##############################################################################
##############################################################################
###
### 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 4.4.1 (2024-06-14)
* using platform: aarch64-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 Ventura 13.6.6
* 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       54.815  2.046  57.072
FSmethod      52.579  2.141  54.991
corr_plot     51.738  2.166  54.217
pred_ensembel 15.858  0.293  13.566
enrichfindP    0.512  0.072   6.815
* 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-arm64/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 4.4.1 (2024-06-14) -- "Race for Your Life"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-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 103.896375 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.925653 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.730192 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.232573 
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.944395 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.839013 
iter  10 value 92.914910
final  value 92.845238 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.759829 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 110.767720 
iter  10 value 94.275362
iter  10 value 94.275362
iter  10 value 94.275362
final  value 94.275362 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.639630 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.640397 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.886411 
iter  10 value 94.242919
final  value 94.241589 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.488176 
final  value 94.275362 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.770477 
iter  10 value 93.424059
iter  20 value 89.493965
iter  30 value 89.194363
iter  40 value 89.189414
final  value 89.189350 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.752912 
iter  10 value 92.635448
iter  20 value 92.634655
final  value 92.634650 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.289307 
iter  10 value 90.951087
iter  20 value 84.663235
iter  30 value 84.432855
iter  40 value 82.846779
final  value 82.846754 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.111181 
iter  10 value 94.488636
iter  20 value 94.026232
final  value 93.977919 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.551574 
iter  10 value 94.487628
iter  20 value 94.029699
iter  30 value 93.966330
iter  40 value 86.358099
iter  50 value 85.589708
iter  60 value 85.309016
iter  70 value 85.293706
iter  80 value 85.279399
iter  90 value 84.071527
iter 100 value 83.754550
final  value 83.754550 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 113.018830 
iter  10 value 93.667015
iter  20 value 86.226851
iter  30 value 85.005144
iter  40 value 83.940410
iter  50 value 83.801628
iter  60 value 83.747926
final  value 83.746304 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.296988 
iter  10 value 94.507225
iter  20 value 91.656123
iter  30 value 88.001339
iter  40 value 86.532410
iter  50 value 83.971116
iter  60 value 83.789666
iter  70 value 83.748073
final  value 83.746304 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.400090 
iter  10 value 94.093947
iter  20 value 93.916624
iter  30 value 89.346933
iter  40 value 85.367625
iter  50 value 84.851600
iter  60 value 84.108265
iter  70 value 84.009394
iter  80 value 83.757600
iter  90 value 83.746389
final  value 83.746304 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.127547 
iter  10 value 94.258210
iter  20 value 87.154800
iter  30 value 85.673882
iter  40 value 83.855915
iter  50 value 82.687113
iter  60 value 82.445042
iter  70 value 82.089656
iter  80 value 81.761197
iter  90 value 81.567073
iter 100 value 81.077594
final  value 81.077594 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.638024 
iter  10 value 93.666544
iter  20 value 90.649959
iter  30 value 89.700806
iter  40 value 82.337391
iter  50 value 81.536100
iter  60 value 80.696866
iter  70 value 80.361284
iter  80 value 80.309670
iter  90 value 80.203012
iter 100 value 80.174876
final  value 80.174876 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 125.897069 
iter  10 value 94.497467
iter  20 value 93.741276
iter  30 value 86.438566
iter  40 value 86.171215
iter  50 value 84.123040
iter  60 value 82.373839
iter  70 value 81.969493
iter  80 value 81.852693
iter  90 value 81.626472
iter 100 value 81.389603
final  value 81.389603 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 128.628856 
iter  10 value 94.342854
iter  20 value 93.093754
iter  30 value 86.502915
iter  40 value 82.711518
iter  50 value 82.168506
iter  60 value 81.871720
iter  70 value 81.733144
iter  80 value 80.901471
iter  90 value 80.708585
iter 100 value 80.475889
final  value 80.475889 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.514621 
iter  10 value 94.513388
iter  20 value 93.714230
iter  30 value 87.109463
iter  40 value 84.418618
iter  50 value 83.639725
iter  60 value 83.506456
iter  70 value 83.488915
iter  80 value 83.465966
iter  90 value 83.445181
iter 100 value 81.854845
final  value 81.854845 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 121.949838 
iter  10 value 95.793009
iter  20 value 84.958628
iter  30 value 83.167330
iter  40 value 81.555871
iter  50 value 81.142412
iter  60 value 80.556288
iter  70 value 80.279162
iter  80 value 80.113512
iter  90 value 79.989351
iter 100 value 79.890647
final  value 79.890647 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 129.262433 
iter  10 value 95.927992
iter  20 value 94.006137
iter  30 value 93.913890
iter  40 value 93.282604
iter  50 value 83.423670
iter  60 value 82.960057
iter  70 value 81.948783
iter  80 value 81.169131
iter  90 value 80.991309
iter 100 value 80.810385
final  value 80.810385 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.986653 
iter  10 value 94.682781
iter  20 value 86.881099
iter  30 value 84.987710
iter  40 value 82.549142
iter  50 value 81.849536
iter  60 value 81.231146
iter  70 value 80.170055
iter  80 value 79.998843
iter  90 value 79.625657
iter 100 value 79.357610
final  value 79.357610 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.902601 
iter  10 value 94.710904
iter  20 value 86.050596
iter  30 value 84.260999
iter  40 value 82.692541
iter  50 value 81.186861
iter  60 value 80.879506
iter  70 value 80.550380
iter  80 value 80.314014
iter  90 value 80.232602
iter 100 value 80.201707
final  value 80.201707 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.313714 
iter  10 value 92.434748
iter  20 value 86.108763
iter  30 value 85.236914
iter  40 value 84.235964
iter  50 value 83.699200
iter  60 value 83.439445
iter  70 value 83.365671
iter  80 value 83.316872
iter  90 value 83.184555
iter 100 value 82.079548
final  value 82.079548 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.120884 
iter  10 value 94.485854
final  value 94.484213 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.868275 
iter  10 value 94.485786
iter  20 value 94.478396
iter  30 value 91.082548
iter  40 value 82.536232
iter  50 value 81.843615
iter  60 value 81.763462
final  value 81.761224 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.344854 
final  value 94.485795 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.956013 
iter  10 value 94.486063
iter  20 value 94.384212
iter  30 value 87.991307
final  value 87.955809 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.586544 
final  value 94.277155 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.265811 
iter  10 value 94.488999
iter  20 value 94.440820
iter  30 value 85.344327
iter  40 value 82.065553
iter  50 value 82.053822
iter  60 value 82.050822
final  value 82.050819 
converged
Fitting Repeat 2 

