##############################################################################
##############################################################################
###
### 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_1.11.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck’
* using R version 4.4.0 RC (2024-04-16 r86468)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
    GNU Fortran (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
* running under: Ubuntu 22.04.4 LTS
* using session charset: UTF-8
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.11.0’
* 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       35.692  0.989  36.681
FSmethod      34.899  0.776  35.677
corr_plot     34.965  0.308  35.274
pred_ensembel 13.643  0.386  10.682
enrichfindP    0.478  0.050   9.557
* 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 4.4.0 RC (2024-04-16 r86468) -- "Puppy Cup"
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 95.653901 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.921416 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 109.901388 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.702767 
iter  10 value 94.035532
final  value 94.032967 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.278183 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.496163 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.952398 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 125.835395 
final  value 94.032967 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.279976 
iter  10 value 94.032967
iter  10 value 94.032967
iter  10 value 94.032967
final  value 94.032967 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.727953 
final  value 94.050051 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.809808 
final  value 94.032967 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.709191 
iter  10 value 85.460280
iter  20 value 85.417259
final  value 85.417144 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.423999 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.004281 
final  value 94.032967 
converged
Fitting Repeat 5 

# weights:  507
initial  value 110.087435 
iter  10 value 94.029327
final  value 94.029316 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.311884 
iter  10 value 94.067020
iter  20 value 92.818079
iter  30 value 87.744277
iter  40 value 87.316415
iter  50 value 87.073165
iter  60 value 86.388484
iter  70 value 85.265739
iter  80 value 85.159504
iter  90 value 85.043913
iter 100 value 84.998703
final  value 84.998703 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 111.742267 
iter  10 value 93.748185
iter  20 value 87.424463
iter  30 value 86.665648
iter  40 value 86.498305
iter  50 value 85.683788
iter  60 value 85.463139
final  value 85.463114 
converged
Fitting Repeat 3 

# weights:  103
initial  value 118.015564 
iter  10 value 92.449078
iter  20 value 87.801258
iter  30 value 87.094441
iter  40 value 86.955448
iter  50 value 85.567972
iter  60 value 85.482467
iter  70 value 84.755824
iter  80 value 84.075895
iter  90 value 83.178834
iter 100 value 83.167300
final  value 83.167300 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 104.925061 
iter  10 value 94.059521
iter  20 value 92.060420
iter  30 value 87.570515
iter  40 value 86.636450
iter  50 value 86.549883
iter  60 value 85.997590
iter  70 value 85.140101
iter  80 value 83.059756
iter  90 value 82.892385
iter 100 value 82.890726
final  value 82.890726 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 98.730056 
iter  10 value 93.997316
iter  20 value 93.835423
iter  30 value 91.594364
iter  40 value 88.161867
iter  50 value 87.747248
iter  60 value 87.511347
iter  70 value 86.704191
iter  80 value 86.348001
iter  90 value 85.916100
iter 100 value 85.894736
final  value 85.894736 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 111.950926 
iter  10 value 91.681977
iter  20 value 85.635948
iter  30 value 84.952451
iter  40 value 84.914973
iter  50 value 84.831307
iter  60 value 83.978690
iter  70 value 82.309408
iter  80 value 81.771207
iter  90 value 81.610807
iter 100 value 81.213858
final  value 81.213858 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 115.969118 
iter  10 value 94.102794
iter  20 value 93.470307
iter  30 value 89.629257
iter  40 value 87.048714
iter  50 value 86.797112
iter  60 value 85.589710
iter  70 value 84.677422
iter  80 value 83.062195
iter  90 value 82.454549
iter 100 value 82.009166
final  value 82.009166 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.558160 
iter  10 value 93.724249
iter  20 value 87.375930
iter  30 value 85.849912
iter  40 value 85.361690
iter  50 value 84.689173
iter  60 value 83.833674
iter  70 value 83.751514
iter  80 value 83.574992
iter  90 value 82.120241
iter 100 value 81.721916
final  value 81.721916 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.703773 
iter  10 value 94.192665
iter  20 value 94.043666
iter  30 value 93.051034
iter  40 value 88.647915
iter  50 value 86.555153
iter  60 value 85.614233
iter  70 value 85.416138
iter  80 value 85.327544
iter  90 value 84.297952
iter 100 value 82.817064
final  value 82.817064 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.595272 
iter  10 value 92.313633
iter  20 value 87.576536
iter  30 value 86.628240
iter  40 value 85.995264
iter  50 value 83.736216
iter  60 value 82.831734
iter  70 value 82.544946
iter  80 value 82.384610
iter  90 value 82.125726
iter 100 value 82.065116
final  value 82.065116 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.532940 
iter  10 value 94.081283
iter  20 value 93.686648
iter  30 value 90.025647
iter  40 value 87.821247
iter  50 value 85.862051
iter  60 value 85.769090
iter  70 value 85.554702
iter  80 value 84.551680
iter  90 value 84.281228
iter 100 value 84.055022
final  value 84.055022 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.756561 
iter  10 value 95.680206
iter  20 value 92.157659
iter  30 value 87.461011
iter  40 value 86.200900
iter  50 value 85.614189
iter  60 value 85.381212
iter  70 value 84.950012
iter  80 value 83.055267
iter  90 value 82.272983
iter 100 value 81.688207
final  value 81.688207 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 115.518669 
iter  10 value 94.676111
iter  20 value 93.334927
iter  30 value 88.322462
iter  40 value 85.760570
iter  50 value 85.092871
iter  60 value 84.883096
iter  70 value 84.511378
iter  80 value 83.929236
iter  90 value 82.929485
iter 100 value 82.153896
final  value 82.153896 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.541826 
iter  10 value 94.061679
iter  20 value 93.449261
iter  30 value 92.013573
iter  40 value 91.513400
iter  50 value 85.951714
iter  60 value 83.037939
iter  70 value 82.576672
iter  80 value 82.440106
iter  90 value 82.093201
iter 100 value 81.652436
final  value 81.652436 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.003214 
iter  10 value 99.998026
iter  20 value 92.566525
iter  30 value 91.246993
iter  40 value 85.824339
iter  50 value 84.425037
iter  60 value 84.052778
iter  70 value 83.453370
iter  80 value 82.952847
iter  90 value 82.615700
iter 100 value 82.330350
final  value 82.330350 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.553896 
final  value 94.054503 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.711982 
iter  10 value 94.054590
iter  20 value 93.863592
iter  30 value 92.856319
iter  40 value 92.841432
iter  50 value 92.841180
iter  50 value 92.841179
iter  50 value 92.841179
final  value 92.841179 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.459231 
iter  10 value 94.036867
iter  20 value 94.034716
iter  30 value 85.981601
iter  40 value 85.335741
iter  50 value 84.978058
iter  60 value 84.972905
iter  70 value 84.972239
iter  80 value 84.970885
final  value 84.970505 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.551286 
final  value 94.054514 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.272227 
final  value 94.054543 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.888487 
iter  10 value 94.056404
iter  20 value 93.773671
iter  30 value 93.771559
iter  40 value 93.768050
iter  50 value 93.767349
iter  60 value 93.766952
iter  70 value 91.380910
iter  80 value 91.364946
iter  90 value 90.358932
iter 100 value 87.078461
final  value 87.078461 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 95.922422 
iter  10 value 94.057694
iter  20 value 94.050869
iter  30 value 90.556019
iter  40 value 87.131121
iter  50 value 87.129975
iter  60 value 87.065991
iter  70 value 85.428570
final  value 85.426070 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.857478 
iter  10 value 93.868826
iter  20 value 93.825825
final  value 93.822430 
converged
Fitting Repeat 4 

