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


* using log directory ‘/home/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck’
* using R version 4.4.1 (2024-06-14)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 13.2.0-23ubuntu4) 13.2.0
    GNU Fortran (Ubuntu 13.2.0-23ubuntu4) 13.2.0
* running under: Ubuntu 24.04.1 LTS
* using session charset: UTF-8
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.12.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ...Warning: unable to access index for repository https://CRAN.R-project.org/src/contrib:
  cannot open URL 'https://CRAN.R-project.org/src/contrib/PACKAGES'
 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
Unknown package ‘ftrCOOL’ in Rd xrefs
* 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
FSmethod      32.198  0.346  32.547
var_imp       31.857  0.598  32.456
corr_plot     31.868  0.208  32.080
pred_ensembel 13.393  0.486  10.441
enrichfindP    0.486  0.030   9.060
* 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 4.4.1 (2024-06-14) -- "Race for Your Life"
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 95.545053 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.339301 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.903673 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.931595 
final  value 93.915746 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.339798 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.446458 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.410311 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.638713 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 127.699485 
iter  10 value 94.052910
iter  10 value 94.052910
iter  10 value 94.052910
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 115.028148 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.723983 
final  value 94.011429 
converged
Fitting Repeat 2 

# weights:  507
initial  value 120.460504 
iter  10 value 94.011429
iter  10 value 94.011429
iter  10 value 94.011429
final  value 94.011429 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.942009 
iter  10 value 93.877268
iter  20 value 93.839514
final  value 93.839506 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.656100 
final  value 94.011429 
converged
Fitting Repeat 5 

# weights:  507
initial  value 120.503640 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.920924 
iter  10 value 94.062851
iter  20 value 88.231491
iter  30 value 84.866430
iter  40 value 84.623080
iter  50 value 84.410754
iter  60 value 84.345536
iter  70 value 84.302570
final  value 84.301275 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.338554 
iter  10 value 94.055132
iter  20 value 93.766452
iter  30 value 91.524712
iter  40 value 90.893126
iter  50 value 90.879057
iter  60 value 90.875115
iter  70 value 90.849708
iter  80 value 90.847573
final  value 90.847570 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.863261 
iter  10 value 93.833396
iter  20 value 85.444402
iter  30 value 84.565313
iter  40 value 84.516461
iter  50 value 84.302600
final  value 84.301275 
converged
Fitting Repeat 4 

