##############################################################################
##############################################################################
###
### 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 4.4.2 (2024-10-31)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 13.2.0-23ubuntu4) 13.2.0
    GNU Fortran (Ubuntu 13.2.0-23ubuntu4) 13.2.0
* running under: Ubuntu 24.04.1 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       35.247  0.535  35.793
FSmethod      33.850  0.436  34.288
corr_plot     33.339  0.086  33.426
pred_ensembel 12.777  0.261  11.773
enrichfindP    0.501  0.029   8.911
* 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 4.4.2 (2024-10-31) -- "Pile of Leaves"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

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

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

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

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

# weights:  103
initial  value 95.815741 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.180058 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.698753 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.399235 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.755851 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.524986 
iter  10 value 87.950318
iter  20 value 86.931003
iter  30 value 86.604768
final  value 86.604706 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.024877 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 112.596951 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.415640 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.148633 
final  value 93.582418 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.717616 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.703311 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.554358 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.036339 
iter  10 value 93.309958
final  value 93.301231 
converged
Fitting Repeat 5 

# weights:  507
initial  value 120.632648 
iter  10 value 94.100716
final  value 94.052911 
converged
Fitting Repeat 1 

# weights:  103
initial  value 106.095575 
iter  10 value 93.759347
iter  20 value 85.359542
iter  30 value 84.811947
iter  40 value 83.852867
iter  50 value 83.364288
iter  60 value 82.871377
iter  70 value 82.372699
iter  80 value 82.340454
final  value 82.340452 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.579485 
iter  10 value 93.796947
iter  20 value 87.458938
iter  30 value 86.252267
iter  40 value 86.085206
iter  50 value 85.640409
iter  60 value 85.471785
iter  70 value 85.467357
final  value 85.466123 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.612024 
iter  10 value 93.891111
iter  20 value 86.121138
iter  30 value 83.939430
iter  40 value 83.537212
iter  50 value 82.648314
iter  60 value 82.397934
iter  70 value 82.335215
final  value 82.334912 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.015123 
iter  10 value 94.055046
iter  20 value 93.692604
iter  30 value 93.684504
iter  40 value 93.635731
iter  50 value 93.450814
iter  60 value 92.790796
iter  70 value 88.091262
iter  80 value 84.639578
iter  90 value 83.872588
iter 100 value 83.518883
final  value 83.518883 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 107.482953 
iter  10 value 93.801543
iter  20 value 88.560994
iter  30 value 85.609904
iter  40 value 83.632791
iter  50 value 83.054878
iter  60 value 82.232013
iter  70 value 82.142909
iter  80 value 82.116766
iter  90 value 82.095088
final  value 82.091655 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.225619 
iter  10 value 93.934910
iter  20 value 93.462329
iter  30 value 93.313269
iter  40 value 90.228857
iter  50 value 86.427502
iter  60 value 86.272453
iter  70 value 86.091886
iter  80 value 85.807102
iter  90 value 84.428305
iter 100 value 83.225019
final  value 83.225019 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.294646 
iter  10 value 93.854501
iter  20 value 90.367009
iter  30 value 88.297788
iter  40 value 87.414431
iter  50 value 86.300458
iter  60 value 84.711735
iter  70 value 84.217563
iter  80 value 83.050415
iter  90 value 82.477568
iter 100 value 81.785148
final  value 81.785148 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.006295 
iter  10 value 93.925142
iter  20 value 85.615333
iter  30 value 84.624719
iter  40 value 83.755988
iter  50 value 83.022638
iter  60 value 82.501430
iter  70 value 82.054631
iter  80 value 81.443270
iter  90 value 81.126209
iter 100 value 81.048715
final  value 81.048715 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.204920 
iter  10 value 94.002047
iter  20 value 90.476271
iter  30 value 87.522762
iter  40 value 85.593976
iter  50 value 83.131515
iter  60 value 82.800914
iter  70 value 82.388908
iter  80 value 81.370205
iter  90 value 80.984055
iter 100 value 80.897236
final  value 80.897236 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.682347 
iter  10 value 93.849233
iter  20 value 93.463867
iter  30 value 92.764382
iter  40 value 90.140757
iter  50 value 89.710023
iter  60 value 85.927377
iter  70 value 84.482761
iter  80 value 84.045489
iter  90 value 83.537308
iter 100 value 83.336751
final  value 83.336751 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 114.088658 
iter  10 value 94.165759
iter  20 value 92.240242
iter  30 value 92.012066
iter  40 value 88.853162
iter  50 value 85.164215
iter  60 value 84.551080
iter  70 value 84.334933
iter  80 value 83.937825
iter  90 value 83.841052
iter 100 value 83.500898
final  value 83.500898 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.579742 
iter  10 value 92.595772
iter  20 value 85.373643
iter  30 value 83.473043
