##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.20-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.20-bioc/R/site-library --timings HPiP_1.12.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck’
* using R version 4.4.3 (2025-02-28)
* 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 24.04.2 LTS
* using session charset: UTF-8
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.12.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
var_imp       35.047  0.609  35.657
corr_plot     33.462  0.371  33.893
FSmethod      33.274  0.549  33.824
pred_ensembel 12.996  0.302  11.980
enrichfindP    0.496  0.035   8.843
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE

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

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


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

R version 4.4.3 (2025-02-28) -- "Trophy Case"
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 95.581101 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.639029 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.213540 
final  value 94.325945 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.108344 
iter  10 value 85.747474
iter  20 value 84.791761
iter  30 value 83.652969
final  value 83.652698 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.657558 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.619985 
iter  10 value 81.266338
iter  20 value 81.097057
final  value 81.096851 
converged
Fitting Repeat 2 

# weights:  305
initial  value 108.696154 
iter  10 value 93.772990
final  value 93.772973 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.489735 
iter  10 value 93.772975
final  value 93.772973 
converged
Fitting Repeat 4 

# weights:  305
initial  value 110.022185 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.387649 
iter  10 value 93.772992
final  value 93.772973 
converged
Fitting Repeat 1 

# weights:  507
initial  value 111.756621 
iter  10 value 93.772982
final  value 93.772973 
converged
Fitting Repeat 2 

# weights:  507
initial  value 111.542115 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.414387 
iter  10 value 93.642941
final  value 93.642934 
converged
Fitting Repeat 4 

# weights:  507
initial  value 150.234500 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.900104 
final  value 94.470284 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.317829 
iter  10 value 94.486567
iter  20 value 89.630625
iter  30 value 88.373223
iter  40 value 87.805804
iter  50 value 86.390148
iter  60 value 83.442451
iter  70 value 81.405649
iter  80 value 80.683856
iter  90 value 80.612574
iter 100 value 80.611299
final  value 80.611299 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 106.264592 
iter  10 value 92.887335
iter  20 value 83.703927
final  value 83.607531 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.140070 
iter  10 value 93.965213
iter  20 value 92.933987
iter  30 value 89.672320
iter  40 value 86.857399
iter  50 value 86.584777
iter  60 value 86.236589
iter  70 value 84.005100
iter  80 value 81.347294
iter  90 value 80.658412
iter 100 value 80.070432
final  value 80.070432 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 103.863340 
iter  10 value 94.486686
iter  20 value 94.110502
iter  30 value 89.767726
iter  40 value 82.817357
iter  50 value 82.241155
iter  60 value 82.121317
iter  70 value 81.157010
iter  80 value 80.615267
iter  90 value 80.611365
final  value 80.611115 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.411322 
iter  10 value 94.486860
iter  20 value 88.502697
iter  30 value 86.706387
iter  40 value 85.401140
iter  50 value 82.301302
iter  60 value 81.284799
iter  70 value 81.158965
iter  80 value 81.140815
iter  80 value 81.140815
iter  80 value 81.140815
final  value 81.140815 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.301633 
iter  10 value 94.913987
iter  20 value 88.427875
iter  30 value 82.461691
iter  40 value 82.112167
iter  50 value 79.875485
iter  60 value 79.620994
iter  70 value 79.271503
iter  80 value 79.130705
iter  90 value 79.046922
iter 100 value 78.828722
final  value 78.828722 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.260088 
iter  10 value 89.671411
iter  20 value 85.068761
iter  30 value 84.410396
iter  40 value 84.211596
iter  50 value 83.071745
iter  60 value 82.512414
iter  70 value 80.731397
iter  80 value 80.300608
iter  90 value 79.896578
iter 100 value 79.587071
final  value 79.587071 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 115.122313 
iter  10 value 101.107367
iter  20 value 93.949772
iter  30 value 83.597121
iter  40 value 82.640848
iter  50 value 82.026043
iter  60 value 79.265403
iter  70 value 77.863287
iter  80 value 77.404261
iter  90 value 77.278738
iter 100 value 77.174023
final  value 77.174023 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 113.407714 
iter  10 value 94.493298
iter  20 value 94.086925
iter  30 value 94.062839
iter  40 value 93.544205
iter  50 value 86.174550
iter  60 value 83.092819
iter  70 value 82.030536
iter  80 value 78.718598
iter  90 value 77.998644
iter 100 value 77.833784
final  value 77.833784 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 119.910469 
iter  10 value 95.244620
iter  20 value 93.175460
iter  30 value 91.900343
iter  40 value 85.987946
iter  50 value 82.856775
iter  60 value 82.044986
iter  70 value 79.803680
iter  80 value 78.390609
iter  90 value 78.040252
iter 100 value 77.594590
final  value 77.594590 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.014005 
iter  10 value 94.925388
iter  20 value 93.905010
iter  30 value 87.429948
iter  40 value 83.392188
iter  50 value 79.064817
iter  60 value 78.212162
iter  70 value 77.748815
iter  80 value 77.467909
iter  90 value 77.236926
iter 100 value 77.221640
final  value 77.221640 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 120.094014 
iter  10 value 95.276098
iter  20 value 89.643656
iter  30 value 83.147815
iter  40 value 82.230941
iter  50 value 81.493678
iter  60 value 78.275285
iter  70 value 77.628204
iter  80 value 77.505437
iter  90 value 77.341995
iter 100 value 77.191347
final  value 77.191347 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.847929 
iter  10 value 96.656123
iter  20 value 95.691705
iter  30 value 92.631998
iter  40 value 88.019285
iter  50 value 87.208071
iter  60 value 82.741847
iter  70 value 80.986166
iter  80 value 80.172179
iter  90 value 78.465218
iter 100 value 77.464285
final  value 77.464285 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.313586 
iter  10 value 91.560802
iter  20 value 84.152779
iter  30 value 82.792289
iter  40 value 81.883999
iter  50 value 81.050931
iter  60 value 80.898296
iter  70 value 79.890251
iter  80 value 78.466655
iter  90 value 77.973074
iter 100 value 77.846235
final  value 77.846235 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 114.677420 
iter  10 value 94.717148
iter  20 value 91.515080
iter  30 value 90.754120
iter  40 value 90.151914
iter  50 value 82.172772
iter  60 value 80.716681
iter  70 value 80.055202
iter  80 value 79.956077
iter  90 value 79.898744
iter 100 value 79.874659
final  value 79.874659 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.556611 
final  value 94.486263 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.255744 
final  value 94.486093 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.978099 
iter  10 value 94.485841
iter  20 value 94.251607
iter  30 value 82.481000
iter  40 value 82.478274
iter  50 value 82.478022
iter  60 value 82.473344
iter  70 value 81.774261
final  value 81.773819 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.297022 
final  value 94.327406 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.708950 
final  value 94.486540 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.978773 
iter  10 value 93.727449
iter  20 value 93.727087
iter  30 value 93.720600
iter  40 value 84.851016
iter  50 value 82.538995
iter  60 value 79.999033
iter  70 value 77.247717
iter  80 value 77.221656
iter  90 value 77.209114
final  value 77.208869 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.238296 
iter  10 value 92.470272
iter  20 value 92.469190
iter  30 value 90.409471
iter  40 value 90.152949
final  value 90.139283 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.151682 
iter  10 value 93.839818
iter  20 value 93.377823
iter  30 value 92.560157
iter  40 value 92.503559
iter  50 value 92.502700
iter  60 value 90.800630
iter  70 value 90.793063
iter  80 value 90.790767
iter  90 value 90.727653
iter 100 value 90.698990
final  value 90.698990 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.085824 
iter  10 value 94.489408
iter  20 value 94.484581
final  value 94.484565 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.965229 
iter  10 value 92.268761
iter  20 value 91.418800
iter  20 value 91.418800
final  value 91.418800 
converged
Fitting Repeat 1 

