##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.20-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.20-bioc/R/site-library --timings HPiP_1.11.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck’
* using R version 4.4.1 (2024-06-14)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
    GNU Fortran (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
* running under: Ubuntu 22.04.4 LTS
* using session charset: UTF-8
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.11.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
var_imp       36.148  0.972  37.120
FSmethod      33.881  0.460  34.340
corr_plot     33.888  0.372  34.260
pred_ensembel 13.295  0.676  10.671
enrichfindP    0.443  0.068  10.531
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE

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

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.20-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.20-bioc/R/site-library’
* installing *source* package ‘HPiP’ ...
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R version 4.4.1 (2024-06-14) -- "Race for Your Life"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> BiocGenerics:::testPackage('HPiP')
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
avNNet
Loading required package: ggplot2
Loading required package: lattice
Fitting Repeat 1 

# weights:  103
initial  value 101.402659 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.389280 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.450045 
final  value 94.050052 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.188248 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.047891 
final  value 94.033149 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.201961 
final  value 94.038251 
converged
Fitting Repeat 2 

# weights:  305
initial  value 106.962921 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.833688 
final  value 94.033149 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.948226 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.663456 
iter  10 value 92.406070
final  value 92.406061 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.537788 
final  value 94.038251 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.240584 
iter  10 value 92.730631
iter  20 value 88.477388
iter  30 value 87.958887
iter  40 value 87.882348
iter  50 value 87.882233
final  value 87.882232 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.218241 
iter  10 value 94.052910
iter  10 value 94.052910
iter  10 value 94.052910
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.253758 
final  value 94.038251 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.254851 
iter  10 value 94.031564
iter  10 value 94.031564
iter  10 value 94.031564
final  value 94.031564 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.898032 
iter  10 value 93.211974
iter  20 value 92.711872
iter  30 value 86.166963
iter  40 value 85.829155
iter  50 value 85.593039
iter  60 value 85.519275
final  value 85.519189 
converged
Fitting Repeat 2 

