##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings HPiP_1.16.1.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.22-bioc/meat/HPiP.Rcheck’
* using R version 4.5.2 (2025-10-31)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
    GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
* running under: Ubuntu 24.04.3 LTS
* using session charset: UTF-8
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.16.1’
* 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
corr_plot     33.743  0.484  34.228
var_imp       33.023  0.722  33.746
FSmethod      33.180  0.513  33.696
pred_ensembel 12.776  0.217  11.719
enrichfindP    0.602  0.037  12.416
* 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-3.22-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.22-bioc/R/site-library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.16.1’
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

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

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

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

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

# weights:  103
initial  value 97.224860 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.689566 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 114.289374 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.617534 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 112.480028 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.827139 
final  value 94.038251 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.833008 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.187359 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.821652 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 121.244238 
final  value 93.473743 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.165755 
final  value 94.052907 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.186046 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.796192 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.642656 
iter  10 value 84.812023
iter  20 value 83.392662
iter  30 value 83.140256
iter  40 value 83.075957
final  value 83.075930 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.676158 
iter  10 value 93.471676
final  value 93.464368 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.112487 
iter  10 value 94.059199
iter  20 value 94.038935
iter  30 value 93.576743
iter  40 value 93.571779
iter  50 value 83.591517
iter  60 value 82.580654
iter  70 value 82.405291
iter  80 value 81.725388
iter  90 value 81.203328
iter 100 value 79.813308
final  value 79.813308 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 103.818154 
iter  10 value 92.529046
iter  20 value 84.456346
iter  30 value 82.694492
iter  40 value 80.875606
iter  50 value 79.741688
final  value 79.737851 
converged
Fitting Repeat 3 

# weights:  103
initial  value 112.878337 
iter  10 value 94.010672
iter  20 value 91.194281
iter  30 value 88.020705
iter  40 value 87.677561
iter  50 value 86.633338
iter  60 value 86.355405
iter  70 value 85.745569
iter  80 value 79.273291
iter  90 value 78.424609
iter 100 value 78.405256
final  value 78.405256 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.255792 
iter  10 value 94.054899
iter  20 value 93.660427
iter  30 value 93.466378
iter  40 value 92.713409
iter  50 value 84.153607
iter  60 value 83.136795
iter  70 value 82.011328
iter  80 value 81.798939
iter  90 value 81.505896
iter 100 value 81.393559
final  value 81.393559 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.633211 
iter  10 value 94.057454
iter  20 value 84.652743
iter  30 value 83.836127
iter  40 value 83.466828
iter  50 value 82.720481
iter  60 value 82.060471
final  value 82.060332 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.975299 
iter  10 value 94.297113
iter  20 value 92.391541
iter  30 value 90.125672
iter  40 value 89.937149
iter  50 value 84.489847
iter  60 value 81.777432
iter  70 value 78.830605
iter  80 value 78.275288
iter  90 value 77.840833
iter 100 value 77.504877
final  value 77.504877 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 109.277053 
iter  10 value 92.746994
iter  20 value 84.724858
iter  30 value 83.022576
iter  40 value 80.437246
iter  50 value 78.695720
iter  60 value 78.453166
iter  70 value 77.871956
iter  80 value 77.605427
iter  90 value 76.888176
iter 100 value 76.596585
final  value 76.596585 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.254333 
iter  10 value 94.063527
iter  20 value 80.659581
iter  30 value 80.033675
iter  40 value 79.900165
iter  50 value 79.722700
final  value 79.710721 
converged
Fitting Repeat 4 

# weights:  305
initial  value 112.913077 
iter  10 value 93.996477
iter  20 value 87.464727
iter  30 value 85.330867
iter  40 value 83.760319
iter  50 value 83.209012
iter  60 value 82.459137
iter  70 value 82.066080
iter  80 value 81.599340
iter  90 value 80.404849
iter 100 value 79.381380
final  value 79.381380 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.272818 
iter  10 value 94.023702
iter  20 value 89.717475
iter  30 value 85.177859
iter  40 value 83.296360
iter  50 value 82.766418
iter  60 value 82.031220
iter  70 value 81.294512
iter  80 value 80.816635
iter  90 value 80.310334
iter 100 value 79.845947
final  value 79.845947 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.941897 
iter  10 value 96.602926
iter  20 value 84.704422
iter  30 value 80.759884
iter  40 value 78.525211
iter  50 value 77.171156
iter  60 value 76.783210
iter  70 value 76.329516
iter  80 value 76.176555
iter  90 value 76.105357
iter 100 value 76.048888
final  value 76.048888 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.643904 
iter  10 value 94.159032
iter  20 value 90.165827
iter  30 value 85.263161
iter  40 value 82.479955
iter  50 value 78.699092
iter  60 value 78.151319
iter  70 value 77.685696
iter  80 value 77.391226
iter  90 value 77.375544
iter 100 value 77.342354
final  value 77.342354 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 119.061374 
iter  10 value 93.980876
iter  20 value 85.983137
iter  30 value 82.733568
iter  40 value 82.036660
iter  50 value 79.462197
iter  60 value 77.932436
iter  70 value 77.673250
iter  80 value 77.228059
iter  90 value 77.053137
iter 100 value 76.985475
final  value 76.985475 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.730258 
iter  10 value 98.428158
iter  20 value 88.875547
iter  30 value 83.568106
iter  40 value 81.583073
iter  50 value 80.822941
iter  60 value 80.374718
iter  70 value 79.882933
iter  80 value 78.321673
iter  90 value 78.053890
iter 100 value 78.011409
final  value 78.011409 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 140.812525 
iter  10 value 95.270645
iter  20 value 94.128282
iter  30 value 93.103358
iter  40 value 89.890218
iter  50 value 88.732532
iter  60 value 88.521372
iter  70 value 86.684971
iter  80 value 83.578202
iter  90 value 80.633063
iter 100 value 79.958028
final  value 79.958028 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.794757 
final  value 94.039897 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.849763 
iter  10 value 94.039795
final  value 94.039785 
converged
Fitting Repeat 3 