# weights:  507
initial  value 124.354309 
iter  10 value 94.492881
iter  20 value 94.147177
iter  30 value 92.613307
iter  40 value 91.700116
iter  50 value 90.948218
iter  60 value 90.945198
iter  70 value 90.936209
final  value 90.934782 
converged
Fitting Repeat 2 

# weights:  507
initial  value 115.924877 
iter  10 value 84.255211
iter  20 value 84.077576
iter  30 value 83.677609
iter  40 value 83.676859
iter  50 value 83.672046
iter  60 value 83.670156
iter  70 value 83.589243
iter  80 value 83.311180
final  value 83.273350 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.487018 
iter  10 value 94.491817
iter  20 value 94.410133
iter  30 value 93.923660
iter  40 value 93.732478
final  value 93.724003 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.098587 
iter  10 value 93.785414
iter  20 value 93.780662
iter  30 value 93.457686
iter  40 value 83.103663
iter  50 value 81.277867
iter  60 value 80.542935
iter  70 value 79.027349
iter  80 value 77.750435
iter  90 value 77.738329
iter 100 value 77.737858
final  value 77.737858 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 95.228286 
iter  10 value 93.780990
iter  20 value 92.473224
iter  30 value 90.596572
iter  40 value 83.255973
iter  50 value 79.408557
iter  60 value 77.678123
iter  70 value 77.578012
iter  80 value 77.576488
iter  90 value 77.576306
final  value 77.576189 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.679105 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 111.398981 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.253830 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.944261 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.237898 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.810153 
final  value 94.467391 
converged
Fitting Repeat 2 