# weights:  103
initial  value 109.169848 
iter  10 value 93.707644
iter  20 value 92.963349
iter  30 value 91.499326
iter  40 value 86.346076
iter  50 value 85.376401
iter  60 value 84.058702
iter  70 value 83.896935
iter  80 value 83.892999
final  value 83.892927 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.173754 
iter  10 value 94.055223
iter  20 value 94.052839
iter  30 value 93.653204
iter  40 value 92.739147
iter  50 value 92.672378
iter  60 value 92.366132
iter  70 value 91.539706
iter  80 value 91.053290
iter  90 value 91.024268
iter 100 value 91.022990
final  value 91.022990 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 128.767575 
iter  10 value 94.050131
iter  20 value 93.319031
iter  30 value 90.375984
iter  40 value 85.982767
iter  50 value 84.125529
iter  60 value 82.804903
iter  70 value 82.470938
iter  80 value 81.839667
iter  90 value 81.594287
iter 100 value 81.567951
final  value 81.567951 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 98.727083 
iter  10 value 93.913135
iter  20 value 91.552335
iter  30 value 84.269547
iter  40 value 83.559122
iter  50 value 82.856587
iter  60 value 82.690976
iter  70 value 82.253833
iter  80 value 82.129833
iter  90 value 81.781271
iter 100 value 81.668998
final  value 81.668998 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.671559 
iter  10 value 94.098513
iter  20 value 94.023002
iter  30 value 91.970731
iter  40 value 88.615961
iter  50 value 87.021872
iter  60 value 85.788480
iter  70 value 83.861150
iter  80 value 82.780584
iter  90 value 82.532395
iter 100 value 82.254188
final  value 82.254188 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.532723 
iter  10 value 94.076516
iter  20 value 93.774294
iter  30 value 92.811840
iter  40 value 88.620857
iter  50 value 84.795339
iter  60 value 83.085272
iter  70 value 82.042250
iter  80 value 81.718143
iter  90 value 81.603903
iter 100 value 81.548112
final  value 81.548112 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 128.165830 
iter  10 value 94.348751
iter  20 value 91.204432
iter  30 value 88.828652
iter  40 value 85.478504
iter  50 value 83.574936
iter  60 value 83.135717
iter  70 value 83.048167
iter  80 value 82.923277
iter  90 value 82.647014
iter 100 value 82.101154
final  value 82.101154 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.174367 
iter  10 value 93.363946
iter  20 value 84.612165
iter  30 value 84.346012
iter  40 value 84.231319
iter  50 value 83.295890
iter  60 value 82.543016
iter  70 value 81.775398
iter  80 value 81.456810
iter  90 value 81.367501
iter 100 value 81.315943
final  value 81.315943 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 122.392685 
iter  10 value 93.837669
iter  20 value 88.379077
iter  30 value 85.691893
iter  40 value 83.410020
iter  50 value 81.772627
iter  60 value 81.333817
iter  70 value 81.200287
iter  80 value 81.180299
iter  90 value 81.081279
iter 100 value 81.036169
final  value 81.036169 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 121.872454 
iter  10 value 94.285719
iter  20 value 90.527826
iter  30 value 84.774420
iter  40 value 83.922250
iter  50 value 83.270477
iter  60 value 82.703587
iter  70 value 82.209542
iter  80 value 81.909865
iter  90 value 81.785078
iter 100 value 81.488674
final  value 81.488674 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.975967 
iter  10 value 92.391671
iter  20 value 91.318191
iter  30 value 86.771661
iter  40 value 84.873063
iter  50 value 83.701097
iter  60 value 82.786038
iter  70 value 82.141158
iter  80 value 81.988571
iter  90 value 81.777848
iter 100 value 81.362169
final  value 81.362169 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 115.815088 
iter  10 value 93.496719
iter  20 value 88.792757
iter  30 value 84.792958
iter  40 value 83.911257
iter  50 value 82.427458
iter  60 value 81.904900
iter  70 value 81.381039
iter  80 value 81.208518
iter  90 value 81.119007
iter 100 value 81.065887
final  value 81.065887 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.359587 
final  value 94.054612 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.111789 
final  value 94.054410 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.731411 
final  value 94.054529 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.756458 
final  value 94.054669 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.706366 
final  value 94.054659 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.116683 
iter  10 value 93.920645
iter  20 value 93.099447
iter  30 value 85.338665
iter  40 value 85.059550
iter  50 value 85.058671
final  value 85.058202 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.737409 
iter  10 value 93.920739
iter  20 value 93.915917
iter  30 value 86.661084
iter  40 value 85.445338
iter  50 value 85.418265
iter  60 value 84.928718
iter  70 value 84.142327
final  value 84.142320 
converged
Fitting Repeat 3 

# weights:  305
initial  value 113.198946 
iter  10 value 94.058122
iter  20 value 94.053238
iter  30 value 93.936796
iter  40 value 93.617906
iter  50 value 92.677308
iter  60 value 92.664903
iter  70 value 92.664423
iter  80 value 92.663138
iter  90 value 92.018941
iter 100 value 86.832051
final  value 86.832051 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.641149 
iter  10 value 93.725652
iter  20 value 93.655712
iter  30 value 93.515154
iter  40 value 93.500233
iter  50 value 93.499489
iter  60 value 92.510091
iter  70 value 92.509455
final  value 92.509395 
converged
Fitting Repeat 5 