# weights:  305
initial  value 136.597677 
iter  10 value 94.281056
iter  20 value 94.101596
iter  30 value 92.660644
iter  40 value 86.438997
iter  50 value 85.433951
iter  60 value 85.027737
iter  70 value 85.018833
iter  80 value 85.017962
iter  90 value 84.971043
iter 100 value 84.590476
final  value 84.590476 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 117.218413 
iter  10 value 94.489159
iter  20 value 94.339275
iter  30 value 94.229348
iter  30 value 94.229347
iter  40 value 93.872580
iter  50 value 93.872183
final  value 93.872180 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.529705 
iter  10 value 94.501114
iter  20 value 94.496017
iter  30 value 86.995486
iter  40 value 84.465321
iter  50 value 84.456972
iter  60 value 84.453150
iter  70 value 84.452583
iter  70 value 84.452583
final  value 84.452583 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.070283 
iter  10 value 93.489314
iter  20 value 93.486069
iter  30 value 93.356202
iter  40 value 92.379509
iter  50 value 91.066187
iter  60 value 90.905829
final  value 90.905682 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.050196 
iter  10 value 94.292463
iter  20 value 94.281017
iter  30 value 94.277131
iter  40 value 94.276270
iter  50 value 93.830412
iter  60 value 88.241165
iter  70 value 88.239474
iter  80 value 88.109333
iter  90 value 87.502890
iter 100 value 84.359080
final  value 84.359080 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 95.004098 
iter  10 value 94.283730
iter  20 value 94.230288
iter  30 value 89.914229
iter  40 value 85.278143
iter  40 value 85.278142
iter  40 value 85.278142
final  value 85.278142 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.184709 
iter  10 value 92.941926
iter  20 value 92.930663
iter  30 value 92.915628
iter  40 value 87.414237
iter  50 value 82.948642
iter  60 value 82.615926
iter  70 value 82.607953
iter  80 value 82.597398
iter  90 value 82.586013
iter 100 value 82.582236
final  value 82.582236 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.268631 
iter  10 value 94.492355
iter  20 value 89.336145
iter  30 value 82.772101
iter  40 value 82.219768
iter  50 value 82.142916
final  value 82.142873 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.610864 
iter  10 value 94.284265
iter  20 value 94.254809
final  value 94.230532 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.902626 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.672912 
iter  10 value 94.053192
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.305809 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.192563 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.036584 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.546247 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.447827 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.743376 
iter  10 value 94.035366
final  value 94.032967 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.884285 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.499571 
iter  10 value 93.886056
iter  10 value 93.886056
iter  10 value 93.886056
final  value 93.886056 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.418190 
final  value 94.052911 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.818875 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.351299 
iter  10 value 93.869295
final  value 93.868979 
converged
Fitting Repeat 4 