iter  40 value 83.345177
iter  50 value 83.257186
iter  60 value 82.387300
iter  70 value 81.592773
iter  80 value 81.019691
iter  90 value 80.883527
iter 100 value 80.692893
final  value 80.692893 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.112497 
iter  10 value 94.291662
iter  20 value 91.749708
iter  30 value 85.367251
iter  40 value 85.139161
iter  50 value 84.919857
iter  60 value 84.020991
iter  70 value 83.239995
iter  80 value 82.831472
iter  90 value 82.780978
iter 100 value 82.751734
final  value 82.751734 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.417992 
iter  10 value 93.832378
iter  20 value 91.540858
iter  30 value 86.120195
iter  40 value 84.302553
iter  50 value 82.954426
iter  60 value 82.167987
iter  70 value 82.004296
iter  80 value 81.669632
iter  90 value 81.381912
iter 100 value 81.295729
final  value 81.295729 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.004846 
iter  10 value 94.333135
iter  20 value 88.990446
iter  30 value 84.658337
iter  40 value 83.710087
iter  50 value 83.624739
iter  60 value 83.610345
iter  70 value 83.574659
iter  80 value 83.391861
iter  90 value 82.979027
iter 100 value 82.356123
final  value 82.356123 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 107.583411 
final  value 94.054515 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.197375 
final  value 94.054663 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.338563 
final  value 94.054645 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.930801 
final  value 94.054798 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.574638 
final  value 94.054598 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.622657 
iter  10 value 93.876277
iter  20 value 92.817707
iter  30 value 88.018949
iter  40 value 87.947444
iter  50 value 87.939488
iter  60 value 86.448707
iter  70 value 85.762249
iter  80 value 85.685769
iter  90 value 85.612313
final  value 85.612265 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.798856 
iter  10 value 93.565631
iter  20 value 93.415430
iter  30 value 93.410619
iter  40 value 87.070502
iter  50 value 83.615494
iter  60 value 83.400243
iter  70 value 83.077770
iter  80 value 82.869893
iter  90 value 82.427448
iter 100 value 82.067240
final  value 82.067240 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.081440 
iter  10 value 93.371129
iter  20 value 93.369127
iter  30 value 93.366149
iter  40 value 93.291022
iter  50 value 86.465310
iter  60 value 85.267811
iter  70 value 82.061499
iter  80 value 80.245819
iter  90 value 80.036906
iter 100 value 79.965300
final  value 79.965300 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.475771 
iter  10 value 93.844389
iter  20 value 91.719410
iter  30 value 87.277275
final  value 87.277090 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.318053 
iter  10 value 93.894896
iter  20 value 93.368464
iter  30 value 85.892299
iter  40 value 85.869783
iter  50 value 85.850610
iter  60 value 85.288660
iter  70 value 84.951970
final  value 84.950898 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.860574 
iter  10 value 94.061132
iter  20 value 94.000959
iter  30 value 92.449257
iter  40 value 84.407405
iter  50 value 84.312740
iter  60 value 84.284145
final  value 84.279610 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.064178 
iter  10 value 93.385869
iter  20 value 93.380734
iter  30 value 93.302970
iter  40 value 93.302621
iter  50 value 93.299819
iter  60 value 89.710064
iter  70 value 89.123510
iter  80 value 83.282200
iter  90 value 80.866721
iter 100 value 80.732359
final  value 80.732359 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 95.714412 
iter  10 value 94.061412
iter  20 value 94.042344
iter  30 value 93.622847
iter  40 value 88.637292
iter  50 value 88.042872
iter  60 value 87.961633
iter  70 value 87.949257
iter  80 value 87.945394
iter  90 value 84.494301
iter 100 value 84.443961
final  value 84.443961 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 101.205080 
iter  10 value 93.617350
iter  20 value 93.612402
iter  30 value 93.606860
iter  40 value 93.561187
final  value 93.528787 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.110723 
iter  10 value 93.863130
iter  20 value 93.374786
iter  30 value 92.953188
iter  40 value 84.075396
iter  50 value 83.469502
iter  60 value 83.036741
iter  70 value 83.035075
iter  80 value 83.033753
iter  90 value 82.676275
iter 100 value 82.458036
final  value 82.458036 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.537587 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.496429 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 109.576361 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.245621 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.171850 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.339334 
iter  10 value 94.482393
final  value 94.482149 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.544659 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 130.499289 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 108.912360 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.753568 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.720609 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.098210 
iter  10 value 94.116364
iter  20 value 87.301514
iter  30 value 85.516226
iter  40 value 85.511292
final  value 85.511214 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.531979 
iter  10 value 87.599676
iter  20 value 84.055351
iter  30 value 83.540884
iter  40 value 83.531195
iter  50 value 83.111052
iter  60 value 82.985814
final  value 82.985738 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.117562 
iter  10 value 93.690012
final  value 93.654971 
converged
Fitting Repeat 5 