# weights:  103
initial  value 110.077055 
final  value 93.862040 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.292840 
final  value 94.054313 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.305481 
final  value 94.054620 
converged
Fitting Repeat 1 

# weights:  305
initial  value 114.501375 
iter  10 value 93.962616
iter  20 value 89.162280
iter  30 value 86.745549
iter  40 value 78.735776
iter  50 value 77.786169
iter  60 value 77.656777
iter  70 value 77.604673
final  value 77.601790 
converged
Fitting Repeat 2 

# weights:  305
initial  value 110.792484 
iter  10 value 94.057565
iter  20 value 93.951263
iter  30 value 90.632863
final  value 90.459215 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.600250 
iter  10 value 94.042876
iter  20 value 94.038290
iter  30 value 93.266003
iter  40 value 91.790384
iter  50 value 90.747653
iter  60 value 90.711509
final  value 90.711461 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.407882 
iter  10 value 94.042980
iter  20 value 94.038750
final  value 94.038732 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.793305 
iter  10 value 94.016354
iter  20 value 93.659632
iter  30 value 82.004378
final  value 82.002996 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.152555 
iter  10 value 94.046813
iter  20 value 94.038636
iter  30 value 90.808763
iter  40 value 81.953837
iter  50 value 79.550748
iter  60 value 77.171680
iter  70 value 77.119604
iter  80 value 77.118446
iter  90 value 77.118081
final  value 77.118045 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.746778 
iter  10 value 94.060930
iter  20 value 94.052416
iter  30 value 93.657843
iter  40 value 89.809469
iter  50 value 88.338662
iter  60 value 87.759295
iter  70 value 84.772358
iter  80 value 83.057720
iter  90 value 82.997392
final  value 82.992018 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.881900 
iter  10 value 90.920144
iter  20 value 83.037873
iter  30 value 82.343968
iter  40 value 82.174535
iter  50 value 82.169163
iter  60 value 81.267622
iter  70 value 80.352000
iter  80 value 79.962656
iter  90 value 79.962199
final  value 79.962197 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.357542 
iter  10 value 94.019938
iter  20 value 92.256814
iter  30 value 86.523440
iter  40 value 85.743158
iter  50 value 85.067761
iter  60 value 80.765647
iter  70 value 78.026051
iter  80 value 78.021068
iter  90 value 76.422657
iter 100 value 76.010822
final  value 76.010822 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 97.520734 
iter  10 value 93.144935
iter  20 value 92.831841
iter  30 value 92.830538
iter  40 value 91.974915
iter  50 value 91.604105
iter  60 value 91.601745
iter  70 value 87.733011
iter  80 value 81.120595
iter  90 value 80.885996
iter 100 value 80.879291
final  value 80.879291 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.613696 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.103671 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.280044 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 109.229129 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.086479 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.491854 
iter  10 value 94.390170
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  305
initial  value 115.876405 
iter  10 value 94.354397
final  value 94.354396 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.494533 
iter  10 value 94.323188
iter  20 value 94.322912
final  value 94.322898 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.167501 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.346444 
final  value 94.428839 
converged
Fitting Repeat 1 

# weights:  507
initial  value 129.971098 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 116.655889 
iter  10 value 94.231175
iter  20 value 93.022365
iter  30 value 92.593058
iter  40 value 92.591271
final  value 92.591269 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.622470 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.694100 
iter  10 value 94.358026
final  value 94.354391 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.316671 
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.735721 
iter  10 value 94.468185
iter  20 value 94.381905
iter  30 value 93.380083
iter  40 value 88.830737
iter  50 value 88.479573
iter  60 value 87.252965
iter  70 value 85.785346
iter  80 value 85.757426
iter  90 value 85.710499
iter 100 value 85.274664
final  value 85.274664 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 103.911504 
iter  10 value 94.486447
iter  20 value 89.422974
iter  30 value 86.611140
iter  40 value 86.437256
iter  50 value 86.084115
iter  60 value 84.799573
iter  70 value 84.321686
iter  80 value 83.725974
iter  90 value 83.532110
iter 100 value 83.530841
final  value 83.530841 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 104.622116 
iter  10 value 94.544971
iter  20 value 94.481794
iter  30 value 94.386164
iter  40 value 94.384652
iter  50 value 89.746950
iter  60 value 88.807973
iter  70 value 88.471068
iter  80 value 87.972392
iter  90 value 85.730402
iter 100 value 85.176915
final  value 85.176915 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 102.708398 
iter  10 value 94.493787
iter  20 value 93.663959
iter  30 value 92.975565
iter  40 value 92.896727
iter  50 value 92.822443
iter  60 value 92.605260
iter  70 value 92.171897
iter  80 value 89.052133
iter  90 value 87.981791
iter 100 value 86.522997
final  value 86.522997 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 114.971612 
iter  10 value 94.205289
iter  20 value 87.056350
iter  30 value 86.629254
iter  40 value 85.975220
iter  50 value 85.390427
iter  60 value 84.928143
iter  70 value 84.747698
iter  80 value 84.725199
final  value 84.725080 
converged
Fitting Repeat 1 