# weights:  507
initial  value 114.670037 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.337553 
iter  10 value 93.566579
iter  20 value 92.411103
iter  30 value 85.268219
iter  40 value 84.370768
iter  50 value 84.314950
iter  60 value 84.314740
iter  60 value 84.314740
final  value 84.314740 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.548142 
iter  10 value 94.005160
iter  20 value 92.975069
iter  30 value 84.584715
iter  40 value 83.225270
iter  50 value 82.474289
iter  60 value 82.038174
iter  70 value 81.846473
iter  80 value 80.950169
iter  90 value 80.683851
iter 100 value 80.632973
final  value 80.632973 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 113.954051 
iter  10 value 94.062029
iter  20 value 94.056188
iter  30 value 93.592468
iter  40 value 93.534293
iter  50 value 93.503564
iter  60 value 93.449545
final  value 93.449066 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.026025 
iter  10 value 93.861981
iter  20 value 86.654415
iter  30 value 83.213954
iter  40 value 83.080258
iter  50 value 82.940088
iter  60 value 82.932584
iter  70 value 82.886932
iter  80 value 82.838167
final  value 82.837467 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.702372 
iter  10 value 94.057530
iter  20 value 92.632691
iter  30 value 85.227760
iter  40 value 83.264184
iter  50 value 81.795368
iter  60 value 81.677807
iter  70 value 81.615023
iter  80 value 81.335116
iter  90 value 81.070150
final  value 81.065794 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.089569 
iter  10 value 94.056678
iter  20 value 93.896366
iter  30 value 89.746928
iter  40 value 89.010544
iter  50 value 88.848113
iter  60 value 86.729754
iter  70 value 83.073729
iter  80 value 81.497468
iter  90 value 81.377487
iter 100 value 81.276385
final  value 81.276385 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 99.133135 
iter  10 value 93.844913
iter  20 value 88.967053
iter  30 value 85.647413
iter  40 value 85.229042
iter  50 value 85.132027
iter  60 value 84.529937
iter  70 value 84.356450
iter  80 value 83.509666
iter  90 value 82.075894
iter 100 value 81.861177
final  value 81.861177 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.163879 
iter  10 value 94.887237
iter  20 value 94.070706
iter  30 value 88.256015
iter  40 value 86.017591
iter  50 value 84.366338
iter  60 value 84.118730
iter  70 value 84.111592
iter  80 value 83.405347
iter  90 value 81.994898
iter 100 value 81.682127
final  value 81.682127 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.823387 
iter  10 value 94.010648
iter  20 value 92.738949
iter  30 value 86.636177
iter  40 value 86.314906
iter  50 value 86.240729
iter  60 value 86.183159
iter  70 value 84.289053
iter  80 value 81.338312
iter  90 value 80.084982
iter 100 value 80.062324
final  value 80.062324 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.268294 
iter  10 value 94.156296
iter  20 value 92.520343
iter  30 value 86.378733
iter  40 value 86.047751
iter  50 value 84.918421
iter  60 value 84.640180
iter  70 value 81.945141
iter  80 value 81.209121
iter  90 value 80.935102
iter 100 value 80.845808
final  value 80.845808 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.592419 
iter  10 value 93.488658
iter  20 value 85.874765
iter  30 value 84.434076
iter  40 value 83.636507
iter  50 value 83.466337
iter  60 value 83.255118
iter  70 value 83.205158
iter  80 value 83.160314
iter  90 value 83.070805
iter 100 value 82.183429
final  value 82.183429 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 116.040182 
iter  10 value 94.059009
iter  20 value 94.051483
iter  30 value 88.863097
iter  40 value 82.691188
iter  50 value 82.413685
iter  60 value 82.024646
iter  70 value 80.549658
iter  80 value 80.004324
iter  90 value 79.919540
iter 100 value 79.551701
final  value 79.551701 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 127.212273 
iter  10 value 94.196802
iter  20 value 93.357329
iter  30 value 85.076233
iter  40 value 84.610376
iter  50 value 81.829845
iter  60 value 81.369203
iter  70 value 81.098328
iter  80 value 80.813579
iter  90 value 80.397109
iter 100 value 79.828129
final  value 79.828129 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 112.104312 
iter  10 value 93.921664
iter  20 value 90.469082
iter  30 value 88.204696
iter  40 value 85.517762
iter  50 value 83.424299
iter  60 value 83.129120
iter  70 value 82.970212
iter  80 value 82.535991
iter  90 value 80.507158
iter 100 value 80.046279
final  value 80.046279 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.897847 
iter  10 value 94.473221
iter  20 value 93.142942
iter  30 value 87.645089
iter  40 value 81.512637
iter  50 value 81.275554
iter  60 value 81.213747
iter  70 value 80.881342
iter  80 value 80.729759
iter  90 value 80.618051
iter 100 value 80.019079
final  value 80.019079 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.493521 
iter  10 value 94.070963
iter  20 value 88.751224
iter  30 value 86.745205
iter  40 value 85.397648
iter  50 value 83.982018
iter  60 value 82.143922
iter  70 value 81.606624
iter  80 value 81.318380
iter  90 value 81.290310
iter 100 value 81.068182
final  value 81.068182 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.265828 
final  value 94.054581 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.209555 
final  value 94.054518 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.782908 
final  value 94.054515 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.462162 
final  value 94.051750 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.087389 
iter  10 value 94.054537
iter  20 value 94.052698
iter  30 value 93.037095
iter  40 value 87.628739
iter  50 value 87.624779
iter  60 value 87.573701
iter  70 value 86.796988
iter  80 value 85.932807
iter  90 value 85.911784
iter 100 value 85.910445
final  value 85.910445 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 101.653440 
iter  10 value 94.058262
final  value 94.052936 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.322821 
iter  10 value 94.058399
iter  20 value 93.966642
iter  30 value 90.591151
iter  40 value 80.939435
iter  50 value 80.928476
iter  60 value 79.871324
iter  70 value 79.801196
iter  80 value 79.713592
iter  90 value 79.162896
iter 100 value 78.256897
final  value 78.256897 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.660483 
iter  10 value 94.057839
iter  20 value 94.029857
iter  30 value 89.002920
iter  40 value 88.662608
iter  50 value 88.390190
iter  60 value 87.984076
iter  70 value 87.974004
iter  80 value 87.088756
iter  90 value 81.355642
iter 100 value 79.843669
final  value 79.843669 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.318520 
iter  10 value 94.055752
iter  20 value 94.049562
final  value 94.033212 
converged
Fitting Repeat 5 

# weights:  305
initial  value 112.042743 
iter  10 value 94.057182
iter  20 value 93.914537
iter  30 value 85.906394
iter  40 value 84.814070
iter  50 value 80.930284
iter  60 value 80.017551
iter  70 value 79.807948
iter  80 value 79.768750
iter  90 value 79.725935
iter 100 value 79.706709
final  value 79.706709 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 100.844693 
iter  10 value 93.057342
iter  20 value 92.756731
iter  30 value 92.756164
iter  40 value 92.752212
iter  50 value 92.733436
iter  60 value 91.752128
iter  70 value 83.875514
iter  80 value 80.688326
iter  90 value 79.526370
iter 100 value 79.435693
final  value 79.435693 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.011805 
iter  10 value 92.876533
iter  20 value 89.503563
iter  30 value 89.481936
final  value 89.481477 
converged
Fitting Repeat 3 