# weights:  507
initial  value 115.568512 
iter  10 value 94.443244
iter  10 value 94.443244
iter  10 value 94.443244
final  value 94.443244 
converged
Fitting Repeat 1 

# weights:  103
initial  value 108.724747 
iter  10 value 94.452911
iter  20 value 94.003881
iter  30 value 93.173373
iter  40 value 85.879860
iter  50 value 85.257532
iter  60 value 84.459967
iter  70 value 84.060598
iter  80 value 83.468332
iter  90 value 83.204432
iter 100 value 82.171664
final  value 82.171664 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.554022 
iter  10 value 94.484779
iter  20 value 92.074781
iter  30 value 85.982751
iter  40 value 84.724544
iter  50 value 84.257015
iter  60 value 84.130569
final  value 84.130053 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.431276 
iter  10 value 94.428849
iter  20 value 89.727671
iter  30 value 87.090393
iter  40 value 84.308621
iter  50 value 83.548748
iter  60 value 82.456795
iter  70 value 81.506697
iter  80 value 81.480671
iter  90 value 81.452628
final  value 81.452607 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.533053 
iter  10 value 94.433274
iter  20 value 89.321340
iter  30 value 88.276728
iter  40 value 87.984014
iter  50 value 87.879901
iter  60 value 87.442283
iter  70 value 87.125316
iter  80 value 84.067331
iter  90 value 83.718660
iter 100 value 83.711956
final  value 83.711956 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 103.649321 
iter  10 value 94.292141
iter  20 value 91.332603
iter  30 value 88.300622
iter  40 value 85.672603
iter  50 value 83.278190
iter  60 value 82.320171
iter  70 value 82.037444
iter  80 value 81.773906
iter  90 value 81.608298
iter 100 value 81.588819
final  value 81.588819 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 101.797805 
iter  10 value 94.544529
iter  20 value 90.824883
iter  30 value 90.087602
iter  40 value 88.006561
iter  50 value 84.439837
iter  60 value 83.088992
iter  70 value 82.778523
iter  80 value 82.691913
iter  90 value 82.491189
iter 100 value 81.726073
final  value 81.726073 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.773242 
iter  10 value 94.416803
iter  20 value 91.711476
iter  30 value 89.878235
iter  40 value 89.432802
iter  50 value 87.350949
iter  60 value 84.106622
iter  70 value 82.917035
iter  80 value 82.649718
iter  90 value 81.832560
iter 100 value 80.803835
final  value 80.803835 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 113.901701 
iter  10 value 94.383092
iter  20 value 93.052030
iter  30 value 91.436288
iter  40 value 91.111005
iter  50 value 90.995424
iter  60 value 88.021141
iter  70 value 83.301127
iter  80 value 83.222889
iter  90 value 82.765992
iter 100 value 82.031134
final  value 82.031134 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.675489 
iter  10 value 92.304666
iter  20 value 91.854885
iter  30 value 88.794449
iter  40 value 83.557279
iter  50 value 82.714891
iter  60 value 81.292137
iter  70 value 80.650399
iter  80 value 80.441314
iter  90 value 80.373582
iter 100 value 80.250199
final  value 80.250199 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.829141 
iter  10 value 94.486067
iter  20 value 92.576363
iter  30 value 85.719814
iter  40 value 84.555227
iter  50 value 82.028854
iter  60 value 81.367885
iter  70 value 80.779470
iter  80 value 80.629899
iter  90 value 80.571689
iter 100 value 80.569574
final  value 80.569574 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 122.195007 
iter  10 value 93.955329
iter  20 value 91.516735
iter  30 value 86.053535
iter  40 value 82.119182
iter  50 value 80.692080
iter  60 value 80.454258
iter  70 value 80.336948
iter  80 value 80.119112
iter  90 value 80.021052
iter 100 value 79.952228
final  value 79.952228 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.073517 
iter  10 value 93.171100
iter  20 value 91.807415
iter  30 value 87.175226
iter  40 value 84.277901
iter  50 value 83.297987
iter  60 value 82.843186
iter  70 value 82.369792
iter  80 value 81.669578
iter  90 value 80.685766
iter 100 value 80.227132
final  value 80.227132 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.911541 
iter  10 value 94.889373
iter  20 value 93.825151
iter  30 value 87.404698
iter  40 value 85.045612
iter  50 value 83.414484
iter  60 value 81.693856
iter  70 value 80.947597
iter  80 value 80.240038
iter  90 value 80.179698
iter 100 value 79.974974
final  value 79.974974 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.386310 
iter  10 value 94.662440
iter  20 value 93.499569
iter  30 value 92.509929
iter  40 value 91.291952
iter  50 value 85.578392
iter  60 value 84.936741
iter  70 value 84.577868
iter  80 value 83.660796
iter  90 value 83.502266
iter 100 value 83.047987
final  value 83.047987 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 127.055930 
iter  10 value 94.421967
iter  20 value 87.553306
iter  30 value 85.831386
iter  40 value 84.728973
iter  50 value 84.523455
iter  60 value 83.964536
iter  70 value 81.410756
iter  80 value 81.184954
iter  90 value 80.660712
iter 100 value 80.120203
final  value 80.120203 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.115527 
final  value 94.486089 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.951491 
final  value 94.485714 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.017129 
final  value 94.485769 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.295116 
final  value 94.114627 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.289873 
final  value 94.485711 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.463504 
iter  10 value 94.488370
iter  20 value 94.355442
iter  30 value 86.646314
iter  40 value 85.749617
iter  50 value 85.228793
iter  60 value 83.956463
iter  70 value 83.936717
iter  80 value 83.841871
iter  90 value 83.792407
iter 100 value 83.764193
final  value 83.764193 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 98.510530 
iter  10 value 94.487956
iter  20 value 94.484219
final  value 94.484214 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.845775 
iter  10 value 90.294908
iter  20 value 88.737566
iter  30 value 86.812511
iter  40 value 86.730178
iter  50 value 85.954198
iter  60 value 85.950733
final  value 85.946596 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.623070 
iter  10 value 94.448023
iter  20 value 94.369236
final  value 93.703147 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.546814 
iter  10 value 93.112956
iter  20 value 88.637095
iter  30 value 88.315533
iter  40 value 88.314439
iter  50 value 88.236186
iter  60 value 88.169899
iter  70 value 88.168708
final  value 88.166630 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.614722 
iter  10 value 88.094465
iter  20 value 82.376320
iter  30 value 81.696072
iter  40 value 81.579647
iter  50 value 80.581426
iter  60 value 80.536047
iter  70 value 80.519295
iter  80 value 80.288298
iter  90 value 79.637122
iter 100 value 79.598399
final  value 79.598399 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 96.856780 
iter  10 value 88.148815
iter  20 value 83.796908
iter  30 value 83.789742
iter  40 value 83.784009
iter  50 value 83.782886
iter  60 value 83.540412
iter  70 value 83.422141
iter  80 value 83.418850
iter  90 value 83.401490
iter 100 value 83.191967
final  value 83.191967 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 95.902934 
iter  10 value 93.681059
iter  20 value 93.673449
iter  30 value 86.540382
iter  40 value 84.241746
iter  50 value 83.782041
iter  60 value 83.778492
final  value 83.778401 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.478107 
iter  10 value 94.492148
iter  20 value 94.466221
final  value 94.166051 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.814184 
iter  10 value 94.492691
iter  20 value 94.485861
iter  30 value 94.333035
iter  40 value 84.750598
iter  50 value 83.794782
iter  60 value 83.789210
iter  70 value 83.785496
iter  80 value 83.780513
iter  90 value 83.760004
iter 100 value 83.605960
final  value 83.605960 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.507873 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.438051 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.741235 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.702306 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.334457 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.084936 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.933518 
final  value 93.836066 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.707835 
iter  10 value 93.836066
iter  10 value 93.836066
iter  10 value 93.836066
final  value 93.836066 
converged
Fitting Repeat 4 