# weights:  103
initial  value 116.143329 
iter  10 value 94.055406
iter  20 value 93.718224
iter  30 value 91.855130
iter  40 value 87.562764
iter  50 value 85.967450
iter  60 value 85.840451
iter  70 value 85.678543
iter  80 value 85.510941
final  value 85.482162 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.713403 
iter  10 value 94.056544
iter  20 value 93.847320
iter  30 value 91.528052
iter  40 value 87.417633
iter  50 value 86.892244
iter  60 value 86.711708
iter  70 value 86.630586
iter  80 value 86.295500
final  value 86.287082 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.720265 
iter  10 value 94.057467
iter  20 value 94.056237
iter  30 value 93.996578
iter  40 value 93.079812
iter  50 value 90.494364
iter  60 value 89.370818
iter  70 value 88.151492
iter  80 value 87.751263
iter  90 value 87.391188
iter 100 value 86.482224
final  value 86.482224 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 96.228197 
iter  10 value 94.057292
iter  20 value 93.925549
iter  30 value 93.889491
iter  40 value 88.011247
iter  50 value 87.637629
iter  60 value 87.060436
iter  70 value 86.868414
iter  80 value 86.378725
final  value 86.287082 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.273261 
iter  10 value 94.537826
iter  20 value 94.359619
iter  30 value 93.292565
iter  40 value 92.518561
iter  50 value 87.579589
iter  60 value 86.810360
iter  70 value 85.638430
iter  80 value 84.327339
iter  90 value 83.815146
iter 100 value 83.682803
final  value 83.682803 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 113.748996 
iter  10 value 93.569670
iter  20 value 89.397113
iter  30 value 88.479416
iter  40 value 87.287289
iter  50 value 85.758083
iter  60 value 85.561576
iter  70 value 84.819950
iter  80 value 84.345323
iter  90 value 83.950546
iter 100 value 83.859500
final  value 83.859500 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 120.444068 
iter  10 value 94.101014
iter  20 value 91.922969
iter  30 value 87.569604
iter  40 value 85.738572
iter  50 value 84.997149
iter  60 value 84.306064
iter  70 value 82.593782
iter  80 value 82.287310
iter  90 value 82.146755
iter 100 value 82.077875
final  value 82.077875 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.648408 
iter  10 value 91.679246
iter  20 value 88.550597
iter  30 value 87.001894
iter  40 value 85.649029
iter  50 value 85.499307
iter  60 value 85.403859
iter  70 value 85.280722
iter  80 value 85.163689
iter  90 value 84.897806
iter 100 value 84.177561
final  value 84.177561 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 113.786990 
iter  10 value 94.014068
iter  20 value 91.529585
iter  30 value 88.087870
iter  40 value 87.869418
iter  50 value 87.101744
iter  60 value 84.437385
iter  70 value 83.384849
iter  80 value 83.024194
iter  90 value 82.993197
iter 100 value 82.879609
final  value 82.879609 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.705138 
iter  10 value 94.136988
iter  20 value 93.172209
iter  30 value 87.835519
iter  40 value 87.585233
iter  50 value 87.167144
iter  60 value 86.630515
iter  70 value 86.391151
iter  80 value 85.890847
iter  90 value 84.996920
iter 100 value 82.925564
final  value 82.925564 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.055261 
iter  10 value 94.061180
iter  20 value 92.772774
iter  30 value 87.436625
iter  40 value 85.121421
iter  50 value 83.163080
iter  60 value 82.794977
iter  70 value 82.421977
iter  80 value 82.261685
iter  90 value 82.124360
iter 100 value 82.026777
final  value 82.026777 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 125.640617 
iter  10 value 94.483058
iter  20 value 94.144864
iter  30 value 89.722318
iter  40 value 87.499615
iter  50 value 86.778030
iter  60 value 86.625908
iter  70 value 84.487844
iter  80 value 83.597824
iter  90 value 82.840464
iter 100 value 82.354097
final  value 82.354097 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.707864 
iter  10 value 94.173279
iter  20 value 93.429033
iter  30 value 91.952978
iter  40 value 87.380538
iter  50 value 85.217865
iter  60 value 83.589866
iter  70 value 82.968910
iter  80 value 82.855241
iter  90 value 82.768765
iter 100 value 82.652386
final  value 82.652386 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 112.382335 
iter  10 value 90.336307
iter  20 value 89.197055
iter  30 value 88.383026
iter  40 value 86.954465
iter  50 value 85.188935
iter  60 value 84.497211
iter  70 value 83.622218
iter  80 value 83.337988
iter  90 value 83.021823
iter 100 value 82.838526
final  value 82.838526 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.452064 
final  value 94.054566 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.911653 
final  value 94.054718 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.217506 
final  value 94.054672 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.493058 
final  value 94.054524 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.202207 
final  value 94.054612 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.450921 
iter  10 value 94.057929
iter  20 value 92.964081
iter  30 value 86.942402
iter  40 value 86.858649
iter  40 value 86.858648
iter  40 value 86.858648
final  value 86.858648 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.514768 
iter  10 value 94.057910
iter  20 value 91.110063
iter  30 value 88.795337
iter  40 value 88.794718
iter  50 value 88.793244
iter  50 value 88.793243
iter  50 value 88.793243
final  value 88.793243 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.011455 
iter  10 value 94.038269
iter  20 value 92.672258
final  value 88.791386 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.399503 
iter  10 value 94.057800
iter  20 value 94.052918
iter  30 value 88.757065
iter  40 value 88.647036
iter  50 value 88.645887
final  value 88.645871 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.702083 
iter  10 value 89.522713
iter  20 value 88.832834
iter  30 value 88.718962
iter  40 value 88.717055
iter  50 value 88.279320
iter  60 value 86.707482
iter  70 value 83.885309
iter  80 value 82.580600
iter  90 value 82.248681
iter 100 value 81.936232
final  value 81.936232 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 93.543436 
iter  10 value 90.211974
iter  20 value 86.677914
iter  30 value 86.519670
iter  40 value 86.501304
iter  50 value 86.500054
iter  60 value 86.499284
iter  70 value 86.499054
iter  80 value 85.075409
iter  90 value 82.858177
iter 100 value 82.477250
final  value 82.477250 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 97.717761 
iter  10 value 94.046666
iter  20 value 94.038305
iter  30 value 94.019791
iter  40 value 91.691540
iter  50 value 86.957799
iter  60 value 86.813014
iter  70 value 86.812632
iter  80 value 86.645644
iter  90 value 86.159023
iter 100 value 86.104443
final  value 86.104443 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 98.672445 
iter  10 value 94.039283
iter  20 value 93.714516
iter  30 value 93.712274
iter  40 value 93.709708
iter  50 value 93.709376
iter  60 value 93.708755
final  value 93.707670 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.204922 
iter  10 value 94.060630
iter  20 value 94.049946
iter  30 value 93.150269
iter  40 value 92.823316
iter  50 value 89.034362
iter  60 value 87.607749
iter  70 value 86.795072
final  value 86.754630 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.310115 
iter  10 value 94.027510
iter  20 value 94.022166
iter  30 value 94.014930
iter  40 value 88.070626
iter  50 value 87.992532
iter  60 value 86.369749
iter  70 value 86.069394
iter  80 value 83.346451
iter  90 value 82.257434
iter 100 value 82.017004
final  value 82.017004 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.490300 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.872046 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.056168 
final  value 94.448052 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.265047 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.766045 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.219990 
final  value 94.026542 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.171807 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.241334 
iter  10 value 93.974475
iter  20 value 93.926154
iter  30 value 93.925182
final  value 93.925180 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.998878 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.336486 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.495659 
final  value 94.026542 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.701920 
final  value 94.026542 
converged
Fitting Repeat 3 

# weights:  507
initial  value 110.228815 
iter  10 value 93.272920
final  value 93.257143 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.348494 
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 95.245711 
final  value 94.112570 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.666401 
iter  10 value 93.708538
iter  20 value 85.262063
iter  30 value 84.664365
iter  40 value 84.360489
iter  50 value 84.173756
iter  60 value 84.154017
final  value 84.153973 
converged
Fitting Repeat 2 