# weights:  305
initial  value 111.587307 
iter  10 value 94.467521
iter  20 value 94.467393
iter  20 value 94.467392
iter  20 value 94.467392
final  value 94.467392 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.976086 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 128.546042 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.189991 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.648674 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.145149 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.647105 
final  value 94.467391 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.358982 
final  value 94.453333 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.644406 
iter  10 value 94.044265
iter  20 value 92.613932
final  value 92.613874 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.766790 
iter  10 value 94.429388
iter  20 value 91.276605
iter  30 value 88.008012
iter  40 value 87.422194
iter  50 value 87.238263
iter  60 value 86.267555
iter  70 value 85.695637
iter  80 value 85.393315
iter  90 value 85.378161
final  value 85.378006 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.048386 
iter  10 value 92.781760
iter  20 value 87.090349
iter  30 value 86.809324
iter  40 value 86.163974
iter  50 value 85.540856
iter  60 value 85.378844
final  value 85.378006 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.789589 
iter  10 value 94.251787
iter  20 value 87.721671
iter  30 value 86.973214
iter  40 value 86.504063
iter  50 value 86.045695
iter  60 value 85.778449
iter  70 value 85.744557
final  value 85.744106 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.652802 
iter  10 value 94.455386
iter  20 value 92.426866
iter  30 value 88.345717
iter  40 value 87.901842
iter  50 value 86.757322
iter  60 value 86.341917
iter  70 value 86.118885
iter  80 value 86.031750
iter  90 value 85.994371
iter  90 value 85.994371
iter  90 value 85.994371
final  value 85.994371 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.073502 
iter  10 value 93.974252
iter  20 value 88.380844
iter  30 value 87.911218
iter  40 value 87.152300
iter  50 value 86.722239
iter  60 value 86.258462
final  value 86.241556 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.669924 
iter  10 value 94.562676
iter  20 value 88.663447
iter  30 value 87.644647
iter  40 value 86.785429
iter  50 value 86.424229
iter  60 value 85.978861
iter  70 value 85.428296
iter  80 value 83.505691
iter  90 value 83.270912
iter 100 value 83.112620
final  value 83.112620 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.183874 
iter  10 value 94.207349
iter  20 value 88.864934
iter  30 value 87.452421
iter  40 value 87.044677
iter  50 value 87.024823
iter  60 value 86.656964
iter  70 value 84.968194
iter  80 value 84.385108
iter  90 value 84.083674
iter 100 value 83.217580
final  value 83.217580 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 116.705268 
iter  10 value 94.809711
iter  20 value 94.435254
iter  30 value 89.739558
iter  40 value 87.135830
iter  50 value 86.489574
iter  60 value 86.009638
iter  70 value 85.687288
iter  80 value 84.804296
iter  90 value 84.245533
iter 100 value 83.439016
final  value 83.439016 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.666496 
iter  10 value 93.709770
iter  20 value 92.453720
iter  30 value 92.411901
iter  40 value 92.308065
iter  50 value 87.518293
iter  60 value 86.517331
iter  70 value 86.322326
iter  80 value 84.863627
iter  90 value 84.008491
iter 100 value 83.596562
final  value 83.596562 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.384748 
iter  10 value 94.530131
iter  20 value 94.356143
iter  30 value 93.007859
iter  40 value 92.521722
iter  50 value 92.437212
iter  60 value 90.720745
iter  70 value 87.811580
iter  80 value 86.792094
iter  90 value 86.338287
iter 100 value 84.121797
final  value 84.121797 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 122.020955 
iter  10 value 94.524028
iter  20 value 93.784028
iter  30 value 86.189145
iter  40 value 85.580692
iter  50 value 85.174095
iter  60 value 84.237025
iter  70 value 83.793077
iter  80 value 83.383873
iter  90 value 83.242126
iter 100 value 83.193525
final  value 83.193525 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 126.510105 
iter  10 value 94.851745
iter  20 value 93.219891
iter  30 value 89.349226
iter  40 value 87.283583
iter  50 value 85.334989
iter  60 value 84.704797
iter  70 value 84.597888
iter  80 value 84.074952
iter  90 value 83.666737
iter 100 value 83.494753
final  value 83.494753 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 124.858421 
iter  10 value 97.612850
iter  20 value 88.483885
iter  30 value 86.720548
iter  40 value 86.068544
iter  50 value 85.795271
iter  60 value 84.292137
iter  70 value 83.456690
iter  80 value 83.086059
iter  90 value 83.029800
iter 100 value 83.015685
final  value 83.015685 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 126.061828 
iter  10 value 94.961478
iter  20 value 94.439647
iter  30 value 89.970001
iter  40 value 85.117807
iter  50 value 83.750686
iter  60 value 83.402975
iter  70 value 83.193522
iter  80 value 83.071779
iter  90 value 83.010658
iter 100 value 82.983160
final  value 82.983160 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.552080 
iter  10 value 94.317047
iter  20 value 90.867367
iter  30 value 88.789393
iter  40 value 87.902798
iter  50 value 86.752898
iter  60 value 84.397294
iter  70 value 83.741309
iter  80 value 83.149455
iter  90 value 83.001997
iter 100 value 82.899468
final  value 82.899468 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.272511 
iter  10 value 94.485855
iter  20 value 94.470820
iter  30 value 92.396142
iter  40 value 91.173789
iter  50 value 91.171554
iter  60 value 90.428917
iter  70 value 90.307427
iter  80 value 90.252212
iter  90 value 90.249840
final  value 90.249802 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.681534 
iter  10 value 88.446082
iter  20 value 88.341092
iter  30 value 88.036788
iter  40 value 88.027483
iter  50 value 87.653971
iter  60 value 87.600863
iter  70 value 85.829538
iter  80 value 84.254679
iter  90 value 83.387017
iter 100 value 83.244827
final  value 83.244827 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 106.008312 
final  value 94.463120 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.296219 
final  value 94.485855 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.562192 
final  value 94.485701 
converged
Fitting Repeat 1 

# weights:  305
initial  value 129.209828 
iter  10 value 94.488853
iter  20 value 94.484205
iter  30 value 94.365081
iter  40 value 94.274748
iter  50 value 88.570414
iter  60 value 86.138224
iter  70 value 85.540728
iter  80 value 85.413800
iter  90 value 85.365514
final  value 85.270757 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.694583 
final  value 94.488917 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.327797 
iter  10 value 94.507378
final  value 94.502638 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.576656 
iter  10 value 94.143448
iter  20 value 94.092372
iter  30 value 94.090674
iter  40 value 94.087473
iter  50 value 90.965586
iter  60 value 89.423509
iter  70 value 87.395296
iter  80 value 83.579768
iter  90 value 82.823256
iter 100 value 82.808724
final  value 82.808724 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 96.680464 
iter  10 value 94.488356
iter  20 value 93.647859
iter  30 value 92.627329
iter  40 value 92.623535
iter  50 value 92.622812
iter  60 value 92.514449
iter  70 value 85.886830
iter  80 value 85.657638
iter  90 value 85.635366
iter 100 value 85.602770
final  value 85.602770 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 101.129563 
iter  10 value 94.476518
iter  20 value 94.440704
iter  30 value 94.241046
iter  40 value 87.303773
iter  50 value 86.581322
iter  60 value 86.476591
iter  70 value 86.470429
iter  80 value 86.442228
iter  90 value 85.854602
iter 100 value 85.755108
final  value 85.755108 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 96.081376 
iter  10 value 94.492282
iter  20 value 93.610666
iter  30 value 88.448164
iter  40 value 87.923219
iter  50 value 85.484531
iter  60 value 85.394577
iter  70 value 85.392072
iter  80 value 85.368495
iter  90 value 85.358946
final  value 85.358430 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.435791 
iter  10 value 94.477403
iter  20 value 94.475779
iter  30 value 94.475082
iter  40 value 94.467292
iter  50 value 92.191843
iter  60 value 87.465749
iter  70 value 84.845335
iter  80 value 84.735592
final  value 84.728710 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.313734 
iter  10 value 94.492614
iter  20 value 94.477763
iter  30 value 90.624761
iter  40 value 87.161507
iter  50 value 87.117835
final  value 87.117693 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.290226 
iter  10 value 94.492592
iter  20 value 94.484205
iter  30 value 94.167381
iter  40 value 90.171595
iter  50 value 86.787371
iter  60 value 83.785056
iter  70 value 82.519298
iter  80 value 82.096845
iter  90 value 82.013679
iter 100 value 81.997374
final  value 81.997374 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.346575 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.540796 
final  value 93.915746 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.274495 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.247251 
iter  10 value 83.635358
iter  20 value 81.942590
iter  30 value 81.928962
final  value 81.928955 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.590279 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.439966 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.384259 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.529188 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.243945 
final  value 94.052911 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.680495 
iter  10 value 90.516154
iter  20 value 89.568673
iter  30 value 89.562196
iter  40 value 89.562148
final  value 89.562147 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.200767 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.209365 
iter  10 value 91.542602
iter  20 value 83.702836
final  value 83.670403 
converged
Fitting Repeat 3 