# weights:  305
initial  value 122.704248 
iter  10 value 93.836068
final  value 93.836066 
converged
Fitting Repeat 5 

# weights:  305
initial  value 119.275882 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 118.754370 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 112.928206 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.483145 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 119.439181 
iter  10 value 93.836084
final  value 93.836066 
converged
Fitting Repeat 5 

# weights:  507
initial  value 92.721070 
iter  10 value 86.458025
iter  20 value 85.971045
iter  30 value 85.970229
iter  30 value 85.970228
iter  30 value 85.970228
final  value 85.970228 
converged
Fitting Repeat 1 

# weights:  103
initial  value 107.652422 
iter  10 value 94.114022
iter  20 value 94.044205
iter  30 value 93.477867
iter  40 value 93.468042
iter  50 value 93.446905
iter  60 value 90.476405
iter  70 value 87.921241
iter  80 value 86.200607
iter  90 value 82.881681
iter 100 value 82.163914
final  value 82.163914 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.239769 
iter  10 value 94.056504
iter  20 value 93.907023
iter  30 value 93.889419
iter  40 value 93.817656
iter  50 value 92.565820
iter  60 value 91.457933
iter  70 value 91.161407
iter  80 value 91.141783
final  value 91.141589 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.277364 
iter  10 value 94.085117
iter  20 value 93.730805
iter  30 value 93.519729
iter  40 value 93.447777
iter  50 value 88.918339
iter  60 value 86.255435
iter  70 value 86.101001
iter  80 value 85.246586
iter  90 value 84.403145
iter 100 value 84.284784
final  value 84.284784 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.235218 
iter  10 value 89.981007
iter  20 value 85.028851
iter  30 value 84.901868
iter  40 value 82.548438
iter  50 value 81.700516
iter  60 value 81.377434
iter  70 value 81.276765
iter  80 value 81.268834
iter  80 value 81.268834
iter  80 value 81.268834
final  value 81.268834 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.155182 
iter  10 value 94.055254
iter  20 value 93.754458
iter  30 value 93.569702
iter  40 value 86.584565
iter  50 value 86.068073
iter  60 value 85.967725
iter  70 value 84.615654
iter  80 value 84.050634
iter  90 value 83.809731
iter 100 value 83.808298
final  value 83.808298 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 101.282398 
iter  10 value 94.106124
iter  20 value 91.525092
iter  30 value 86.484144
iter  40 value 84.298875
iter  50 value 84.091201
iter  60 value 82.702079
iter  70 value 81.270819
iter  80 value 80.551186
iter  90 value 80.290419
iter 100 value 79.929488
final  value 79.929488 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.912163 
iter  10 value 90.318242
iter  20 value 87.284214
iter  30 value 87.046893
iter  40 value 85.261067
iter  50 value 83.139465
iter  60 value 82.902099
iter  70 value 82.303925
iter  80 value 82.081367
iter  90 value 82.033373
iter 100 value 81.898269
final  value 81.898269 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 111.321031 
iter  10 value 93.970155
iter  20 value 93.079891
iter  30 value 90.532684
iter  40 value 86.115633
iter  50 value 84.584244
iter  60 value 84.039804
iter  70 value 83.568704
iter  80 value 81.713723
iter  90 value 81.364319
iter 100 value 81.110012
final  value 81.110012 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 119.699234 
iter  10 value 90.844229
iter  20 value 86.254217
iter  30 value 85.972718
iter  40 value 83.101565
iter  50 value 82.759954
iter  60 value 82.362511
iter  70 value 81.712608
iter  80 value 80.292455
iter  90 value 80.191701
iter 100 value 80.179916
final  value 80.179916 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.789358 
iter  10 value 92.086698
iter  20 value 86.333697
iter  30 value 85.929259
iter  40 value 84.279438
iter  50 value 82.295015
iter  60 value 81.745237
iter  70 value 80.309957
iter  80 value 79.909564
iter  90 value 79.711779
iter 100 value 79.655647
final  value 79.655647 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.079256 
iter  10 value 94.961787
iter  20 value 93.728440
iter  30 value 89.894192
iter  40 value 83.333845
iter  50 value 82.178225
iter  60 value 81.930045
iter  70 value 81.473760
iter  80 value 80.259801
iter  90 value 80.070071
iter 100 value 79.973783
final  value 79.973783 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 120.310104 
iter  10 value 94.259686
iter  20 value 93.202282
iter  30 value 92.612244
iter  40 value 89.295771
iter  50 value 83.746018
iter  60 value 82.819717
iter  70 value 81.341113
iter  80 value 80.408425
iter  90 value 80.094488
iter 100 value 80.062056
final  value 80.062056 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.104791 
iter  10 value 94.030870
iter  20 value 86.147167
iter  30 value 85.693098
iter  40 value 83.470155
iter  50 value 82.510700
iter  60 value 81.855980
iter  70 value 81.413944
iter  80 value 81.231587
iter  90 value 80.919117
iter 100 value 80.675174
final  value 80.675174 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 138.682702 
iter  10 value 94.063808
iter  20 value 86.760218
iter  30 value 85.953013
iter  40 value 84.575874
iter  50 value 84.183904
iter  60 value 83.016830
iter  70 value 82.682197
iter  80 value 82.552270
iter  90 value 81.750792
iter 100 value 80.890631
final  value 80.890631 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.175810 
iter  10 value 93.992459
iter  20 value 88.114077
iter  30 value 87.433777
iter  40 value 85.582098
iter  50 value 83.268422
iter  60 value 82.822044
iter  70 value 82.349632
iter  80 value 81.670526
iter  90 value 80.990580
iter 100 value 80.679071
final  value 80.679071 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.654455 
final  value 94.054518 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.543299 
final  value 94.054449 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.105459 
final  value 94.056478 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.325703 
final  value 94.054515 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.640666 
final  value 94.054466 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.653483 
iter  10 value 93.841019
iter  20 value 93.480421
iter  30 value 93.377963
iter  40 value 93.377587
iter  40 value 93.377586
iter  40 value 93.377586
final  value 93.377586 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.133382 
iter  10 value 94.057049
iter  20 value 94.052915
iter  30 value 90.687295
iter  40 value 85.632894
iter  50 value 84.512854
final  value 84.512701 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.218323 
iter  10 value 94.057643
iter  20 value 94.050955
iter  30 value 88.770545
iter  40 value 85.611808
iter  50 value 85.610945
iter  60 value 85.471426
iter  70 value 85.320298
iter  80 value 83.287813
iter  90 value 82.515854
iter 100 value 82.265187
final  value 82.265187 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 112.408473 
iter  10 value 94.036172
iter  20 value 93.383952
iter  30 value 93.382158
iter  40 value 92.940255
iter  50 value 86.940571
iter  60 value 86.303586
iter  70 value 86.275856
iter  80 value 84.368456
iter  90 value 84.286930
iter 100 value 84.253939
final  value 84.253939 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.735198 
iter  10 value 93.875074
iter  20 value 93.872245
iter  30 value 93.112324
iter  40 value 85.487525
iter  50 value 85.431082
iter  60 value 85.410482
iter  70 value 85.410196
iter  80 value 85.409331
iter  90 value 85.408822
iter 100 value 85.392702
final  value 85.392702 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.585804 
iter  10 value 94.060059
iter  20 value 93.533099
iter  30 value 85.552504
iter  40 value 83.550631
iter  50 value 81.644541
iter  60 value 80.768692
iter  70 value 79.936517
iter  80 value 79.442012
iter  90 value 79.440841
iter 100 value 79.437207
final  value 79.437207 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.334257 
iter  10 value 94.059937
iter  20 value 93.252689
iter  30 value 86.575816
iter  40 value 85.979399
iter  50 value 85.909864
iter  60 value 85.869304
iter  70 value 84.025658
iter  80 value 83.709027
iter  90 value 83.698182
iter 100 value 83.447369
final  value 83.447369 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 138.669311 
iter  10 value 92.425378
iter  20 value 91.882207
iter  30 value 91.344200
iter  40 value 91.334892
iter  50 value 91.321935
iter  60 value 91.314102
final  value 91.313960 
converged
Fitting Repeat 4 