# weights:  305
initial  value 111.857669 
iter  10 value 94.405145
iter  20 value 92.945809
iter  30 value 92.006236
iter  40 value 87.342621
iter  50 value 85.588383
iter  60 value 85.210013
iter  70 value 84.984265
iter  80 value 84.285036
iter  90 value 83.807743
iter 100 value 83.216018
final  value 83.216018 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.824907 
iter  10 value 94.424469
iter  20 value 91.844388
iter  30 value 87.923797
iter  40 value 86.406455
iter  50 value 86.085829
iter  60 value 85.675365
iter  70 value 84.660838
iter  80 value 83.785539
iter  90 value 82.697259
iter 100 value 82.573972
final  value 82.573972 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 114.924333 
iter  10 value 94.484380
iter  20 value 94.222921
iter  30 value 93.940364
iter  40 value 92.485047
iter  50 value 87.228808
iter  60 value 85.624759
iter  70 value 84.116584
iter  80 value 83.401023
iter  90 value 82.799725
iter 100 value 82.378987
final  value 82.378987 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.454459 
iter  10 value 94.027049
iter  20 value 92.277036
iter  30 value 91.950979
iter  40 value 86.282735
iter  50 value 84.689071
iter  60 value 84.430943
iter  70 value 84.247736
iter  80 value 84.112509
iter  90 value 84.052997
iter 100 value 83.709612
final  value 83.709612 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.112361 
iter  10 value 94.511665
iter  20 value 92.918392
iter  30 value 87.445752
iter  40 value 86.646707
iter  50 value 86.481453
iter  60 value 85.986743
iter  70 value 84.894427
iter  80 value 84.833432
iter  90 value 84.826260
iter 100 value 84.764214
final  value 84.764214 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.427332 
iter  10 value 91.643830
iter  20 value 87.870058
iter  30 value 85.383621
iter  40 value 84.411263
iter  50 value 84.196494
iter  60 value 83.836552
iter  70 value 82.962701
iter  80 value 82.645379
iter  90 value 82.491553
iter 100 value 82.342346
final  value 82.342346 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 110.459649 
iter  10 value 95.073953
iter  20 value 88.921250
iter  30 value 88.181240
iter  40 value 87.761235
iter  50 value 87.300183
iter  60 value 85.718247
iter  70 value 84.701755
iter  80 value 83.442311
iter  90 value 82.742501
iter 100 value 82.548182
final  value 82.548182 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.437198 
iter  10 value 95.318629
iter  20 value 88.485766
iter  30 value 87.152268
iter  40 value 86.649665
iter  50 value 85.174519
iter  60 value 84.058570
iter  70 value 83.431223
iter  80 value 83.048293
iter  90 value 82.629262
iter 100 value 82.426550
final  value 82.426550 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.935519 
iter  10 value 94.351726
iter  20 value 90.570228
iter  30 value 86.767451
iter  40 value 85.063084
iter  50 value 84.558942
iter  60 value 84.507651
iter  70 value 84.348385
iter  80 value 84.238344
iter  90 value 83.879892
iter 100 value 83.719729
final  value 83.719729 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.767932 
iter  10 value 95.821942
iter  20 value 94.007311
iter  30 value 86.373253
iter  40 value 85.223740
iter  50 value 85.089570
iter  60 value 84.667550
iter  70 value 83.513705
iter  80 value 83.097457
iter  90 value 82.620391
iter 100 value 82.237940
final  value 82.237940 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.236814 
final  value 94.486149 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.631695 
final  value 94.486020 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.824408 
final  value 94.485991 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.244908 
final  value 94.485933 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.421032 
final  value 94.443607 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.291719 
iter  10 value 94.488016
iter  20 value 94.461190
iter  30 value 93.524557
iter  40 value 92.624105
iter  50 value 92.579621
final  value 92.579317 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.510888 
iter  10 value 94.488545
iter  20 value 91.759463
iter  30 value 87.476432
iter  40 value 86.312858
iter  50 value 86.311037
iter  60 value 86.097131
iter  70 value 85.966925
iter  80 value 85.662426
iter  90 value 85.429967
final  value 85.429960 
converged
Fitting Repeat 3 

# weights:  305
initial  value 116.335248 
iter  10 value 94.488927
iter  20 value 94.484375
iter  30 value 94.059684
iter  40 value 87.644094
iter  50 value 87.546556
final  value 87.524398 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.191023 
iter  10 value 94.489236
iter  20 value 94.135228
iter  30 value 91.827717
iter  40 value 88.198107
iter  50 value 88.197413
iter  60 value 87.680037
iter  70 value 84.812926
iter  80 value 82.651558
iter  90 value 81.911827
iter 100 value 81.493664
final  value 81.493664 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.223904 
iter  10 value 94.486859
iter  20 value 91.979002
iter  30 value 86.345233
iter  40 value 86.333899
iter  50 value 86.322176
iter  60 value 86.305833
iter  70 value 86.305585
iter  80 value 86.304744
iter  90 value 86.086892
iter 100 value 86.070976
final  value 86.070976 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 96.469615 
iter  10 value 94.362823
iter  20 value 94.356267
iter  30 value 94.354367
iter  40 value 94.128234
iter  50 value 91.361276
iter  60 value 91.352094
iter  70 value 91.260876
iter  80 value 90.130368
iter  90 value 89.423640
iter 100 value 89.417988
final  value 89.417988 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 102.446414 
iter  10 value 94.362524
iter  20 value 94.358731
iter  30 value 94.354541
iter  40 value 94.354398
iter  50 value 91.741732
iter  60 value 86.333195
iter  60 value 86.333194
iter  60 value 86.333194
final  value 86.333194 
converged
Fitting Repeat 3 