# weights:  103
initial  value 119.229318 
iter  10 value 94.239670
iter  20 value 94.135925
iter  30 value 93.421737
iter  40 value 89.393173
iter  50 value 87.829971
iter  60 value 87.747767
iter  70 value 87.368425
iter  80 value 83.545986
iter  90 value 82.845495
iter 100 value 82.398279
final  value 82.398279 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 103.862261 
iter  10 value 94.482616
iter  20 value 86.762647
iter  30 value 85.264477
iter  40 value 84.696584
iter  50 value 84.281241
iter  60 value 84.036181
iter  70 value 84.022709
iter  80 value 84.004142
final  value 84.003900 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.402408 
iter  10 value 94.478937
iter  20 value 87.021703
iter  30 value 84.173043
iter  40 value 82.539584
iter  50 value 82.047832
iter  60 value 81.935271
iter  70 value 81.923968
iter  80 value 81.595874
iter  90 value 81.386742
iter 100 value 81.381763
final  value 81.381763 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 101.112427 
iter  10 value 94.235531
iter  20 value 84.683938
iter  30 value 84.533552
iter  40 value 84.294615
iter  50 value 84.192081
iter  60 value 84.154062
final  value 84.154014 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.796038 
iter  10 value 94.491066
iter  20 value 94.184534
iter  30 value 87.168152
iter  40 value 85.870701
iter  50 value 85.114137
iter  60 value 84.254050
iter  70 value 83.103903
iter  80 value 82.013377
iter  90 value 81.681808
iter 100 value 81.486852
final  value 81.486852 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 119.695345 
iter  10 value 94.174741
iter  20 value 87.497451
iter  30 value 86.971143
iter  40 value 86.708715
iter  50 value 85.925209
iter  60 value 84.512210
iter  70 value 84.111268
iter  80 value 83.685227
iter  90 value 82.310927
iter 100 value 81.344309
final  value 81.344309 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 107.751646 
iter  10 value 94.579230
iter  20 value 92.738943
iter  30 value 90.986803
iter  40 value 90.674950
iter  50 value 85.780368
iter  60 value 84.168686
iter  70 value 83.943590
iter  80 value 82.909637
iter  90 value 82.530897
iter 100 value 82.436447
final  value 82.436447 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.190801 
iter  10 value 94.054865
iter  20 value 88.714840
iter  30 value 85.803876
iter  40 value 85.168064
iter  50 value 84.221103
iter  60 value 82.229936
iter  70 value 81.351193
iter  80 value 81.185248
iter  90 value 80.977019
iter 100 value 80.588249
final  value 80.588249 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.049740 
iter  10 value 94.129333
iter  20 value 92.397275
iter  30 value 84.448530
iter  40 value 83.407397
iter  50 value 82.401298
iter  60 value 81.139119
iter  70 value 80.488694
iter  80 value 80.307698
iter  90 value 80.182030
iter 100 value 80.032572
final  value 80.032572 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 124.681260 
iter  10 value 94.231915
iter  20 value 93.563950
iter  30 value 85.315929
iter  40 value 81.358220
iter  50 value 81.024509
iter  60 value 80.325993
iter  70 value 79.882196
iter  80 value 79.562782
iter  90 value 79.314829
iter 100 value 79.207643
final  value 79.207643 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 137.562855 
iter  10 value 96.046115
iter  20 value 88.072570
iter  30 value 85.157677
iter  40 value 83.358887
iter  50 value 82.158036
iter  60 value 80.556269
iter  70 value 80.372043
iter  80 value 80.163523
iter  90 value 79.931932
iter 100 value 79.733331
final  value 79.733331 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 112.390359 
iter  10 value 94.540379
iter  20 value 87.639495
iter  30 value 86.177967
iter  40 value 84.793904
iter  50 value 84.084282
iter  60 value 82.080823
iter  70 value 81.124825
iter  80 value 81.062678
iter  90 value 80.859516
iter 100 value 80.743959
final  value 80.743959 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 122.943555 
iter  10 value 94.301338
iter  20 value 86.076641
iter  30 value 85.679084
iter  40 value 83.652100
iter  50 value 82.163119
iter  60 value 81.597723
iter  70 value 81.352734
iter  80 value 80.857984
iter  90 value 80.821048
iter 100 value 80.727898
final  value 80.727898 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 118.021153 
iter  10 value 95.950652
iter  20 value 93.288082
iter  30 value 88.397789
iter  40 value 83.990856
iter  50 value 83.702304
iter  60 value 81.923138
iter  70 value 81.175021
iter  80 value 81.099354
iter  90 value 81.005927
iter 100 value 80.936867
final  value 80.936867 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.469934 
final  value 94.485478 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.094666 
final  value 94.485766 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.032989 
iter  10 value 94.489929
final  value 94.488090 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.648337 
final  value 94.485824 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.546180 
final  value 94.485934 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.503557 
iter  10 value 94.488456
iter  20 value 94.482307
iter  30 value 86.362937
final  value 86.309316 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.732954 
iter  10 value 94.489075
iter  20 value 94.151193
iter  30 value 85.181470
final  value 85.063797 
converged
Fitting Repeat 3 

# weights:  305
initial  value 111.431169 
iter  10 value 94.478484
iter  20 value 94.008748
iter  30 value 86.374553
iter  40 value 86.319616
iter  50 value 86.296626
iter  60 value 84.360355
final  value 84.291680 
converged
Fitting Repeat 4 

# weights:  305
initial  value 118.057967 
iter  10 value 94.487427
iter  20 value 94.484361
final  value 94.484338 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.492061 
iter  10 value 94.489498
iter  20 value 94.484245
final  value 94.484213 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.408826 
iter  10 value 94.489026
iter  20 value 94.082042
final  value 94.026741 
converged
Fitting Repeat 2 

# weights:  507
initial  value 94.923465 
iter  10 value 94.212460
iter  20 value 94.171633
iter  30 value 93.977661
iter  40 value 93.976001
iter  50 value 93.974757
final  value 93.974739 
converged
Fitting Repeat 3 

# weights:  507
initial  value 117.271328 
iter  10 value 94.034671
iter  20 value 94.027990
iter  30 value 92.956973
iter  40 value 85.034186
iter  50 value 82.991538
iter  60 value 82.975939
iter  70 value 82.964447
iter  80 value 82.963710
final  value 82.963665 
converged
Fitting Repeat 4 

