##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.21-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.21-bioc/R/site-library --timings HPiP_1.13.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2025-01-20 r87609)
* 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 ‘1.13.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... INFO
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
var_imp       34.450  0.615  35.115
FSmethod      33.936  0.751  34.740
corr_plot     34.174  0.354  34.570
pred_ensembel 13.048  0.313  12.001
enrichfindP    0.509  0.024   8.632
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE

Status: 2 NOTEs
See
  ‘/home/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.21-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.21-bioc/R/site-library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.13.0’
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R Under development (unstable) (2025-01-20 r87609) -- "Unsuffered Consequences"
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 98.012103 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.647871 
final  value 93.915746 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.388213 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.204081 
iter  10 value 91.510180
iter  20 value 91.384969
final  value 91.384891 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.439902 
final  value 93.915746 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.993893 
iter  10 value 93.987122
iter  20 value 93.962021
final  value 93.962012 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.336150 
final  value 93.915746 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.611037 
final  value 93.865909 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.521754 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 109.352460 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.126736 
final  value 93.915746 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.225335 
iter  10 value 92.957523
iter  20 value 90.302964
final  value 90.302874 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.598219 
iter  10 value 93.920449
iter  20 value 93.915749
final  value 93.915747 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.430501 
iter  10 value 93.763751
iter  10 value 93.763751
iter  10 value 93.763751
final  value 93.763751 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.859173 
final  value 93.915746 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.000886 
iter  10 value 90.350297
iter  20 value 87.293180
iter  30 value 83.005737
iter  40 value 82.196313
iter  50 value 82.158335
iter  60 value 82.153609
iter  70 value 82.146727
final  value 82.146677 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.930768 
iter  10 value 94.073911
iter  20 value 91.279386
iter  30 value 89.566951
iter  40 value 89.233948
iter  50 value 82.766211
iter  60 value 82.621800
iter  70 value 80.452927
iter  80 value 79.960532
iter  90 value 79.593338
iter 100 value 79.284166
final  value 79.284166 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 100.644295 
iter  10 value 94.058609
iter  20 value 93.923586
iter  30 value 93.795486
iter  40 value 85.502720
iter  50 value 84.684474
iter  60 value 83.826098
iter  70 value 83.549098
iter  80 value 83.524005
final  value 83.519473 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.589265 
iter  10 value 94.020978
iter  20 value 93.824643
iter  30 value 90.806745
iter  40 value 85.694971
iter  50 value 85.193529
iter  60 value 84.693042
iter  70 value 82.848088
iter  80 value 82.106415
iter  90 value 82.027112
iter 100 value 81.980050
final  value 81.980050 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 118.603711 
iter  10 value 93.928751
iter  20 value 85.954550
iter  30 value 82.883230
iter  40 value 82.484376
iter  50 value 82.407366
iter  60 value 80.510764
iter  70 value 79.910675
iter  80 value 79.823310
iter  90 value 79.823016
iter 100 value 79.819734
final  value 79.819734 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 103.222140 
iter  10 value 94.094783
iter  20 value 88.749375
iter  30 value 82.977332
iter  40 value 82.113304
iter  50 value 81.524436
iter  60 value 80.596858
iter  70 value 80.436982
iter  80 value 80.298551
iter  90 value 80.245783
iter 100 value 79.893162
final  value 79.893162 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 118.256387 
iter  10 value 94.071768
iter  20 value 91.976218
iter  30 value 89.571023
iter  40 value 88.601241
iter  50 value 83.868457
iter  60 value 83.140404
iter  70 value 83.018788
iter  80 value 82.347833
iter  90 value 80.141069
iter 100 value 79.603683
final  value 79.603683 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 112.625433 
iter  10 value 90.000647
iter  20 value 86.017462
iter  30 value 84.233395
iter  40 value 82.683060
iter  50 value 80.883196
iter  60 value 79.189951
iter  70 value 78.994769
iter  80 value 78.825356
iter  90 value 78.759182
iter 100 value 78.708584
final  value 78.708584 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 113.917979 
iter  10 value 93.917337
iter  20 value 87.442272
iter  30 value 86.232780
iter  40 value 85.808936
iter  50 value 83.582957
iter  60 value 79.898249
iter  70 value 79.624280
iter  80 value 79.571652
iter  90 value 79.235449
iter 100 value 79.179540
final  value 79.179540 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 115.748820 
iter  10 value 94.151858
iter  20 value 87.600562
iter  30 value 84.616780
iter  40 value 82.632627
iter  50 value 82.254943
iter  60 value 81.936716
iter  70 value 80.194310
iter  80 value 79.329545
iter  90 value 79.118061
iter 100 value 78.582810
final  value 78.582810 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 102.425543 
iter  10 value 95.865214
iter  20 value 94.237498
iter  30 value 83.314439
iter  40 value 82.511894
iter  50 value 81.929218
iter  60 value 81.698347
iter  70 value 81.616977
iter  80 value 81.343945
iter  90 value 79.905382
iter 100 value 78.567868
final  value 78.567868 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 118.632660 
iter  10 value 93.981514
iter  20 value 83.499667
iter  30 value 81.582595
iter  40 value 79.396666
iter  50 value 78.538271
iter  60 value 78.341581
iter  70 value 78.024636
iter  80 value 77.711584
iter  90 value 77.568500
iter 100 value 77.391663
final  value 77.391663 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.323576 
iter  10 value 92.868130
iter  20 value 83.371362
iter  30 value 82.398743
iter  40 value 81.939797
iter  50 value 80.616550
iter  60 value 78.762830
iter  70 value 77.868853
iter  80 value 77.669999
iter  90 value 77.620270
iter 100 value 77.582942
final  value 77.582942 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 120.037526 
iter  10 value 94.201557
iter  20 value 93.666312
iter  30 value 85.619896
iter  40 value 85.186307
iter  50 value 81.783585
iter  60 value 79.786905
iter  70 value 79.503429
iter  80 value 79.474864
iter  90 value 79.367597
iter 100 value 79.322273
final  value 79.322273 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 115.013570 
iter  10 value 94.794999
iter  20 value 89.488481
iter  30 value 82.116305
iter  40 value 80.515624
iter  50 value 80.371789
iter  60 value 79.742795
iter  70 value 78.747562
iter  80 value 78.421769
iter  90 value 78.280413
iter 100 value 78.219085
final  value 78.219085 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 107.355078 
final  value 94.054528 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.786497 
final  value 94.054488 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.057764 
iter  10 value 94.054624
final  value 94.052916 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.590738 
final  value 94.054387 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.856020 
final  value 94.054538 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.460595 
iter  10 value 94.058118
iter  20 value 94.006144
iter  30 value 93.764637
final  value 93.764506 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.548919 
iter  10 value 94.041750
iter  20 value 93.889841
final  value 93.289441 
converged
Fitting Repeat 3 