# weights:  305
initial  value 110.028085 
iter  10 value 93.921142
iter  20 value 93.916303
iter  30 value 87.279074
iter  40 value 87.045929
iter  50 value 87.045859
iter  60 value 86.844194
iter  70 value 86.701868
iter  80 value 86.671743
final  value 86.671583 
converged
Fitting Repeat 1 

# weights:  507
initial  value 112.930085 
iter  10 value 93.923509
iter  20 value 93.883895
iter  30 value 93.810859
iter  40 value 93.809910
final  value 93.809862 
converged
Fitting Repeat 2 

# weights:  507
initial  value 112.216374 
iter  10 value 94.060592
iter  20 value 94.008204
iter  30 value 93.148864
iter  40 value 86.699324
iter  50 value 86.641400
iter  60 value 86.640680
iter  70 value 86.638726
iter  80 value 86.637975
iter  90 value 86.637369
iter 100 value 86.637033
final  value 86.637033 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.760887 
iter  10 value 94.061296
iter  20 value 94.038923
iter  30 value 92.941782
iter  40 value 87.067180
iter  50 value 87.065558
iter  60 value 86.526094
iter  70 value 85.258910
iter  80 value 85.254748
iter  90 value 85.153889
iter 100 value 85.152549
final  value 85.152549 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.239624 
iter  10 value 93.924043
iter  20 value 93.919403
iter  30 value 93.876645
iter  40 value 93.803115
iter  50 value 93.799368
iter  60 value 93.798310
iter  70 value 93.797950
iter  80 value 93.797882
iter  90 value 93.797727
iter 100 value 92.497480
final  value 92.497480 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.921144 
iter  10 value 93.923839
iter  20 value 93.917365
iter  30 value 93.855753
iter  40 value 93.849588
iter  50 value 93.849482
final  value 93.849480 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.117902 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.878292 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.575116 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.354355 
final  value 94.008696 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.457172 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.297635 
final  value 94.008696 
converged
Fitting Repeat 2 

# weights:  305
initial  value 109.203246 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 108.072576 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.687247 
final  value 94.008696 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.185579 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.916477 
iter  10 value 94.052886
iter  10 value 94.052886
iter  20 value 93.450770
final  value 93.448534 
converged
Fitting Repeat 2 