# weights:  507
initial  value 109.810341 
iter  10 value 94.492454
iter  20 value 94.488119
iter  30 value 94.448983
iter  40 value 94.444832
iter  50 value 88.277194
iter  60 value 86.476398
iter  70 value 83.023330
iter  80 value 80.756354
iter  90 value 80.320215
iter 100 value 80.293418
final  value 80.293418 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.777596 
iter  10 value 92.079685
iter  20 value 92.037947
iter  30 value 92.035056
iter  40 value 92.033042
iter  50 value 92.032849
final  value 92.032219 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.866013 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.899822 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.372592 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.675958 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.041897 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.611026 
final  value 94.008696 
converged
Fitting Repeat 2 

# weights:  305
initial  value 113.850333 
final  value 93.730996 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.518209 
final  value 94.008696 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.865943 
final  value 94.008696 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.280645 
iter  10 value 92.567928
iter  20 value 92.546122
iter  30 value 86.398913
iter  40 value 86.340724
final  value 86.339468 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.833734 
iter  10 value 93.698120
iter  20 value 93.691698
iter  30 value 93.368864
final  value 93.340620 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.291901 
final  value 93.697143 
converged
Fitting Repeat 3 

# weights:  507
initial  value 112.777232 
final  value 92.453524 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.661939 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.026200 
final  value 94.008696 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.507234 
iter  10 value 93.805205
iter  20 value 86.482611
iter  30 value 85.610920
iter  40 value 85.479238
iter  50 value 84.370370
iter  60 value 83.484681
iter  70 value 83.444440
final  value 83.444421 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.983883 
iter  10 value 93.929515
iter  20 value 89.400751
iter  30 value 88.023593
iter  40 value 87.406335
iter  50 value 87.022460
iter  60 value 84.241458
iter  70 value 83.671740
iter  80 value 83.669527
iter  80 value 83.669527
iter  80 value 83.669527
final  value 83.669527 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.134682 
iter  10 value 94.056487
iter  20 value 93.260944
iter  30 value 86.198739
iter  40 value 85.820750
iter  50 value 83.848744
iter  60 value 83.672923
final  value 83.669527 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.855040 
iter  10 value 94.056538
iter  20 value 93.791323
iter  30 value 93.345928
iter  40 value 93.193800
iter  50 value 93.173447
iter  60 value 87.572396
iter  70 value 87.080519
iter  80 value 85.440806
iter  90 value 84.154080
iter 100 value 83.675416
final  value 83.675416 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 100.608527 
iter  10 value 93.588087
iter  20 value 90.701972
iter  30 value 84.776779
iter  40 value 81.804798
iter  50 value 81.418662
iter  60 value 80.371766
iter  70 value 80.185828
iter  80 value 80.057395
iter  90 value 79.696868
final  value 79.695415 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.453634 
iter  10 value 94.066425
iter  20 value 94.004584
iter  30 value 91.894862
iter  40 value 86.643578
iter  50 value 84.974280
iter  60 value 83.516827
iter  70 value 83.386457
iter  80 value 81.786750
iter  90 value 81.671001
iter 100 value 81.249920
final  value 81.249920 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 120.645509 
iter  10 value 94.611633
iter  20 value 86.141671
iter  30 value 84.798029
iter  40 value 84.411951
iter  50 value 82.726622
iter  60 value 79.772879
iter  70 value 79.317543
iter  80 value 79.024231
iter  90 value 78.842815
iter 100 value 78.813855
final  value 78.813855 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.117461 
iter  10 value 94.026339
iter  20 value 86.451214
iter  30 value 86.209011
iter  40 value 86.021883
iter  50 value 85.011885
iter  60 value 80.902095
iter  70 value 80.171682
iter  80 value 79.435443
iter  90 value 78.641684
iter 100 value 78.511340
final  value 78.511340 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.435802 
iter  10 value 94.013768
iter  20 value 86.756355
iter  30 value 83.501844
iter  40 value 81.214415
iter  50 value 80.813505
iter  60 value 80.413952
iter  70 value 80.045500
iter  80 value 79.782817
iter  90 value 79.511676
iter 100 value 79.214445
final  value 79.214445 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.164032 
iter  10 value 94.116859
iter  20 value 86.589353
iter  30 value 85.937353
iter  40 value 85.423552
iter  50 value 81.033407
iter  60 value 79.365806
iter  70 value 78.628978
iter  80 value 78.522035
iter  90 value 78.233033
iter 100 value 78.140704
final  value 78.140704 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.732649 
iter  10 value 94.000412
iter  20 value 88.221265
iter  30 value 83.587658
iter  40 value 82.656883
iter  50 value 80.200903
iter  60 value 79.694248
iter  70 value 79.140271
iter  80 value 79.025047
iter  90 value 78.854349
iter 100 value 78.771222
final  value 78.771222 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 144.012837 
iter  10 value 93.705116
iter  20 value 86.866238
iter  30 value 86.182226
iter  40 value 83.986454
iter  50 value 83.740537
iter  60 value 83.539140
iter  70 value 82.613185
iter  80 value 81.816261
iter  90 value 81.621385
iter 100 value 81.002224
final  value 81.002224 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.105624 
iter  10 value 94.333955
iter  20 value 93.600804
iter  30 value 93.285610
iter  40 value 91.814232
iter  50 value 87.385225
iter  60 value 86.264611
iter  70 value 84.754939
iter  80 value 79.689346
iter  90 value 78.948792
iter 100 value 78.578347
final  value 78.578347 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 130.449592 
iter  10 value 94.059008
iter  20 value 93.727671
iter  30 value 93.317354
iter  40 value 90.090500
iter  50 value 84.049888
iter  60 value 83.463539
iter  70 value 82.342337
iter  80 value 80.410781
iter  90 value 79.109439
iter 100 value 78.582715
final  value 78.582715 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.053104 
iter  10 value 94.840886
iter  20 value 89.420199
iter  30 value 88.206304
iter  40 value 86.565005
iter  50 value 83.398598
iter  60 value 81.544454
iter  70 value 81.234990
iter  80 value 80.525205
iter  90 value 79.627927
iter 100 value 79.008927
final  value 79.008927 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.852604 
iter  10 value 94.057317
iter  20 value 91.160027
iter  30 value 83.420202
iter  40 value 81.009297
iter  50 value 80.442869
iter  60 value 80.086761
iter  70 value 80.021276
final  value 80.020416 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.973357 
iter  10 value 94.054500
iter  20 value 94.052876
iter  30 value 85.776605
iter  40 value 85.212557
iter  50 value 85.202144
iter  60 value 85.200906
iter  70 value 85.200815
final  value 85.200813 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.485536 
final  value 94.054392 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.024780 
final  value 94.054374 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.550863 
iter  10 value 94.054654
final  value 94.052913 
converged
Fitting Repeat 1 