# weights:  507
initial  value 110.991716 
iter  10 value 91.381334
iter  20 value 85.022746
iter  30 value 85.020100
iter  40 value 84.744153
iter  50 value 84.693636
final  value 84.693412 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.165689 
iter  10 value 93.868841
iter  20 value 93.829828
iter  30 value 93.812978
iter  40 value 93.810374
iter  50 value 93.805324
iter  60 value 93.798286
iter  70 value 92.004568
iter  80 value 88.999331
iter  90 value 88.753085
iter 100 value 88.752018
final  value 88.752018 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 100.730605 
iter  10 value 92.402149
iter  20 value 89.299560
iter  30 value 89.008406
iter  40 value 88.871966
iter  50 value 88.536586
iter  60 value 88.471807
iter  70 value 87.974799
iter  80 value 86.445956
iter  90 value 84.181027
iter 100 value 83.615812
final  value 83.615812 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.831083 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.605013 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.353938 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.442414 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.969072 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.092349 
final  value 94.443243 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.996510 
final  value 94.443243 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.243941 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 110.593899 
final  value 94.443243 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.450540 
iter  10 value 92.944216
iter  20 value 92.933360
iter  30 value 92.933284
final  value 92.933278 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.718361 
iter  10 value 94.049369
final  value 94.049334 
converged
Fitting Repeat 2 

# weights:  507
initial  value 119.322569 
final  value 94.484208 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.055793 
iter  10 value 91.089714
iter  20 value 88.832759
iter  30 value 88.808584
final  value 88.808482 
converged
Fitting Repeat 4 

# weights:  507
initial  value 118.154249 
iter  10 value 94.443249
final  value 94.443243 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.053970 
iter  10 value 94.060161
final  value 94.057229 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.646910 
iter  10 value 94.228054
iter  20 value 85.828958
iter  30 value 84.825086
iter  40 value 83.027479
iter  50 value 81.785714
iter  60 value 81.520683
iter  70 value 81.491399
final  value 81.491223 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.979308 
iter  10 value 94.491686
iter  20 value 94.314360
iter  30 value 92.786622
iter  40 value 88.192249
iter  50 value 86.140857
iter  60 value 84.972217
iter  70 value 84.758443
iter  80 value 83.531434
iter  90 value 83.176611
iter 100 value 83.164217
final  value 83.164217 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 99.054486 
iter  10 value 94.499975
iter  20 value 94.101908
iter  30 value 86.424527
iter  40 value 85.144791
iter  50 value 84.974746
iter  60 value 84.736530
iter  60 value 84.736529
final  value 84.736529 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.798975 
iter  10 value 94.509095
iter  20 value 94.182269
iter  30 value 84.842308
iter  40 value 84.650522
iter  50 value 84.491193
iter  60 value 83.412897
iter  70 value 83.180547
iter  80 value 83.164849
final  value 83.164170 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.760091 
iter  10 value 94.534397
iter  20 value 94.492264
iter  30 value 94.466823
iter  40 value 94.369788
iter  50 value 91.829914
iter  60 value 89.941496
iter  70 value 87.257401
iter  80 value 83.912807
iter  90 value 83.579629
iter 100 value 83.243597
final  value 83.243597 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 108.923666 
iter  10 value 94.617491
iter  20 value 90.788925
iter  30 value 85.372433
iter  40 value 84.716426
iter  50 value 82.803778
iter  60 value 81.644163
iter  70 value 81.064839
iter  80 value 80.690378
iter  90 value 80.507680
iter 100 value 80.440253
final  value 80.440253 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.758785 
iter  10 value 94.945167
iter  20 value 91.145337
iter  30 value 85.559611
iter  40 value 84.431389
iter  50 value 83.290716
iter  60 value 82.812557
iter  70 value 82.000329
iter  80 value 81.791836
iter  90 value 81.659419
iter 100 value 81.571836
final  value 81.571836 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 113.299294 
iter  10 value 95.646603
iter  20 value 85.191793
iter  30 value 84.670409
iter  40 value 83.605509
iter  50 value 82.329631
iter  60 value 81.373629
iter  70 value 81.213153
iter  80 value 80.983744
iter  90 value 80.979062
iter 100 value 80.970864
final  value 80.970864 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.547357 
iter  10 value 93.676935
iter  20 value 93.058339
iter  30 value 92.949806
iter  40 value 88.489620
iter  50 value 83.419561
iter  60 value 81.062375
iter  70 value 80.872165
iter  80 value 80.836615
iter  90 value 80.809871
iter 100 value 80.688001
final  value 80.688001 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 110.922690 
iter  10 value 94.331175
iter  20 value 91.863172
iter  30 value 87.234366
iter  40 value 85.419540
iter  50 value 84.240160
iter  60 value 83.964448
iter  70 value 82.577024
iter  80 value 82.317736
iter  90 value 81.035996
iter 100 value 80.835069
final  value 80.835069 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 115.609036 
iter  10 value 90.621009
iter  20 value 84.999005
iter  30 value 84.424533
iter  40 value 84.370319
iter  50 value 82.550918
iter  60 value 81.721768
iter  70 value 80.478182
iter  80 value 80.190663
iter  90 value 80.157403
iter 100 value 80.103055
final  value 80.103055 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 143.684319 
iter  10 value 95.872548
iter  20 value 86.141947
iter  30 value 85.300996
iter  40 value 84.736782
iter  50 value 83.880643
iter  60 value 83.626443
iter  70 value 83.127368
iter  80 value 82.700916
iter  90 value 82.451104
iter 100 value 81.749098
final  value 81.749098 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 119.148844 
iter  10 value 94.670942
iter  20 value 93.937449
iter  30 value 89.882445
iter  40 value 88.704295
iter  50 value 85.578724
iter  60 value 83.349444
iter  70 value 82.735861
iter  80 value 81.572765
iter  90 value 81.386118
iter 100 value 81.001234
final  value 81.001234 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.651742 
iter  10 value 94.895704
iter  20 value 86.555041
iter  30 value 83.994340
iter  40 value 83.056521
iter  50 value 82.470270
iter  60 value 82.119703
iter  70 value 81.422296
iter  80 value 81.065000
iter  90 value 80.870193
iter 100 value 80.829351
final  value 80.829351 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.143738 
iter  10 value 94.593770
iter  20 value 90.476234
iter  30 value 85.024417
iter  40 value 84.527736
iter  50 value 82.479165
iter  60 value 82.274273
iter  70 value 82.117081
iter  80 value 82.051519
iter  90 value 81.633828
iter 100 value 80.825092
final  value 80.825092 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.820518 
final  value 94.485636 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.864093 
final  value 94.485982 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.171896 
iter  10 value 83.343301
iter  20 value 83.070906
iter  30 value 83.062403
iter  40 value 82.983286
iter  50 value 82.762237
iter  60 value 82.677969
iter  70 value 82.102450
iter  80 value 81.722372
final  value 81.722371 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.237856 
final  value 94.485839 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.096544 
final  value 94.486087 
converged
Fitting Repeat 1 