# weights:  507
initial  value 115.608060 
iter  10 value 94.041547
iter  20 value 94.033733
iter  30 value 91.562493
iter  40 value 87.606550
iter  50 value 87.605525
iter  60 value 85.587734
iter  70 value 84.611985
iter  80 value 81.194254
iter  90 value 80.018394
iter 100 value 80.011324
final  value 80.011324 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 119.646282 
iter  10 value 94.101031
iter  20 value 94.091004
iter  30 value 94.078729
iter  40 value 87.813081
iter  50 value 82.304712
iter  60 value 82.153535
iter  70 value 81.868728
iter  80 value 81.847483
iter  90 value 81.771707
iter 100 value 81.631516
final  value 81.631516 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 96.456448 
iter  10 value 94.041050
iter  20 value 94.013014
final  value 94.011791 
converged
Fitting Repeat 1 

# weights:  103
initial  value 113.438568 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.595098 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.973806 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 112.714330 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.442107 
final  value 94.323810 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.597273 
iter  10 value 93.773031
final  value 93.772973 
converged
Fitting Repeat 2 

# weights:  305
initial  value 112.174865 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.895443 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.425594 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.256543 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.531463 
iter  10 value 92.749332
iter  20 value 87.355273
iter  30 value 85.743846
iter  40 value 85.311051
iter  40 value 85.311050
iter  40 value 85.311050
final  value 85.311050 
converged
Fitting Repeat 2 

# weights:  507
initial  value 119.302588 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 121.101484 
final  value 93.935238 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.769330 
iter  10 value 89.451443
iter  20 value 83.874514
final  value 83.874396 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.981675 
iter  10 value 93.772978
final  value 93.772973 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.696553 
iter  10 value 93.431907
iter  20 value 93.295730
iter  30 value 93.158310
iter  40 value 88.899449
iter  50 value 87.838041
iter  60 value 86.215739
iter  70 value 84.781307
iter  80 value 84.658436
iter  90 value 84.577618
iter 100 value 84.557495
final  value 84.557495 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.881887 
iter  10 value 94.487227
iter  20 value 93.470533
iter  30 value 93.154820
iter  40 value 87.181268
iter  50 value 83.316035
iter  60 value 80.966658
iter  70 value 79.857796
final  value 79.849947 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.838158 
iter  10 value 94.488299
iter  20 value 93.969198
iter  30 value 85.739259
iter  40 value 82.941841
iter  50 value 82.537088
iter  60 value 82.499544
iter  70 value 82.478416
final  value 82.463687 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.731518 
iter  10 value 94.488564
iter  20 value 93.441224
iter  30 value 93.176794
iter  40 value 90.302847
iter  50 value 83.829759
iter  60 value 82.840121
iter  70 value 82.581348
iter  80 value 82.208376
iter  90 value 81.865150
iter 100 value 80.358654
final  value 80.358654 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 99.038661 
iter  10 value 94.196500
iter  20 value 93.392354
iter  30 value 93.032963
iter  40 value 86.592281
iter  50 value 85.870565
iter  60 value 83.587768
iter  70 value 82.772378
iter  80 value 82.639099
iter  90 value 82.406300
iter 100 value 82.373874
final  value 82.373874 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 102.686631 
iter  10 value 91.487331
iter  20 value 87.219611
iter  30 value 85.917340
iter  40 value 82.939584
iter  50 value 82.498710
iter  60 value 81.692712
iter  70 value 79.893551
iter  80 value 79.135543
iter  90 value 78.684865
iter 100 value 78.603733
final  value 78.603733 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.599128 
iter  10 value 94.419188
iter  20 value 93.387936
iter  30 value 90.461676
iter  40 value 86.672444
iter  50 value 83.793227
iter  60 value 82.845845
iter  70 value 79.939990
iter  80 value 78.781686
iter  90 value 78.491111
iter 100 value 78.460071
final  value 78.460071 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 107.423548 
iter  10 value 93.614958
iter  20 value 92.019603
iter  30 value 83.415260
iter  40 value 82.832124
iter  50 value 82.344305
iter  60 value 82.277735
iter  70 value 81.796052
iter  80 value 81.670833
iter  90 value 81.545381
iter 100 value 81.172493
final  value 81.172493 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.479052 
iter  10 value 94.503419
iter  20 value 93.725532
iter  30 value 93.189256
iter  40 value 93.102169
iter  50 value 85.603597
iter  60 value 83.990811
iter  70 value 83.211925
iter  80 value 82.396171
iter  90 value 81.620809
iter 100 value 81.047275
final  value 81.047275 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.748511 
iter  10 value 93.533276
iter  20 value 87.588890
iter  30 value 84.703092
iter  40 value 83.787588
iter  50 value 82.836815
iter  60 value 82.595655
iter  70 value 82.482436
iter  80 value 80.205009
iter  90 value 78.854710
iter 100 value 78.577812
final  value 78.577812 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 128.210247 
iter  10 value 94.962293
iter  20 value 93.314544
iter  30 value 86.754499
iter  40 value 86.578408
iter  50 value 85.045631
iter  60 value 81.774741
iter  70 value 80.314257
iter  80 value 79.831966
iter  90 value 78.944112
iter 100 value 78.599908
final  value 78.599908 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 123.740338 
iter  10 value 94.608412
iter  20 value 86.328062
iter  30 value 83.692764
iter  40 value 82.361475
iter  50 value 81.034414
iter  60 value 80.159356
iter  70 value 79.627811
iter  80 value 79.366527
iter  90 value 79.326023
iter 100 value 79.175876
final  value 79.175876 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.909117 
iter  10 value 93.485711
iter  20 value 86.166692
iter  30 value 83.377715
iter  40 value 81.533424
iter  50 value 81.161745
iter  60 value 79.742784
iter  70 value 78.893589
iter  80 value 78.454321
iter  90 value 78.346197
iter 100 value 78.288463
final  value 78.288463 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.709213 
iter  10 value 93.091361
iter  20 value 85.029883
iter  30 value 82.213167
iter  40 value 80.623169
iter  50 value 80.128979
iter  60 value 79.717201
iter  70 value 79.641286
iter  80 value 79.230399
iter  90 value 78.971633
iter 100 value 78.589546
final  value 78.589546 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 112.959894 
iter  10 value 94.259092
iter  20 value 88.243050
iter  30 value 85.124222
iter  40 value 83.797205
iter  50 value 83.289019
iter  60 value 81.903229
iter  70 value 81.263477
iter  80 value 80.748605
iter  90 value 80.124592
iter 100 value 79.898287
final  value 79.898287 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 110.622379 
final  value 94.485813 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.597917 
final  value 94.485817 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.857976 
final  value 94.485941 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.890887 
final  value 94.486035 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.978305 
final  value 94.485961 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.399146 
iter  10 value 94.489343
iter  20 value 94.484224
iter  30 value 93.948065
final  value 93.294488 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.280160 
iter  10 value 93.305156
iter  20 value 91.972069
iter  30 value 89.489418
iter  40 value 89.103431
iter  50 value 89.101256
iter  60 value 89.085001
final  value 89.070371 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.892471 
iter  10 value 89.997447
iter  20 value 89.917084
iter  30 value 89.829171
iter  40 value 89.642153
iter  50 value 89.641398
iter  60 value 85.913999
iter  70 value 82.979959
iter  80 value 82.486921
iter  90 value 81.089845
iter 100 value 81.053608
final  value 81.053608 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 96.146312 
iter  10 value 94.488676
iter  20 value 93.103505
iter  30 value 91.311714
iter  40 value 86.073474
iter  50 value 84.083709
iter  60 value 82.588028
iter  70 value 81.926766
iter  80 value 80.280757
iter  90 value 80.267990
iter 100 value 80.263837
final  value 80.263837 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.856781 
iter  10 value 93.777999
iter  20 value 93.773627
final  value 93.773347 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.597672 
iter  10 value 93.820377
iter  20 value 93.780956
iter  30 value 93.750108
iter  40 value 92.923585
iter  50 value 92.489790
iter  60 value 89.764490
iter  70 value 86.947474
iter  80 value 82.402274
final  value 82.333533 
converged
Fitting Repeat 2 