# weights:  507
initial  value 109.696334 
iter  10 value 94.064900
iter  20 value 93.990041
iter  30 value 93.414270
iter  40 value 93.412158
iter  50 value 93.411072
final  value 93.410511 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.658089 
iter  10 value 92.195357
iter  20 value 88.006076
iter  30 value 85.635769
iter  40 value 85.544793
iter  50 value 85.350510
iter  60 value 85.166915
iter  70 value 85.052339
iter  80 value 84.926854
iter  90 value 84.776573
iter 100 value 84.770333
final  value 84.770333 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.101735 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.221373 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.397095 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.876888 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.403346 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.003379 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.536917 
final  value 93.300000 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.206932 
iter  10 value 93.916788
final  value 93.753527 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.813678 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.884806 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.590053 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.075912 
final  value 94.482478 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.437869 
final  value 93.738782 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.278021 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.950925 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.770319 
iter  10 value 94.488308
iter  20 value 88.976474
iter  30 value 86.585540
iter  40 value 86.490139
iter  50 value 86.449381
iter  60 value 86.438547
iter  70 value 86.366686
iter  80 value 86.340229
final  value 86.340084 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.323191 
iter  10 value 94.489667
iter  20 value 94.196677
iter  30 value 89.052998
iter  40 value 88.398149
iter  50 value 88.177348
iter  60 value 88.137241
iter  70 value 86.298887
iter  80 value 85.808903
iter  90 value 84.980406
iter 100 value 84.069577
final  value 84.069577 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.945195 
iter  10 value 94.513448
iter  20 value 94.421178
iter  30 value 92.963626
iter  40 value 92.460900
iter  50 value 88.724278
iter  60 value 86.610557
iter  70 value 86.159373
iter  80 value 86.110165
iter  90 value 84.922688
iter 100 value 83.950446
final  value 83.950446 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.546659 
iter  10 value 93.553665
iter  20 value 91.239672
iter  30 value 87.937153
iter  40 value 87.019876
iter  50 value 86.761419
iter  60 value 86.281929
iter  70 value 86.025132
final  value 86.020403 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.080513 
iter  10 value 94.470228
iter  20 value 87.519644
iter  30 value 86.771667
iter  40 value 86.535106
iter  50 value 86.392694
iter  60 value 86.340630
final  value 86.340025 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.995712 
iter  10 value 94.779267
iter  20 value 94.463052
iter  30 value 94.139002
iter  40 value 91.493583
iter  50 value 88.823791
iter  60 value 88.070500
iter  70 value 87.469740
iter  80 value 87.062165
iter  90 value 86.628948
iter 100 value 86.009668
final  value 86.009668 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 114.290536 
iter  10 value 94.738510
iter  20 value 94.498691
iter  30 value 94.145447
iter  40 value 87.359732
iter  50 value 85.049067
iter  60 value 83.873201
iter  70 value 83.550397
iter  80 value 82.796443
iter  90 value 82.696293
iter 100 value 82.592300
final  value 82.592300 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.563190 
iter  10 value 94.506587
iter  20 value 94.487836
iter  30 value 90.669140
iter  40 value 88.453725
iter  50 value 88.211548
iter  60 value 87.188845
iter  70 value 84.567753
iter  80 value 83.618654
iter  90 value 83.392757
iter 100 value 83.198401
final  value 83.198401 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.041054 
iter  10 value 94.822806
iter  20 value 94.598962
iter  30 value 93.675828
iter  40 value 88.551460
iter  50 value 88.338522
iter  60 value 86.979525
iter  70 value 86.096747
iter  80 value 85.983009
iter  90 value 85.127531
iter 100 value 84.012602
final  value 84.012602 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.097635 
iter  10 value 94.491925
iter  20 value 88.519920
iter  30 value 88.073517
iter  40 value 87.894443
iter  50 value 86.436966
iter  60 value 85.880218
iter  70 value 84.733823
iter  80 value 84.028651
iter  90 value 83.582133
iter 100 value 83.298938
final  value 83.298938 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 113.634427 
iter  10 value 94.423127
iter  20 value 90.314842
iter  30 value 89.928102
iter  40 value 88.816464
iter  50 value 88.402945
iter  60 value 88.036740
iter  70 value 87.029648
iter  80 value 84.799357
iter  90 value 83.711341
iter 100 value 83.600006
final  value 83.600006 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.029104 
iter  10 value 94.072656
iter  20 value 92.553157
iter  30 value 86.372866
iter  40 value 85.695123
iter  50 value 84.866229
iter  60 value 84.260374
iter  70 value 83.439405
iter  80 value 82.987940
iter  90 value 82.838486
iter 100 value 82.783035
final  value 82.783035 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 119.886986 
iter  10 value 98.293315
iter  20 value 92.935701
iter  30 value 91.904551
iter  40 value 91.123728
iter  50 value 89.546297
iter  60 value 88.012751
iter  70 value 87.579733
iter  80 value 87.001238
iter  90 value 86.955304
iter 100 value 86.094289
final  value 86.094289 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 125.943551 
iter  10 value 94.480712
iter  20 value 90.779821
iter  30 value 88.199093
iter  40 value 87.863997
iter  50 value 86.269666
iter  60 value 85.312125
iter  70 value 83.831035
iter  80 value 83.495733
iter  90 value 83.341970
iter 100 value 83.033001
final  value 83.033001 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 125.984302 
iter  10 value 94.536405
iter  20 value 87.986215
iter  30 value 87.631506
iter  40 value 84.941530
iter  50 value 84.023041
iter  60 value 83.875372
iter  70 value 83.775117
iter  80 value 83.358217
iter  90 value 82.845885
iter 100 value 82.729578
final  value 82.729578 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.292351 
final  value 94.485881 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.427173 
final  value 94.486008 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.296200 
iter  10 value 94.486245
iter  20 value 94.484264
iter  30 value 88.680584
iter  40 value 88.441096
iter  50 value 88.387762
final  value 88.387239 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.093449 
final  value 94.486096 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.281410 
final  value 94.486049 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.471471 
iter  10 value 93.904751
iter  20 value 93.713339
final  value 93.301278 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.590101 
iter  10 value 94.471358
iter  20 value 94.441924
final  value 93.301242 
converged
Fitting Repeat 3 