# weights:  507
initial  value 112.889906 
iter  10 value 94.005274
final  value 94.004835 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.141132 
iter  10 value 94.009131
final  value 94.008696 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.168813 
final  value 94.008696 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.453013 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.228142 
iter  10 value 93.411682
iter  20 value 93.119832
iter  30 value 85.496756
iter  40 value 84.716074
iter  50 value 84.290274
iter  60 value 82.783677
iter  70 value 82.502855
iter  80 value 82.498344
iter  90 value 81.227030
iter 100 value 80.996863
final  value 80.996863 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 116.184473 
iter  10 value 93.993211
iter  20 value 88.901276
iter  30 value 83.993287
iter  40 value 83.752133
iter  50 value 82.724398
iter  60 value 81.636275
iter  70 value 80.672319
iter  80 value 80.562067
iter  90 value 80.505468
final  value 80.505334 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.337218 
iter  10 value 93.286563
iter  20 value 89.929537
iter  30 value 84.184280
iter  40 value 83.524705
iter  50 value 83.342277
iter  60 value 82.300162
iter  70 value 82.102201
iter  80 value 81.666676
iter  90 value 80.566540
iter 100 value 80.472034
final  value 80.472034 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 106.217645 
iter  10 value 93.854764
iter  20 value 91.643731
iter  30 value 91.180899
iter  40 value 90.925957
iter  50 value 90.913093
final  value 90.913071 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.253383 
iter  10 value 93.904974
iter  20 value 93.601021
iter  30 value 93.304881
iter  40 value 92.251197
iter  50 value 85.536924
iter  60 value 84.871771
iter  70 value 84.705253
iter  80 value 84.654616
iter  90 value 84.174227
iter 100 value 83.143703
final  value 83.143703 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 104.875948 
iter  10 value 94.038664
iter  20 value 88.494564
iter  30 value 84.553817
iter  40 value 84.085783
iter  50 value 83.912891
iter  60 value 83.742045
iter  70 value 83.653538
iter  80 value 83.619750
iter  90 value 83.498790
iter 100 value 79.880337
final  value 79.880337 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 112.037169 
iter  10 value 94.013300
iter  20 value 93.397207
iter  30 value 93.009364
iter  40 value 91.793250
iter  50 value 85.191628
iter  60 value 84.128925
iter  70 value 82.506654
iter  80 value 81.622857
iter  90 value 81.124491
iter 100 value 81.054390
final  value 81.054390 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 115.219370 
iter  10 value 94.017731
iter  20 value 93.053940
iter  30 value 91.053798
iter  40 value 89.434950
iter  50 value 84.564219
iter  60 value 83.680046
iter  70 value 83.145090
iter  80 value 83.024881
iter  90 value 82.136879
iter 100 value 81.806693
final  value 81.806693 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.176841 
iter  10 value 93.708321
iter  20 value 86.829401
iter  30 value 85.339059
iter  40 value 84.912822
iter  50 value 84.684490
iter  60 value 84.616205
iter  70 value 84.599453
iter  80 value 82.375701
iter  90 value 81.495054
iter 100 value 81.272300
final  value 81.272300 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.780596 
iter  10 value 93.996432
iter  20 value 91.288390
iter  30 value 90.753314
iter  40 value 84.751269
iter  50 value 82.378214
iter  60 value 81.361699
iter  70 value 81.277187
iter  80 value 81.152642
iter  90 value 81.083553
iter 100 value 81.041947
final  value 81.041947 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.978517 
iter  10 value 94.027398
iter  20 value 86.452056
iter  30 value 85.435936
iter  40 value 84.838536
iter  50 value 82.791278
iter  60 value 81.187299
iter  70 value 80.736439
iter  80 value 80.315317
iter  90 value 79.913522
iter 100 value 79.817703
final  value 79.817703 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.495532 
iter  10 value 94.119193
iter  20 value 86.571190
iter  30 value 85.374687
iter  40 value 84.722134
iter  50 value 82.829332
iter  60 value 80.425191
iter  70 value 79.160537
iter  80 value 79.016589
iter  90 value 78.832728
iter 100 value 78.760508
final  value 78.760508 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 116.723785 
iter  10 value 94.153482
iter  20 value 93.431400
iter  30 value 92.791154
iter  40 value 88.951786
iter  50 value 84.218783
iter  60 value 83.584073
iter  70 value 82.157026
iter  80 value 79.938203
iter  90 value 79.587719
iter 100 value 79.202926
final  value 79.202926 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.983811 
iter  10 value 94.872305
iter  20 value 93.593583
iter  30 value 91.999861
iter  40 value 86.142183
iter  50 value 82.445056
iter  60 value 81.697159
iter  70 value 81.224504
iter  80 value 80.340594
iter  90 value 79.349253
iter 100 value 78.921443
final  value 78.921443 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.121457 
iter  10 value 95.527634
iter  20 value 88.171858
iter  30 value 87.983809
iter  40 value 87.574703
iter  50 value 86.405790
iter  60 value 85.662974
iter  70 value 82.526967
iter  80 value 81.419702
iter  90 value 79.979112
iter 100 value 79.443192
final  value 79.443192 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.505705 
final  value 94.054601 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.228190 
final  value 94.054542 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.115533 
final  value 94.054890 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.983677 
final  value 94.010381 
converged
Fitting Repeat 5 