# weights:  507
initial  value 94.506524 
final  value 94.492334 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.076968 
iter  10 value 93.052292
iter  20 value 93.030484
iter  30 value 93.026005
iter  40 value 93.025676
iter  50 value 92.954224
iter  60 value 92.826295
iter  70 value 92.825353
final  value 92.825167 
converged
Fitting Repeat 4 

# weights:  507
initial  value 119.221133 
iter  10 value 91.749634
iter  20 value 91.659843
iter  30 value 89.728364
iter  40 value 89.536822
iter  50 value 89.263654
iter  60 value 88.764317
iter  70 value 88.720331
iter  80 value 86.619454
iter  90 value 82.923354
iter 100 value 78.930531
final  value 78.930531 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 130.347330 
iter  10 value 92.799883
iter  20 value 83.331613
iter  30 value 83.290254
iter  40 value 83.101529
iter  50 value 81.859159
iter  60 value 81.616866
iter  70 value 81.596636
iter  80 value 81.436269
iter  90 value 81.088535
final  value 81.077008 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.482432 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.681379 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.103313 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.870936 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.365018 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.873432 
iter  10 value 86.027859
iter  20 value 84.863488
final  value 84.863483 
converged
Fitting Repeat 2 

# weights:  305
initial  value 111.702418 
iter  10 value 94.484211
iter  10 value 94.484211
iter  10 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.067900 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.949638 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 114.800555 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.936741 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.569025 
iter  10 value 94.110661
final  value 94.104010 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.030890 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  507
initial  value 124.841863 
iter  10 value 94.466823
iter  10 value 94.466823
iter  10 value 94.466823
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.444999 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.502810 
iter  10 value 93.733521
iter  20 value 86.873680
iter  30 value 86.175851
iter  40 value 84.665432
iter  50 value 83.471248
iter  60 value 82.938215
iter  70 value 82.655896
iter  80 value 82.162174
iter  90 value 81.843699
iter 100 value 81.800211
final  value 81.800211 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 102.775841 
iter  10 value 94.538826
iter  20 value 94.155074
iter  30 value 85.263078
iter  40 value 84.587099
iter  50 value 83.803894
iter  60 value 82.848683
iter  70 value 82.536077
iter  80 value 82.525328
iter  90 value 82.519895
iter 100 value 82.150464
final  value 82.150464 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.628826 
iter  10 value 91.840251
iter  20 value 87.567700
iter  30 value 86.657943
iter  40 value 85.693259
iter  50 value 84.763549
final  value 84.753323 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.418780 
iter  10 value 94.478672
iter  20 value 93.168171
iter  30 value 87.827346
iter  40 value 85.097258
iter  50 value 84.593672
iter  60 value 83.795221
iter  70 value 83.668224
iter  80 value 83.614745
iter  90 value 82.474587
iter 100 value 82.082921
final  value 82.082921 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 100.102974 
iter  10 value 94.384661
iter  20 value 92.661626
iter  30 value 92.603551
iter  40 value 92.595264
iter  50 value 88.199122
iter  60 value 86.132228
iter  70 value 84.535841
iter  80 value 84.116220
iter  90 value 83.474304
iter 100 value 82.427964
final  value 82.427964 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 105.745271 
iter  10 value 94.944783
iter  20 value 94.811672
iter  30 value 92.510046
iter  40 value 87.849918
iter  50 value 87.452285
iter  60 value 86.457092
iter  70 value 83.389281
iter  80 value 82.775992
iter  90 value 82.479518
iter 100 value 82.291595
final  value 82.291595 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.400427 
iter  10 value 94.339293
iter  20 value 92.474895
iter  30 value 92.385098
iter  40 value 90.102705
iter  50 value 87.842916
iter  60 value 86.018763
iter  70 value 83.963082
iter  80 value 83.385926
iter  90 value 82.790736
iter 100 value 82.627213
final  value 82.627213 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 125.411651 
iter  10 value 94.547138
iter  20 value 90.037910
iter  30 value 87.267304
iter  40 value 83.400192
iter  50 value 82.840259
iter  60 value 81.911784
iter  70 value 81.076219
iter  80 value 80.970438
iter  90 value 80.816358
iter 100 value 80.792306
final  value 80.792306 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.998882 
iter  10 value 94.490729
iter  20 value 87.576985
iter  30 value 84.680840
iter  40 value 83.807027
iter  50 value 83.148885
iter  60 value 82.393805
iter  70 value 82.147966
iter  80 value 81.958534
iter  90 value 81.823128
iter 100 value 81.010226
final  value 81.010226 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.686279 
iter  10 value 94.621829
iter  20 value 89.249958
iter  30 value 83.833827
iter  40 value 82.373235
iter  50 value 81.609938
iter  60 value 81.188168
iter  70 value 80.997927
iter  80 value 80.751489
iter  90 value 80.683032
iter 100 value 80.644049
final  value 80.644049 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 117.005020 
iter  10 value 94.445913
iter  20 value 88.319088
iter  30 value 85.780340
iter  40 value 82.318553
iter  50 value 80.944157
iter  60 value 80.547288
iter  70 value 80.374065
iter  80 value 80.154537
iter  90 value 80.129407
iter 100 value 80.109944
final  value 80.109944 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.974837 
iter  10 value 93.489096
iter  20 value 91.257757
iter  30 value 86.455401
iter  40 value 81.897893
iter  50 value 80.940735
iter  60 value 80.409661
iter  70 value 80.167029
iter  80 value 79.906534
iter  90 value 79.875256
iter 100 value 79.864527
final  value 79.864527 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.726096 
iter  10 value 96.669259
iter  20 value 87.371445
iter  30 value 84.435735
iter  40 value 82.328111
iter  50 value 82.121580
iter  60 value 81.979586
iter  70 value 81.719467
iter  80 value 81.026369
iter  90 value 80.889249
iter 100 value 80.715715
final  value 80.715715 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.284033 
iter  10 value 94.661889
iter  20 value 93.632565
iter  30 value 88.149894
iter  40 value 86.396112
iter  50 value 85.475809
iter  60 value 82.916899
iter  70 value 81.843682
iter  80 value 81.192676
iter  90 value 80.497860
iter 100 value 80.244466
final  value 80.244466 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.049224 
iter  10 value 94.501296
iter  20 value 89.378721
iter  30 value 85.259156
iter  40 value 84.743723
iter  50 value 84.340279
iter  60 value 83.776662
iter  70 value 82.838875
iter  80 value 82.648095
iter  90 value 82.209613
iter 100 value 80.862649
final  value 80.862649 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.675765 
iter  10 value 94.486127
iter  20 value 94.439701
iter  30 value 90.032671
final  value 88.675360 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.893829 
iter  10 value 94.485878
final  value 94.484219 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.382805 
final  value 94.485849 
converged
Fitting Repeat 4 

# weights:  103
initial  value 112.397002 
final  value 94.485807 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.679100 
final  value 94.485975 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.341839 
iter  10 value 94.485828
iter  20 value 91.604625
iter  30 value 91.230499
iter  40 value 91.230085
iter  50 value 90.963290
iter  60 value 90.915010
iter  70 value 90.905837
iter  80 value 89.760061
iter  90 value 86.616235
iter 100 value 86.573036
final  value 86.573036 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.212664 
iter  10 value 94.489298
iter  20 value 94.265634
iter  30 value 94.253340
final  value 94.253288 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.994969 
iter  10 value 94.119298
iter  20 value 94.115123
final  value 94.115117 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.171173 
iter  10 value 94.488440
iter  20 value 94.460880
iter  30 value 94.265779
iter  40 value 94.205529
iter  50 value 88.345337
iter  60 value 86.761265
iter  70 value 86.735262
final  value 86.734915 
converged
Fitting Repeat 5 

