##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.24-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.24-bioc/R/site-library --timings HPiP_1.19.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.24-bioc/meat/HPiP.Rcheck’
* using R version 4.6.0 RC (2026-04-17 r89917)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
    GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
* running under: Ubuntu 24.04.4 LTS
* using session charset: UTF-8
* current time: 2026-05-15 04:50:10 UTC
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.19.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... INFO
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
FSmethod      34.830  0.509  36.468
var_imp       34.150  0.482  34.661
corr_plot     33.966  0.441  34.491
pred_ensembel 13.103  0.156  12.002
enrichfindP    0.531  0.031  17.364
* 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: 2 NOTEs
See
  ‘/home/biocbuild/bbs-3.24-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.24-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.24-bioc/R/site-library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.19.0’
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R version 4.6.0 RC (2026-04-17 r89917) -- "Because it was There"
Copyright (C) 2026 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
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 108.045045 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.481407 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.256822 
iter  10 value 88.176692
iter  20 value 86.987188
final  value 86.986792 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.217113 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.454787 
final  value 93.915746 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.892062 
final  value 93.915746 
converged
Fitting Repeat 2 

# weights:  305
initial  value 109.194645 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.175443 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 91.760693 
iter  10 value 87.894637
iter  20 value 87.877354
final  value 87.877316 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.761696 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.752563 
iter  10 value 93.628236
iter  20 value 93.025432
final  value 93.025205 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.174387 
final  value 93.697143 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.882375 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.093698 
iter  10 value 89.298567
iter  20 value 86.837878
iter  30 value 86.773584
final  value 86.771499 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.302213 
iter  10 value 92.773080
iter  20 value 92.312061
iter  30 value 92.286815
final  value 92.286652 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.551181 
iter  10 value 94.055356
iter  20 value 93.800943
iter  30 value 91.068725
iter  40 value 85.877017
iter  50 value 85.390768
iter  60 value 85.192367
iter  70 value 84.801270
iter  80 value 84.282994
iter  90 value 83.297042
iter 100 value 83.023848
final  value 83.023848 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 100.536784 
iter  10 value 93.291503
iter  20 value 91.791090
iter  30 value 91.244840
iter  40 value 91.064651
final  value 91.064162 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.025956 
iter  10 value 93.702000
iter  20 value 87.226506
iter  30 value 85.644364
iter  40 value 84.639160
iter  50 value 82.096457
iter  60 value 81.834312
iter  70 value 81.833078
final  value 81.833075 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.513699 
iter  10 value 94.026390
iter  20 value 92.112697
iter  30 value 84.352780
iter  40 value 82.379428
iter  50 value 81.636180
iter  60 value 80.258209
iter  70 value 80.146455
iter  80 value 80.069408
final  value 80.069404 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.143554 
iter  10 value 93.793826
iter  20 value 93.641373
iter  30 value 92.669713
iter  40 value 89.294336
iter  50 value 86.249008
iter  60 value 85.482402
iter  70 value 83.521184
iter  80 value 83.158966
iter  90 value 82.999933
final  value 82.999856 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.961575 
iter  10 value 93.837717
iter  20 value 92.114762
iter  30 value 90.272711
iter  40 value 89.520095
iter  50 value 89.364561
iter  60 value 86.980556
iter  70 value 81.874686
iter  80 value 81.494950
iter  90 value 80.706328
iter 100 value 80.326053
final  value 80.326053 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 111.318475 
iter  10 value 93.970878
iter  20 value 87.708324
iter  30 value 84.266643
iter  40 value 83.230655
iter  50 value 81.917709
iter  60 value 80.028627
iter  70 value 79.535846
iter  80 value 79.493095
iter  90 value 79.160556
iter 100 value 78.772817
final  value 78.772817 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 120.110851 
iter  10 value 94.059865
iter  20 value 86.990227
iter  30 value 83.708945
iter  40 value 82.548360
iter  50 value 82.190491
iter  60 value 80.535258
iter  70 value 80.309105
iter  80 value 80.041610
iter  90 value 79.992898
iter 100 value 79.548991
final  value 79.548991 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.754436 
iter  10 value 94.440907
iter  20 value 91.877566
iter  30 value 90.453943
iter  40 value 89.391047
iter  50 value 83.061612
iter  60 value 81.318887
iter  70 value 80.731463
iter  80 value 79.977961
iter  90 value 79.829060
iter 100 value 79.695118
final  value 79.695118 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 115.375305 
iter  10 value 92.044531
iter  20 value 89.532362
iter  30 value 89.453728
iter  40 value 89.151528
iter  50 value 88.281347
iter  60 value 81.415178
iter  70 value 80.256353
iter  80 value 79.692088
iter  90 value 78.839119
iter 100 value 78.681424
final  value 78.681424 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.349271 
iter  10 value 94.071302
iter  20 value 84.639735
iter  30 value 83.030776
iter  40 value 81.380010
iter  50 value 81.151550
iter  60 value 80.894363
iter  70 value 79.581515
iter  80 value 79.306565
iter  90 value 78.470232
iter 100 value 78.188229
final  value 78.188229 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.025626 
iter  10 value 93.988101
iter  20 value 83.549634
iter  30 value 83.120862
iter  40 value 80.910616
iter  50 value 79.677306
iter  60 value 79.014298
iter  70 value 78.706448
iter  80 value 78.327283
iter  90 value 78.230359
iter 100 value 78.210143
final  value 78.210143 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 123.262792 
iter  10 value 94.103169
iter  20 value 93.778985
iter  30 value 89.179019
iter  40 value 83.975932
iter  50 value 82.014767
iter  60 value 81.891465
iter  70 value 81.555822
iter  80 value 79.826149
iter  90 value 79.354074
iter 100 value 78.914085
final  value 78.914085 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 136.196639 
iter  10 value 93.735191
iter  20 value 88.280901
iter  30 value 86.977852
iter  40 value 83.789093
iter  50 value 81.236813
iter  60 value 80.349264
iter  70 value 80.062488
iter  80 value 79.660172
iter  90 value 79.409877
iter 100 value 78.772380
final  value 78.772380 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.993830 
iter  10 value 95.190783
iter  20 value 85.550987
iter  30 value 84.807273
iter  40 value 82.347524
iter  50 value 81.813748
iter  60 value 80.001297
iter  70 value 79.357533
iter  80 value 79.220550
iter  90 value 79.104262
iter 100 value 78.984992
final  value 78.984992 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.210949 
final  value 94.054712 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.635672 
final  value 94.054638 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.148331 
final  value 94.054616 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.252198 
final  value 94.054659 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.814258 
final  value 94.054515 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.545862 
iter  10 value 94.057591
iter  20 value 93.266792
iter  30 value 83.692675
iter  40 value 83.682810
iter  50 value 83.644911
iter  60 value 83.642401
final  value 83.641918 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.345223 
iter  10 value 93.518013
iter  20 value 93.497029
iter  30 value 92.042370
iter  40 value 91.739348
iter  50 value 91.737360
iter  60 value 91.735154
final  value 91.735153 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.246290 
iter  10 value 83.677975
iter  20 value 83.676125
iter  30 value 83.596273
iter  40 value 83.596148
iter  50 value 83.593899
final  value 83.593795 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.760660 
iter  10 value 94.057574
iter  20 value 92.617052
iter  30 value 85.837347
iter  40 value 84.066049
iter  50 value 84.015676
iter  60 value 83.997972
iter  70 value 83.992904
iter  80 value 83.991636
iter  90 value 83.834642
iter 100 value 83.393251
final  value 83.393251 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 95.513913 
iter  10 value 94.056738
iter  20 value 93.982414
iter  30 value 93.635601
iter  40 value 93.634123
final  value 93.633822 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.376264 
iter  10 value 93.923466
iter  20 value 93.620444
iter  30 value 89.697738
iter  40 value 88.556631
final  value 88.542438 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.548896 
iter  10 value 94.061405
iter  20 value 93.955923
iter  30 value 90.086994
iter  40 value 84.661133
iter  50 value 82.717763
iter  60 value 82.677786
iter  70 value 82.641954
iter  80 value 82.511177
iter  90 value 82.483646
final  value 82.483489 
converged
Fitting Repeat 3 