# weights:  305
initial  value 112.159848 
iter  10 value 94.058084
iter  20 value 93.996428
iter  30 value 88.631927
iter  40 value 87.250005
iter  50 value 87.249505
iter  60 value 87.247047
iter  60 value 87.247047
iter  60 value 87.247047
final  value 87.247047 
converged
Fitting Repeat 5 

# weights:  305
initial  value 122.274093 
iter  10 value 94.037743
iter  20 value 94.007388
iter  30 value 91.696009
iter  40 value 91.185532
iter  50 value 91.183666
iter  60 value 91.182339
iter  70 value 91.181575
iter  80 value 91.181347
final  value 91.181287 
converged
Fitting Repeat 1 

# weights:  507
initial  value 113.719845 
iter  10 value 94.041164
iter  20 value 93.875847
iter  30 value 93.854589
iter  40 value 93.811309
iter  50 value 87.258298
iter  60 value 87.135453
iter  70 value 87.109432
final  value 87.109284 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.595253 
iter  10 value 92.074274
iter  20 value 86.088042
iter  30 value 85.404312
iter  40 value 84.948220
iter  50 value 84.376341
iter  60 value 84.195310
iter  70 value 84.194191
iter  80 value 83.776362
iter  90 value 83.638117
iter 100 value 83.633964
final  value 83.633964 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 95.725058 
iter  10 value 94.060885
iter  20 value 94.030714
iter  30 value 93.102627
iter  40 value 90.955785
iter  50 value 87.156752
iter  60 value 87.052617
iter  70 value 87.013279
iter  80 value 86.811886
iter  90 value 86.659900
iter 100 value 86.215713
final  value 86.215713 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.595952 
iter  10 value 94.060644
iter  20 value 94.037322
iter  30 value 88.401326
iter  40 value 86.016150
iter  50 value 82.768207
iter  60 value 81.641285
iter  70 value 81.621033
iter  80 value 81.620902
final  value 81.620488 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.325997 
iter  10 value 93.926257
iter  20 value 93.922543
iter  30 value 93.038942
iter  40 value 87.560140
iter  50 value 86.719189
iter  60 value 86.592256
iter  70 value 85.816759
iter  80 value 85.499386
iter  90 value 85.357269
iter 100 value 85.352292
final  value 85.352292 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.565964 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.979573 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.650259 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.871028 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.846608 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.637277 
iter  10 value 93.976602
final  value 93.976245 
converged
Fitting Repeat 2 

# weights:  305
initial  value 108.995189 
iter  10 value 94.026542
iter  10 value 94.026542
iter  10 value 94.026542
final  value 94.026542 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.656261 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.187065 
iter  10 value 84.721050
iter  20 value 83.745084
iter  30 value 83.743160
iter  40 value 83.735375
final  value 83.728889 
converged
Fitting Repeat 5 

# weights:  305
initial  value 109.441172 
iter  10 value 94.026542
iter  10 value 94.026542
iter  10 value 94.026542
final  value 94.026542 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.496152 
final  value 94.026542 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.780292 
iter  10 value 92.669166
iter  20 value 92.354165
iter  30 value 92.320939
final  value 92.320915 
converged
Fitting Repeat 3 

# weights:  507
initial  value 113.113909 
final  value 94.470284 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.274445 
iter  10 value 86.778328
iter  20 value 84.204398
iter  30 value 83.477127
iter  40 value 83.469004
final  value 83.468993 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.428921 
iter  10 value 93.362239
iter  20 value 91.149005
iter  20 value 91.149004
iter  30 value 90.851042
iter  40 value 90.845429
final  value 90.845422 
converged
Fitting Repeat 1 