# weights:  305
initial  value 116.205871 
iter  10 value 94.471582
iter  20 value 94.247108
iter  30 value 91.955802
iter  40 value 91.935711
final  value 91.933995 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.249264 
iter  10 value 94.474791
iter  20 value 94.463911
iter  30 value 94.097016
iter  40 value 88.634857
iter  50 value 84.912977
iter  60 value 84.904323
iter  70 value 82.838596
iter  80 value 82.510904
iter  90 value 82.507295
iter 100 value 82.506698
final  value 82.506698 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 95.636000 
iter  10 value 94.491721
iter  20 value 94.457938
iter  30 value 93.058066
iter  40 value 87.594494
iter  50 value 87.454666
iter  60 value 87.453161
iter  70 value 87.406560
iter  80 value 87.391515
iter  90 value 87.388832
iter 100 value 87.388204
final  value 87.388204 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 99.297072 
iter  10 value 91.559288
iter  20 value 87.408649
iter  30 value 87.405040
final  value 87.404595 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.199091 
iter  10 value 94.154143
iter  20 value 87.872947
iter  30 value 86.876189
iter  40 value 86.844689
iter  50 value 86.843541
iter  60 value 86.842913
final  value 86.840095 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.115591 
iter  10 value 93.333345
iter  20 value 88.406168
iter  30 value 87.084664
iter  40 value 85.549320
iter  50 value 84.546455
iter  60 value 84.382421
iter  70 value 84.244606
iter  80 value 84.244088
iter  90 value 84.239198
iter 100 value 84.194970
final  value 84.194970 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.652463 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.846577 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.775891 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.515614 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.943222 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.872908 
final  value 93.244970 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.486957 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.592880 
final  value 93.836066 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.929897 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.162253 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.085656 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.185314 
final  value 94.032967 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.550532 
final  value 94.032967 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.969496 
final  value 94.032967 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.665309 
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.043195 
iter  10 value 94.058124
iter  20 value 90.738386
iter  30 value 86.501964
iter  40 value 85.781078
iter  50 value 85.506062
iter  60 value 85.112855
iter  70 value 84.897447
final  value 84.897185 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.090695 
iter  10 value 92.817074
iter  20 value 85.400900
iter  30 value 85.061541
iter  40 value 84.837713
final  value 84.813493 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.162050 
iter  10 value 94.155665
iter  20 value 93.964463
iter  30 value 86.635415
iter  40 value 85.998899
iter  50 value 84.933261
iter  60 value 84.929921
iter  70 value 84.858789
iter  80 value 84.813495
final  value 84.813493 
converged
Fitting Repeat 4 

# weights:  103
initial  value 113.067707 
iter  10 value 94.056292
iter  20 value 93.483850
iter  30 value 86.151354
iter  40 value 85.805564
iter  50 value 85.680748
iter  60 value 85.032830
iter  70 value 84.814213
final  value 84.813493 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.658410 
iter  10 value 94.085551
iter  20 value 86.805529
iter  30 value 85.986880
iter  40 value 85.230049
iter  50 value 85.005652
iter  60 value 84.905223
iter  70 value 84.813768
final  value 84.813494 
converged
Fitting Repeat 1 