# weights:  507
initial  value 112.242056 
iter  10 value 93.923954
iter  20 value 93.737897
iter  30 value 93.672842
iter  40 value 93.624892
iter  50 value 93.622553
iter  60 value 93.622432
iter  70 value 93.622050
final  value 93.622030 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.264150 
iter  10 value 93.693800
iter  20 value 93.689023
iter  30 value 88.413589
iter  40 value 80.737039
iter  50 value 80.403449
iter  60 value 80.363539
final  value 80.363247 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.172533 
iter  10 value 94.060648
iter  20 value 94.052948
iter  30 value 84.187074
iter  40 value 83.676900
iter  50 value 83.644548
iter  60 value 83.637248
final  value 83.634215 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.042161 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.692040 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.904588 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.952429 
final  value 94.483810 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.741058 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.444157 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.935441 
iter  10 value 94.494577
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.871211 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.759930 
final  value 94.379747 
converged
Fitting Repeat 5 

# weights:  305
initial  value 112.714138 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.169438 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 110.473481 
iter  10 value 85.863926
iter  20 value 85.648789
iter  30 value 85.647282
final  value 85.647280 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.963868 
final  value 94.473118 
converged
Fitting Repeat 4 

# weights:  507
initial  value 130.435226 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 110.210693 
final  value 94.473118 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.069849 
iter  10 value 94.495292
iter  20 value 93.783475
iter  30 value 87.193151
iter  40 value 85.246297
iter  50 value 84.834087
iter  60 value 83.570488
iter  70 value 83.131916
iter  80 value 83.116780
iter  90 value 83.108989
final  value 83.108910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.548350 
iter  10 value 95.560011
iter  20 value 94.487570
iter  30 value 87.097950
iter  40 value 84.222415
iter  50 value 82.975131
iter  60 value 82.784077
iter  70 value 82.710324
iter  80 value 82.656682
final  value 82.656666 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.336797 
iter  10 value 94.503254
iter  20 value 94.483537
iter  30 value 93.369112
iter  40 value 93.266551
iter  50 value 90.339154
iter  60 value 86.047676
iter  70 value 85.770028
iter  80 value 84.715626
iter  90 value 84.427711
iter 100 value 84.369327
final  value 84.369327 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 101.738139 
iter  10 value 94.488002
iter  20 value 89.380525
iter  30 value 85.649796
iter  40 value 84.618455
iter  50 value 82.767584
iter  60 value 81.644060
iter  70 value 81.418373
final  value 81.417555 
converged
Fitting Repeat 5 