# weights:  103
initial  value 107.364150 
iter  10 value 94.448709
iter  20 value 93.075425
iter  30 value 92.985233
iter  40 value 91.721829
iter  50 value 86.250751
iter  60 value 85.767530
iter  70 value 83.661720
iter  80 value 82.900562
iter  90 value 82.514745
iter 100 value 82.030638
final  value 82.030638 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.858150 
iter  10 value 92.778405
iter  20 value 84.125493
iter  30 value 83.917215
iter  40 value 83.641311
iter  50 value 82.913777
iter  60 value 82.597933
iter  70 value 82.465386
iter  80 value 82.383317
iter  80 value 82.383316
iter  80 value 82.383316
final  value 82.383316 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.405010 
iter  10 value 91.652816
iter  20 value 87.490490
iter  30 value 84.242727
iter  40 value 83.966653
iter  50 value 83.107678
iter  60 value 82.785444
iter  70 value 82.685183
iter  80 value 82.662076
final  value 82.662036 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.859525 
iter  10 value 94.229958
iter  20 value 91.750765
iter  30 value 91.130551
iter  40 value 91.062307
iter  50 value 91.036123
iter  60 value 91.034794
final  value 91.034663 
converged
Fitting Repeat 5 

# weights:  103
initial  value 109.250778 
iter  10 value 94.081733
iter  20 value 88.673577
iter  30 value 87.895431
iter  40 value 85.739190
iter  50 value 84.752063
iter  60 value 84.660219
final  value 84.657979 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.817550 
iter  10 value 94.363296
iter  20 value 86.094625
iter  30 value 84.212327
iter  40 value 83.465613
iter  50 value 83.161170
iter  60 value 82.947197
iter  70 value 82.803274
iter  80 value 82.179681
iter  90 value 80.909637
iter 100 value 80.595762
final  value 80.595762 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.818988 
iter  10 value 94.920858
iter  20 value 93.963903
iter  30 value 85.941763
iter  40 value 84.273164
iter  50 value 83.311833
iter  60 value 82.631684
iter  70 value 82.347001
iter  80 value 82.180105
iter  90 value 81.871253
iter 100 value 81.307149
final  value 81.307149 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 119.165790 
iter  10 value 94.650235
iter  20 value 86.956801
iter  30 value 83.910747
iter  40 value 83.776161
iter  50 value 83.448838
iter  60 value 82.926443
iter  70 value 82.830742
iter  80 value 81.392565
iter  90 value 81.079745
iter 100 value 81.010774
final  value 81.010774 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.609043 
iter  10 value 94.564445
iter  20 value 90.372851
iter  30 value 87.732862
iter  40 value 85.166119
iter  50 value 85.086812
iter  60 value 84.420093
iter  70 value 82.134037
iter  80 value 80.676898
iter  90 value 80.498217
iter 100 value 80.390655
final  value 80.390655 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.860081 
iter  10 value 93.111141
iter  20 value 88.221751
iter  30 value 86.821057
iter  40 value 85.652948
iter  50 value 83.632874
iter  60 value 82.351709
iter  70 value 81.437794
iter  80 value 80.704180
iter  90 value 80.615474
iter 100 value 80.583972
final  value 80.583972 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 148.739218 
iter  10 value 93.992145
iter  20 value 89.589282
iter  30 value 85.964940
iter  40 value 82.532566
iter  50 value 81.812327
iter  60 value 80.860222
iter  70 value 80.296083
iter  80 value 80.048514
iter  90 value 79.970065
iter 100 value 79.785775
final  value 79.785775 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 114.334349 
iter  10 value 94.367509
iter  20 value 88.571627
iter  30 value 85.650704
iter  40 value 84.422963
iter  50 value 83.975347
iter  60 value 83.037437
iter  70 value 82.567630
iter  80 value 82.094020
iter  90 value 82.042024
iter 100 value 81.950487
final  value 81.950487 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 119.355714 
iter  10 value 94.794338
iter  20 value 89.375017
iter  30 value 86.966783
iter  40 value 82.800936
iter  50 value 81.668293
iter  60 value 81.297468
iter  70 value 81.051010
iter  80 value 80.801963
iter  90 value 80.559566
iter 100 value 80.233853
final  value 80.233853 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 121.036346 
iter  10 value 94.540197
iter  20 value 87.074974
iter  30 value 86.847603
iter  40 value 85.333290
iter  50 value 83.802777
iter  60 value 83.596904
iter  70 value 82.435699
iter  80 value 80.889647
iter  90 value 80.778178
iter 100 value 80.600785
final  value 80.600785 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 132.438005 
iter  10 value 94.599404
iter  20 value 94.382482
iter  30 value 92.488273
iter  40 value 91.060977
iter  50 value 86.068530
iter  60 value 83.128002
iter  70 value 81.870497
iter  80 value 81.462148
iter  90 value 81.231015
iter 100 value 80.598294
final  value 80.598294 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.342315 
iter  10 value 94.485818
iter  20 value 94.484282
iter  30 value 94.056535
iter  40 value 89.564144
iter  50 value 89.437455
iter  60 value 89.130792
iter  70 value 88.906466
iter  80 value 88.905888
iter  90 value 88.903440
final  value 88.902709 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.885330 
final  value 94.485973 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.041823 
final  value 94.486004 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.150836 
final  value 94.486575 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.493692 
final  value 94.485951 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.223714 
iter  10 value 90.638010
iter  20 value 83.480252
iter  30 value 83.036803
iter  40 value 82.571351
final  value 82.571211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.600254 
iter  10 value 90.654616
iter  20 value 88.312228
iter  30 value 87.642915
iter  40 value 87.639472
iter  50 value 86.390875
iter  60 value 86.389865
iter  70 value 86.388719
iter  80 value 86.388505
final  value 86.388499 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.840366 
iter  10 value 94.485676
iter  20 value 94.433581
iter  30 value 94.050659
iter  40 value 92.136602
iter  50 value 90.336917
iter  60 value 89.938601
iter  70 value 89.611365
iter  80 value 89.554707
iter  90 value 89.552003
iter 100 value 89.551898
final  value 89.551898 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 95.169498 
iter  10 value 94.288916
iter  20 value 94.041662
iter  30 value 94.030663
iter  40 value 93.916065
iter  50 value 92.150608
iter  60 value 91.834940
iter  70 value 91.834383
iter  80 value 91.833615
iter  90 value 91.833535
final  value 91.833480 
converged
Fitting Repeat 5 