# weights:  305
initial  value 112.223392 
iter  10 value 94.058167
iter  20 value 94.053038
iter  30 value 81.998650
iter  40 value 81.561260
iter  40 value 81.561260
final  value 81.561260 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.224147 
iter  10 value 94.042180
iter  20 value 93.603643
iter  30 value 83.823314
iter  40 value 83.819477
iter  50 value 83.023894
iter  60 value 82.337141
iter  70 value 82.334676
iter  80 value 82.334395
iter  90 value 81.716837
iter 100 value 81.515873
final  value 81.515873 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 95.647838 
iter  10 value 93.920513
iter  20 value 91.586009
iter  30 value 82.132176
iter  40 value 81.379115
iter  50 value 81.334260
iter  60 value 81.333052
iter  70 value 81.331540
final  value 81.331182 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.175322 
iter  10 value 93.923447
iter  20 value 93.825337
iter  30 value 93.762115
iter  40 value 93.757458
iter  50 value 93.757377
final  value 93.757369 
converged
Fitting Repeat 2 

# weights:  507
initial  value 111.695766 
iter  10 value 94.061087
iter  20 value 93.906913
iter  30 value 83.405367
iter  40 value 80.112247
iter  50 value 80.081357
iter  60 value 80.080122
final  value 80.079938 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.017477 
iter  10 value 91.909009
iter  20 value 91.862386
iter  30 value 91.408734
iter  40 value 91.390096
iter  50 value 91.389445
iter  60 value 91.387283
iter  70 value 91.385081
iter  80 value 91.262298
iter  90 value 84.043484
iter 100 value 84.031721
final  value 84.031721 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 98.437650 
iter  10 value 90.793758
iter  20 value 86.653800
iter  30 value 85.225355
iter  40 value 85.224158
iter  50 value 83.649892
iter  60 value 82.341081
iter  70 value 82.335684
iter  80 value 82.222326
iter  90 value 81.374240
iter 100 value 81.358994
final  value 81.358994 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 101.632946 
iter  10 value 93.826517
iter  20 value 93.771518
iter  30 value 93.765444
iter  40 value 93.762080
iter  50 value 85.852616
iter  60 value 81.855139
final  value 81.854066 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.151910 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.182643 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.142426 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.167306 
final  value 94.443182 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.329269 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 111.258562 
final  value 94.409357 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.706881 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.284155 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.734036 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.979818 
iter  10 value 94.309409
iter  20 value 94.262975
final  value 94.262867 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.666201 
iter  10 value 90.516063
iter  20 value 87.330362
iter  30 value 86.799116
final  value 86.799078 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.016966 
iter  10 value 94.417727
final  value 94.139368 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.435933 
final  value 94.466821 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.490331 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 114.225646 
iter  10 value 94.334216
final  value 94.052434 
converged
Fitting Repeat 1 