# weights:  507
initial  value 120.347065 
iter  10 value 93.860355
iter  10 value 93.860355
iter  10 value 93.860355
final  value 93.860355 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.644492 
iter  10 value 93.166445
iter  20 value 93.023932
iter  30 value 92.790376
iter  40 value 92.775622
iter  50 value 92.775001
iter  50 value 92.775001
iter  50 value 92.775001
final  value 92.775001 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.262528 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.930442 
iter  10 value 94.187266
iter  20 value 86.923181
iter  30 value 83.962466
iter  40 value 83.779378
iter  50 value 83.646576
iter  60 value 83.248995
iter  70 value 82.745398
iter  80 value 82.634175
iter  90 value 82.440815
iter 100 value 81.624464
final  value 81.624464 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 111.428402 
iter  10 value 94.041899
iter  20 value 91.580542
iter  30 value 88.018515
iter  40 value 87.629624
iter  50 value 86.741117
iter  60 value 81.503597
iter  70 value 80.923469
iter  80 value 80.614939
iter  90 value 80.252344
iter 100 value 80.049287
final  value 80.049287 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.142355 
iter  10 value 94.034960
iter  20 value 93.836616
iter  30 value 93.821027
iter  40 value 91.823802
iter  50 value 90.367787
iter  60 value 90.132779
iter  70 value 90.117253
iter  70 value 90.117253
iter  70 value 90.117253
final  value 90.117253 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.930228 
iter  10 value 94.251071
iter  20 value 94.056648
iter  30 value 86.097278
iter  40 value 84.857543
iter  50 value 84.012111
iter  60 value 82.282189
iter  70 value 81.343055
iter  80 value 81.307336
iter  90 value 81.175553
iter 100 value 80.668602
final  value 80.668602 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 117.637366 
iter  10 value 94.017350
iter  20 value 93.642170
iter  30 value 93.592024
iter  40 value 84.597357
iter  50 value 83.906804
iter  60 value 83.729729
iter  70 value 83.565420
iter  80 value 83.505104
iter  90 value 82.962331
iter 100 value 82.489732
final  value 82.489732 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 103.689877 
iter  10 value 94.064501
iter  20 value 93.907747
iter  30 value 90.789895
iter  40 value 90.116424
iter  50 value 89.120747
iter  60 value 82.709359
iter  70 value 81.234069
iter  80 value 80.327014
iter  90 value 79.980101
iter 100 value 79.812406
final  value 79.812406 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 121.845921 
iter  10 value 94.147501
iter  20 value 87.567564
iter  30 value 86.793607
iter  40 value 83.877806
iter  50 value 81.924379
iter  60 value 81.374739
iter  70 value 81.031101
iter  80 value 80.919739
iter  90 value 80.813558
iter 100 value 80.499783
final  value 80.499783 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.367815 
iter  10 value 94.230812
iter  20 value 86.168860
iter  30 value 84.542923
iter  40 value 81.808491
iter  50 value 80.550039
iter  60 value 80.083897
iter  70 value 79.812366
iter  80 value 79.757945
iter  90 value 79.320697
iter 100 value 78.899618
final  value 78.899618 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 113.273074 
iter  10 value 93.928267
iter  20 value 89.439266
iter  30 value 84.307814
iter  40 value 83.512851
iter  50 value 81.825640
iter  60 value 81.002876
iter  70 value 80.522845
iter  80 value 79.688664
iter  90 value 79.197506
iter 100 value 78.495694
final  value 78.495694 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 113.272964 
iter  10 value 94.754849
iter  20 value 94.100044
iter  30 value 91.014741
iter  40 value 84.089738
iter  50 value 80.259624
iter  60 value 79.641230
iter  70 value 78.706887
iter  80 value 78.628353
iter  90 value 78.579053
iter 100 value 78.545958
final  value 78.545958 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.980590 
iter  10 value 94.082866
iter  20 value 93.729528
iter  30 value 88.893944
iter  40 value 85.273439
iter  50 value 83.502711
iter  60 value 81.057386
iter  70 value 79.986335
iter  80 value 79.062664
iter  90 value 77.920103
iter 100 value 77.668241
final  value 77.668241 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 114.741400 
iter  10 value 96.588312
iter  20 value 91.043677
iter  30 value 84.120572
iter  40 value 82.825025
iter  50 value 81.850217
iter  60 value 79.759379
iter  70 value 78.803418
iter  80 value 78.528110
iter  90 value 78.357330
iter 100 value 77.929985
final  value 77.929985 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 125.077806 
iter  10 value 94.038163
iter  20 value 90.758081
iter  30 value 83.704804
iter  40 value 81.757261
iter  50 value 80.921911
iter  60 value 80.254399
iter  70 value 79.555825
iter  80 value 78.573374
iter  90 value 78.207432
iter 100 value 77.913862
final  value 77.913862 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.289763 
iter  10 value 94.068690
iter  20 value 93.871576
iter  30 value 91.711638
iter  40 value 85.044008
iter  50 value 82.241803
iter  60 value 80.473329
iter  70 value 80.360183
iter  80 value 79.660819
iter  90 value 79.314726
iter 100 value 78.578828
final  value 78.578828 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 125.737501 
iter  10 value 94.058575
iter  20 value 93.080304
iter  30 value 86.781274
iter  40 value 80.718710
iter  50 value 79.734464
iter  60 value 79.062156
iter  70 value 78.672090
iter  80 value 78.532294
iter  90 value 78.486399
iter 100 value 78.446450
final  value 78.446450 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.499873 
final  value 94.054497 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.533042 
iter  10 value 93.882288
final  value 93.862109 
converged
Fitting Repeat 3 