# weights:  305
initial  value 110.853090 
iter  10 value 94.489082
iter  20 value 94.484236
iter  30 value 94.391372
iter  40 value 94.026507
iter  50 value 93.948087
iter  60 value 85.916662
iter  70 value 85.193703
iter  80 value 85.130671
iter  90 value 85.115294
iter 100 value 83.472151
final  value 83.472151 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.074139 
iter  10 value 94.072640
iter  20 value 94.034226
iter  30 value 94.029324
iter  40 value 94.027761
iter  50 value 93.802858
iter  60 value 88.077427
iter  70 value 81.962058
iter  80 value 81.626893
iter  90 value 80.879714
iter 100 value 80.181181
final  value 80.181181 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.379216 
iter  10 value 94.450367
iter  20 value 94.310428
iter  30 value 86.563574
iter  40 value 82.606825
iter  50 value 82.362632
iter  60 value 82.328818
iter  70 value 82.318084
iter  80 value 82.288724
iter  90 value 82.278863
final  value 82.278830 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.340527 
iter  10 value 94.034804
iter  20 value 94.027296
final  value 94.026822 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.689648 
iter  10 value 94.035513
iter  20 value 94.027820
iter  30 value 94.026699
iter  40 value 93.599542
iter  50 value 91.105153
iter  60 value 89.959581
final  value 89.958130 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.811341 
iter  10 value 94.491768
iter  20 value 94.481234
iter  30 value 89.510029
iter  40 value 89.214299
final  value 89.212115 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.359919 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.642360 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.749438 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.930939 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.608969 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 93.681287 
iter  10 value 85.394111
iter  20 value 85.393876
iter  20 value 85.393875
iter  20 value 85.393875
final  value 85.393875 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.578059 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 108.818577 
iter  10 value 94.338790
final  value 94.338752 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.036507 
final  value 94.291892 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.744972 
final  value 94.484210 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.060168 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 123.176390 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 108.832974 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.542202 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.996791 
iter  10 value 93.946830
iter  10 value 93.946830
iter  10 value 93.946830
final  value 93.946830 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.463797 
iter  10 value 94.548474
iter  20 value 93.789179
iter  30 value 90.499106
iter  40 value 89.798021
iter  50 value 89.687801
iter  60 value 83.270168
iter  70 value 82.009170
iter  80 value 80.533921
iter  90 value 80.300099
iter 100 value 80.200049
final  value 80.200049 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.574920 
iter  10 value 85.896941
iter  20 value 83.371335
iter  30 value 83.159033
iter  40 value 81.430042
iter  50 value 81.252975
final  value 81.252948 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.503232 
iter  10 value 93.484137
iter  20 value 89.997034
iter  30 value 87.074286
iter  40 value 84.127249
iter  50 value 83.575679
iter  60 value 81.884264
iter  70 value 81.414226
iter  80 value 81.210006
iter  90 value 81.197713
final  value 81.197675 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.247916 
iter  10 value 94.494551
iter  20 value 90.266554
iter  30 value 82.685908
iter  40 value 81.898327
iter  50 value 81.662785
iter  60 value 81.644498
iter  70 value 81.631612
iter  80 value 81.605791
final  value 81.604397 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.072766 
iter  10 value 87.194700
iter  20 value 83.876270
iter  30 value 82.331422
iter  40 value 81.811540
iter  50 value 81.258232
iter  60 value 81.197873
final  value 81.197675 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.473601 
iter  10 value 95.059261
iter  20 value 94.646630
iter  30 value 86.373019
iter  40 value 85.796038
iter  50 value 85.693453
iter  60 value 85.348768
iter  70 value 84.629625
iter  80 value 79.922319
iter  90 value 79.278995
iter 100 value 79.194517
final  value 79.194517 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.697742 
iter  10 value 94.461263
iter  20 value 83.883541
iter  30 value 83.604905
iter  40 value 83.073092
iter  50 value 82.171566
iter  60 value 81.845736
iter  70 value 81.699601
iter  80 value 81.227346
iter  90 value 81.196337
iter 100 value 81.187212
final  value 81.187212 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.491221 
iter  10 value 94.615970
iter  20 value 86.181733
iter  30 value 83.046053
iter  40 value 81.603120
iter  50 value 81.415796
iter  60 value 81.402898
iter  70 value 81.321115
iter  80 value 80.822617
iter  90 value 80.642297
iter 100 value 80.359287
final  value 80.359287 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 114.318659 
iter  10 value 94.617129
iter  20 value 90.777532
iter  30 value 82.635325
iter  40 value 81.856177
iter  50 value 81.591127
iter  60 value 80.888416
iter  70 value 80.705983
iter  80 value 80.645098
iter  90 value 80.079241
iter 100 value 79.600362
final  value 79.600362 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.455970 
iter  10 value 94.428771
iter  20 value 88.576700
iter  30 value 86.433678
iter  40 value 84.934180
iter  50 value 84.347354
iter  60 value 84.005443
iter  70 value 83.453705
iter  80 value 80.609840
iter  90 value 79.933454
iter 100 value 79.330235
final  value 79.330235 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 126.603769 
iter  10 value 95.801917
iter  20 value 94.348729
iter  30 value 94.338973
iter  40 value 88.794404
iter  50 value 82.770032
iter  60 value 82.437985
iter  70 value 81.938089
iter  80 value 81.165997
iter  90 value 80.713035
iter 100 value 80.491426
final  value 80.491426 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.673056 
iter  10 value 94.376342
iter  20 value 87.255506
iter  30 value 82.761637
iter  40 value 81.917261
iter  50 value 80.491354
iter  60 value 79.510434
iter  70 value 78.922499
iter  80 value 78.850296
iter  90 value 78.732126
iter 100 value 78.638039
final  value 78.638039 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.546396 
iter  10 value 94.757208
iter  20 value 94.508609
iter  30 value 84.198241
iter  40 value 83.968563
iter  50 value 83.566096
iter  60 value 83.191699
iter  70 value 83.040124
iter  80 value 81.768995
iter  90 value 80.740603
iter 100 value 80.436626
final  value 80.436626 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.217771 
iter  10 value 95.269374
iter  20 value 84.243705
iter  30 value 83.878739
iter  40 value 83.366279
iter  50 value 82.165312
iter  60 value 81.393075
iter  70 value 81.269921
iter  80 value 80.046053
iter  90 value 79.351286
iter 100 value 79.288350
final  value 79.288350 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.167430 
iter  10 value 94.626282
iter  20 value 88.827306
iter  30 value 84.973184
iter  40 value 82.833582
iter  50 value 80.169132
iter  60 value 79.414495
iter  70 value 79.106285
iter  80 value 79.063308
iter  90 value 79.023660
iter 100 value 78.970091
final  value 78.970091 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.418121 
iter  10 value 94.485791
iter  20 value 94.484221
iter  20 value 94.484221
iter  20 value 94.484221
final  value 94.484221 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.416555 
final  value 94.485917 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.371714 
final  value 94.485821 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.918777 
final  value 94.485659 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.601078 
iter  10 value 94.294062
iter  20 value 94.293365
iter  30 value 94.292026
final  value 94.292000 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.540004 
iter  10 value 94.487653
iter  20 value 85.393008
iter  30 value 84.770556
iter  40 value 84.769628
iter  50 value 84.377789
final  value 84.343726 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.587615 
iter  10 value 92.736067
iter  20 value 85.175239
iter  30 value 85.169085
iter  40 value 85.006678
iter  50 value 82.787731
iter  60 value 82.749691
iter  70 value 82.747227
iter  80 value 82.599933
iter  90 value 82.477279
iter 100 value 82.476310
final  value 82.476310 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.086008 
iter  10 value 92.665501
iter  20 value 92.508017
iter  30 value 91.114555
iter  40 value 85.169610
iter  50 value 85.130173
iter  60 value 85.016118
iter  70 value 85.011654
iter  80 value 84.771604
final  value 84.739989 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.217711 
iter  10 value 94.296592
iter  20 value 94.294966
iter  30 value 94.292112
iter  40 value 94.174038
iter  50 value 89.778649
iter  60 value 89.183103
final  value 89.181003 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.688855 
iter  10 value 94.496831
iter  20 value 94.432102
iter  30 value 83.006518
iter  40 value 82.556289
iter  50 value 82.548433
iter  60 value 82.516074
final  value 82.513982 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.295789 
iter  10 value 92.711958
iter  20 value 92.621914
iter  30 value 91.650508
iter  40 value 81.758808
iter  50 value 80.389702
iter  60 value 80.187586
iter  70 value 79.961891
iter  80 value 79.961447
iter  90 value 79.960576
iter 100 value 79.879869
final  value 79.879869 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.286082 
iter  10 value 94.492145
iter  20 value 94.085882
iter  30 value 83.268761
iter  40 value 82.787104
iter  50 value 80.717871
iter  60 value 79.632731
iter  70 value 79.611616
iter  80 value 79.583363
iter  90 value 79.565728
iter 100 value 79.561783
final  value 79.561783 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.813443 
iter  10 value 94.492604
iter  20 value 94.398625
final  value 94.292210 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.449028 
iter  10 value 93.876063
iter  20 value 93.856643
iter  30 value 93.761808
iter  40 value 93.760673
iter  50 value 91.210852
iter  60 value 91.041818
iter  70 value 90.880581
iter  80 value 90.764547
final  value 90.764484 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.665251 
iter  10 value 94.299958
iter  20 value 94.292781
final  value 94.292000 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.863574 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.633707 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.195169 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.454080 
iter  10 value 86.118484
iter  20 value 85.603963
final  value 85.603283 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.110258 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.797498 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.143287 
iter  10 value 86.946089
iter  20 value 83.978926
iter  30 value 83.975167
final  value 83.975155 
converged
Fitting Repeat 3 