# weights:  305
initial  value 119.523098 
iter  10 value 92.596657
iter  20 value 92.594314
iter  30 value 92.479105
iter  40 value 92.444923
iter  50 value 92.294863
final  value 92.294752 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.234410 
iter  10 value 94.448094
iter  20 value 94.443780
final  value 94.443292 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.832903 
iter  10 value 94.488026
iter  20 value 94.403913
iter  30 value 92.234274
iter  40 value 89.705112
iter  50 value 85.302492
iter  60 value 81.889447
iter  70 value 81.752560
iter  80 value 81.748293
final  value 81.740413 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.631636 
iter  10 value 92.631007
iter  20 value 92.043431
iter  30 value 86.436512
iter  40 value 84.041470
iter  50 value 83.790247
iter  60 value 83.780324
final  value 83.779747 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.324581 
iter  10 value 93.772046
iter  20 value 93.713228
iter  30 value 93.384202
iter  40 value 93.377715
iter  50 value 93.376658
iter  60 value 93.374796
final  value 93.374627 
converged
Fitting Repeat 1 

# weights:  507
initial  value 111.167706 
iter  10 value 94.457735
iter  20 value 94.411961
iter  30 value 94.261334
iter  40 value 94.058828
final  value 94.058524 
converged
Fitting Repeat 2 

# weights:  507
initial  value 110.938983 
iter  10 value 94.492271
iter  20 value 94.477784
iter  30 value 94.192622
iter  40 value 84.147813
iter  50 value 83.919709
iter  60 value 83.901788
iter  70 value 83.891901
iter  80 value 83.763518
iter  90 value 83.681949
iter 100 value 83.061835
final  value 83.061835 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 97.765961 
iter  10 value 92.803946
iter  20 value 87.678444
iter  30 value 84.959792
iter  40 value 84.791091
iter  50 value 83.395386
iter  60 value 81.203119
iter  70 value 81.123375
iter  80 value 81.064642
iter  90 value 81.060962
iter 100 value 80.858476
final  value 80.858476 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.190987 
iter  10 value 85.653321
iter  20 value 83.091172
iter  30 value 82.843953
iter  40 value 82.627054
iter  50 value 82.625413
iter  60 value 82.618451
iter  70 value 82.279471
iter  80 value 82.274143
iter  90 value 82.262331
final  value 82.262296 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.436872 
iter  10 value 94.089715
iter  20 value 94.080697
iter  30 value 94.078277
iter  40 value 94.054925
iter  50 value 88.899060
iter  60 value 83.020811
iter  70 value 82.370410
iter  80 value 81.791062
iter  90 value 81.540649
iter 100 value 81.300628
final  value 81.300628 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.366755 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.607136 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.079551 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.802602 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 111.843399 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.425812 
final  value 93.394928 
converged
Fitting Repeat 2 

# weights:  305
initial  value 110.336705 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.506041 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 111.558308 
iter  10 value 93.688631
final  value 93.688363 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.005569 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.941591 
iter  10 value 93.396761
final  value 93.394928 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.760801 
iter  10 value 93.394931
final  value 93.394928 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.063667 
iter  10 value 92.994792
final  value 92.994741 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.403624 
iter  10 value 86.367455
iter  20 value 82.898896
iter  30 value 82.223415
iter  40 value 82.188302
final  value 82.188287 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.267268 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.072254 
iter  10 value 94.221592
iter  20 value 89.241651
iter  30 value 85.289662
iter  40 value 84.110524
iter  50 value 82.867585
iter  60 value 80.904716
iter  70 value 80.224120
iter  80 value 79.965655
final  value 79.956131 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.875412 
iter  10 value 94.486519
iter  20 value 93.582853
iter  30 value 86.092037
iter  40 value 85.639380
iter  50 value 85.608537
iter  60 value 85.107416
iter  70 value 83.818008
iter  80 value 83.494789
iter  90 value 83.388167
iter 100 value 83.333083
final  value 83.333083 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.882153 
iter  10 value 94.489615
iter  20 value 94.063934
iter  30 value 93.730729
iter  40 value 93.701795
iter  50 value 93.676678
iter  60 value 92.975631
iter  70 value 85.840298
iter  80 value 84.384223
iter  90 value 83.287107
iter 100 value 83.228521
final  value 83.228521 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 116.731504 
iter  10 value 94.480110
iter  20 value 93.274903
iter  30 value 92.726859
iter  40 value 92.702956
iter  50 value 86.479842
iter  60 value 85.813952
iter  70 value 85.326327
iter  80 value 83.832411
iter  90 value 83.583057
iter 100 value 83.572093
final  value 83.572093 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.623679 
iter  10 value 93.772407
iter  20 value 93.284841
iter  30 value 87.036752
iter  40 value 83.289283
iter  50 value 81.731454
iter  60 value 81.013026
iter  70 value 80.122674
iter  80 value 79.957661
final  value 79.956131 
converged
Fitting Repeat 1 