# weights:  305
initial  value 122.409753 
iter  10 value 98.866288
iter  20 value 94.148631
iter  30 value 91.507630
iter  40 value 85.730567
iter  50 value 83.570867
iter  60 value 82.882979
iter  70 value 82.375402
iter  80 value 82.156173
iter  90 value 81.917088
iter 100 value 81.594169
final  value 81.594169 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.899054 
iter  10 value 91.788241
iter  20 value 87.728265
iter  30 value 87.641039
iter  40 value 87.395798
iter  50 value 85.648454
iter  60 value 84.858615
iter  70 value 84.689091
iter  80 value 84.625233
iter  90 value 84.585380
iter 100 value 84.501885
final  value 84.501885 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 116.991100 
iter  10 value 94.318520
iter  20 value 89.635534
iter  30 value 87.731216
iter  40 value 84.852828
iter  50 value 83.799615
iter  60 value 83.596155
iter  70 value 83.547073
iter  80 value 82.944457
iter  90 value 81.994517
iter 100 value 81.789949
final  value 81.789949 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.816270 
iter  10 value 90.709552
iter  20 value 87.038993
iter  30 value 85.632212
iter  40 value 84.566355
iter  50 value 84.477114
iter  60 value 83.709901
iter  70 value 82.588358
iter  80 value 82.309947
iter  90 value 81.906686
iter 100 value 81.581894
final  value 81.581894 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 152.840240 
iter  10 value 93.474712
iter  20 value 85.409588
iter  30 value 85.280781
iter  40 value 85.018606
iter  50 value 84.923872
iter  60 value 84.769737
iter  70 value 84.603364
iter  80 value 84.095828
iter  90 value 83.100040
iter 100 value 81.869200
final  value 81.869200 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 113.947388 
iter  10 value 94.090909
iter  20 value 92.291391
iter  30 value 91.808474
iter  40 value 91.401806
iter  50 value 91.169687
iter  60 value 90.612202
iter  70 value 88.169450
iter  80 value 85.746253
iter  90 value 83.239023
iter 100 value 82.658347
final  value 82.658347 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.809718 
iter  10 value 93.716887
iter  20 value 87.555234
iter  30 value 86.194263
iter  40 value 85.092489
iter  50 value 83.270410
iter  60 value 83.142688
iter  70 value 82.621387
iter  80 value 81.915453
iter  90 value 81.739467
iter 100 value 81.461272
final  value 81.461272 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 121.648057 
iter  10 value 94.351990
iter  20 value 94.071702
iter  30 value 93.484863
iter  40 value 91.800113
iter  50 value 90.119642
iter  60 value 86.086253
iter  70 value 84.047564
iter  80 value 82.744144
iter  90 value 82.255932
iter 100 value 82.086156
final  value 82.086156 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.956948 
iter  10 value 93.317602
iter  20 value 89.072370
iter  30 value 84.497241
iter  40 value 83.136255
iter  50 value 82.703395
iter  60 value 82.589483
iter  70 value 82.442466
iter  80 value 81.962255
iter  90 value 81.594338
iter 100 value 81.432739
final  value 81.432739 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.590508 
iter  10 value 95.847675
iter  20 value 85.459661
iter  30 value 84.584189
iter  40 value 82.706095
iter  50 value 82.314412
iter  60 value 81.813983
iter  70 value 81.532480
iter  80 value 81.441156
iter  90 value 81.374105
iter 100 value 81.351639
final  value 81.351639 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.907414 
final  value 94.055013 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.705115 
final  value 94.054381 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.974277 
iter  10 value 94.054776
iter  20 value 94.052932
final  value 94.052919 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.897815 
iter  10 value 94.054668
final  value 94.033551 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.059348 
iter  10 value 93.290710
iter  20 value 93.289525
iter  30 value 84.781529
iter  40 value 84.250283
iter  50 value 84.218597
iter  60 value 84.193133
iter  70 value 84.186501
iter  80 value 84.164814
iter  90 value 84.116381
final  value 84.116053 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.756126 
iter  10 value 94.057883
iter  20 value 93.775065
iter  30 value 85.603753
iter  40 value 85.504315
iter  50 value 85.446088
iter  60 value 85.434585
iter  70 value 85.297228
iter  80 value 83.765642