# weights:  103
initial  value 116.216530 
iter  10 value 94.416807
iter  20 value 87.357285
iter  30 value 85.366346
iter  40 value 84.858519
iter  50 value 84.370614
iter  60 value 84.235249
iter  70 value 83.978467
iter  80 value 83.932481
final  value 83.909762 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.193254 
iter  10 value 92.307049
iter  20 value 83.691227
iter  30 value 83.495588
iter  40 value 83.023085
iter  50 value 82.818742
iter  60 value 82.062682
iter  70 value 81.898402
iter  80 value 81.748449
iter  90 value 81.586201
iter 100 value 80.906265
final  value 80.906265 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.078612 
iter  10 value 94.607574
iter  20 value 93.864870
iter  30 value 89.501355
iter  40 value 89.032142
iter  50 value 88.608255
iter  60 value 88.344829
iter  70 value 86.594584
iter  80 value 85.609915
iter  90 value 82.715596
iter 100 value 81.580243
final  value 81.580243 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.125034 
iter  10 value 94.538373
iter  20 value 94.462507
iter  30 value 88.789945
iter  40 value 84.934024
iter  50 value 83.600176
iter  60 value 83.096409
iter  70 value 82.874503
iter  80 value 82.717936
iter  90 value 81.478091
iter 100 value 80.427409
final  value 80.427409 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.021996 
iter  10 value 94.476520
iter  20 value 91.312234
iter  30 value 87.507700
iter  40 value 86.950212
iter  50 value 84.838241
iter  60 value 84.091577
iter  70 value 83.803603
iter  80 value 83.572430
iter  90 value 83.195816
iter 100 value 82.958938
final  value 82.958938 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 119.451613 
iter  10 value 94.482558
iter  20 value 92.554306
iter  30 value 86.695626
iter  40 value 86.091221
iter  50 value 85.896004
iter  60 value 85.340875
iter  70 value 83.865038
iter  80 value 82.453058
iter  90 value 80.960370
iter 100 value 80.322074
final  value 80.322074 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.190716 
iter  10 value 94.732499
iter  20 value 93.503248
iter  30 value 91.815249
iter  40 value 91.655020
iter  50 value 91.373576
final  value 91.346792 
converged
Fitting Repeat 2 

# weights:  507
initial  value 122.352301 
iter  10 value 87.504701
iter  20 value 84.571230
iter  30 value 83.311164
iter  40 value 83.194952
iter  50 value 82.228015
iter  60 value 81.692211
iter  70 value 80.850531
iter  80 value 80.550070
iter  90 value 80.459215
iter 100 value 80.385600
final  value 80.385600 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 129.912297 
iter  10 value 95.064461
iter  20 value 94.056181
iter  30 value 88.342198
iter  40 value 85.504947
iter  50 value 85.164634
iter  60 value 82.289966
iter  70 value 81.839430
iter  80 value 81.339373
iter  90 value 80.823492
iter 100 value 80.522195
final  value 80.522195 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.627412 
iter  10 value 94.498253
iter  20 value 93.269968
iter  30 value 87.856909
iter  40 value 85.179486
iter  50 value 83.814079
iter  60 value 81.705943
iter  70 value 81.410512
iter  80 value 81.118070
iter  90 value 80.857871
iter 100 value 80.529988
final  value 80.529988 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.414259 
iter  10 value 94.332902
iter  20 value 87.096507
iter  30 value 83.418615
iter  40 value 82.751774
iter  50 value 82.269924
iter  60 value 82.147180
iter  70 value 82.128231
iter  80 value 81.969063
iter  90 value 81.691682
iter 100 value 80.146724
final  value 80.146724 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.671660 
final  value 94.485873 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.197893 
iter  10 value 94.485750
iter  20 value 94.461850
iter  30 value 94.141670
iter  40 value 94.134468
iter  40 value 94.134467
final  value 94.134368 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.373202 
final  value 94.474774 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.374259 
final  value 94.485946 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.727100 
iter  10 value 94.485769
iter  20 value 94.484214
iter  30 value 90.212282
iter  40 value 86.690414
iter  50 value 86.502089
iter  60 value 86.501535
iter  70 value 84.524398
iter  80 value 83.071828
iter  90 value 83.033328
iter 100 value 82.496175
final  value 82.496175 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 95.230685 
iter  10 value 94.488831
iter  20 value 94.484228
final  value 94.484218 
converged
Fitting Repeat 2 

# weights:  305
initial  value 122.209326 
iter  10 value 94.478179
iter  20 value 94.476784
iter  30 value 94.473352
final  value 94.473141 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.387398 
iter  10 value 94.489154
iter  20 value 94.483426
final  value 94.473279 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.035272 
iter  10 value 94.119368
iter  20 value 94.118352
iter  30 value 94.117177
iter  40 value 94.113901
iter  50 value 94.112717
iter  60 value 94.110882
iter  70 value 94.093361
final  value 94.092683 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.098668 
iter  10 value 94.488588
iter  20 value 94.478328
iter  30 value 91.001623
iter  40 value 82.907631
final  value 82.627742 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.255753 
iter  10 value 86.378099
iter  20 value 85.578700
iter  30 value 85.575813
iter  40 value 85.572998
iter  50 value 85.506778
iter  60 value 84.877075
iter  70 value 81.578526
iter  80 value 81.102915
iter  90 value 80.261628
iter 100 value 79.699757
final  value 79.699757 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 96.713086 
iter  10 value 93.805321
iter  20 value 92.148604
iter  30 value 88.000571
iter  40 value 87.948566
iter  50 value 87.944322
iter  60 value 86.656672
iter  70 value 85.028977
iter  80 value 84.471476
iter  90 value 84.360381
iter 100 value 84.356466
final  value 84.356466 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 95.900378 
iter  10 value 94.488406
iter  20 value 88.209054
iter  30 value 87.318251
iter  40 value 87.126469
iter  50 value 86.594869
iter  60 value 85.626198
iter  70 value 85.559805
iter  80 value 84.250503
iter  90 value 84.206901
iter 100 value 84.186184
final  value 84.186184 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 100.251341 
iter  10 value 94.490974
iter  20 value 94.487458
iter  30 value 94.479701
iter  40 value 94.475488
iter  50 value 93.736903
iter  60 value 93.703427
iter  70 value 93.685823
final  value 93.684912 
converged
Fitting Repeat 5 