# weights:  103
initial  value 109.563091 
iter  10 value 94.487762
iter  20 value 94.453074
iter  30 value 93.929600
iter  40 value 88.649303
iter  50 value 85.599510
iter  60 value 84.587828
iter  70 value 84.334758
iter  80 value 83.747955
iter  90 value 83.372179
iter 100 value 83.047505
final  value 83.047505 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.431837 
iter  10 value 89.148356
iter  20 value 87.670771
iter  30 value 87.487596
iter  40 value 87.436865
iter  50 value 84.059125
iter  60 value 83.748653
iter  70 value 83.203471
iter  80 value 81.984761
final  value 81.805717 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.774572 
iter  10 value 94.515079
iter  20 value 94.442831
iter  30 value 94.161713
iter  40 value 91.188313
iter  50 value 90.784858
iter  60 value 90.752605
iter  70 value 87.767752
iter  80 value 87.157978
iter  90 value 86.841278
iter 100 value 83.963108
final  value 83.963108 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.264552 
iter  10 value 94.488540
iter  20 value 87.490766
iter  30 value 86.877565
iter  40 value 85.887082
iter  50 value 84.653748
iter  60 value 83.788045
iter  70 value 83.738864
final  value 83.738647 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.402834 
iter  10 value 94.349312
iter  20 value 86.973508
iter  30 value 86.412338
iter  40 value 86.225756
iter  50 value 85.013935
iter  60 value 83.762632
iter  70 value 83.715890
final  value 83.712461 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.216539 
iter  10 value 94.843495
iter  20 value 92.182834
iter  30 value 91.902329
iter  40 value 91.757242
iter  50 value 88.115341
iter  60 value 85.678876
iter  70 value 84.270584
iter  80 value 84.019351
iter  90 value 82.896331
iter 100 value 82.089283
final  value 82.089283 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.430443 
iter  10 value 91.512735
iter  20 value 85.106893
iter  30 value 83.624629
iter  40 value 83.557678
iter  50 value 82.922098
iter  60 value 82.232019
iter  70 value 81.848863
iter  80 value 81.401617
iter  90 value 81.190968
iter 100 value 81.016909
final  value 81.016909 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.276316 
iter  10 value 93.521299
iter  20 value 91.872702
iter  30 value 91.524732
iter  40 value 91.005788
iter  50 value 88.601880
iter  60 value 86.482686
iter  70 value 84.889078
iter  80 value 83.935533
iter  90 value 83.156812
iter 100 value 82.779988
final  value 82.779988 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.912627 
iter  10 value 94.437026
iter  20 value 91.347954
iter  30 value 86.609172
iter  40 value 84.724372
iter  50 value 83.004135
iter  60 value 81.418059
iter  70 value 80.974817
iter  80 value 80.756493
iter  90 value 80.454167
iter 100 value 80.437434
final  value 80.437434 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 114.692037 
iter  10 value 94.752269
iter  20 value 94.490528
iter  30 value 89.790249
iter  40 value 86.310291
iter  50 value 85.916795
iter  60 value 83.988974
iter  70 value 81.148234
iter  80 value 80.835840
iter  90 value 80.721645
iter 100 value 80.616675
final  value 80.616675 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.253433 
iter  10 value 94.513158
iter  20 value 93.978232
iter  30 value 89.579931
iter  40 value 87.087247
iter  50 value 84.657106
iter  60 value 82.498249
iter  70 value 81.584811
iter  80 value 81.339154
iter  90 value 81.216036
iter 100 value 80.755510
final  value 80.755510 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 122.163371 
iter  10 value 95.578574
iter  20 value 89.355430
iter  30 value 85.513862
iter  40 value 83.557129
iter  50 value 82.819659
iter  60 value 81.919060
iter  70 value 80.700816
iter  80 value 80.522864
iter  90 value 80.483810
iter 100 value 80.458649
final  value 80.458649 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.908176 
iter  10 value 91.228462
iter  20 value 86.664129
iter  30 value 86.170929
iter  40 value 83.756052
iter  50 value 82.009522
iter  60 value 81.418469
iter  70 value 80.693017
iter  80 value 80.580275
iter  90 value 80.324384
iter 100 value 80.204996
final  value 80.204996 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 121.059247 
iter  10 value 89.879312
iter  20 value 88.179843
iter  30 value 84.354411
iter  40 value 83.370439
iter  50 value 82.076666
iter  60 value 81.118591
iter  70 value 80.704170
iter  80 value 80.556926
iter  90 value 80.306355
iter 100 value 80.208326
final  value 80.208326 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.707343 
iter  10 value 94.126454
iter  20 value 86.704668
iter  30 value 84.834095
iter  40 value 82.862854
iter  50 value 81.634676
iter  60 value 80.820807
iter  70 value 80.481584
iter  80 value 80.238380
iter  90 value 79.914506
iter 100 value 79.809349
final  value 79.809349 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.739364 
iter  10 value 94.114449
iter  20 value 94.054166
iter  30 value 94.053033
final  value 94.053021 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.880347 
final  value 94.485829 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.447802 
final  value 94.485837 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.605869 
iter  10 value 89.229946
iter  20 value 87.296069
final  value 87.222639 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.525388 
final  value 94.485660 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.617302 
iter  10 value 94.487262
iter  20 value 94.481344
iter  30 value 91.531224
iter  40 value 89.455471
iter  50 value 89.423768
iter  60 value 89.098681
iter  70 value 84.074742
iter  80 value 83.961355
iter  90 value 83.960364
iter 100 value 83.510256
final  value 83.510256 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.745701 
iter  10 value 94.471611
iter  20 value 94.468823
iter  30 value 94.468626
iter  30 value 94.468626
final  value 94.468624 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.749445 
iter  10 value 94.489275
iter  20 value 94.481872
iter  30 value 90.025526
iter  40 value 86.902634
iter  50 value 86.841515
iter  60 value 86.789956
iter  70 value 86.789176
iter  80 value 86.784089
iter  90 value 86.783166
iter 100 value 86.773405
final  value 86.773405 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 111.029868 
iter  10 value 94.053494
iter  20 value 94.033091
iter  30 value 94.000432
iter  40 value 93.746589
iter  50 value 93.470046
iter  60 value 92.408114
iter  70 value 92.232045
iter  80 value 91.893762
iter  90 value 91.893119
iter 100 value 91.891911
final  value 91.891911 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 96.889106 
iter  10 value 93.778879
iter  20 value 93.771011
iter  30 value 93.768007
iter  40 value 93.709209
iter  50 value 86.561525
iter  60 value 81.641550
iter  70 value 80.910116
iter  80 value 80.856271
iter  90 value 80.852938
iter 100 value 80.843495
final  value 80.843495 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 96.403272 
iter  10 value 86.863548
iter  20 value 86.740391
iter  30 value 86.714538
iter  40 value 86.196909
iter  50 value 85.851339
iter  60 value 85.801209
iter  70 value 85.686397
iter  80 value 85.667103
iter  90 value 85.667046
final  value 85.667042 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.072172 
iter  10 value 94.476971
iter  20 value 89.247040
iter  30 value 85.007955
iter  40 value 84.105422
iter  50 value 84.103504
iter  60 value 84.095383
iter  70 value 84.090660
final  value 84.090365 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.039451 
iter  10 value 94.474714
iter  20 value 94.388289
iter  30 value 94.289347
iter  40 value 93.946672
iter  50 value 93.944794
iter  60 value 93.893341
iter  70 value 93.793760
iter  80 value 87.915328
final  value 87.034117 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.745961 
iter  10 value 94.060891
iter  20 value 93.604478
iter  30 value 93.596285
final  value 93.595928 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.453862 
iter  10 value 94.475067
iter  20 value 94.469265
iter  30 value 94.215890
iter  40 value 89.605265
iter  50 value 86.028467
iter  60 value 85.637747
iter  70 value 85.406955
iter  80 value 85.119656
final  value 85.118599 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.981449 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.434911 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.284381 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.358619 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.074791 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.672251 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 120.307715 
final  value 93.018688 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.071476 
final  value 94.291892 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.541418 
final  value 94.416667 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.675365 
iter  10 value 93.111276
iter  20 value 92.036622
final  value 92.036247 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.335349 
final  value 94.291892 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.743163 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.738497 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.417935 
final  value 94.320299 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.302545 
final  value 94.291892 
converged
Fitting Repeat 1 