# weights:  305
initial  value 115.415676 
iter  10 value 94.058044
iter  20 value 93.255035
final  value 93.226480 
converged
Fitting Repeat 2 

# weights:  305
initial  value 119.040481 
iter  10 value 94.058126
iter  20 value 94.053373
iter  30 value 87.255955
final  value 87.238543 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.172907 
iter  10 value 94.090553
iter  20 value 94.082944
iter  30 value 94.082641
iter  40 value 93.729889
iter  50 value 93.671765
iter  60 value 93.354307
iter  70 value 93.204756
iter  80 value 93.182179
iter  90 value 90.074836
iter 100 value 89.939200
final  value 89.939200 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 95.648305 
iter  10 value 91.238533
iter  20 value 87.619152
iter  30 value 87.604564
iter  40 value 87.603735
iter  50 value 87.600982
final  value 87.599931 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.720857 
iter  10 value 94.057419
iter  20 value 94.053038
final  value 94.052921 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.320844 
iter  10 value 93.563347
iter  20 value 90.289724
iter  30 value 83.231483
iter  40 value 81.523578
iter  50 value 80.571179
iter  60 value 79.499349
iter  70 value 78.851333
iter  80 value 78.218799
iter  90 value 78.145815
iter 100 value 78.144278
final  value 78.144278 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.790955 
iter  10 value 94.017436
iter  20 value 93.322414
iter  30 value 93.228462
iter  40 value 92.312060
iter  50 value 90.769325
iter  60 value 90.263981
iter  70 value 90.245351
iter  80 value 90.223427
iter  90 value 89.913975
iter 100 value 89.906949
final  value 89.906949 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 112.908448 
iter  10 value 86.431602
iter  20 value 83.760499
iter  30 value 83.748034
iter  40 value 83.747206
iter  50 value 83.746601
iter  60 value 83.402401
iter  70 value 81.500325
iter  80 value 81.147842
iter  90 value 80.627043
iter 100 value 80.576614
final  value 80.576614 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 114.724715 
iter  10 value 93.380364
iter  20 value 89.797957
iter  30 value 88.838543
iter  40 value 88.795199
final  value 88.795184 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.607985 
iter  10 value 94.060991
iter  20 value 93.293848
iter  30 value 92.246984
iter  40 value 82.676830
iter  50 value 81.492328
final  value 81.479186 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.264627 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 123.014287 
iter  10 value 94.484243
iter  10 value 94.484243
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.686043 
iter  10 value 94.292604
final  value 94.288572 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.182241 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 109.921908 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.105958 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.851652 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.443557 
iter  10 value 89.598803
iter  20 value 87.401559
iter  30 value 86.983522
iter  40 value 86.538889
iter  50 value 86.522720
iter  60 value 86.521728
iter  70 value 86.521629
final  value 86.521627 
converged
Fitting Repeat 4 