# weights:  507
initial  value 111.908476 
iter  10 value 92.227706
iter  20 value 92.225682
final  value 92.225423 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.711665 
iter  10 value 88.859197
iter  20 value 86.105476
iter  30 value 85.518478
final  value 85.518070 
converged
Fitting Repeat 2 

# weights:  103
initial  value 114.239943 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.462002 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 113.516192 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.220141 
iter  10 value 94.200478
final  value 94.067633 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.261859 
final  value 94.266667 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.415811 
final  value 94.275354 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.975908 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.876396 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 114.521661 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.360076 
iter  10 value 94.275363
iter  10 value 94.275363
iter  10 value 94.275363
final  value 94.275363 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.253135 
iter  10 value 90.923461
iter  20 value 83.749252
iter  30 value 82.170194
final  value 82.167808 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.735015 
final  value 94.275362 
converged
Fitting Repeat 4 

# weights:  507
initial  value 111.144605 
iter  10 value 93.688566
iter  20 value 88.825627
iter  30 value 88.655352
final  value 88.655283 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.465715 
iter  10 value 94.268814
iter  20 value 94.230468
iter  30 value 94.229818
iter  30 value 94.229818
iter  30 value 94.229818
final  value 94.229818 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.708776 
iter  10 value 93.990158
iter  20 value 90.772251
iter  30 value 89.689943
iter  40 value 88.042875
iter  50 value 87.594706
iter  60 value 86.036567
iter  70 value 85.742723
iter  80 value 85.442509
iter  90 value 85.280149
final  value 85.278773 
converged
Fitting Repeat 2 

# weights:  103
initial  value 111.465745 
iter  10 value 94.432660
iter  20 value 89.293523
iter  30 value 88.478867
iter  40 value 87.561197
iter  50 value 86.035582
iter  60 value 85.657314
iter  70 value 85.440270
iter  80 value 85.400164
final  value 85.397711 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.018999 
iter  10 value 94.478745
iter  20 value 93.907172
iter  30 value 90.937000
iter  40 value 87.002138
iter  50 value 86.645945
iter  60 value 86.556415
iter  70 value 86.516590
iter  80 value 86.360947
iter  90 value 84.865982
final  value 84.865461 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.848003 
iter  10 value 94.493643
iter  20 value 87.546246
iter  30 value 86.529252
iter  40 value 86.040773
iter  50 value 85.017187
iter  60 value 84.419370
iter  70 value 83.910728
iter  80 value 83.696035
iter  90 value 83.675249
iter  90 value 83.675249
iter  90 value 83.675249
final  value 83.675249 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.349181 
iter  10 value 94.483128
iter  20 value 90.511374
iter  30 value 88.184849
iter  40 value 87.933345
iter  50 value 85.597570
iter  60 value 84.932383
iter  70 value 84.865927
iter  80 value 84.865498
final  value 84.865494 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.294493 
iter  10 value 94.487679
iter  20 value 94.230406
iter  30 value 89.509446
iter  40 value 87.755751
iter  50 value 84.033887
iter  60 value 83.833133
iter  70 value 81.876805
iter  80 value 81.195102
iter  90 value 80.981901
iter 100 value 80.908112
final  value 80.908112 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.985006 
iter  10 value 93.279260
iter  20 value 93.000577
iter  30 value 92.283031
iter  40 value 86.384229
iter  50 value 84.222234
iter  60 value 83.213851
iter  70 value 82.746790
iter  80 value 81.895174
iter  90 value 81.325577
iter 100 value 80.835139
final  value 80.835139 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 107.246202 
iter  10 value 94.494003
iter  20 value 94.330974
iter  30 value 91.923549
iter  40 value 88.738393
iter  50 value 84.903683
iter  60 value 83.072991
iter  70 value 82.701661
iter  80 value 81.996766
iter  90 value 81.909068
iter 100 value 81.533602
final  value 81.533602 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 114.712200 
iter  10 value 95.123357
iter  20 value 94.495495
iter  30 value 94.330345
iter  40 value 87.786112
iter  50 value 87.542508
iter  60 value 87.013186
iter  70 value 85.144871
iter  80 value 83.155848
iter  90 value 82.372024
iter 100 value 82.017450
final  value 82.017450 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.844099 
iter  10 value 94.503318
iter  20 value 94.351269
iter  30 value 92.589654
iter  40 value 89.923888
iter  50 value 85.344716
iter  60 value 83.526710
iter  70 value 82.138942
iter  80 value 81.682879
iter  90 value 81.575921
iter 100 value 81.528047
final  value 81.528047 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.758300 
iter  10 value 94.595588
iter  20 value 93.457356
iter  30 value 84.510576
iter  40 value 83.283538
iter  50 value 83.086820
iter  60 value 82.383288
iter  70 value 81.645204
iter  80 value 81.233448
iter  90 value 80.767201
iter 100 value 80.453842
final  value 80.453842 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.287280 
iter  10 value 95.347849
iter  20 value 91.272857
iter  30 value 86.450968
iter  40 value 85.434990
iter  50 value 85.077260
iter  60 value 84.576131
iter  70 value 84.495895
iter  80 value 84.134565
iter  90 value 82.329851
iter 100 value 81.933367
final  value 81.933367 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.376992 
iter  10 value 94.039498
iter  20 value 85.783715
iter  30 value 84.459853
iter  40 value 81.706299
iter  50 value 80.625024
iter  60 value 80.462235
iter  70 value 80.274486
iter  80 value 80.000645
iter  90 value 79.869550
iter 100 value 79.855280
final  value 79.855280 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 120.778677 
iter  10 value 94.340337
iter  20 value 88.376776
iter  30 value 87.093434
iter  40 value 85.605421
iter  50 value 84.349309
iter  60 value 81.714947
iter  70 value 81.341526
iter  80 value 80.494610
iter  90 value 80.303744
iter 100 value 80.214470
final  value 80.214470 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.421674 
iter  10 value 94.439370
iter  20 value 93.066599
iter  30 value 92.325145
iter  40 value 87.426010
iter  50 value 84.556147
iter  60 value 83.379287
iter  70 value 83.086567
iter  80 value 82.483012
iter  90 value 81.823503
iter 100 value 81.663834
final  value 81.663834 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.298472 
final  value 94.485495 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.371990 
final  value 94.485929 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.286087 
final  value 94.485863 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.564072 
final  value 94.485900 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.191136 
iter  10 value 94.485925
iter  20 value 92.991213
iter  30 value 87.194203
iter  40 value 85.807352
iter  50 value 84.732938
final  value 84.732396 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.212604 
iter  10 value 94.489145
iter  20 value 94.484214
iter  30 value 90.592572
iter  40 value 87.617133
final  value 87.613060 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.449202 
iter  10 value 94.280089
iter  20 value 94.275624
iter  30 value 88.294104
iter  40 value 86.879325
final  value 86.879092 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.686426 
iter  10 value 94.489088
iter  20 value 94.484368
final  value 94.484216 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.067312 
iter  10 value 94.488344
iter  20 value 94.479487
final  value 94.396705 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.234734 
iter  10 value 94.488282
iter  20 value 87.763534
iter  30 value 85.026262
iter  40 value 84.632765
iter  50 value 84.628089
iter  60 value 84.622143
iter  60 value 84.622143
final  value 84.622143 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.096987 
iter  10 value 92.309048
iter  20 value 92.146241
iter  30 value 92.140495
iter  40 value 92.125266
iter  50 value 92.120132
iter  60 value 92.120057
final  value 92.119863 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.651733 
iter  10 value 94.021247
iter  20 value 93.825665
iter  30 value 93.820329
iter  40 value 91.824876
iter  50 value 85.341618
iter  60 value 84.780192
iter  70 value 84.011987
iter  80 value 83.935315
iter  90 value 83.915738
iter 100 value 83.912362
final  value 83.912362 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.330028 
iter  10 value 94.436172
iter  20 value 94.357998
iter  30 value 89.095069
iter  40 value 88.027976
iter  50 value 87.703670
iter  60 value 86.552710
iter  70 value 86.480575
iter  80 value 86.479078
iter  90 value 86.478885
final  value 86.478764 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.336207 
iter  10 value 94.490477
iter  20 value 94.484388
iter  30 value 94.155964
iter  40 value 84.815730
iter  50 value 84.477883
iter  60 value 84.473891
iter  70 value 84.083958
iter  80 value 83.990003
final  value 83.989998 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.548502 
iter  10 value 94.491835
iter  20 value 94.412279
iter  30 value 89.384407
iter  40 value 88.513911
iter  50 value 88.511910
final  value 88.511528 
converged
Fitting Repeat 1 