# weights:  103
initial  value 127.612603 
iter  10 value 94.397953
iter  20 value 90.452739
iter  30 value 88.518771
iter  40 value 87.043127
iter  50 value 86.390721
iter  60 value 84.981282
iter  70 value 84.414463
iter  80 value 83.010504
iter  90 value 82.611066
iter 100 value 82.174812
final  value 82.174812 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 100.151731 
iter  10 value 94.396528
iter  20 value 94.029844
iter  30 value 92.344736
iter  40 value 91.933052
iter  50 value 91.423606
iter  60 value 91.326043
iter  70 value 91.318446
iter  70 value 91.318446
iter  70 value 91.318446
final  value 91.318446 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.476795 
iter  10 value 94.496858
iter  20 value 94.480232
iter  30 value 89.993526
iter  40 value 86.450494
iter  50 value 85.736270
iter  60 value 85.457149
iter  70 value 84.070137
iter  80 value 83.708303
iter  90 value 83.699775
final  value 83.698926 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.338700 
iter  10 value 94.486795
iter  20 value 94.462675
iter  30 value 92.234570
iter  40 value 88.496561
iter  50 value 86.474796
iter  60 value 85.795838
iter  70 value 85.481719
iter  80 value 85.060929
iter  90 value 85.024483
iter 100 value 84.422513
final  value 84.422513 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 101.274943 
iter  10 value 94.484885
iter  20 value 93.515186
iter  30 value 92.113888
iter  40 value 91.749848
iter  50 value 84.843025
iter  60 value 84.461110
iter  70 value 84.037867
iter  80 value 82.395845
iter  90 value 81.822872
iter 100 value 81.576944
final  value 81.576944 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 113.005371 
iter  10 value 94.289240
iter  20 value 85.537153
iter  30 value 84.382090
iter  40 value 81.892533
iter  50 value 80.461066
iter  60 value 79.819349
iter  70 value 79.249063
iter  80 value 79.160664
iter  90 value 79.069759
iter 100 value 79.037742
final  value 79.037742 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.878766 
iter  10 value 94.321290
iter  20 value 85.777610
iter  30 value 83.744704
iter  40 value 82.759227
iter  50 value 82.250383
iter  60 value 81.909449
iter  70 value 81.661606
iter  80 value 81.505300
iter  90 value 81.074005
iter 100 value 80.719214
final  value 80.719214 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 112.717614 
iter  10 value 94.468941
iter  20 value 92.434889
iter  30 value 82.754597
iter  40 value 81.384432
iter  50 value 80.603121
iter  60 value 79.860739
iter  70 value 79.406081
iter  80 value 78.740185
iter  90 value 78.640693
iter 100 value 78.531012
final  value 78.531012 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.221964 
iter  10 value 94.630998
iter  20 value 94.440607
iter  30 value 88.894968
iter  40 value 87.173893
iter  50 value 84.945186
iter  60 value 83.503769
iter  70 value 82.380164
iter  80 value 80.480283
iter  90 value 80.417159
iter 100 value 80.158007
final  value 80.158007 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.090375 
iter  10 value 94.596720
iter  20 value 92.802871
iter  30 value 86.410217
iter  40 value 85.051415
iter  50 value 84.387555
iter  60 value 83.307728
iter  70 value 82.016489
iter  80 value 81.443537
iter  90 value 81.225638
iter 100 value 80.319736
final  value 80.319736 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 102.947584 
iter  10 value 98.945986
iter  20 value 93.475643
iter  30 value 92.035623
iter  40 value 86.211346
iter  50 value 83.377451
iter  60 value 81.481124
iter  70 value 79.335282
iter  80 value 78.727936
iter  90 value 78.595985
iter 100 value 78.419425
final  value 78.419425 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 119.468535 
iter  10 value 94.155373
iter  20 value 88.417866
iter  30 value 86.047980
iter  40 value 84.146034
iter  50 value 82.841026
iter  60 value 80.865638
iter  70 value 79.913580
iter  80 value 79.459989
iter  90 value 79.088047
iter 100 value 78.974687
final  value 78.974687 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.962665 
iter  10 value 92.822319
iter  20 value 86.398151
iter  30 value 84.386009
iter  40 value 82.943558
iter  50 value 82.394751
iter  60 value 81.727968
iter  70 value 80.574628
iter  80 value 79.801676
iter  90 value 79.277284
iter 100 value 79.068029
final  value 79.068029 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.293765 
iter  10 value 95.880493
iter  20 value 89.788455
iter  30 value 87.894572
iter  40 value 82.064911
iter  50 value 80.370925
iter  60 value 79.267044
iter  70 value 78.638297
iter  80 value 78.560622
iter  90 value 78.361793
iter 100 value 78.209694
final  value 78.209694 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.866503 
iter  10 value 94.719205
iter  20 value 88.255896
iter  30 value 84.023281
iter  40 value 81.123194
iter  50 value 80.433961
iter  60 value 79.705514
iter  70 value 79.468067
iter  80 value 79.270870
iter  90 value 79.173170
iter 100 value 79.046727
final  value 79.046727 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.202121 
final  value 94.293652 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.068468 
iter  10 value 94.293316
iter  20 value 94.292383
final  value 94.292026 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.437315 
iter  10 value 94.485977
iter  20 value 94.484269
iter  30 value 94.181878
iter  40 value 90.755597
iter  50 value 84.428777
iter  60 value 83.919081
iter  70 value 83.844418
iter  80 value 83.543475
final  value 83.198095 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.572367 
final  value 94.486089 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.700826 
final  value 94.485948 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.765326 
iter  10 value 94.296943
iter  20 value 94.292443
iter  30 value 94.195783
iter  40 value 89.563946
final  value 89.432401 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.692589 
iter  10 value 94.297326
iter  20 value 94.161026
iter  30 value 85.211619
iter  40 value 85.048242
iter  50 value 85.046788
iter  60 value 85.039770
iter  70 value 83.867692
iter  80 value 81.367778
iter  90 value 80.551953
iter 100 value 80.510404
final  value 80.510404 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 97.377914 
iter  10 value 92.859164
iter  20 value 92.755252
iter  30 value 92.752120
iter  40 value 91.921043
iter  50 value 91.789015
iter  60 value 91.788336
final  value 91.788190 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.566714 
iter  10 value 89.516073
iter  20 value 87.978312
iter  30 value 87.954905
iter  40 value 85.434723
iter  50 value 85.203018
final  value 85.201709 
converged
Fitting Repeat 5 