# weights:  305
initial  value 126.245467 
iter  10 value 94.492590
iter  20 value 94.415638
iter  30 value 89.094490
iter  40 value 89.085317
iter  50 value 89.046300
final  value 89.045966 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.151782 
iter  10 value 89.272826
iter  20 value 87.137291
iter  30 value 86.896063
iter  40 value 86.881061
iter  50 value 86.880246
iter  60 value 86.879924
iter  70 value 86.879097
final  value 86.878746 
converged
Fitting Repeat 5 

# weights:  305
initial  value 112.064966 
iter  10 value 94.488135
iter  20 value 94.461195
iter  30 value 94.425739
iter  40 value 93.349947
final  value 93.300817 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.585588 
iter  10 value 93.033351
iter  20 value 92.611806
iter  30 value 92.609460
iter  40 value 87.595427
iter  50 value 87.591680
final  value 87.589102 
converged
Fitting Repeat 2 

# weights:  507
initial  value 128.255407 
iter  10 value 94.432331
iter  20 value 94.245687
iter  30 value 91.966097
iter  40 value 91.797159
iter  50 value 91.795330
final  value 91.795161 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.623823 
iter  10 value 94.492368
iter  20 value 94.457302
iter  30 value 91.960121
iter  40 value 86.415468
iter  50 value 85.933524
iter  60 value 85.553616
iter  70 value 85.134622
iter  80 value 85.077366
iter  90 value 85.076440
iter 100 value 85.076107
final  value 85.076107 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 117.839408 
iter  10 value 94.492253
iter  20 value 94.484345
iter  30 value 85.782903
iter  40 value 85.690704
iter  50 value 85.674180
iter  60 value 84.467729
iter  70 value 84.448873
iter  80 value 84.438033
iter  90 value 84.120748
iter 100 value 83.039376
final  value 83.039376 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 100.640530 
iter  10 value 94.472372
iter  20 value 94.465469
final  value 94.465415 
converged
Fitting Repeat 1 