# weights:  305
initial  value 118.761615 
iter  10 value 94.554913
iter  20 value 93.944541
iter  30 value 93.681970
iter  40 value 89.116103
iter  50 value 85.151983
iter  60 value 84.787828
iter  70 value 84.540206
iter  80 value 83.762024
iter  90 value 82.845425
iter 100 value 82.500760
final  value 82.500760 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.211269 
iter  10 value 93.909096
iter  20 value 93.293462
iter  30 value 88.952784
iter  40 value 83.891463
iter  50 value 82.083355
iter  60 value 80.770564
iter  70 value 79.970530
iter  80 value 79.835798
iter  90 value 79.451482
iter 100 value 79.308379
final  value 79.308379 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 109.841689 
iter  10 value 91.897364
iter  20 value 84.693382
iter  30 value 83.542895
iter  40 value 80.685741
iter  50 value 80.259148
iter  60 value 80.135427
iter  70 value 79.956951
iter  80 value 79.472804
iter  90 value 79.180916
iter 100 value 79.161886
final  value 79.161886 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.340674 
iter  10 value 94.452250
iter  20 value 93.957715
iter  30 value 88.636876
iter  40 value 87.970266
iter  50 value 87.814509
iter  60 value 87.163883
iter  70 value 83.232601
iter  80 value 82.168569
iter  90 value 80.105735
iter 100 value 79.691016
final  value 79.691016 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.093831 
iter  10 value 94.534612
iter  20 value 94.267015
iter  30 value 90.932379
iter  40 value 89.240975
iter  50 value 83.686072
iter  60 value 80.590691
iter  70 value 79.837658
iter  80 value 79.517851
iter  90 value 79.448152
iter 100 value 79.339446
final  value 79.339446 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 149.912978 
iter  10 value 94.716913
iter  20 value 94.497465
iter  30 value 84.627226
iter  40 value 83.621228
iter  50 value 81.232989
iter  60 value 79.208781
iter  70 value 78.947548
iter  80 value 78.758577
iter  90 value 78.544364
iter 100 value 78.469019
final  value 78.469019 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.395890 
iter  10 value 92.533893
iter  20 value 87.731512
iter  30 value 86.134277
iter  40 value 84.548103
iter  50 value 83.891099
iter  60 value 83.674830
iter  70 value 83.329818
iter  80 value 82.534367
iter  90 value 80.111581
iter 100 value 79.303083
final  value 79.303083 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.108543 
iter  10 value 90.791125
iter  20 value 86.487488
iter  30 value 83.202055
iter  40 value 80.521186
iter  50 value 79.285016
iter  60 value 78.688835
iter  70 value 78.491248
iter  80 value 78.475417
iter  90 value 78.412111
iter 100 value 78.331617
final  value 78.331617 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 121.700133 
iter  10 value 93.792644
iter  20 value 89.792615
iter  30 value 86.340861
iter  40 value 83.307271
iter  50 value 82.052449
iter  60 value 81.484444
iter  70 value 80.416759
iter  80 value 79.316856
iter  90 value 79.233558
iter 100 value 78.961406
final  value 78.961406 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 117.041206 
iter  10 value 93.882681
iter  20 value 88.432058
iter  30 value 87.160743
iter  40 value 83.328371
iter  50 value 81.761527
iter  60 value 81.475910
iter  70 value 81.350331
iter  80 value 80.259975
iter  90 value 79.624558
iter 100 value 79.383035
final  value 79.383035 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.589305 
final  value 94.485904 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.526647 
final  value 94.486464 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.868647 
iter  10 value 94.486020
final  value 94.484221 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.985841 
iter  10 value 93.397830
iter  20 value 93.397591
iter  30 value 93.359357
iter  40 value 93.082205
iter  50 value 82.348779
iter  60 value 79.056243
iter  70 value 78.544799
final  value 78.474775 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.794271 
final  value 94.485939 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.973194 
iter  10 value 94.489168
iter  20 value 94.451263
iter  30 value 93.424331
final  value 93.424329 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.723183 
iter  10 value 94.485454
final  value 94.484226 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.435368 
iter  10 value 94.488005
final  value 94.484240 
converged
Fitting Repeat 4 