# weights:  103
initial  value 108.472835 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.589743 
final  value 94.476190 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.766277 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.922989 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.232351 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.980452 
final  value 94.275362 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.575913 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.359502 
iter  10 value 94.264858
iter  10 value 94.264858
iter  10 value 94.264858
final  value 94.264858 
converged
Fitting Repeat 4 

# weights:  305
initial  value 114.913709 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.816517 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.401944 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.425320 
final  value 94.275362 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.102792 
final  value 94.275362 
converged
Fitting Repeat 4 

# weights:  507
initial  value 115.269503 
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.123773 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.010490 
iter  10 value 94.488542
iter  20 value 88.874771
iter  30 value 84.718325
iter  40 value 84.043558
iter  50 value 83.794480
iter  60 value 83.171401
iter  70 value 82.907611
iter  80 value 82.871209
final  value 82.870845 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.941097 
iter  10 value 94.549777
iter  20 value 92.946427
iter  30 value 91.799541
iter  40 value 85.281912
iter  50 value 84.341915
iter  60 value 84.197633
iter  70 value 83.749788
iter  80 value 82.946465
iter  90 value 82.876838
iter 100 value 82.870845
final  value 82.870845 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 107.128505 
iter  10 value 94.354396
iter  20 value 93.137053
iter  30 value 90.507793
iter  40 value 86.822128
iter  50 value 85.965118
iter  60 value 85.778904
final  value 85.778200 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.928761 
iter  10 value 94.485136
iter  20 value 94.254986
iter  30 value 94.216854
iter  40 value 89.966995
iter  50 value 87.509651
iter  60 value 86.454030
iter  70 value 85.802040
iter  80 value 85.778879
iter  90 value 85.776078
iter  90 value 85.776077
iter  90 value 85.776077
final  value 85.776077 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.970648 
iter  10 value 94.488606
iter  20 value 89.613799
iter  30 value 88.282242
iter  40 value 86.384123
iter  50 value 85.552188
iter  60 value 83.766120
iter  70 value 82.955385
iter  80 value 82.631328
iter  90 value 82.591550
final  value 82.591153 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.188501 
iter  10 value 94.642550
iter  20 value 92.066620
iter  30 value 87.428217
iter  40 value 85.679286
iter  50 value 84.536985
iter  60 value 84.268487
iter  70 value 84.097086
iter  80 value 83.379940
iter  90 value 82.401806
iter 100 value 82.173918
final  value 82.173918 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.707759 
iter  10 value 94.431817
iter  20 value 86.691510
iter  30 value 85.763294
iter  40 value 84.467874
iter  50 value 83.086996
iter  60 value 82.138633
iter  70 value 81.568908
iter  80 value 81.493340
iter  90 value 81.459985
iter 100 value 81.455157
final  value 81.455157 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.725050 
iter  10 value 94.497477
iter  20 value 90.117434
iter  30 value 89.375260
iter  40 value 88.337938
iter  50 value 88.117832
final  value 88.113997 
converged
Fitting Repeat 4 