# weights:  305
initial  value 112.111927 
iter  10 value 94.297473
iter  20 value 94.295267
final  value 94.295237 
converged
Fitting Repeat 1 

# weights:  507
initial  value 110.629313 
iter  10 value 94.056119
iter  20 value 93.738740
iter  30 value 92.291520
iter  40 value 92.267806
iter  50 value 92.067224
iter  60 value 92.062296
iter  70 value 91.769066
final  value 91.695639 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.270817 
iter  10 value 94.491537
iter  20 value 92.778736
iter  30 value 86.374783
iter  40 value 86.212322
final  value 86.212310 
converged
Fitting Repeat 3 

# weights:  507
initial  value 129.511039 
iter  10 value 94.493742
iter  20 value 94.461454
iter  30 value 93.001582
iter  40 value 84.556393
iter  50 value 83.685870
iter  60 value 83.680903
iter  70 value 83.669961
iter  80 value 83.399082
iter  90 value 78.535203
iter 100 value 78.457992
final  value 78.457992 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.783941 
iter  10 value 94.299903
iter  20 value 94.293044
iter  30 value 89.933137
iter  40 value 84.223416
final  value 84.222539 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.349495 
iter  10 value 93.862491
iter  20 value 91.673101
iter  30 value 91.487232
iter  40 value 91.472151
iter  50 value 91.107749
iter  60 value 91.046578
iter  70 value 91.045183
iter  80 value 91.044628
iter  90 value 91.044391
iter 100 value 91.040866
final  value 91.040866 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.681216 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.085556 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 112.406707 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 118.210625 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.269463 
iter  10 value 94.026553
final  value 94.026542 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.345734 
iter  10 value 93.637379
iter  10 value 93.637379
iter  10 value 93.637379
final  value 93.637379 
converged
Fitting Repeat 2 