# weights:  103
initial  value 114.304074 
iter  10 value 90.644263
iter  20 value 90.476460
iter  30 value 90.451397
iter  40 value 90.450363
final  value 90.450166 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.291895 
final  value 93.917247 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.689302 
final  value 94.054469 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.758121 
iter  10 value 93.920907
iter  20 value 93.916731
iter  30 value 92.400030
iter  40 value 85.465277
iter  50 value 80.586864
iter  60 value 80.519541
iter  70 value 80.515886
iter  80 value 80.515570
final  value 80.515568 
converged
Fitting Repeat 2 

# weights:  305
initial  value 93.784021 
iter  10 value 88.059074
iter  20 value 85.414507
iter  30 value 85.297925
iter  40 value 85.297554
iter  50 value 85.294619
iter  60 value 82.313022
iter  70 value 80.052997
iter  80 value 80.039663
iter  90 value 77.830634
iter 100 value 77.540580
final  value 77.540580 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 121.431212 
iter  10 value 93.921166
iter  20 value 93.916799
iter  30 value 93.844218
final  value 93.844211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.097439 
iter  10 value 94.057569
iter  20 value 94.052560
iter  30 value 93.805427
iter  40 value 91.816981
iter  50 value 83.664051
iter  60 value 83.648390
iter  70 value 83.636340
iter  80 value 82.765905
iter  90 value 82.670573
iter 100 value 82.631384
final  value 82.631384 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 97.157673 
iter  10 value 94.058411
iter  20 value 94.053667
iter  30 value 93.957324
iter  40 value 93.916278
final  value 93.916130 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.075551 
iter  10 value 94.067575
iter  20 value 94.059063
iter  30 value 92.544311
iter  40 value 82.675504
iter  50 value 82.041447
iter  60 value 82.029541
iter  70 value 81.197641
iter  80 value 79.667943
iter  90 value 78.619477
iter 100 value 78.618407
final  value 78.618407 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.263465 
iter  10 value 93.453855
iter  20 value 93.437731
iter  30 value 93.430264
iter  40 value 93.422897
iter  50 value 91.597584
iter  60 value 91.162648
iter  70 value 91.160311
iter  80 value 91.088154
final  value 91.078463 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.122396 
iter  10 value 93.999735
iter  20 value 88.896382
iter  30 value 82.015540
iter  40 value 80.208324
iter  50 value 80.165610
iter  60 value 80.165433
final  value 80.164584 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.059771 
iter  10 value 93.880004
iter  20 value 93.875753
iter  30 value 93.873421
iter  40 value 87.289625
iter  50 value 86.209015
iter  60 value 86.206606
iter  70 value 86.203231
iter  80 value 86.201226
iter  90 value 85.996995
iter 100 value 84.369211
final  value 84.369211 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.705188 
iter  10 value 93.923963
iter  20 value 93.085592
iter  30 value 83.791918
iter  40 value 82.983028
iter  50 value 82.445097
iter  60 value 80.787798
iter  70 value 79.088492
iter  80 value 78.535713
final  value 78.535699 
converged
Fitting Repeat 1 