# weights:  305
initial  value 126.628280 
final  value 94.354396 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.217129 
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.174822 
final  value 94.427726 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.148903 
final  value 94.354396 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.913148 
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  507
initial  value 129.324357 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 110.677888 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.359454 
iter  10 value 94.376257
iter  20 value 93.118018
iter  30 value 90.958024
iter  40 value 86.088470
iter  50 value 85.461644
iter  60 value 85.435714
iter  70 value 85.387599
iter  80 value 84.834279
iter  90 value 82.422871
iter 100 value 81.640810
final  value 81.640810 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 100.199298 
iter  10 value 94.539028
iter  20 value 94.486642
iter  30 value 89.801492
iter  40 value 88.292176
iter  50 value 84.301403
iter  60 value 83.604641
iter  70 value 83.285050
iter  80 value 83.276431
iter  90 value 81.598670
iter 100 value 81.171354
final  value 81.171354 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 103.732393 
iter  10 value 94.486827
iter  20 value 91.349773
iter  30 value 84.761275
iter  40 value 83.187056
iter  50 value 82.378261
iter  60 value 81.677801
iter  70 value 81.592040
iter  80 value 81.575283
iter  90 value 81.557391
iter  90 value 81.557391
iter  90 value 81.557391
final  value 81.557391 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.894386 
iter  10 value 93.351005
iter  20 value 85.347628
iter  30 value 84.623217
iter  40 value 84.181181
iter  50 value 83.925690
iter  60 value 83.783745
iter  70 value 83.482471
iter  80 value 83.262304
final  value 83.262182 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.309854 
iter  10 value 94.484613
iter  20 value 86.356432
iter  30 value 85.795145
iter  40 value 85.514306
iter  50 value 84.400124
iter  60 value 82.078970
iter  70 value 81.680624
iter  80 value 81.633812
iter  90 value 81.597701
iter 100 value 81.557533
final  value 81.557533 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 105.468106 
iter  10 value 94.680358
iter  20 value 94.417954
iter  30 value 86.149359
iter  40 value 84.490348
iter  50 value 84.034299
iter  60 value 83.821155
iter  70 value 82.750920
iter  80 value 82.685435
iter  90 value 82.658811
iter 100 value 81.981507
final  value 81.981507 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.460367 
iter  10 value 94.421745
iter  20 value 89.608429
iter  30 value 89.003777
iter  40 value 85.754731
iter  50 value 84.284374
iter  60 value 84.116615
iter  70 value 83.898700
iter  80 value 81.496527
iter  90 value 80.635522
iter 100 value 80.401405
final  value 80.401405 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.491871 
iter  10 value 94.685378
iter  20 value 94.478267
iter  30 value 89.488643
iter  40 value 87.521548
iter  50 value 83.066427
iter  60 value 82.868268
iter  70 value 82.660718
iter  80 value 81.792430
iter  90 value 81.479176
iter 100 value 81.395041
final  value 81.395041 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 113.141126 
iter  10 value 95.960579
iter  20 value 93.479105
iter  30 value 85.683130
iter  40 value 82.918461
iter  50 value 82.113352
iter  60 value 81.901907
iter  70 value 81.562444
iter  80 value 81.524565
iter  90 value 81.355223
iter 100 value 81.279267
final  value 81.279267 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.594997 
iter  10 value 94.443622
iter  20 value 87.398814
iter  30 value 84.723481
iter  40 value 81.901764
iter  50 value 81.509646
iter  60 value 80.717915
iter  70 value 80.525321
iter  80 value 80.247004
iter  90 value 80.219678
iter 100 value 80.032841
final  value 80.032841 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.196471 
iter  10 value 94.837989
iter  20 value 94.492011
iter  30 value 94.400772
iter  40 value 90.564499
iter  50 value 85.925648
iter  60 value 83.956885
iter  70 value 83.092833
iter  80 value 81.835695
iter  90 value 81.518092
iter 100 value 81.305121
final  value 81.305121 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.302761 
iter  10 value 89.686173
iter  20 value 85.128822
iter  30 value 83.325260
iter  40 value 82.744566
iter  50 value 82.190183
iter  60 value 81.113920
iter  70 value 80.815943
iter  80 value 80.761167
iter  90 value 80.619862
iter 100 value 80.541818
final  value 80.541818 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 120.402764 
iter  10 value 94.859446
iter  20 value 91.628686
iter  30 value 84.915820
iter  40 value 81.958707
iter  50 value 81.633630
iter  60 value 81.041489
iter  70 value 80.826560
iter  80 value 80.716917
iter  90 value 80.493146
iter 100 value 80.291454
final  value 80.291454 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 114.851106 
iter  10 value 94.545549
iter  20 value 94.458621
iter  30 value 89.804712
iter  40 value 87.908350
iter  50 value 84.435770
iter  60 value 82.779820
iter  70 value 81.430723
iter  80 value 80.203267
iter  90 value 79.973034
iter 100 value 79.886725
final  value 79.886725 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.701871 
iter  10 value 94.867291
iter  20 value 87.661922
iter  30 value 86.720144
iter  40 value 86.211630
iter  50 value 82.856277
iter  60 value 82.124125
iter  70 value 81.904518
iter  80 value 80.883213
iter  90 value 80.065618
iter 100 value 79.863224
final  value 79.863224 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.348021 
iter  10 value 87.239644
iter  20 value 85.213234
iter  30 value 85.212407
final  value 85.211710 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.531425 
iter  10 value 94.315433
iter  20 value 94.025530
iter  30 value 93.580110
final  value 93.572665 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.430042 
final  value 94.485916 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.697680 
final  value 94.355961 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.623354 
final  value 94.290271 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.166816 
iter  10 value 94.359826
iter  20 value 93.566864
iter  30 value 85.654531
iter  40 value 84.110262
iter  50 value 84.056929
iter  60 value 83.951481
final  value 83.950866 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.111460 
iter  10 value 94.359612
iter  20 value 94.356031
iter  30 value 92.973519
iter  40 value 91.977401
final  value 91.977295 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.446583 
iter  10 value 94.214388
iter  20 value 93.809119
iter  30 value 93.664063
iter  40 value 93.661784
iter  50 value 93.640427
iter  60 value 93.479677
iter  70 value 93.476401
iter  80 value 93.277536
iter  90 value 87.851885
iter 100 value 87.529337
final  value 87.529337 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.842046 
iter  10 value 94.489154
final  value 94.484221 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.606363 
iter  10 value 94.359642
iter  20 value 94.355073
final  value 94.354675 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.793631 
iter  10 value 94.492790
iter  20 value 94.455362
iter  30 value 90.663024
iter  40 value 86.944938
iter  50 value 86.908778
iter  60 value 85.521306
iter  70 value 85.464867
iter  80 value 82.998551
iter  90 value 81.922190
iter 100 value 81.878210
final  value 81.878210 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 123.292675 
iter  10 value 94.362897
iter  20 value 94.292573
iter  30 value 92.332407
iter  40 value 87.827752
iter  50 value 87.823317
iter  60 value 87.776048
iter  70 value 87.574873
iter  80 value 87.571086
iter  90 value 87.570755
iter  90 value 87.570755
final  value 87.570755 
converged
Fitting Repeat 3 

# weights:  507
initial  value 111.273178 
final  value 94.362848 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.983536 
iter  10 value 94.203483
iter  20 value 94.199181
iter  30 value 90.180327
iter  40 value 85.630317
iter  50 value 85.595772
iter  60 value 85.594017
iter  70 value 85.593368
final  value 85.592951 
converged
Fitting Repeat 5 