# weights:  305
initial  value 112.598040 
final  value 94.026542 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.568534 
iter  10 value 94.357037
final  value 94.026542 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.868661 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.320256 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.587575 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 114.659585 
iter  10 value 94.026546
final  value 94.026542 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.815628 
iter  10 value 89.082413
iter  20 value 88.636913
iter  30 value 88.630985
final  value 88.630970 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.672891 
iter  10 value 93.966489
final  value 93.966300 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.885900 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.418852 
iter  10 value 93.880279
iter  20 value 93.715347
iter  30 value 93.529313
iter  40 value 91.455945
iter  50 value 88.589817
iter  60 value 87.013821
iter  70 value 85.840489
iter  80 value 84.430939
iter  90 value 84.089902
iter 100 value 83.650858
final  value 83.650858 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.357995 
iter  10 value 94.548713
iter  20 value 94.419852
iter  30 value 89.554687
iter  40 value 87.900908
iter  50 value 85.645499
iter  60 value 84.179493
iter  70 value 83.575294
iter  80 value 83.475591
iter  90 value 83.329780
iter 100 value 83.170568
final  value 83.170568 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 114.389798 
iter  10 value 94.496590
iter  20 value 94.128664
iter  30 value 93.774413
iter  40 value 93.708472
iter  50 value 87.442740
iter  60 value 86.084176
iter  70 value 85.652109
iter  80 value 85.306343
iter  90 value 83.824037
iter 100 value 83.438216
final  value 83.438216 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 118.700592 
iter  10 value 94.486824
iter  20 value 93.756975
iter  30 value 90.256818
iter  40 value 89.817644
iter  50 value 88.944467
iter  60 value 87.874693
iter  70 value 87.803913
iter  80 value 87.802701
final  value 87.802324 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.327184 
iter  10 value 93.759418
iter  20 value 90.945514
iter  30 value 88.958969
iter  40 value 87.144426
iter  50 value 85.898200
iter  60 value 85.847078
final  value 85.846942 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.829521 
iter  10 value 94.490052
iter  20 value 91.612000
iter  30 value 88.633407
iter  40 value 87.073626
iter  50 value 85.823376
iter  60 value 84.308999
iter  70 value 83.065508
iter  80 value 82.525116
iter  90 value 82.370390
iter 100 value 82.283000
final  value 82.283000 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.673455 
iter  10 value 94.344119
iter  20 value 87.070644
iter  30 value 85.234782
iter  40 value 84.214574
iter  50 value 83.551604
iter  60 value 83.297415
iter  70 value 83.260659
iter  80 value 83.257713
iter  90 value 83.256451
iter 100 value 83.255551
final  value 83.255551 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 116.736704 
iter  10 value 94.454189
iter  20 value 93.659772
iter  30 value 89.072282
iter  40 value 88.197100
iter  50 value 85.806360
iter  60 value 85.511970
iter  70 value 84.682856
iter  80 value 83.280164
iter  90 value 82.886880
iter 100 value 82.798798
final  value 82.798798 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.776855 
iter  10 value 94.818208
iter  20 value 94.395465
iter  30 value 89.654782
iter  40 value 88.140994
iter  50 value 84.333496
iter  60 value 83.449164
iter  70 value 82.788554
iter  80 value 82.572492
iter  90 value 82.425911
iter 100 value 82.404034
final  value 82.404034 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.342790 
iter  10 value 93.492462
iter  20 value 89.359266
iter  30 value 86.007674
iter  40 value 83.550767
iter  50 value 83.231289
iter  60 value 83.206880
iter  70 value 83.193819
iter  80 value 83.186071
iter  90 value 83.147587
iter 100 value 82.922153
final  value 82.922153 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 114.973239 
iter  10 value 94.650767
iter  20 value 92.928318
iter  30 value 88.189331
iter  40 value 85.869207
iter  50 value 84.823001
iter  60 value 84.042222
iter  70 value 83.540257
iter  80 value 82.939497
iter  90 value 82.628544
iter 100 value 82.468694
final  value 82.468694 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.424009 
iter  10 value 94.478116
iter  20 value 91.275544
iter  30 value 88.886248
iter  40 value 87.599969
iter  50 value 85.400950
iter  60 value 84.755378
iter  70 value 82.643012
iter  80 value 82.378415
iter  90 value 82.284145
iter 100 value 82.230048
final  value 82.230048 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.409718 
iter  10 value 95.587678
iter  20 value 94.493504
iter  30 value 93.976442
iter  40 value 93.739134
iter  50 value 93.506764
iter  60 value 92.697232
iter  70 value 86.917346
iter  80 value 84.739342
iter  90 value 83.687194
iter 100 value 83.220919
final  value 83.220919 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 131.137457 
iter  10 value 95.224888
iter  20 value 94.484807
iter  30 value 89.360038
iter  40 value 85.277482
iter  50 value 85.113454
iter  60 value 84.904588
iter  70 value 84.474729
iter  80 value 83.487245
iter  90 value 82.809610
iter 100 value 82.699636
final  value 82.699636 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 102.518274 
iter  10 value 94.548651
iter  20 value 93.483515
iter  30 value 89.778207
iter  40 value 86.367806
iter  50 value 84.619320
iter  60 value 83.552550
iter  70 value 82.834733
iter  80 value 82.657835
iter  90 value 82.486288
iter 100 value 82.300667
final  value 82.300667 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.093641 
final  value 94.485685 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.691794 
final  value 94.485759 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.018315 
final  value 94.485778 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.138632 
final  value 94.485900 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.871800 
final  value 94.485867 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.979792 
iter  10 value 93.751885
iter  20 value 93.112528
iter  30 value 89.000927
iter  40 value 88.656929
iter  50 value 88.554912
iter  60 value 88.435896
iter  70 value 88.431232
iter  80 value 86.806880
iter  90 value 86.009366
iter 100 value 86.006721
final  value 86.006721 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 95.835186 
iter  10 value 92.169407
iter  20 value 90.994163
iter  30 value 90.982880
iter  40 value 89.909294
iter  50 value 85.980372
iter  60 value 83.550376
iter  70 value 83.531572
iter  80 value 83.531230
iter  90 value 83.525993
iter 100 value 82.851776
final  value 82.851776 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 107.320036 
iter  10 value 94.489110
iter  20 value 94.036612
iter  30 value 92.589224
iter  40 value 88.871667
iter  50 value 88.808517
iter  60 value 88.755744
iter  70 value 88.742627
final  value 88.742563 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.500010 
iter  10 value 94.489262
iter  20 value 94.151122
iter  30 value 88.835832
iter  40 value 88.802324
iter  50 value 88.801580
final  value 88.800863 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.412305 
iter  10 value 94.031313
iter  20 value 94.027288
iter  30 value 93.928816
iter  40 value 90.778322
iter  50 value 88.165495
iter  60 value 85.054876
iter  70 value 83.348928
iter  80 value 81.678881
iter  90 value 81.634481
iter 100 value 81.628027
final  value 81.628027 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 98.234150 
iter  10 value 94.034638
iter  20 value 90.400511
iter  30 value 86.832282
iter  40 value 86.826324
iter  50 value 86.317356
iter  60 value 84.875205
iter  70 value 83.418773
iter  80 value 83.411070
iter  90 value 83.248202
iter 100 value 82.178571
final  value 82.178571 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.604942 
iter  10 value 94.492239
iter  20 value 94.157664
final  value 94.026750 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.324682 
iter  10 value 94.034786
iter  20 value 94.027252
iter  30 value 93.637747
iter  40 value 93.580046
iter  50 value 93.010099
iter  60 value 89.530165
iter  70 value 87.876874
iter  80 value 82.670273
iter  90 value 82.620355
iter 100 value 82.619470
final  value 82.619470 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.286886 
iter  10 value 94.034657
iter  20 value 93.721745
iter  30 value 93.574632
iter  40 value 93.574066
final  value 93.572880 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.843229 
iter  10 value 94.054865
iter  20 value 94.051653
iter  30 value 93.757161
iter  40 value 88.915321
iter  50 value 88.801041
final  value 88.801006 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.997116 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.062905 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.996790 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.040503 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.421764 
iter  10 value 93.328269
final  value 93.328261 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.799517 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.637605 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.475619 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.849269 
iter  10 value 92.915172
final  value 92.905242 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.002272 
iter  10 value 92.326972
iter  20 value 92.150131
iter  30 value 86.387162
iter  40 value 79.921599
iter  50 value 79.835156
iter  60 value 79.691873
iter  70 value 79.646741
final  value 79.646717 
converged
Fitting Repeat 1 