# weights:  305
initial  value 111.810023 
iter  10 value 94.526999
iter  20 value 89.939716
iter  30 value 87.394551
iter  40 value 86.612381
iter  50 value 86.088377
iter  60 value 84.520066
iter  70 value 82.900912
iter  80 value 82.469954
iter  90 value 82.252480
iter 100 value 82.068709
final  value 82.068709 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.867420 
iter  10 value 94.582225
iter  20 value 91.535157
iter  30 value 87.414654
iter  40 value 86.326113
iter  50 value 84.735286
iter  60 value 83.431780
iter  70 value 82.868401
iter  80 value 82.746104
iter  90 value 82.702558
iter 100 value 82.588965
final  value 82.588965 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 113.505840 
iter  10 value 94.458099
iter  20 value 91.807654
iter  30 value 91.308167
iter  40 value 88.672091
iter  50 value 85.466051
iter  60 value 84.747448
iter  70 value 83.464279
iter  80 value 83.103773
iter  90 value 83.074718
iter 100 value 82.712772
final  value 82.712772 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.697602 
iter  10 value 97.315215
iter  20 value 93.170543
iter  30 value 88.306007
iter  40 value 84.449457
iter  50 value 83.902353
iter  60 value 82.372660
iter  70 value 82.013039
iter  80 value 81.919555
iter  90 value 81.847383
iter 100 value 81.832903
final  value 81.832903 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 142.804851 
iter  10 value 95.558396
iter  20 value 93.065776
iter  30 value 85.882228
iter  40 value 84.829838
iter  50 value 84.605938
iter  60 value 84.047791
iter  70 value 83.461798
iter  80 value 81.922808
iter  90 value 81.658054
iter 100 value 81.510348
final  value 81.510348 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 130.398090 
iter  10 value 94.329144
iter  20 value 89.285675
iter  30 value 84.172158
iter  40 value 83.656994
iter  50 value 83.230339
iter  60 value 82.892331
iter  70 value 82.811072
iter  80 value 82.708547
iter  90 value 82.454273
iter 100 value 82.390710
final  value 82.390710 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 119.809743 
iter  10 value 95.032238
iter  20 value 88.846745
iter  30 value 85.140968
iter  40 value 83.844759
iter  50 value 83.204776
iter  60 value 82.396899
iter  70 value 82.034271
iter  80 value 81.885496
iter  90 value 81.604016
iter 100 value 81.496756
final  value 81.496756 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.624646 
final  value 94.485875 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.431428 
final  value 94.485716 
converged
Fitting Repeat 3 

# weights:  103
initial  value 108.820633 
final  value 94.485545 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.628177 
final  value 94.486042 
converged
Fitting Repeat 5 

# weights:  103
initial  value 107.599382 
final  value 94.485651 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.345216 
iter  10 value 94.489142
iter  20 value 94.297723
iter  30 value 91.623374
iter  40 value 91.529551
iter  50 value 90.531219
iter  60 value 90.527439
iter  70 value 90.526414
iter  80 value 90.526175
iter  90 value 90.524797
final  value 90.524112 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.512920 
iter  10 value 94.488563
iter  20 value 94.484226
final  value 94.484221 
converged
Fitting Repeat 3 

# weights:  305
initial  value 115.696724 
iter  10 value 94.489426
iter  20 value 94.422194
iter  30 value 94.278361
iter  40 value 94.275424
iter  50 value 89.690662
iter  60 value 88.010140
iter  70 value 86.481915
iter  80 value 86.395421
iter  90 value 83.165211
iter 100 value 82.891278
final  value 82.891278 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.406214 
iter  10 value 94.270092
iter  20 value 94.210465
iter  30 value 89.153553
iter  40 value 89.146577
iter  50 value 89.144882
iter  60 value 86.492851
iter  70 value 86.230125
final  value 86.228832 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.401254 
iter  10 value 94.489717
iter  20 value 94.479138
iter  30 value 86.368877
iter  40 value 85.463279
final  value 85.462746 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.039566 
iter  10 value 94.491518
iter  20 value 94.463659
iter  30 value 86.640580
final  value 86.639271 
converged
Fitting Repeat 2 

# weights:  507
initial  value 112.908451 
iter  10 value 94.492225
iter  20 value 94.437869
iter  30 value 94.433375
iter  40 value 94.391739
iter  50 value 94.387469
iter  60 value 94.200551
final  value 94.183086 
converged
Fitting Repeat 3 

# weights:  507
initial  value 127.759205 
iter  10 value 94.283922
iter  20 value 94.240880
iter  30 value 86.887251
iter  40 value 86.632877
iter  50 value 86.008776
iter  60 value 85.826469
iter  70 value 85.823877
iter  80 value 85.758986
iter  90 value 85.753678
final  value 85.753506 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.921664 
iter  10 value 94.491132
iter  20 value 94.405326
iter  30 value 84.404654
iter  40 value 83.648202
iter  50 value 83.641406
iter  60 value 83.641177
iter  70 value 83.199168
iter  80 value 82.746007
iter  90 value 82.385538
iter 100 value 81.141136
final  value 81.141136 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 97.046406 
iter  10 value 94.491157
iter  20 value 93.185330
iter  30 value 86.624782
iter  40 value 86.242139
iter  50 value 86.228558
iter  60 value 85.605552
iter  70 value 85.017872
iter  80 value 84.697687
iter  90 value 84.694582
iter 100 value 84.690654
final  value 84.690654 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.456963 
final  value 94.032967 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.747187 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.877321 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.742270 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.789548 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.558038 
iter  10 value 93.420463
iter  20 value 93.224260
iter  30 value 93.156057
final  value 93.155651 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.974420 
final  value 94.032967 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.154678 
iter  10 value 91.114791
iter  20 value 85.303692
iter  30 value 85.250030
iter  40 value 85.208210
iter  50 value 85.185284
final  value 85.185261 
converged
Fitting Repeat 4 