# weights:  103
initial  value 94.856208 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.731769 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.480401 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.720082 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.492627 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.318413 
iter  10 value 87.493968
iter  20 value 84.275437
iter  30 value 83.631329
iter  40 value 83.625847
final  value 83.625833 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.729522 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.244203 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.377874 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.231316 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  507
initial  value 118.024879 
iter  10 value 94.294335
final  value 94.294332 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.086852 
final  value 94.476471 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.425888 
iter  10 value 94.466823
iter  10 value 94.466823
iter  10 value 94.466823
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  507
initial  value 107.949853 
final  value 94.214007 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.172979 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.957090 
iter  10 value 94.480706
iter  20 value 93.948113
iter  30 value 93.797200
iter  40 value 93.230448
iter  50 value 90.020447
iter  60 value 89.494591
iter  70 value 84.926336
iter  80 value 83.780266
iter  90 value 82.124914
iter 100 value 81.404059
final  value 81.404059 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.012707 
iter  10 value 94.487311
iter  20 value 94.387753
iter  30 value 93.264466
iter  40 value 85.854930
iter  50 value 85.655977
iter  60 value 85.508030
iter  70 value 84.484923
iter  80 value 83.213714
iter  90 value 83.150624
iter 100 value 83.150208
final  value 83.150208 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.639167 
iter  10 value 94.465540
iter  20 value 93.975282
iter  30 value 93.751114
iter  40 value 93.668457
iter  50 value 90.606671
iter  60 value 84.756944
iter  70 value 84.478813
iter  80 value 82.127416
iter  90 value 81.366919
iter 100 value 80.975783
final  value 80.975783 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.588765 
iter  10 value 94.492096
iter  20 value 93.972530
iter  30 value 89.445502
iter  40 value 87.844276
iter  50 value 87.027573
iter  60 value 86.925633
iter  70 value 86.812617
iter  80 value 86.771190
iter  90 value 86.659820
final  value 86.651629 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.055195 
iter  10 value 92.961919
iter  20 value 91.286112
iter  30 value 90.340661
iter  40 value 89.807421
iter  50 value 89.795118
final  value 89.795104 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.633792 
iter  10 value 94.560665
iter  20 value 91.289722
iter  30 value 87.972921
iter  40 value 86.619332
iter  50 value 84.603093
iter  60 value 82.565705
iter  70 value 80.612424
iter  80 value 79.943458
iter  90 value 79.843809
iter 100 value 79.604698
final  value 79.604698 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.399937 
iter  10 value 94.471894
iter  20 value 89.971414
iter  30 value 85.399502
iter  40 value 83.145960
iter  50 value 80.902709
iter  60 value 80.051376
iter  70 value 79.928277
iter  80 value 79.897327
iter  90 value 79.788803
iter 100 value 79.638108
final  value 79.638108 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 114.211868 
iter  10 value 94.464863
iter  20 value 90.785848
iter  30 value 87.801770
iter  40 value 84.957381
iter  50 value 83.751319
iter  60 value 82.436290
iter  70 value 81.809287
iter  80 value 81.576065
iter  90 value 81.371151
iter 100 value 81.239922
final  value 81.239922 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 129.106244 
iter  10 value 94.422068
iter  20 value 87.741248
iter  30 value 84.880894
iter  40 value 84.489251
iter  50 value 83.800793
iter  60 value 83.178024
iter  70 value 82.720428
iter  80 value 81.677572
iter  90 value 81.413183
iter 100 value 81.363216
final  value 81.363216 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 110.530867 
iter  10 value 94.495171
iter  20 value 88.678034
iter  30 value 86.693841
iter  40 value 86.601025
iter  50 value 86.442739
iter  60 value 86.305936
iter  70 value 86.095106
iter  80 value 83.553934
iter  90 value 82.449261
iter 100 value 82.333615
final  value 82.333615 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 101.759731 
iter  10 value 94.647769
iter  20 value 89.020483
iter  30 value 85.599152
iter  40 value 82.823393
iter  50 value 81.753508
iter  60 value 80.727834
iter  70 value 80.181218
iter  80 value 79.629331
iter  90 value 79.408135
iter 100 value 79.372222
final  value 79.372222 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 128.882356 
iter  10 value 94.511044
iter  20 value 94.220901
iter  30 value 94.049794
iter  40 value 89.084221
iter  50 value 85.915227
iter  60 value 83.707875
iter  70 value 81.609950
iter  80 value 80.090578
iter  90 value 79.959902
iter 100 value 79.901487
final  value 79.901487 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.891491 
iter  10 value 95.141419
iter  20 value 94.886142
iter  30 value 93.964875
iter  40 value 90.694169
iter  50 value 88.541770
iter  60 value 88.412297
iter  70 value 86.713764
iter  80 value 83.535816
iter  90 value 83.409446
iter 100 value 83.108211
final  value 83.108211 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.136265 
iter  10 value 94.588672
iter  20 value 93.157842
iter  30 value 92.229438
iter  40 value 90.371438
iter  50 value 84.461785
iter  60 value 82.501351
iter  70 value 81.758870
iter  80 value 81.573089
iter  90 value 81.375924
iter 100 value 81.197000
final  value 81.197000 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.920365 
iter  10 value 94.718175
iter  20 value 86.155595
iter  30 value 81.787201
iter  40 value 80.927446
iter  50 value 80.323699
iter  60 value 79.608679
iter  70 value 79.458376
iter  80 value 79.405187
iter  90 value 79.389421
iter 100 value 79.323786
final  value 79.323786 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 108.385441 
iter  10 value 94.485905
iter  20 value 94.484211
iter  30 value 94.187431
iter  40 value 93.533508
final  value 93.532734 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.620049 
iter  10 value 94.485718
iter  20 value 94.484216
iter  30 value 89.481766
iter  40 value 89.144991
final  value 89.140664 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.885832 
iter  10 value 94.485941
iter  20 value 94.484273
iter  30 value 93.922463
final  value 93.922441 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.829164 
final  value 94.468329 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.727813 
iter  10 value 94.485753
iter  20 value 94.480917
iter  30 value 94.204790
iter  40 value 92.753565
iter  50 value 90.115840
iter  60 value 88.914803
iter  70 value 85.180808
iter  80 value 85.179903
iter  90 value 85.179665
final  value 85.179660 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.179698 
iter  10 value 94.489189
iter  20 value 94.431085
iter  30 value 93.854990
iter  40 value 93.164513
iter  50 value 93.140666
iter  60 value 92.765097
iter  70 value 92.753078
iter  80 value 92.751245
iter  90 value 92.750040
final  value 92.748916 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.116657 
iter  10 value 94.488852
iter  20 value 94.484466
iter  30 value 89.443217
iter  40 value 89.406599
iter  50 value 89.357890
iter  60 value 87.989892
iter  70 value 87.977558
iter  80 value 87.977170
iter  90 value 84.033093
iter 100 value 81.257105
final  value 81.257105 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.825072 
iter  10 value 94.471735
iter  20 value 94.265833
iter  30 value 91.244957
iter  40 value 87.544510
iter  50 value 86.327210
iter  60 value 86.184249
iter  70 value 86.183546
iter  80 value 85.176433
iter  90 value 84.937418
final  value 84.935594 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.800699 
iter  10 value 94.286707
iter  20 value 93.166973
iter  30 value 93.163948
iter  40 value 93.157590
iter  50 value 93.156881
final  value 93.156795 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.070249 
iter  10 value 94.490679
iter  20 value 94.485899
iter  30 value 92.961956
iter  40 value 89.969175
iter  50 value 89.898265
iter  60 value 89.885487
iter  70 value 89.842844
iter  80 value 89.840945
iter  80 value 89.840944
iter  90 value 89.839104
iter 100 value 89.829983
final  value 89.829983 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 121.418722 
iter  10 value 94.493520
iter  20 value 94.485579
iter  30 value 94.481127
iter  40 value 92.127936
iter  50 value 91.566316
iter  60 value 91.112556
iter  70 value 90.935065
iter  80 value 90.930997
final  value 90.929901 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.019037 
iter  10 value 92.638904
iter  20 value 91.731865
iter  30 value 89.876890
iter  40 value 89.872691
iter  50 value 89.440780
iter  60 value 89.402363
iter  70 value 89.391480
iter  80 value 89.391173
iter  90 value 87.919987
iter 100 value 87.741696
final  value 87.741696 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.249889 
iter  10 value 94.336457
iter  20 value 88.052824
iter  30 value 86.562811
iter  40 value 86.352793
iter  50 value 86.191658
iter  60 value 86.190383
iter  70 value 86.182711
iter  80 value 85.389719
iter  90 value 83.612179
iter 100 value 83.611747
final  value 83.611747 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 98.077051 
iter  10 value 94.491870
iter  20 value 94.479985
iter  30 value 93.980667
iter  40 value 93.810029
iter  50 value 91.942365
iter  60 value 87.560322
iter  70 value 83.306684
iter  80 value 83.289985
iter  90 value 80.871267
iter 100 value 80.782300
final  value 80.782300 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 99.363021 
iter  10 value 94.492311
iter  20 value 90.874915
iter  30 value 88.277288
iter  40 value 88.263145
iter  50 value 88.131756
final  value 88.130616 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.378821 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.719236 
iter  10 value 93.828915
final  value 93.828167 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.506003 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 108.458977 
iter  10 value 88.377121
iter  20 value 87.195991
iter  30 value 87.160261
iter  40 value 85.488453
iter  50 value 85.322578
final  value 85.312893 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.511114 
final  value 93.356643 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.318961 
final  value 93.628453 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.828501 
iter  10 value 94.053168
final  value 94.052911 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.610800 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.703806 
iter  10 value 93.477887
final  value 93.034769 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.885401 
final  value 93.836066 
converged
Fitting Repeat 1 