# weights:  103
initial  value 115.854074 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.844227 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.357057 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.622861 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 107.238478 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.352849 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.056377 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.254462 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.680559 
final  value 94.484210 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.322134 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.968338 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.864562 
iter  10 value 93.720884
final  value 93.720833 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.104807 
iter  10 value 94.474155
final  value 94.466830 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.248299 
iter  10 value 94.101572
final  value 94.090583 
converged
Fitting Repeat 5 

# weights:  507
initial  value 112.957246 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.537658 
iter  10 value 94.794305
iter  20 value 94.476055
iter  30 value 87.077735
iter  40 value 85.706970
iter  50 value 84.331725
iter  60 value 82.474378
iter  70 value 81.677859
iter  80 value 81.462349
final  value 81.461628 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.528374 
iter  10 value 94.494537
iter  20 value 86.321041
iter  30 value 83.322895
iter  40 value 82.849962
iter  50 value 82.509964
iter  60 value 82.424072
iter  70 value 82.388410
final  value 82.386354 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.689634 
iter  10 value 94.488583
iter  20 value 87.050970
iter  30 value 84.612273
iter  40 value 82.870310
iter  50 value 81.449184
iter  60 value 81.173471
iter  70 value 80.955636
iter  80 value 80.910697
final  value 80.910270 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.610620 
iter  10 value 94.483445
iter  20 value 93.916926
iter  30 value 92.709844
iter  40 value 92.577286
iter  50 value 92.472853
iter  60 value 86.506891
iter  70 value 84.491818
iter  80 value 81.113124
iter  90 value 80.286284
iter 100 value 79.857095
final  value 79.857095 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 98.017081 
iter  10 value 94.462955
iter  20 value 92.902430
iter  30 value 87.076301
iter  40 value 86.160548
iter  50 value 83.569490
iter  60 value 82.922014
iter  70 value 82.722182
iter  80 value 82.622854
final  value 82.621674 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.224283 
iter  10 value 94.457584
iter  20 value 90.133606
iter  30 value 87.429307
iter  40 value 84.615392
iter  50 value 82.401675
iter  60 value 79.872627
iter  70 value 78.678781
iter  80 value 78.448068
iter  90 value 78.260806
iter 100 value 78.234741
final  value 78.234741 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.601260 
iter  10 value 95.065393
iter  20 value 94.294391
iter  30 value 88.410984
iter  40 value 85.241297
iter  50 value 84.908930
iter  60 value 83.444333
iter  70 value 82.257585
iter  80 value 81.069111
iter  90 value 79.654501
iter 100 value 79.521684
final  value 79.521684 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.926023 
iter  10 value 94.463100
iter  20 value 89.476474
iter  30 value 83.873205
iter  40 value 80.659709
iter  50 value 79.810797
iter  60 value 79.102056
iter  70 value 78.840666
iter  80 value 78.666153
iter  90 value 78.576487
iter 100 value 78.393644
final  value 78.393644 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.845589 
iter  10 value 94.565155
iter  20 value 94.411864
iter  30 value 88.765215
iter  40 value 87.208773
iter  50 value 86.845962
iter  60 value 84.471281
iter  70 value 81.092150
iter  80 value 79.167811
iter  90 value 78.443900
iter 100 value 78.283116
final  value 78.283116 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.738524 
iter  10 value 93.288608
iter  20 value 84.115537
iter  30 value 81.100653
iter  40 value 80.232842
iter  50 value 79.847243
iter  60 value 78.855261
iter  70 value 78.354211
iter  80 value 78.266350
iter  90 value 78.234297
iter 100 value 78.116384
final  value 78.116384 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.982280 
iter  10 value 94.765109
iter  20 value 87.723908
iter  30 value 83.917520
iter  40 value 82.879710
iter  50 value 80.808493
iter  60 value 78.850542
iter  70 value 78.641719
iter  80 value 78.507395
iter  90 value 78.427381
iter 100 value 78.181374
final  value 78.181374 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 146.419381 
iter  10 value 94.708678
iter  20 value 94.046124
iter  30 value 87.121949
iter  40 value 84.894659
iter  50 value 83.150834
iter  60 value 81.995731
iter  70 value 81.582529
iter  80 value 81.390787
iter  90 value 81.276435
iter 100 value 81.208731
final  value 81.208731 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.405471 
iter  10 value 94.549031
iter  20 value 94.049140
iter  30 value 93.311830
iter  40 value 86.011731
iter  50 value 84.985235
iter  60 value 82.966172
iter  70 value 82.365867
iter  80 value 80.730366
iter  90 value 80.033120
iter 100 value 79.780392
final  value 79.780392 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 116.871896 
iter  10 value 92.277559
iter  20 value 84.105381
iter  30 value 83.721292
iter  40 value 82.797077
iter  50 value 79.964407
iter  60 value 78.924510
iter  70 value 78.578295
iter  80 value 78.351978
iter  90 value 78.208274
iter 100 value 78.051707
final  value 78.051707 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.955987 
iter  10 value 94.710354
iter  20 value 84.412982
iter  30 value 83.486021
iter  40 value 83.119548
iter  50 value 82.702030
iter  60 value 80.798938
iter  70 value 79.754916
iter  80 value 79.213108
iter  90 value 78.434357
iter 100 value 78.114653
final  value 78.114653 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.115633 
final  value 94.485820 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.055540 
iter  10 value 94.468321
iter  20 value 94.466897
iter  30 value 88.070529
iter  40 value 87.541091
iter  50 value 86.638790
final  value 86.632317 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.588303 
final  value 94.485874 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.577938 
final  value 94.485645 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.905797 
final  value 94.485790 
converged
Fitting Repeat 1 