# weights:  305
initial  value 114.312940 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.162448 
final  value 94.052916 
converged
Fitting Repeat 1 

# weights:  507
initial  value 118.174347 
iter  10 value 93.899641
iter  20 value 93.860354
iter  30 value 92.846869
iter  40 value 83.911079
iter  50 value 81.607069
iter  60 value 81.521348
iter  70 value 81.519525
iter  70 value 81.519524
final  value 81.519524 
converged
Fitting Repeat 2 

# weights:  507
initial  value 111.923349 
iter  10 value 94.004476
final  value 93.991525 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.095670 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 125.349761 
iter  10 value 84.056023
iter  20 value 83.701563
iter  30 value 83.674850
iter  40 value 83.294140
iter  50 value 83.238778
final  value 83.238766 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.899748 
iter  10 value 87.092293
iter  20 value 86.474964
iter  30 value 86.471269
final  value 86.471250 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.103006 
iter  10 value 94.064979
iter  20 value 86.217198
iter  30 value 84.660125
iter  40 value 82.759570
iter  50 value 82.172670
iter  60 value 82.069267
iter  70 value 81.246535
iter  80 value 79.790295
iter  90 value 79.740290
iter 100 value 79.726744
final  value 79.726744 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.653079 
iter  10 value 94.085588
iter  20 value 89.262827
iter  30 value 86.138026
iter  40 value 85.254741
iter  50 value 84.647036
iter  60 value 84.122808
iter  70 value 83.997949
final  value 83.997820 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.348858 
iter  10 value 93.834789
iter  20 value 84.159239
iter  30 value 83.706715
iter  40 value 82.247737
iter  50 value 81.665790
iter  60 value 81.525129
iter  70 value 81.416553
iter  80 value 80.984570
iter  90 value 79.221914
final  value 79.220683 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.116558 
iter  10 value 93.760319
iter  20 value 84.444684
iter  30 value 82.811968
iter  40 value 82.526352
iter  50 value 81.262088
iter  60 value 80.759745
iter  70 value 80.400878
iter  80 value 79.589819
final  value 79.587286 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.875998 
iter  10 value 94.025163
iter  20 value 93.493169
iter  30 value 92.931094
iter  40 value 86.989760
iter  50 value 84.494407
iter  60 value 83.583451
iter  70 value 82.824086
iter  80 value 81.868101
iter  90 value 81.549599
iter 100 value 81.261678
final  value 81.261678 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 102.890729 
iter  10 value 94.467551
iter  20 value 94.004113
iter  30 value 91.915056
iter  40 value 90.449882
iter  50 value 88.403687
iter  60 value 82.841275
iter  70 value 82.754838
iter  80 value 82.618250
iter  90 value 80.367547
iter 100 value 79.089078
final  value 79.089078 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.399827 
iter  10 value 90.056862
iter  20 value 85.982972
iter  30 value 85.232412
iter  40 value 81.438172
iter  50 value 80.368707
iter  60 value 80.086389
iter  70 value 79.947851
iter  80 value 79.305610
iter  90 value 77.935889
iter 100 value 77.504407
final  value 77.504407 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.557411 
iter  10 value 94.052917
iter  20 value 93.439517
iter  30 value 93.320343
iter  40 value 87.390148
iter  50 value 80.872546
iter  60 value 79.360005
iter  70 value 78.033183
iter  80 value 77.794449
iter  90 value 77.733390
iter 100 value 77.710311
final  value 77.710311 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 125.935486 
iter  10 value 93.743995
iter  20 value 90.517443
iter  30 value 90.077727
iter  40 value 86.529076
iter  50 value 84.377555
iter  60 value 83.862528
iter  70 value 82.499507
iter  80 value 80.433242
iter  90 value 79.388627
iter 100 value 79.283383
final  value 79.283383 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.453166 
iter  10 value 86.373313
iter  20 value 84.265946
iter  30 value 83.771850
iter  40 value 83.402712
iter  50 value 81.021018
iter  60 value 80.396943
iter  70 value 79.880526
iter  80 value 79.689223
iter  90 value 79.384726
iter 100 value 78.961748
final  value 78.961748 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 150.096355 
iter  10 value 94.516393
iter  20 value 88.219019
iter  30 value 86.070551
iter  40 value 82.410111
iter  50 value 81.978679
iter  60 value 79.975355
iter  70 value 78.362284
iter  80 value 78.159590
iter  90 value 77.741823
iter 100 value 77.652837
final  value 77.652837 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 127.892569 
iter  10 value 94.120316
iter  20 value 91.567210
iter  30 value 91.182358
iter  40 value 91.086779
iter  50 value 90.975062
iter  60 value 84.646694
iter  70 value 81.890334
iter  80 value 81.744904
iter  90 value 79.872456
iter 100 value 79.119756
final  value 79.119756 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.300543 
iter  10 value 94.426334
iter  20 value 86.527408
iter  30 value 85.091207
iter  40 value 82.923431
iter  50 value 80.852651
iter  60 value 79.967344
iter  70 value 79.898033
iter  80 value 79.849409
iter  90 value 79.529933
iter 100 value 77.910693
final  value 77.910693 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.003995 
iter  10 value 94.501549
iter  20 value 93.873024
iter  30 value 83.109691
iter  40 value 81.357452
iter  50 value 80.097242
iter  60 value 79.350970
iter  70 value 79.092733
iter  80 value 77.935813
iter  90 value 77.377213
iter 100 value 77.175868
final  value 77.175868 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 116.329140 
iter  10 value 94.530751
iter  20 value 87.055393
iter  30 value 85.015504
iter  40 value 82.818991
iter  50 value 79.668461
iter  60 value 78.592561
iter  70 value 78.261861
iter  80 value 78.099982
iter  90 value 77.967206
iter 100 value 77.928052
final  value 77.928052 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.647011 
final  value 93.917386 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.027264 
iter  10 value 94.054760
final  value 94.052912 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.227385 
final  value 94.054645 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.472656 
iter  10 value 94.054514
iter  20 value 94.052975
final  value 94.052919 
converged
Fitting Repeat 5 