# weights:  507
initial  value 110.666877 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.422216 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.954993 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 127.920181 
iter  10 value 88.304221
iter  20 value 85.490174
iter  30 value 85.480521
final  value 85.480503 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.494414 
final  value 93.104644 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.363325 
iter  10 value 94.055640
iter  20 value 93.241305
iter  30 value 93.135650
iter  40 value 93.129067
iter  50 value 93.128630
final  value 93.128217 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.032525 
iter  10 value 93.426285
iter  20 value 93.200003
iter  30 value 93.134138
iter  40 value 90.757274
iter  50 value 86.999374
iter  60 value 86.842573
iter  70 value 84.173763
iter  80 value 83.606550
iter  90 value 83.515699
iter 100 value 83.501659
final  value 83.501659 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 102.027658 
iter  10 value 92.874671
iter  20 value 87.010672
iter  30 value 84.499617
iter  40 value 83.686726
final  value 83.684987 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.318231 
iter  10 value 93.716086
iter  20 value 90.391711
iter  30 value 89.084038
iter  40 value 87.858294
iter  50 value 87.399222
iter  60 value 86.889047
iter  70 value 86.865304
iter  80 value 86.853892
final  value 86.853297 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.190448 
iter  10 value 93.998804
iter  20 value 87.034116
iter  30 value 84.637647
iter  40 value 84.441982
iter  50 value 84.036994
iter  60 value 83.962645
final  value 83.962500 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.437775 
iter  10 value 94.143946
iter  20 value 91.654249
iter  30 value 87.379681
iter  40 value 85.744026
iter  50 value 85.039346
iter  60 value 84.555016
iter  70 value 84.231106
iter  80 value 83.883526
iter  90 value 83.628520
iter 100 value 82.522998
final  value 82.522998 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.056232 
iter  10 value 91.907363
iter  20 value 86.848798
iter  30 value 85.681122
iter  40 value 83.772682
iter  50 value 83.075390
iter  60 value 81.781330
iter  70 value 81.301184
iter  80 value 81.025706
iter  90 value 80.971973
iter 100 value 80.957068
final  value 80.957068 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.385345 
iter  10 value 94.071691
iter  20 value 93.420243
iter  30 value 87.167690
iter  40 value 85.080175
iter  50 value 83.773822
iter  60 value 82.387483
iter  70 value 81.991776
iter  80 value 81.562225
iter  90 value 81.401810
iter 100 value 81.316596
final  value 81.316596 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.054741 
iter  10 value 92.595976
iter  20 value 86.942557
iter  30 value 86.043531
iter  40 value 83.748341
iter  50 value 82.429165
iter  60 value 81.687077
iter  70 value 81.466386
iter  80 value 81.293184
iter  90 value 80.945648
iter 100 value 80.908534
final  value 80.908534 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.374237 
iter  10 value 93.234868
iter  20 value 88.681189
iter  30 value 85.025760
iter  40 value 84.187201
iter  50 value 83.744648
iter  60 value 83.659078
iter  70 value 82.994559
iter  80 value 82.037972
iter  90 value 81.577583
iter 100 value 81.432977
final  value 81.432977 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 115.731391 
iter  10 value 93.540051
iter  20 value 90.444691
iter  30 value 87.141942
iter  40 value 85.708253
iter  50 value 84.158880
iter  60 value 83.006516
iter  70 value 82.291753
iter  80 value 81.567118
iter  90 value 81.368210
iter 100 value 81.287092
final  value 81.287092 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.236197 
iter  10 value 93.821506
iter  20 value 87.559505
iter  30 value 87.202229
iter  40 value 86.493154
iter  50 value 84.674757
iter  60 value 83.251218
iter  70 value 82.858007
iter  80 value 82.396271
iter  90 value 82.296799
iter 100 value 82.281470
final  value 82.281470 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.690392 
iter  10 value 94.408186
iter  20 value 93.816873
iter  30 value 87.382335
iter  40 value 86.208621
iter  50 value 84.619202
iter  60 value 83.660011
iter  70 value 82.466582
iter  80 value 81.342500
iter  90 value 80.991376
iter 100 value 80.881120
final  value 80.881120 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.442434 
iter  10 value 96.061643
iter  20 value 93.291155
iter  30 value 93.136209
iter  40 value 88.089875
iter  50 value 86.631197
iter  60 value 85.955104
iter  70 value 83.725028
iter  80 value 83.483926
iter  90 value 82.725917
iter 100 value 82.157514
final  value 82.157514 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 124.395013 
iter  10 value 94.412901
iter  20 value 93.478853
iter  30 value 90.414017
iter  40 value 89.603160
iter  50 value 88.745209
iter  60 value 86.891081
iter  70 value 84.695067
iter  80 value 84.220350
iter  90 value 82.973275
iter 100 value 82.273007
final  value 82.273007 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.460606 
final  value 94.054525 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.609210 
final  value 94.054495 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.296724 
iter  10 value 94.054601
iter  20 value 94.052952
iter  30 value 93.859674
iter  40 value 93.358788
final  value 93.357208 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.688394 
final  value 94.054688 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.958773 
final  value 94.054825 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.539546 
iter  10 value 93.361734
iter  20 value 93.321128
iter  30 value 91.571674
iter  40 value 91.569398
iter  50 value 91.568664
iter  60 value 91.287484
iter  70 value 87.875469
iter  80 value 84.406919
iter  90 value 82.044381
iter 100 value 81.404705
final  value 81.404705 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.721278 
iter  10 value 93.844774
iter  20 value 93.122446
iter  30 value 90.370633
iter  40 value 90.158363
iter  50 value 90.003175
iter  60 value 90.001486
iter  70 value 89.883052
iter  80 value 89.869005
final  value 89.868944 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.410925 
iter  10 value 93.110016
iter  20 value 93.105327
iter  30 value 93.024169
iter  40 value 91.770595
iter  50 value 85.586723
iter  60 value 84.808424
iter  70 value 84.726246
iter  80 value 84.661668
final  value 84.661049 
converged
Fitting Repeat 4 