# weights:  507
initial  value 111.213184 
iter  10 value 94.363061
iter  20 value 94.361826
iter  30 value 94.245904
iter  40 value 94.124902
iter  50 value 92.600191
iter  60 value 85.882852
iter  70 value 85.562671
iter  80 value 85.556451
final  value 85.556425 
converged
Fitting Repeat 1 

# weights:  103
initial  value 110.348800 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.977756 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.824237 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.560417 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 109.417971 
final  value 94.275362 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.426999 
final  value 94.275362 
converged
Fitting Repeat 2 

# weights:  305
initial  value 106.882298 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 108.293432 
iter  10 value 88.139747
iter  20 value 84.798991
iter  30 value 84.050265
iter  40 value 81.288747
iter  50 value 80.647069
iter  60 value 80.503798
iter  70 value 79.878951
iter  80 value 79.878495
final  value 79.878493 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.160138 
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  305
initial  value 111.271518 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.516368 
iter  10 value 92.767989
iter  20 value 92.613874
iter  20 value 92.613874
iter  20 value 92.613874
final  value 92.613874 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.448798 
final  value 94.275363 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.594035 
iter  10 value 93.798287
final  value 93.057256 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.347287 
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.183740 
final  value 94.275362 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.442875 
iter  10 value 94.489408
iter  20 value 94.311970
iter  30 value 92.714627
iter  40 value 90.496232
iter  50 value 89.939031
iter  60 value 89.091168
iter  70 value 82.480491
iter  80 value 81.942446
iter  90 value 81.890979
iter 100 value 81.646774
final  value 81.646774 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.972936 
iter  10 value 94.494678
iter  20 value 94.024877
iter  30 value 90.930192
iter  40 value 90.064034
iter  50 value 87.731660
iter  60 value 86.716764
iter  70 value 85.865474
iter  80 value 82.475228
iter  90 value 81.279843
iter 100 value 80.808748
final  value 80.808748 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 101.654369 
iter  10 value 94.494698
iter  20 value 94.465271
iter  30 value 83.927569
iter  40 value 83.334827
iter  50 value 83.089002
iter  60 value 82.911378
iter  70 value 82.895191
iter  70 value 82.895191
iter  70 value 82.895191
final  value 82.895191 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.751673 
iter  10 value 94.289865
iter  20 value 86.958405
iter  30 value 84.080747
iter  40 value 83.501989
iter  50 value 83.192677
iter  60 value 82.913936
iter  70 value 82.774198
iter  80 value 82.757485
final  value 82.757438 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.112723 
iter  10 value 94.494752
iter  20 value 93.267739
iter  30 value 90.505430
iter  40 value 84.084067
iter  50 value 83.965692
iter  60 value 83.713407
iter  70 value 83.341342
iter  80 value 83.330085
final  value 83.325956 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.325286 
iter  10 value 94.501110
iter  20 value 93.293435
iter  30 value 91.759438
iter  40 value 88.001113
iter  50 value 84.988067
iter  60 value 83.822867
iter  70 value 81.435936
iter  80 value 80.699196
iter  90 value 80.570179
iter 100 value 80.474570
final  value 80.474570 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.786358 
iter  10 value 94.640261
iter  20 value 92.739220
iter  30 value 91.957276
iter  40 value 83.716770
iter  50 value 81.989987
iter  60 value 81.399831
iter  70 value 80.575384
iter  80 value 79.765708
iter  90 value 79.611062
iter 100 value 79.568140
final  value 79.568140 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 107.784192 
iter  10 value 93.629260
iter  20 value 90.594410
iter  30 value 89.472528
iter  40 value 84.405946
iter  50 value 83.919461
iter  60 value 83.732299
iter  70 value 83.258566
iter  80 value 82.829094
iter  90 value 82.687876
iter 100 value 81.887746
final  value 81.887746 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 113.153290 
iter  10 value 94.475064
iter  20 value 86.652010
iter  30 value 83.688016
iter  40 value 83.252361
iter  50 value 82.848707
iter  60 value 81.001987
iter  70 value 80.382273
iter  80 value 79.963964
iter  90 value 79.864655
iter 100 value 79.764436
final  value 79.764436 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.263440 
iter  10 value 94.469540
iter  20 value 94.070187
iter  30 value 91.736698
iter  40 value 85.250774
iter  50 value 83.319884
iter  60 value 82.006963
iter  70 value 81.443900
iter  80 value 80.608096
iter  90 value 80.089156
iter 100 value 79.963723
final  value 79.963723 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.202575 
iter  10 value 92.593830
iter  20 value 84.614419
iter  30 value 83.165622
iter  40 value 82.191934
iter  50 value 81.674335
iter  60 value 80.326289
iter  70 value 79.802254
iter  80 value 79.652480
iter  90 value 79.380105
iter 100 value 79.165703
final  value 79.165703 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 110.873761 
iter  10 value 95.569307
iter  20 value 94.535087
iter  30 value 93.929455
iter  40 value 84.734799
iter  50 value 82.460687
iter  60 value 80.968125
iter  70 value 80.685216
iter  80 value 80.595799
iter  90 value 80.467171
iter 100 value 80.445688
final  value 80.445688 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.305067 
iter  10 value 98.570262
iter  20 value 84.107156
iter  30 value 81.928136
iter  40 value 81.450742
iter  50 value 81.383655
iter  60 value 80.611940
iter  70 value 80.207159
iter  80 value 80.063675
iter  90 value 80.018493
iter 100 value 79.882667
final  value 79.882667 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.245366 
iter  10 value 94.851097
iter  20 value 90.764594
iter  30 value 87.484957
iter  40 value 87.076753
iter  50 value 84.971011
iter  60 value 83.352211
iter  70 value 80.097160
iter  80 value 79.579448
iter  90 value 79.341867
iter 100 value 79.302871
final  value 79.302871 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 145.267865 
iter  10 value 94.573461
iter  20 value 92.025105
iter  30 value 84.402771
iter  40 value 82.066554
iter  50 value 80.520255
iter  60 value 80.339295
iter  70 value 80.044128
iter  80 value 79.725782
iter  90 value 79.662271
iter 100 value 79.391977
final  value 79.391977 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.589237 
iter  10 value 94.485896
iter  20 value 94.484231
final  value 94.484226 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.767608 
final  value 94.485874 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.308906 
final  value 94.485870 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.068684 
final  value 94.485764 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.516110 
final  value 94.485755 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.171349 
iter  10 value 94.454327
iter  20 value 94.340301
iter  30 value 91.441897
iter  40 value 90.657380
final  value 90.647461 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.325377 
iter  10 value 94.280271
iter  20 value 94.276886
iter  30 value 94.276573
iter  40 value 88.536938
iter  50 value 83.233299
iter  60 value 83.174790
iter  70 value 83.173610
final  value 83.172802 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.402861 
iter  10 value 94.488958
iter  20 value 94.484260
iter  30 value 85.943277
iter  40 value 84.447828
iter  50 value 83.071481
iter  60 value 78.985825
iter  70 value 78.446756
iter  80 value 78.381419
iter  90 value 78.311424
iter 100 value 78.071677
final  value 78.071677 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 97.984476 
iter  10 value 94.489197
iter  20 value 94.484259
iter  30 value 94.366401
iter  40 value 92.421000
iter  50 value 91.566595
iter  60 value 84.978888
iter  70 value 84.623555
iter  80 value 84.608361
iter  90 value 84.594930
iter 100 value 84.577602
final  value 84.577602 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 96.550553 
iter  10 value 94.489401
iter  20 value 94.484510
iter  30 value 91.734479
iter  40 value 91.180591
iter  50 value 91.179301
iter  60 value 91.177152
final  value 91.176949 
converged
Fitting Repeat 1 