# weights:  507
initial  value 117.050739 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.092837 
final  value 94.046815 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.524563 
iter  10 value 93.328270
final  value 93.328261 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.192412 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.329207 
iter  10 value 93.328295
final  value 93.328261 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.033449 
iter  10 value 93.859000
iter  20 value 86.819132
iter  30 value 85.011519
iter  40 value 82.507268
iter  50 value 81.756244
iter  60 value 81.151132
iter  70 value 81.108604
final  value 81.108433 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.359857 
iter  10 value 93.832894
iter  20 value 88.528317
iter  30 value 83.514721
iter  40 value 82.326770
iter  50 value 82.117794
iter  60 value 82.009755
iter  70 value 81.981220
final  value 81.981108 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.876941 
iter  10 value 94.059502
iter  20 value 93.891428
iter  30 value 83.488367
iter  40 value 82.423136
iter  50 value 82.172187
iter  60 value 81.981834
final  value 81.981108 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.021696 
iter  10 value 93.123771
iter  20 value 84.910127
iter  30 value 82.006401
iter  40 value 81.582322
iter  50 value 81.334361
iter  60 value 81.206314
iter  70 value 81.152132
iter  80 value 81.114516
final  value 81.108433 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.868207 
iter  10 value 94.119760
iter  20 value 94.054099
iter  30 value 93.947960
iter  40 value 93.877792
iter  50 value 93.803968
iter  60 value 93.278689
iter  70 value 93.186899
iter  80 value 82.646389
iter  90 value 81.774024
iter 100 value 81.363409
final  value 81.363409 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 105.891483 
iter  10 value 94.155416
iter  20 value 94.058480
iter  30 value 93.374987
iter  40 value 93.123723
iter  50 value 83.797536
iter  60 value 82.426701
iter  70 value 81.857870
iter  80 value 81.725963
iter  90 value 81.055581
iter 100 value 79.822277
final  value 79.822277 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 121.389963 
iter  10 value 93.990509
iter  20 value 92.165866
iter  30 value 87.940275
iter  40 value 84.250073
iter  50 value 83.187347
iter  60 value 81.721499
iter  70 value 80.751394
iter  80 value 79.740118
iter  90 value 79.593573
iter 100 value 79.552371
final  value 79.552371 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.636973 
iter  10 value 90.431563
iter  20 value 84.062957
iter  30 value 82.851027
iter  40 value 82.098650
iter  50 value 81.415978
iter  60 value 81.298557
final  value 81.269560 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.715422 
iter  10 value 93.890345
iter  20 value 86.890368
iter  30 value 82.722822
iter  40 value 82.264753
iter  50 value 82.002448
iter  60 value 81.025842
iter  70 value 79.940740
iter  80 value 79.643132
iter  90 value 79.446789
iter 100 value 79.243335
final  value 79.243335 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.588453 
iter  10 value 94.032366
iter  20 value 92.723619
iter  30 value 86.509299
iter  40 value 81.913909
iter  50 value 81.652434
iter  60 value 81.598890
iter  70 value 81.538440
iter  80 value 80.576545
iter  90 value 79.958955
iter 100 value 79.752359
final  value 79.752359 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.305534 
iter  10 value 94.302857
iter  20 value 87.587798
iter  30 value 81.970481
iter  40 value 81.465951
iter  50 value 80.823143
iter  60 value 80.573694
iter  70 value 80.491756
iter  80 value 80.128063
iter  90 value 79.378986
iter 100 value 78.677516
final  value 78.677516 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 141.129021 
iter  10 value 97.310103
iter  20 value 91.549917
iter  30 value 82.670732
iter  40 value 81.845185
iter  50 value 80.878732
iter  60 value 79.560092
iter  70 value 79.178639
iter  80 value 79.078999
iter  90 value 78.935370
iter 100 value 78.811246
final  value 78.811246 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.574569 
iter  10 value 92.865582
iter  20 value 82.411889
iter  30 value 81.826167
iter  40 value 81.325278
iter  50 value 81.277493
iter  60 value 81.212085
iter  70 value 81.124948
iter  80 value 80.469466
iter  90 value 79.358266
iter 100 value 79.034428
final  value 79.034428 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.285840 
iter  10 value 92.035338
iter  20 value 84.887715
iter  30 value 84.051546
iter  40 value 83.705808
iter  50 value 83.617086
iter  60 value 82.230729
iter  70 value 81.335291
iter  80 value 80.654289
iter  90 value 80.163083
iter 100 value 79.723089
final  value 79.723089 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 102.462415 
iter  10 value 93.517709
iter  20 value 83.740758
iter  30 value 82.323855
iter  40 value 82.180575
iter  50 value 81.426153
iter  60 value 81.329425
iter  70 value 81.117357
iter  80 value 80.729341
iter  90 value 80.373754
iter 100 value 80.266313
final  value 80.266313 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 107.419994 
final  value 94.054518 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.482217 
iter  10 value 92.813622
iter  20 value 92.688447
iter  30 value 92.687824
iter  30 value 92.687824
final  value 92.687824 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.287006 
final  value 94.054652 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.436383 
final  value 94.054984 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.504505 
final  value 94.054828 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.959278 
iter  10 value 94.056466
iter  20 value 92.474475
iter  30 value 83.088490
iter  40 value 80.791051
iter  50 value 80.085592
iter  60 value 79.856552
iter  70 value 79.793626
iter  80 value 79.791461
iter  90 value 79.788768
iter 100 value 79.740729
final  value 79.740729 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 115.168427 
iter  10 value 94.057714
iter  20 value 94.038777
iter  30 value 83.798648
iter  40 value 83.794612
iter  50 value 83.790439
iter  60 value 83.790006
final  value 83.789979 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.997693 
iter  10 value 93.334470
iter  20 value 93.330018
iter  30 value 92.966726
iter  40 value 92.853869
iter  50 value 92.849014
iter  60 value 92.665079
iter  70 value 81.316772
iter  80 value 80.990852
final  value 80.990796 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.464337 
iter  10 value 93.334072
iter  20 value 93.332295
iter  30 value 93.327940
iter  40 value 93.281453
iter  50 value 87.230894
iter  60 value 83.166499
iter  70 value 82.014663
iter  80 value 82.004542
iter  90 value 82.004449
iter 100 value 82.003253
final  value 82.003253 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 93.853609 
iter  10 value 93.333777
iter  20 value 93.256803
iter  30 value 92.888809
iter  40 value 92.843147
iter  50 value 92.612092
iter  60 value 84.445902
iter  70 value 84.212741
final  value 84.212658 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.796202 
iter  10 value 93.133255
iter  20 value 92.949865
iter  30 value 92.946126
iter  40 value 92.942764
iter  50 value 92.582385
final  value 92.582333 
converged
Fitting Repeat 2 