# weights:  305
initial  value 101.403752 
final  value 93.915746 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.915788 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.481678 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.043829 
iter  10 value 91.726265
iter  20 value 91.291905
iter  30 value 90.901071
iter  40 value 90.740136
iter  50 value 90.578447
final  value 90.576979 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.892841 
final  value 93.480994 
converged
Fitting Repeat 3 

# weights:  507
initial  value 114.580538 
final  value 93.915746 
converged
Fitting Repeat 4 

# weights:  507
initial  value 113.649907 
iter  10 value 93.418899
iter  20 value 86.365821
iter  30 value 85.862909
iter  40 value 85.856096
final  value 85.855984 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.056460 
final  value 93.697143 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.469370 
iter  10 value 94.056485
iter  20 value 89.312514
iter  30 value 83.712416
iter  40 value 83.269019
iter  50 value 83.228622
final  value 83.228404 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.015390 
iter  10 value 93.988292
iter  20 value 87.642561
iter  30 value 86.017067
iter  40 value 83.234776
final  value 83.229491 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.385448 
iter  10 value 93.321288
iter  20 value 85.624561
iter  30 value 84.821929
iter  40 value 84.715287
iter  50 value 84.670593
iter  60 value 84.666433
iter  60 value 84.666433
iter  60 value 84.666433
final  value 84.666433 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.437204 
iter  10 value 94.045637
iter  20 value 93.719503
iter  30 value 93.522329
iter  40 value 86.302353
iter  50 value 83.811783
iter  60 value 83.610748
iter  70 value 83.586998
iter  80 value 83.244653
iter  90 value 83.228569
final  value 83.228404 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.662041 
iter  10 value 93.938297
iter  20 value 89.010325
iter  30 value 87.569885
iter  40 value 82.562712
iter  50 value 82.150914
iter  60 value 80.542099
iter  70 value 80.421069
iter  80 value 80.408832
final  value 80.408831 
converged
Fitting Repeat 1 