# weights:  507
initial  value 123.823901 
iter  10 value 94.294900
iter  20 value 94.282555
iter  30 value 94.275950
iter  40 value 93.530967
iter  50 value 92.301641
iter  60 value 85.396234
iter  70 value 82.638790
iter  80 value 82.554298
iter  90 value 82.536974
final  value 82.536903 
converged
Fitting Repeat 2 

# weights:  507
initial  value 113.193064 
iter  10 value 94.284324
iter  20 value 94.278608
iter  30 value 89.874094
iter  40 value 85.215788
iter  50 value 84.598108
final  value 84.598096 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.066390 
iter  10 value 94.284048
iter  20 value 90.339810
iter  30 value 83.215701
iter  40 value 81.423210
iter  50 value 80.602757
iter  60 value 80.406765
iter  70 value 80.405613
iter  80 value 80.400559
iter  90 value 80.398125
iter 100 value 80.396139
final  value 80.396139 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.812687 
iter  10 value 94.283221
iter  20 value 94.275631
iter  30 value 91.376915
iter  40 value 88.599684
iter  50 value 87.523165
iter  60 value 87.382042
iter  70 value 87.380617
iter  80 value 87.368865
iter  90 value 87.364272
iter 100 value 87.363798
final  value 87.363798 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.172030 
iter  10 value 93.822934
iter  20 value 93.198376
iter  30 value 92.545878
iter  40 value 92.544828
iter  50 value 92.416976
iter  60 value 84.485568
iter  70 value 80.925473
iter  80 value 80.843684
iter  90 value 80.616928
iter 100 value 80.577575
final  value 80.577575 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 149.302205 
iter  10 value 117.898584
iter  20 value 117.869925
iter  30 value 107.083285
iter  40 value 106.641241
iter  50 value 103.978597
iter  60 value 100.858542
iter  70 value 100.614767
iter  80 value 100.569751
iter  80 value 100.569751
final  value 100.569751 
converged
Fitting Repeat 2 

# weights:  507
initial  value 161.798571 
iter  10 value 117.767345
iter  20 value 117.721037
iter  30 value 116.751953
iter  40 value 105.365874
iter  50 value 105.343986
iter  60 value 105.342845
iter  70 value 105.341866
iter  80 value 105.327117
iter  90 value 103.337340
iter 100 value 101.878206
final  value 101.878206 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 121.985352 
iter  10 value 117.214270
iter  20 value 115.359454
iter  30 value 114.916616
iter  40 value 114.825235
iter  50 value 114.636312
final  value 114.636308 
converged
Fitting Repeat 4 

# weights:  507
initial  value 129.362663 
iter  10 value 117.898980
iter  20 value 117.887469
iter  30 value 107.149441
iter  40 value 107.004265
iter  50 value 106.389474
iter  60 value 104.298819
iter  70 value 104.298053
iter  80 value 103.842413
iter  90 value 102.241081
iter 100 value 101.806828
final  value 101.806828 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 120.915038 
iter  10 value 117.614661
iter  20 value 117.592138
iter  30 value 117.591905
iter  40 value 117.585287
iter  50 value 110.908236
iter  60 value 109.527712
iter  70 value 109.520836
iter  80 value 109.520006
iter  90 value 109.366546
iter 100 value 105.173817
final  value 105.173817 
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 Jul 24 00:29:58 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 
 42.007   2.019  42.458