# weights:  507
initial  value 111.163114 
iter  10 value 93.336706
iter  20 value 93.332029
iter  30 value 84.712983
iter  40 value 84.672240
iter  50 value 83.634611
iter  60 value 83.155162
iter  70 value 81.789778
iter  80 value 79.626744
iter  90 value 78.648733
iter 100 value 78.560770
final  value 78.560770 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 94.364814 
iter  10 value 91.718066
iter  20 value 90.903209
iter  30 value 90.144831
iter  40 value 81.320127
iter  50 value 80.540637
iter  60 value 80.497684
iter  70 value 80.491653
iter  80 value 80.490768
final  value 80.490691 
converged
Fitting Repeat 4 

# weights:  507
initial  value 93.828986 
iter  10 value 92.932956
iter  20 value 92.930772
iter  30 value 92.925270
iter  40 value 92.924710
iter  50 value 92.896584
iter  60 value 92.896410
final  value 92.896328 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.791075 
iter  10 value 93.393065
iter  20 value 93.282694
iter  30 value 93.188267
iter  40 value 92.962546
iter  50 value 89.518184
iter  60 value 86.154906
iter  70 value 84.410261
iter  80 value 84.273102
iter  90 value 84.025673
iter 100 value 81.661251
final  value 81.661251 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 121.931633 
iter  10 value 117.894780
iter  20 value 117.600566
iter  30 value 117.481814
iter  40 value 110.840786
final  value 110.840733 
converged
Fitting Repeat 2 

# weights:  507
initial  value 125.523010 
iter  10 value 117.897648
iter  20 value 113.519881
iter  30 value 105.609568
iter  40 value 104.415274
iter  50 value 104.401131
final  value 104.400763 
converged
Fitting Repeat 3 

# weights:  507
initial  value 126.911171 
iter  10 value 117.898457
iter  20 value 117.890626
final  value 117.890604 
converged
Fitting Repeat 4 

# weights:  507
initial  value 119.971419 
iter  10 value 117.894785
iter  20 value 117.890672
final  value 117.890656 
converged
Fitting Repeat 5 

# weights:  507
initial  value 133.402962 
iter  10 value 117.777939
iter  20 value 117.772146
iter  30 value 117.500266
iter  40 value 109.425511
iter  50 value 108.518988
iter  60 value 108.512018
iter  70 value 108.509456
iter  80 value 108.492143
iter  90 value 108.205135
iter 100 value 104.492592
final  value 104.492592 
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 -- Tue Feb 18 23:02:07 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 
 39.982   1.283 122.995