# weights:  305
initial  value 123.182308 
iter  10 value 93.949825
iter  20 value 90.832437
iter  30 value 86.626044
iter  40 value 83.017461
iter  50 value 80.194460
iter  60 value 79.860705
iter  70 value 79.603544
iter  80 value 79.567682
iter  90 value 79.536519
iter 100 value 79.394262
final  value 79.394262 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 108.738109 
iter  10 value 94.065623
iter  20 value 93.474596
iter  30 value 88.066852
iter  40 value 84.044413
iter  50 value 82.594935
iter  60 value 82.032590
iter  70 value 80.935721
iter  80 value 80.774734
iter  90 value 80.697470
iter 100 value 80.626536
final  value 80.626536 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.439573 
iter  10 value 90.426717
iter  20 value 86.791971
iter  30 value 82.086646
iter  40 value 81.661065
iter  50 value 81.268451
iter  60 value 80.725096
iter  70 value 80.129469
iter  80 value 79.503297
iter  90 value 78.953166
iter 100 value 78.879112
final  value 78.879112 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.286197 
iter  10 value 94.312522
iter  20 value 91.248222
iter  30 value 84.575404
iter  40 value 83.684232
iter  50 value 83.379201
iter  60 value 83.113366
iter  70 value 82.414910
iter  80 value 80.653627
iter  90 value 79.973906
iter 100 value 79.872407
final  value 79.872407 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.191600 
iter  10 value 93.741365
iter  20 value 87.118537
iter  30 value 85.312152
iter  40 value 84.476821
iter  50 value 82.648926
iter  60 value 81.630954
iter  70 value 81.044896
iter  80 value 79.793515
iter  90 value 79.429747
iter 100 value 79.389174
final  value 79.389174 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 114.453269 
iter  10 value 93.167218
iter  20 value 88.195933
iter  30 value 84.486733
iter  40 value 82.995620
iter  50 value 82.620781
iter  60 value 82.224947
iter  70 value 81.786146
iter  80 value 80.665339
iter  90 value 79.990745
iter 100 value 79.933126
final  value 79.933126 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.979636 
iter  10 value 88.250551
iter  20 value 82.356741
iter  30 value 81.142314
iter  40 value 80.103549
iter  50 value 80.020350
iter  60 value 79.982889
iter  70 value 79.784612
iter  80 value 79.485715
iter  90 value 79.181295
iter 100 value 78.874105
final  value 78.874105 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 117.377670 
iter  10 value 92.555593
iter  20 value 84.366234
iter  30 value 83.402166
iter  40 value 82.490841
iter  50 value 80.035701
iter  60 value 79.418071
iter  70 value 79.156823
iter  80 value 79.012609
iter  90 value 78.854253
iter 100 value 78.688156
final  value 78.688156 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 129.712184 
iter  10 value 94.809142
iter  20 value 90.113157
iter  30 value 83.591023
iter  40 value 83.076109
iter  50 value 82.392284
iter  60 value 80.478946
iter  70 value 80.255957
iter  80 value 80.097431
iter  90 value 79.931681
iter 100 value 79.617078
final  value 79.617078 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.778196 
iter  10 value 93.959156
iter  20 value 93.403024
iter  30 value 89.700785
iter  40 value 81.443503
iter  50 value 80.134990
iter  60 value 80.071104
iter  70 value 80.019829
iter  80 value 79.797382
iter  90 value 79.387638
iter 100 value 79.336104
final  value 79.336104 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.708238 
final  value 94.054520 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.123369 
final  value 94.054533 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.650331 
final  value 94.054641 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.000553 
iter  10 value 93.943020
iter  20 value 93.917880
iter  30 value 93.917332
iter  40 value 93.915947
iter  50 value 85.781413
iter  60 value 85.418810
iter  70 value 82.343002
final  value 82.332787 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.661763 
final  value 94.054350 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.798367 
iter  10 value 94.057307
iter  20 value 94.053006
final  value 94.052914 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.145440 
iter  10 value 93.211239
iter  20 value 86.832686
iter  30 value 86.829391
iter  40 value 86.800587
iter  50 value 84.577061
iter  60 value 83.593471
iter  70 value 83.383489
iter  80 value 83.380020
iter  90 value 83.029367
iter 100 value 82.335544
final  value 82.335544 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 95.811977 
iter  10 value 93.998735
iter  20 value 93.306922
iter  30 value 93.291956
iter  40 value 93.291209
iter  50 value 92.926551
iter  60 value 85.421154
iter  70 value 81.811429
iter  80 value 81.448240
final  value 81.444105 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.520098 
iter  10 value 93.920474
iter  20 value 93.764410
iter  30 value 90.113664
iter  40 value 90.036121
iter  50 value 87.485018
iter  60 value 87.415772
iter  70 value 87.413820
iter  80 value 87.413563
iter  90 value 85.866231
iter 100 value 85.577147
final  value 85.577147 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.961885 
iter  10 value 93.979574
iter  20 value 91.304844
iter  30 value 91.232250
iter  40 value 91.230514
iter  50 value 91.228030
iter  60 value 91.224392
iter  70 value 89.730134
iter  80 value 79.588266
iter  90 value 79.581124
iter 100 value 79.537904
final  value 79.537904 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 96.221387 
iter  10 value 92.584118
iter  20 value 92.578108
iter  30 value 91.959499
iter  40 value 90.848210
iter  50 value 90.773974
iter  60 value 90.723169
iter  70 value 90.722126
iter  80 value 90.721105
iter  90 value 90.715057
iter 100 value 90.708851
final  value 90.708851 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 117.440694 
iter  10 value 90.187808
iter  20 value 90.118223
iter  30 value 90.040255
iter  40 value 90.033576
iter  50 value 89.980201
iter  60 value 89.800287
iter  70 value 85.458548
iter  80 value 84.373326
iter  90 value 84.356468
iter 100 value 83.488150
final  value 83.488150 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 112.238368 
iter  10 value 92.752020
iter  20 value 91.356537
iter  30 value 91.349058
iter  40 value 88.662403
iter  50 value 85.587388
iter  60 value 85.581342
iter  70 value 85.574404
iter  70 value 85.574403
final  value 85.574403 
converged
Fitting Repeat 4 

