78.585719 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.423605 
iter  10 value 94.196933
iter  20 value 85.759061
iter  30 value 84.383519
iter  40 value 82.991964
iter  50 value 82.019395
iter  60 value 80.726176
iter  70 value 79.911128
iter  80 value 79.706722
iter  90 value 79.478036
iter 100 value 79.403359
final  value 79.403359 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 116.396548 
iter  10 value 92.364384
iter  20 value 86.164573
iter  30 value 84.449782
iter  40 value 83.823208
iter  50 value 82.813486
iter  60 value 82.139562
iter  70 value 81.674204
iter  80 value 81.416123
iter  90 value 80.441596
iter 100 value 80.207217
final  value 80.207217 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.407973 
iter  10 value 94.110492
iter  20 value 92.844615
iter  30 value 84.193506
iter  40 value 82.734692
iter  50 value 82.150107
iter  60 value 80.710023
iter  70 value 80.335125
iter  80 value 79.686652
iter  90 value 79.317515
iter 100 value 79.092258
final  value 79.092258 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 114.545230 
iter  10 value 92.880438
iter  20 value 87.189833
iter  30 value 82.048309
iter  40 value 81.530958
iter  50 value 80.564357
iter  60 value 80.157989
iter  70 value 79.568141
iter  80 value 79.482672
iter  90 value 79.455035
iter 100 value 79.438234
final  value 79.438234 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.325295 
iter  10 value 94.054524
iter  20 value 94.051212
iter  30 value 93.053540
iter  40 value 93.001085
iter  50 value 92.981456
iter  60 value 92.974980
iter  70 value 92.972169
iter  80 value 92.952558
iter  90 value 92.948550
iter 100 value 92.948334
final  value 92.948334 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 94.741649 
final  value 94.054670 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.182678 
final  value 94.055265 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.937484 
final  value 94.054478 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.552375 
iter  10 value 92.947940
iter  20 value 92.947613
iter  30 value 92.609353
iter  40 value 82.535684
iter  50 value 82.160887
iter  60 value 81.642454
iter  70 value 81.246119
iter  70 value 81.246119
final  value 81.246119 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.572625 
iter  10 value 92.950935
iter  20 value 92.950179
iter  30 value 91.488373
iter  40 value 83.959730
final  value 83.957959 
converged
Fitting Repeat 2 

# weights:  305
initial  value 113.301592 
iter  10 value 94.057745
iter  20 value 94.052891
iter  30 value 93.485201
iter  40 value 91.951729
iter  50 value 91.610324
iter  60 value 91.608845
iter  60 value 91.608844
iter  60 value 91.608844
final  value 91.608844 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.892803 
iter  10 value 94.057439
iter  20 value 94.021768
iter  30 value 94.017648
iter  40 value 84.790396
iter  50 value 83.208239
iter  60 value 83.146930
iter  70 value 82.799267
iter  80 value 81.292706
iter  90 value 79.442142
iter 100 value 79.357430
final  value 79.357430 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 111.151996 
iter  10 value 90.271205
iter  20 value 86.694972
iter  30 value 86.617134
iter  40 value 86.615474
final  value 86.615438 
converged
Fitting Repeat 5 

# weights:  305
initial  value 123.359874 
iter  10 value 94.059176
iter  20 value 94.056367
iter  30 value 94.054256
iter  40 value 93.586645
iter  50 value 92.678656
iter  60 value 83.584219
iter  70 value 82.584346
iter  80 value 82.328695
final  value 82.327353 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.696508 
iter  10 value 88.839763
iter  20 value 86.087434
iter  30 value 83.990457
iter  40 value 83.500623
iter  50 value 83.020303
iter  60 value 82.703712
iter  70 value 79.409181
iter  80 value 78.773602
iter  90 value 78.597385
iter 100 value 78.567147
final  value 78.567147 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.494092 
iter  10 value 94.061236
iter  20 value 94.044430
iter  30 value 92.473363
iter  40 value 84.259674
iter  50 value 83.684347
iter  60 value 83.022214
iter  70 value 82.459317
iter  80 value 81.802417
iter  90 value 81.781337
final  value 81.780912 
converged
Fitting Repeat 3 

# weights:  507
initial  value 111.196614 
iter  10 value 94.061424
iter  20 value 94.053056
iter  30 value 93.395589
final  value 92.172755 
converged
Fitting Repeat 4 

# weights:  507
initial  value 113.010278 
iter  10 value 92.954025
iter  20 value 92.950220
iter  30 value 92.477085
iter  40 value 89.028429
iter  50 value 88.951543
iter  60 value 88.947725
iter  70 value 88.947349
iter  80 value 88.946286
iter  90 value 87.203340
iter 100 value 85.805414
final  value 85.805414 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 97.002261 
iter  10 value 93.162444
iter  20 value 92.684578
iter  30 value 84.969759
iter  40 value 84.130602
iter  50 value 84.126889
final  value 84.126880 
converged
Fitting Repeat 1 

# weights:  507
initial  value 138.198650 
iter  10 value 118.017730
iter  20 value 108.708093
iter  30 value 105.048658
iter  40 value 104.715105
iter  50 value 104.454710
iter  60 value 102.763545
iter  70 value 102.065959
iter  80 value 101.739342
iter  90 value 101.064441
iter 100 value 100.934822
final  value 100.934822 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 133.398903 
iter  10 value 118.126362
iter  20 value 113.443397
iter  30 value 105.863201
iter  40 value 105.188111
iter  50 value 104.852699
iter  60 value 104.756108
iter  70 value 104.650520
iter  80 value 103.866527
iter  90 value 103.377055
iter 100 value 102.574650
final  value 102.574650 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 150.871947 
iter  10 value 119.148645
iter  20 value 117.568567
iter  30 value 110.029827
iter  40 value 107.162356
iter  50 value 106.622036
iter  60 value 105.103811
iter  70 value 103.563250
iter  80 value 101.959451
iter  90 value 100.680768
iter 100 value 100.450123
final  value 100.450123 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 140.547439 
iter  10 value 118.165863
iter  20 value 109.985638
iter  30 value 108.394457
iter  40 value 107.065878
iter  50 value 105.875163
iter  60 value 105.644671
iter  70 value 104.074281
iter  80 value 103.609298
iter  90 value 103.457366
iter 100 value 103.325507
final  value 103.325507 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 146.723204 
iter  10 value 117.862343
iter  20 value 116.360947
iter  30 value 114.232753
iter  40 value 111.345406
iter  50 value 105.439305
iter  60 value 104.966495
iter  70 value 104.381579
iter  80 value 103.813419
iter  90 value 103.292841
iter 100 value 102.275511
final  value 102.275511 
stopped after 100 iterations
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Wed Jun  5 21:04:24 2024 
*********************************************** 
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 
 44.294   1.787  44.196