iter  90 value 83.470858
final  value 83.467355 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.358708 
iter  10 value 94.037244
iter  20 value 94.035316
iter  30 value 94.034612
iter  40 value 93.928319
iter  50 value 93.644897
iter  60 value 89.175847
iter  70 value 88.923289
iter  80 value 88.470302
iter  90 value 88.119352
iter 100 value 87.650547
final  value 87.650547 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 112.931152 
iter  10 value 93.294128
iter  20 value 88.574844
iter  30 value 85.154920
iter  40 value 84.105968
iter  50 value 83.914523
iter  60 value 83.785352
iter  70 value 83.784587
final  value 83.784030 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.711201 
iter  10 value 94.038584
iter  20 value 94.037418
iter  30 value 94.033934
iter  30 value 94.033934
iter  30 value 94.033934
final  value 94.033934 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.098957 
iter  10 value 94.057389
iter  20 value 93.997652
iter  30 value 91.967078
iter  40 value 91.914031
iter  50 value 91.913577
final  value 91.913561 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.781809 
iter  10 value 94.041615
iter  20 value 94.033942
final  value 94.033639 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.470872 
iter  10 value 94.041596
iter  20 value 93.818545
iter  30 value 86.351756
iter  40 value 84.608864
iter  50 value 83.429189
iter  60 value 83.353149
iter  70 value 83.350956
iter  80 value 82.253485
iter  90 value 82.153722
iter 100 value 81.831058
final  value 81.831058 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 97.626031 
iter  10 value 94.060653
iter  20 value 94.021957
iter  30 value 91.806724
iter  40 value 86.799918
iter  50 value 86.795618
iter  60 value 85.540451
final  value 85.199781 
converged
Fitting Repeat 4 

# weights:  507
initial  value 112.119846 
iter  10 value 93.935459
iter  20 value 87.284061
iter  30 value 87.254617
iter  40 value 87.248966
iter  50 value 87.246740
iter  60 value 87.138431
iter  70 value 86.844910
iter  70 value 86.844909
iter  70 value 86.844909
final  value 86.844909 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.213689 
iter  10 value 92.768486
iter  20 value 91.582178
iter  30 value 91.581080
iter  40 value 88.595271
iter  50 value 87.883846
iter  60 value 86.378519
iter  70 value 83.332532
iter  80 value 80.915491
iter  90 value 80.515032
iter 100 value 80.510717
final  value 80.510717 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 138.257947 
iter  10 value 112.623355
iter  20 value 109.966082
iter  30 value 105.567045
iter  40 value 104.817499
iter  50 value 104.095883
iter  60 value 102.091157
iter  70 value 101.681371
iter  80 value 101.582999
iter  90 value 101.540990
iter 100 value 101.408412
final  value 101.408412 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 147.185559 
iter  10 value 116.893234
iter  20 value 109.656973
iter  30 value 108.712405
iter  40 value 105.320119
iter  50 value 103.453842
iter  60 value 103.266186
iter  70 value 103.102218
iter  80 value 102.706879
iter  90 value 102.021007
iter 100 value 100.918762
final  value 100.918762 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 133.107083 
iter  10 value 120.450303
iter  20 value 117.088461
iter  30 value 109.788424
iter  40 value 107.803381
iter  50 value 105.829017
iter  60 value 104.793878
iter  70 value 103.699777
iter  80 value 102.893936
iter  90 value 102.709901
iter 100 value 102.623079
final  value 102.623079 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 169.612593 
iter  10 value 118.338456
iter  20 value 117.854405
iter  30 value 111.840729
iter  40 value 109.982217
iter  50 value 106.963705
iter  60 value 103.338646
iter  70 value 101.680088
iter  80 value 101.478999
iter  90 value 101.432455
iter 100 value 101.288630
final  value 101.288630 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 148.516493 
iter  10 value 118.222192
iter  20 value 116.649922
iter  30 value 110.269716
iter  40 value 106.370234
iter  50 value 105.677775
iter  60 value 105.507413
iter  70 value 104.434438
iter  80 value 103.875357
iter  90 value 103.740066
iter 100 value 103.654628
final  value 103.654628 
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 -- Mon Aug  5 23:29:20 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 
 49.744   1.200  50.754