# weights:  507
initial  value 109.268376 
iter  10 value 93.370505
iter  20 value 93.292602
iter  30 value 93.281718
final  value 93.281479 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.480127 
iter  10 value 89.722742
iter  20 value 87.464599
iter  30 value 87.453334
iter  40 value 87.447598
iter  50 value 87.446260
iter  60 value 87.377547
iter  70 value 87.275274
iter  80 value 84.173305
iter  90 value 82.904367
iter 100 value 79.136668
final  value 79.136668 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.436982 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.229648 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.126682 
final  value 93.772973 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.127503 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 110.208048 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.603469 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.631911 
iter  10 value 94.484211
iter  10 value 94.484211
iter  10 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.219445 
iter  10 value 94.305882
iter  10 value 94.305882
iter  10 value 94.305882
final  value 94.305882 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.439900 
iter  10 value 94.113046
final  value 94.112903 
converged
Fitting Repeat 5 

# weights:  305
initial  value 118.033615 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.967648 
iter  10 value 91.767371
iter  20 value 91.720527
iter  30 value 89.064628
iter  40 value 88.485357
iter  50 value 88.442353
final  value 88.442269 
converged
Fitting Repeat 2 

# weights:  507
initial  value 116.374118 
iter  10 value 94.483831
final  value 94.483809 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.639195 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 114.513409 
final  value 94.409357 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.692868 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.769530 
iter  10 value 94.486691
iter  20 value 93.703675
iter  30 value 93.603481
iter  40 value 93.599490
iter  50 value 93.593855
iter  60 value 93.592384
iter  70 value 93.591715
iter  80 value 89.298101
iter  90 value 85.210214
iter 100 value 84.852859
final  value 84.852859 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 98.974930 
iter  10 value 94.241916
iter  20 value 92.898937
iter  30 value 84.402274
iter  40 value 83.448101
iter  50 value 83.069400
iter  60 value 82.876681
iter  70 value 82.546966
iter  80 value 82.007018
iter  90 value 81.532725
iter 100 value 81.519247
final  value 81.519247 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 104.265649 
iter  10 value 94.488466
iter  20 value 94.098683
iter  30 value 94.048737
iter  40 value 94.003453
iter  50 value 93.605323
iter  60 value 88.307737
iter  70 value 87.854230
iter  80 value 85.595454
iter  90 value 84.408524
iter 100 value 83.837011
final  value 83.837011 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 105.068604 
iter  10 value 94.482394
iter  20 value 94.184828
iter  30 value 93.928900
iter  40 value 91.722878
iter  50 value 89.654266
iter  60 value 89.579313
iter  70 value 88.455030
iter  80 value 84.173724
iter  90 value 83.080984
iter 100 value 82.520987
final  value 82.520987 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.507423 
iter  10 value 94.450991
iter  20 value 92.866555
iter  30 value 88.944748
iter  40 value 86.796468
iter  50 value 85.127241
iter  60 value 84.481850
iter  70 value 83.958562
iter  80 value 82.697419
iter  90 value 81.672978
iter 100 value 81.530579
final  value 81.530579 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 100.442995 
iter  10 value 94.219263
iter  20 value 91.795820
iter  30 value 84.815068
iter  40 value 82.896398
iter  50 value 81.911981
iter  60 value 81.462554
iter  70 value 81.323193
iter  80 value 80.922323
iter  90 value 80.622896
iter 100 value 80.249590
final  value 80.249590 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 122.712559 
iter  10 value 94.159048
iter  20 value 83.893243
iter  30 value 81.931960
iter  40 value 81.333668
iter  50 value 80.912309
iter  60 value 80.775233
iter  70 value 80.290230
iter  80 value 80.198079
iter  90 value 80.148823
iter 100 value 80.114554
final  value 80.114554 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 115.819311 
iter  10 value 93.714526
iter  20 value 93.407411
iter  30 value 91.685697
iter  40 value 91.473599
iter  50 value 90.984918
iter  60 value 90.390096
iter  70 value 87.763267
iter  80 value 84.483093
iter  90 value 83.980038
iter 100 value 83.599960
final  value 83.599960 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 120.602955 
iter  10 value 94.977739
iter  20 value 87.471334
iter  30 value 86.768996
iter  40 value 86.529445
iter  50 value 85.314177
iter  60 value 84.508666
iter  70 value 84.498110
iter  80 value 84.476621
iter  90 value 84.159927
iter 100 value 82.850064
final  value 82.850064 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.182991 
iter  10 value 93.967768
iter  20 value 89.142502
iter  30 value 86.367480
iter  40 value 83.051671
iter  50 value 81.628460
iter  60 value 80.883550
iter  70 value 80.765833
iter  80 value 80.620780
iter  90 value 80.587568
iter 100 value 80.380818
final  value 80.380818 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.084954 
iter  10 value 94.166011
iter  20 value 90.250524
iter  30 value 86.888907
iter  40 value 84.320321
iter  50 value 82.251347
iter  60 value 81.083637
iter  70 value 80.772387
iter  80 value 80.575662
iter  90 value 80.531395
iter 100 value 80.475090
final  value 80.475090 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.592681 
iter  10 value 94.383577
iter  20 value 90.455456
iter  30 value 86.643454
iter  40 value 85.963088
iter  50 value 84.323595
iter  60 value 81.270403
iter  70 value 80.911397
iter  80 value 80.710888
iter  90 value 80.391165
iter 100 value 80.244388
final  value 80.244388 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.383408 
iter  10 value 95.203678
iter  20 value 88.920268
iter  30 value 86.841989
iter  40 value 86.397594
iter  50 value 85.455993
iter  60 value 85.037457
iter  70 value 83.440647
iter  80 value 81.833073
iter  90 value 80.856115
iter 100 value 80.310057
final  value 80.310057 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.412995 
iter  10 value 95.306621
iter  20 value 93.642302
iter  30 value 92.218607
iter  40 value 87.011811
iter  50 value 85.848180
iter  60 value 85.206764
iter  70 value 84.080408
iter  80 value 83.072342
iter  90 value 82.901898
iter 100 value 82.838820
final  value 82.838820 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 115.246991 
iter  10 value 95.438905
iter  20 value 93.973199
iter  30 value 91.670390
iter  40 value 90.872775
iter  50 value 88.993348
iter  60 value 84.247070
iter  70 value 83.543412
iter  80 value 83.079427
iter  90 value 82.317902
iter 100 value 81.603175
final  value 81.603175 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.815302 
final  value 94.485670 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.334191 
iter  10 value 94.485875
iter  20 value 94.484246
iter  30 value 93.605518
iter  40 value 93.376687
final  value 93.376677 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.459572 
iter  10 value 94.485904
iter  10 value 94.485903
iter  10 value 94.485903
final  value 94.485903 
converged
Fitting Repeat 4 