# weights:  305
initial  value 114.793043 
iter  10 value 94.489637
iter  20 value 94.394378
iter  30 value 86.746674
final  value 86.744516 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.151737 
iter  10 value 94.488937
iter  20 value 94.482111
iter  30 value 91.965351
iter  40 value 91.090550
iter  50 value 90.158796
iter  60 value 84.117601
iter  70 value 80.968804
iter  80 value 80.789688
iter  90 value 79.797057
iter 100 value 79.742108
final  value 79.742108 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.744992 
iter  10 value 94.488576
iter  20 value 94.484071
iter  30 value 93.620233
iter  40 value 93.217815
iter  50 value 92.571294
iter  60 value 88.322986
iter  70 value 86.960240
iter  80 value 85.619584
iter  90 value 80.922089
iter 100 value 80.903902
final  value 80.903902 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 98.617931 
iter  10 value 90.951108
iter  20 value 81.464417
iter  30 value 79.853813
iter  40 value 79.847305
iter  50 value 79.842880
iter  60 value 79.695461
iter  70 value 79.624290
iter  80 value 79.528852
iter  90 value 79.472401
final  value 79.428474 
converged
Fitting Repeat 5 

# weights:  305
initial  value 109.587604 
iter  10 value 94.487334
iter  20 value 94.484724
iter  30 value 94.366275
iter  40 value 89.024324
iter  50 value 89.015621
iter  60 value 89.011306
iter  70 value 88.370387
iter  80 value 87.521830
final  value 87.498842 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.363670 
iter  10 value 93.833040
iter  20 value 93.410571
iter  30 value 93.379495
iter  40 value 93.265291
iter  50 value 93.216294
iter  60 value 93.211877
iter  70 value 93.210691
iter  80 value 93.210126
iter  90 value 93.208666
iter 100 value 93.206492
final  value 93.206492 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 94.793106 
iter  10 value 94.482518
iter  20 value 94.475001
iter  30 value 94.472557
iter  40 value 94.470829
iter  50 value 94.167662
iter  60 value 89.459247
iter  70 value 89.378108
iter  80 value 89.378006
iter  90 value 83.278697
iter 100 value 81.935196
final  value 81.935196 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 112.925734 
iter  10 value 94.506924
iter  20 value 94.377556
iter  30 value 89.076713
iter  40 value 88.739970
iter  50 value 88.468465
iter  60 value 88.465893
iter  70 value 88.451313
iter  80 value 85.079535
iter  90 value 79.667019
iter 100 value 78.956588
final  value 78.956588 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 94.885114 
iter  10 value 94.122653
iter  20 value 94.116928
iter  30 value 94.092738
iter  40 value 94.092111
iter  50 value 94.069038
iter  60 value 88.047996
iter  70 value 83.779148
iter  80 value 81.965963
iter  90 value 78.294082
iter 100 value 76.767747
final  value 76.767747 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 117.042032 
iter  10 value 94.495370
iter  20 value 94.398975
iter  30 value 90.164270
iter  40 value 89.115986
iter  50 value 89.074070
iter  60 value 88.966508
iter  70 value 88.965529
iter  80 value 86.029198
iter  90 value 85.736291
iter 100 value 85.521428
final  value 85.521428 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 133.976084 
iter  10 value 117.534529
iter  20 value 113.707564
iter  30 value 109.093825
iter  40 value 108.907605
iter  50 value 108.905532
iter  60 value 108.866345
iter  70 value 108.766857
iter  80 value 108.248553
iter  90 value 108.126914
final  value 108.125225 
converged
Fitting Repeat 2 

# weights:  507
initial  value 139.959439 
iter  10 value 117.766910
iter  20 value 117.758306
iter  30 value 117.574862
iter  40 value 108.582592
iter  50 value 107.735417
iter  60 value 107.171427
iter  70 value 107.169108
iter  80 value 107.168091
iter  90 value 104.594106
iter 100 value 104.054050
final  value 104.054050 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 142.187865 
iter  10 value 117.766752
iter  20 value 117.761322
iter  30 value 117.738356
iter  40 value 117.730030
iter  50 value 117.311636
iter  60 value 114.529007
iter  70 value 113.519650
iter  80 value 113.341614
final  value 113.222537 
converged
Fitting Repeat 4 

# weights:  507
initial  value 153.867994 
iter  10 value 117.767247
iter  20 value 117.268456
iter  30 value 113.998718
iter  40 value 113.732215
iter  50 value 113.674702
iter  60 value 113.366100
iter  70 value 113.362690
final  value 113.354188 
converged
Fitting Repeat 5 

# weights:  507
initial  value 131.123309 
iter  10 value 117.865647
iter  20 value 115.295358
iter  30 value 108.865537
iter  40 value 108.326216
iter  50 value 105.612697
iter  60 value 105.050950
iter  70 value 104.829016
iter  80 value 104.739368
iter  90 value 103.529027
iter 100 value 103.437114
final  value 103.437114 
stopped after 100 iterations
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Mon Jan 20 23:02:29 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 
 39.334   1.458 126.357