# weights:  305
initial  value 113.535102 
iter  10 value 93.400401
iter  20 value 93.397625
iter  30 value 93.250784
iter  40 value 92.993295
iter  50 value 92.807953
final  value 92.804897 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.139469 
iter  10 value 94.359512
iter  20 value 94.135953
iter  30 value 84.187029
iter  40 value 79.404835
iter  50 value 79.256501
iter  60 value 79.097119
iter  70 value 79.070577
iter  80 value 79.070169
iter  90 value 79.068866
iter 100 value 79.065905
final  value 79.065905 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 100.923309 
iter  10 value 94.331380
iter  20 value 94.324955
iter  30 value 89.759714
iter  40 value 89.116738
iter  50 value 85.322330
iter  60 value 84.881214
iter  70 value 84.879453
iter  80 value 84.872909
iter  90 value 84.722566
iter 100 value 82.311212
final  value 82.311212 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 97.385373 
iter  10 value 93.035511
iter  20 value 91.549193
iter  30 value 91.510699
iter  40 value 91.325010
iter  50 value 91.087003
final  value 91.037510 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.224193 
iter  10 value 93.469840
iter  20 value 89.452197
iter  30 value 86.772846
iter  40 value 86.665939
iter  50 value 86.649988
iter  60 value 86.649375
iter  70 value 86.637800
iter  80 value 86.637241
iter  90 value 86.636329
iter 100 value 86.634485
final  value 86.634485 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.592699 
iter  10 value 93.162346
iter  20 value 93.157940
iter  30 value 92.929601
iter  40 value 92.389837
iter  50 value 86.834755
iter  60 value 86.093809
iter  70 value 83.740439
iter  80 value 81.189624
iter  90 value 79.927403
iter 100 value 79.245050
final  value 79.245050 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.709777 
iter  10 value 93.003219
iter  20 value 89.653162
iter  30 value 83.279678
iter  40 value 83.230670
iter  50 value 83.213872
iter  60 value 83.191295
iter  70 value 83.190844
iter  80 value 83.188502
iter  90 value 82.435517
iter 100 value 80.284882
final  value 80.284882 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.448457 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.419479 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.265386 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.752923 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.236848 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.417618 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 116.334071 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.936700 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.086220 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.454880 
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.371394 
iter  10 value 94.028116
iter  20 value 94.020858
final  value 94.020841 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.039078 
iter  10 value 84.276836
iter  20 value 83.965897
iter  30 value 83.960994
iter  40 value 83.886147
iter  50 value 83.800149
iter  60 value 83.789557
final  value 83.789551 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.145088 
final  value 94.032967 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.053051 
final  value 94.032967 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.884729 
iter  10 value 94.032973
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.293919 
iter  10 value 92.630312
iter  20 value 86.835371
iter  30 value 85.278811
iter  40 value 84.733193
iter  50 value 84.669541
iter  60 value 84.473349
final  value 84.466554 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.392177 
iter  10 value 94.057139
iter  20 value 94.051849
iter  30 value 90.085144
iter  40 value 86.955616
iter  50 value 86.037600
iter  60 value 84.618880
iter  70 value 83.654120
iter  80 value 83.422588
final  value 83.422364 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.634019 
iter  10 value 94.026564
iter  20 value 89.572371
iter  30 value 87.222899
iter  40 value 84.549356
iter  50 value 82.858633
iter  60 value 82.537143
iter  70 value 82.205358
iter  80 value 81.976593
iter  90 value 81.885506
final  value 81.883944 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.884399 
iter  10 value 94.054507
iter  20 value 94.001005
iter  30 value 92.354852
iter  40 value 92.133871
iter  50 value 92.040280
iter  60 value 91.138250
iter  70 value 90.829177
iter  80 value 88.043111
iter  90 value 84.628661
iter 100 value 83.872452
final  value 83.872452 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 105.979863 
iter  10 value 94.056938
iter  20 value 93.634846
iter  30 value 85.534873
iter  40 value 83.837035
iter  50 value 83.590763
iter  60 value 82.961098
iter  70 value 82.335649
iter  80 value 81.894507
final  value 81.883944 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.073011 
iter  10 value 93.992315
iter  20 value 87.416054
iter  30 value 84.073873
iter  40 value 82.251268
iter  50 value 80.470994
iter  60 value 80.137950
iter  70 value 79.992460
iter  80 value 79.904769
iter  90 value 79.878898
iter 100 value 79.876543
final  value 79.876543 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 109.915869 
iter  10 value 93.960088
iter  20 value 87.525829
iter  30 value 85.288203
iter  40 value 84.552494
iter  50 value 82.876474
iter  60 value 80.742727
iter  70 value 80.077132
iter  80 value 79.997139
iter  90 value 79.940080
iter 100 value 79.893842
final  value 79.893842 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.479833 
iter  10 value 90.741224
iter  20 value 87.853900
iter  30 value 87.122614
iter  40 value 86.273595
iter  50 value 86.118035
iter  60 value 85.254311
iter  70 value 84.418410
iter  80 value 84.126217
iter  90 value 81.590493
iter 100 value 80.743054
final  value 80.743054 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.307880 
iter  10 value 93.240540
iter  20 value 85.341939
iter  30 value 84.979258
iter  40 value 84.462765
iter  50 value 84.174054
iter  60 value 83.904650
iter  70 value 82.724824
iter  80 value 82.522186
iter  90 value 82.347503
iter 100 value 82.119949
final  value 82.119949 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 116.219924 
iter  10 value 94.024217
iter  20 value 89.227626
iter  30 value 86.188108
iter  40 value 85.485051
iter  50 value 82.882542
iter  60 value 81.142831
iter  70 value 80.487735
iter  80 value 80.275258
iter  90 value 80.062815
iter 100 value 79.981274
final  value 79.981274 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 113.025699 
iter  10 value 95.406476
iter  20 value 88.807451
iter  30 value 85.385141
iter  40 value 85.202272
iter  50 value 83.368738
iter  60 value 82.833674
iter  70 value 81.505728
iter  80 value 80.221437
iter  90 value 80.063050
iter 100 value 79.949383
final  value 79.949383 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.259528 
iter  10 value 92.991131
iter  20 value 88.563420
iter  30 value 86.044198
iter  40 value 83.108515
iter  50 value 81.809593
iter  60 value 80.584423
iter  70 value 80.261501
iter  80 value 80.053487
iter  90 value 80.024704
iter 100 value 79.968593
final  value 79.968593 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 119.974920 
iter  10 value 96.855867
iter  20 value 92.841780
iter  30 value 92.228061
iter  40 value 92.054081
iter  50 value 91.635215
iter  60 value 89.985238
iter  70 value 88.308926
iter  80 value 84.923036
iter  90 value 82.536663
iter 100 value 81.306747
final  value 81.306747 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 131.692059 
iter  10 value 94.362842
iter  20 value 89.487282
iter  30 value 86.548120
iter  40 value 83.771468
iter  50 value 82.588629
iter  60 value 82.464850
iter  70 value 81.655485
iter  80 value 80.411915
iter  90 value 79.806532
iter 100 value 79.660616
final  value 79.660616 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.027785 
iter  10 value 98.380121
iter  20 value 92.558685
iter  30 value 85.064017
iter  40 value 84.719590
iter  50 value 83.062654
iter  60 value 81.632195
iter  70 value 81.229577
iter  80 value 80.477465
iter  90 value 80.154024
iter 100 value 79.979523
final  value 79.979523 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.646070 
final  value 94.054471 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.215386 
final  value 94.054670 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.213507 
final  value 94.054521 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.240884 
iter  10 value 94.034665
iter  20 value 94.034117
final  value 94.033767 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.273023 
iter  10 value 90.900221
iter  20 value 90.866977
iter  30 value 90.802398
iter  40 value 89.551373
iter  50 value 89.531259
final  value 89.447543 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.652511 
iter  10 value 94.037581
iter  20 value 94.033305
iter  30 value 93.977519
iter  40 value 87.341065
iter  50 value 86.813125
iter  60 value 86.810160
iter  70 value 86.632746
iter  80 value 83.891258
iter  90 value 83.883122
iter 100 value 83.882017
final  value 83.882017 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 112.673136 
iter  10 value 94.057566
iter  20 value 93.987679
iter  30 value 91.593842
iter  40 value 91.328053
iter  50 value 91.323161
iter  60 value 91.323130
iter  70 value 88.595493
iter  80 value 85.738017
iter  90 value 85.709933
iter 100 value 85.699464
final  value 85.699464 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.950874 
iter  10 value 94.034520
iter  20 value 94.031235
iter  30 value 94.029377
iter  40 value 92.209862
iter  50 value 89.608136
iter  60 value 89.603584
iter  70 value 89.600406
iter  80 value 89.599279
final  value 89.599118 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.975334 
iter  10 value 94.061262
iter  20 value 93.025860
iter  30 value 93.019229
iter  40 value 91.023358
iter  50 value 90.650872
final  value 90.617262 
converged
Fitting Repeat 5 