# weights:  103
initial  value 117.927647 
final  value 94.485929 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.630529 
final  value 94.485957 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.819303 
iter  10 value 94.484396
iter  20 value 94.484207
final  value 94.484171 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.073189 
iter  10 value 94.489023
iter  20 value 94.116707
iter  30 value 90.750397
iter  40 value 90.725764
iter  50 value 90.720312
iter  60 value 90.590527
iter  70 value 90.587356
iter  80 value 88.704582
iter  90 value 86.228344
iter 100 value 81.814755
final  value 81.814755 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 110.918489 
iter  10 value 94.488728
iter  20 value 94.477280
iter  30 value 92.637875
iter  40 value 83.613957
iter  50 value 83.176593
iter  60 value 82.808997
iter  70 value 82.765774
iter  80 value 82.741553
iter  90 value 82.721175
iter 100 value 82.703042
final  value 82.703042 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.692284 
iter  10 value 94.488797
iter  20 value 94.252055
iter  30 value 85.333029
iter  40 value 85.318199
iter  50 value 85.003615
iter  60 value 85.001922
iter  70 value 85.001592
final  value 85.000686 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.127401 
iter  10 value 91.035279
iter  20 value 90.277112
iter  30 value 89.991757
iter  40 value 89.303693
iter  50 value 89.296939
iter  60 value 89.295562
iter  70 value 88.265075
iter  80 value 88.115829
iter  90 value 88.114890
iter 100 value 88.114608
final  value 88.114608 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 102.660214 
iter  10 value 94.492634
iter  20 value 94.449810
iter  30 value 85.778615
iter  40 value 84.358951
iter  50 value 84.304925
iter  60 value 80.560155
iter  70 value 79.726692
iter  80 value 79.518716
iter  90 value 79.063866
iter 100 value 78.859696
final  value 78.859696 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 122.231496 
iter  10 value 93.878539
iter  20 value 93.780776
iter  30 value 93.391155
iter  40 value 93.374662
iter  40 value 93.374661
final  value 93.374661 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.887418 
iter  10 value 94.487941
iter  20 value 90.548776
iter  30 value 87.126512
iter  40 value 85.595746
iter  50 value 85.560438
iter  60 value 83.768457
iter  70 value 80.729310
iter  80 value 80.535285
iter  90 value 80.534899
iter 100 value 80.534215
final  value 80.534215 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 95.673967 
iter  10 value 90.787403
iter  20 value 90.772791
iter  30 value 90.695357
final  value 90.695304 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.416830 
iter  10 value 93.452546
iter  20 value 86.647521
iter  30 value 84.851789
iter  40 value 84.849556
final  value 84.849154 
converged
Fitting Repeat 1 

# weights:  305
initial  value 129.203246 
iter  10 value 117.895217
iter  20 value 117.890548
final  value 117.890300 
converged
Fitting Repeat 2 

# weights:  305
initial  value 118.997677 
iter  10 value 117.894962
iter  20 value 117.486630
iter  30 value 109.777169
iter  40 value 107.250531
iter  50 value 106.212708
iter  60 value 103.378660
iter  70 value 102.002392
iter  80 value 101.991106
iter  90 value 101.986343
iter 100 value 101.984494
final  value 101.984494 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 121.807394 
iter  10 value 117.763802
iter  20 value 117.759399
final  value 117.759309 
converged
Fitting Repeat 4 

# weights:  305
initial  value 133.855237 
iter  10 value 117.916604
iter  20 value 117.910328
iter  30 value 117.711611
iter  40 value 114.354193
iter  50 value 114.285481
iter  60 value 112.583942
iter  70 value 112.523427
iter  80 value 112.519041
iter  90 value 112.515150
iter 100 value 112.436474
final  value 112.436474 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 122.422656 
iter  10 value 117.893915
final  value 117.890311 
converged
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Wed May 15 23:20:19 2024 
*********************************************** 
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 
 41.604   1.707  43.485