# weights:  103
initial  value 107.188717 
iter  10 value 93.917210
iter  20 value 93.916143
iter  30 value 93.367001
iter  40 value 83.777920
iter  50 value 83.365802
iter  60 value 83.095139
iter  70 value 83.059321
final  value 83.059308 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.348662 
iter  10 value 93.937007
iter  20 value 93.282128
iter  30 value 93.264659
iter  40 value 93.196705
iter  50 value 91.419386
iter  60 value 83.906287
iter  70 value 82.795871
iter  80 value 82.786464
iter  90 value 82.780583
iter 100 value 82.333306
final  value 82.333306 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 95.881066 
iter  10 value 94.057894
iter  20 value 94.052984
iter  30 value 93.704631
iter  40 value 89.561079
iter  50 value 89.541846
iter  60 value 89.538965
iter  70 value 86.031806
iter  80 value 82.998171
iter  90 value 82.609017
iter 100 value 82.600004
final  value 82.600004 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.316130 
iter  10 value 94.057712
iter  20 value 94.052968
iter  30 value 90.572000
iter  40 value 85.703572
iter  50 value 85.677010
final  value 85.676876 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.561205 
iter  10 value 94.057220
iter  20 value 84.046751
iter  30 value 83.601148
iter  40 value 83.529469
iter  50 value 80.995537
iter  60 value 79.924934
iter  70 value 79.839999
final  value 79.839961 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.780112 
iter  10 value 94.058235
iter  20 value 93.994168
iter  30 value 84.958362
iter  30 value 84.958361
iter  30 value 84.958361
final  value 84.958361 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.074827 
iter  10 value 93.354130
iter  20 value 93.349101
iter  30 value 93.256917
iter  40 value 93.256782
iter  50 value 93.092844
iter  60 value 88.898313
iter  70 value 81.244787
iter  80 value 80.656200
iter  90 value 80.649221
iter 100 value 80.647602
final  value 80.647602 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.950910 
iter  10 value 94.061009
iter  20 value 94.053147
iter  30 value 93.987576
final  value 93.916064 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.527302 
iter  10 value 93.321974
iter  20 value 93.222177
iter  30 value 91.634183
iter  40 value 83.011431
iter  50 value 80.692748
iter  60 value 80.691747
iter  70 value 80.445146
iter  80 value 79.968412
iter  90 value 79.807421
iter 100 value 79.806186
final  value 79.806186 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.529343 
iter  10 value 94.054137
iter  20 value 93.901193
iter  30 value 93.899026
iter  40 value 93.896170
iter  50 value 93.892243
iter  60 value 84.518072
iter  70 value 84.086725
iter  80 value 84.085861
iter  90 value 84.081023
iter 100 value 84.069496
final  value 84.069496 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.090222 
iter  10 value 94.059899
iter  20 value 94.006297
iter  30 value 93.373807
iter  40 value 91.452516
iter  50 value 82.963580
iter  60 value 81.637251
iter  70 value 80.839031
iter  80 value 80.516200
iter  90 value 80.480589
final  value 80.480525 
converged
Fitting Repeat 1 

# weights:  103
initial  value 120.512273 
iter  10 value 117.884121
iter  20 value 108.038527
iter  30 value 106.051590
iter  30 value 106.051589
final  value 106.051589 
converged
Fitting Repeat 2 

# weights:  103
initial  value 122.372411 
iter  10 value 117.894546
iter  20 value 115.759112
iter  30 value 110.976808
iter  40 value 109.464872
iter  50 value 109.247724
iter  60 value 108.056799
iter  70 value 106.031543
iter  80 value 105.947062
iter  90 value 105.799225
iter 100 value 105.290948
final  value 105.290948 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 121.564716 
iter  10 value 117.928579
iter  20 value 117.893674
iter  30 value 117.662618
iter  40 value 117.580602
iter  50 value 110.137479
iter  60 value 108.949910
iter  70 value 105.953847
iter  80 value 105.538027
iter  90 value 105.288991
iter 100 value 105.258365
final  value 105.258365 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 124.342076 
iter  10 value 117.894514
iter  20 value 112.037344
iter  30 value 107.461594
iter  40 value 105.620264
iter  50 value 105.275893
iter  60 value 104.825537
iter  70 value 104.767470
iter  80 value 103.817036
iter  90 value 102.609965
iter 100 value 102.515088
final  value 102.515088 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 129.570771 
iter  10 value 117.661794
iter  20 value 113.636368
iter  30 value 111.649851
iter  40 value 111.512151
iter  50 value 109.695196
iter  60 value 107.033157
iter  70 value 105.265126
iter  80 value 103.903322
iter  90 value 103.281840
iter 100 value 102.513567
final  value 102.513567 
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 -- Fri May 15 00:55:31 2026 
*********************************************** 
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 
 39.775   0.874  90.122