# weights:  305
initial  value 113.591599 
iter  10 value 94.057939
iter  20 value 94.039677
iter  30 value 86.015386
iter  40 value 85.754836
iter  50 value 85.749973
final  value 85.749966 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.950856 
iter  10 value 88.372688
iter  20 value 88.029205
iter  30 value 85.819676
iter  40 value 85.562634
iter  50 value 85.562044
iter  60 value 85.158715
iter  70 value 84.508058
iter  80 value 84.474819
iter  90 value 84.474705
final  value 84.474704 
converged
Fitting Repeat 1 

# weights:  507
initial  value 124.652595 
iter  10 value 93.845234
iter  20 value 93.838798
iter  30 value 92.714644
iter  40 value 86.225508
iter  50 value 85.863823
iter  60 value 83.286660
iter  70 value 82.941167
iter  80 value 82.939829
final  value 82.939382 
converged
Fitting Repeat 2 

# weights:  507
initial  value 110.401169 
iter  10 value 94.060196
iter  20 value 94.047775
iter  30 value 93.360381
iter  40 value 93.340962
final  value 93.105461 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.559856 
iter  10 value 94.060410
iter  20 value 94.053038
iter  30 value 93.163417
iter  40 value 85.304286
iter  50 value 84.717080
final  value 84.685901 
converged
Fitting Repeat 4 

# weights:  507
initial  value 107.358028 
iter  10 value 94.061737
iter  20 value 94.053023
iter  30 value 93.193514
final  value 93.091058 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.653112 
iter  10 value 93.310174
iter  20 value 88.739044
iter  30 value 84.313695
iter  40 value 83.273416
iter  50 value 83.261506
iter  60 value 83.260605
iter  70 value 82.772212
iter  80 value 82.731431
iter  90 value 82.132430
iter 100 value 81.778440
final  value 81.778440 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 125.743977 
iter  10 value 115.841947
iter  20 value 114.526436
iter  30 value 113.766291
iter  40 value 112.949537
iter  50 value 109.583151
iter  60 value 106.156079
iter  70 value 104.586664
iter  80 value 103.314101
iter  90 value 102.321153
iter 100 value 101.317691
final  value 101.317691 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 164.371029 
iter  10 value 117.933587
iter  20 value 111.904106
iter  30 value 110.797246
iter  40 value 108.595293
iter  50 value 103.578988
iter  60 value 101.919954
iter  70 value 101.398453
iter  80 value 101.082780
iter  90 value 101.014107
iter 100 value 100.926521
final  value 100.926521 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 132.688098 
iter  10 value 119.185247
iter  20 value 117.776146
iter  30 value 115.554229
iter  40 value 108.738854
iter  50 value 108.259775
iter  60 value 106.372323
iter  70 value 104.352055
iter  80 value 102.776476
iter  90 value 102.540723
iter 100 value 101.861699
final  value 101.861699 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 133.826404 
iter  10 value 118.408582
iter  20 value 117.599866
iter  30 value 111.773152
iter  40 value 107.809238
iter  50 value 105.627779
iter  60 value 104.115374
iter  70 value 102.527219
iter  80 value 101.951870
iter  90 value 101.452977
iter 100 value 100.674652
final  value 100.674652 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 156.126315 
iter  10 value 117.913658
iter  20 value 115.514045
iter  30 value 110.687995
iter  40 value 107.520580
iter  50 value 106.769611
iter  60 value 104.577230
iter  70 value 103.583781
iter  80 value 103.099960
iter  90 value 101.974128
iter 100 value 101.733328
final  value 101.733328 
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 -- Thu Mar 20 23:06:12 2025 
*********************************************** 
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 
 40.958   1.409 151.594