# weights:  305
initial  value 109.842381 
iter  10 value 94.057715
iter  20 value 92.587896
iter  30 value 91.715413
iter  40 value 91.712247
iter  40 value 91.712246
iter  40 value 91.712246
final  value 91.712246 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.941992 
iter  10 value 94.041046
iter  20 value 91.901564
iter  30 value 83.977194
final  value 83.977189 
converged
Fitting Repeat 2 

# weights:  507
initial  value 112.293919 
iter  10 value 94.037659
iter  20 value 94.031588
iter  30 value 94.029496
iter  40 value 88.138176
iter  50 value 87.805580
iter  60 value 86.742207
iter  70 value 86.374826
iter  80 value 86.370740
iter  90 value 86.364685
iter 100 value 86.362866
final  value 86.362866 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 120.163267 
iter  10 value 94.043368
iter  20 value 94.034315
iter  30 value 90.595882
iter  40 value 85.265744
iter  50 value 84.259105
iter  60 value 80.636344
iter  70 value 79.944402
iter  80 value 78.508457
iter  90 value 78.286371
iter 100 value 78.079919
final  value 78.079919 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.657567 
iter  10 value 94.042043
iter  20 value 94.015066
iter  30 value 91.241545
iter  40 value 88.829539
iter  50 value 88.814187
iter  60 value 88.810190
iter  70 value 88.654019
iter  80 value 87.767502
iter  90 value 87.760386
iter 100 value 87.756427
final  value 87.756427 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.854689 
iter  10 value 94.059885
iter  20 value 93.956486
iter  30 value 89.992212
iter  40 value 81.626202
iter  50 value 81.595615
iter  60 value 80.729009
iter  70 value 80.179356
iter  80 value 80.030343
iter  90 value 80.022062
final  value 80.019595 
converged
Fitting Repeat 1 

# weights:  507
initial  value 131.442423 
iter  10 value 117.732993
iter  20 value 117.602532
iter  30 value 116.491883
iter  40 value 107.834033
iter  50 value 107.527292
iter  60 value 107.520044
iter  70 value 107.515031
final  value 107.514962 
converged
Fitting Repeat 2 

# weights:  507
initial  value 121.566086 
iter  10 value 117.766424
iter  20 value 117.681081
iter  30 value 110.268223
iter  40 value 106.781339
iter  50 value 106.778153
iter  60 value 104.828638
iter  70 value 104.647703
iter  70 value 104.647702
iter  70 value 104.647702
final  value 104.647702 
converged
Fitting Repeat 3 

# weights:  507
initial  value 143.834175 
iter  10 value 117.860653
iter  20 value 117.716679
iter  30 value 116.687251
iter  40 value 109.246713
iter  50 value 108.567168
iter  60 value 105.169175
iter  70 value 102.942505
iter  80 value 102.825522
iter  90 value 102.824716
iter 100 value 102.824422
final  value 102.824422 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 129.352336 
iter  10 value 117.898211
iter  20 value 117.853242
iter  30 value 110.396119
iter  40 value 106.375118
iter  50 value 103.822589
iter  60 value 101.163942
iter  70 value 100.643998
iter  80 value 100.581775
iter  90 value 100.581196
final  value 100.581039 
converged
Fitting Repeat 5 

# weights:  507
initial  value 125.986664 
iter  10 value 117.766043
iter  20 value 112.000765
iter  30 value 105.055532
iter  40 value 105.020239
iter  50 value 105.019405
final  value 105.019112 
converged
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Wed Feb 25 00:43:14 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 
 40.663   1.164  91.992