# weights:  103
initial  value 109.718323 
iter  10 value 94.010136
iter  20 value 93.783675
iter  30 value 92.352233
iter  40 value 92.294580
iter  50 value 83.487275
iter  60 value 83.128811
iter  70 value 81.619526
iter  80 value 80.805132
final  value 80.747910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.776116 
iter  10 value 94.014984
iter  20 value 94.010631
iter  30 value 94.007613
iter  40 value 85.445234
iter  50 value 85.417980
iter  60 value 85.296045
iter  70 value 85.258772
final  value 85.257796 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.288673 
iter  10 value 94.030163
iter  20 value 94.011398
iter  30 value 94.007218
iter  40 value 94.005372
iter  50 value 86.737325
iter  60 value 85.294528
final  value 85.293950 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.685671 
iter  10 value 94.057365
iter  20 value 93.116893
final  value 92.933770 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.788021 
iter  10 value 94.057491
iter  20 value 92.204626
final  value 91.901547 
converged
Fitting Repeat 5 

# weights:  305
initial  value 128.454629 
iter  10 value 94.014316
iter  20 value 94.013663
iter  30 value 94.012538
iter  40 value 93.998977
iter  50 value 85.439287
iter  60 value 85.415898
iter  70 value 84.247962
final  value 84.247341 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.548343 
iter  10 value 94.017291
iter  20 value 94.009109
iter  30 value 84.289968
iter  40 value 79.638637
iter  50 value 78.936354
iter  60 value 78.705289
iter  70 value 78.504530
iter  80 value 78.373794
iter  90 value 78.366504
final  value 78.365851 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.422260 
iter  10 value 92.407553
iter  20 value 92.230729
iter  30 value 92.227516
iter  40 value 92.222273
iter  50 value 91.287745
iter  60 value 84.891014
iter  70 value 80.614327
iter  80 value 79.181499
iter  90 value 78.044710
iter 100 value 77.189074
final  value 77.189074 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.117227 
iter  10 value 94.111629
iter  20 value 93.871929
iter  30 value 85.698454
iter  40 value 82.427891
iter  50 value 80.362065
iter  60 value 79.978049
iter  70 value 79.966121
iter  80 value 79.934881
iter  90 value 79.918697
iter 100 value 79.425551
final  value 79.425551 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.934572 
iter  10 value 94.060947
iter  20 value 93.852732
iter  30 value 92.922644
iter  40 value 92.293218
iter  50 value 87.934373
iter  60 value 83.748916
iter  70 value 82.832188
iter  80 value 82.707253
final  value 82.707029 
converged
Fitting Repeat 5 

# weights:  507
initial  value 120.956215 
iter  10 value 94.016673
iter  20 value 93.985351
iter  30 value 85.414392
final  value 85.414265 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.842718 
iter  10 value 88.835921
iter  20 value 88.008842
iter  30 value 88.000047
final  value 88.000009 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.124795 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.155811 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.999797 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.454129 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.758152 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.031463 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.995047 
iter  10 value 94.477594
iter  10 value 94.477594
iter  10 value 94.477594
final  value 94.477594 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.709839 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.035837 
final  value 94.467391 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.460260 
iter  10 value 93.672679
iter  20 value 86.976576
iter  30 value 86.659086
iter  40 value 86.657114
final  value 86.657112 
converged
Fitting Repeat 2 

# weights:  507
initial  value 130.359582 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.102527 
iter  10 value 92.133594
iter  20 value 85.299805
iter  30 value 83.514049
iter  40 value 82.990052
iter  50 value 82.159406
iter  60 value 81.958231
final  value 81.957419 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.516427 
final  value 94.467391 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.135697 
iter  10 value 94.427726
iter  10 value 94.427726
iter  10 value 94.427726
final  value 94.427726 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.087989 
iter  10 value 94.489077
iter  20 value 93.406445
iter  30 value 93.027746
iter  40 value 92.991117
iter  50 value 86.279328
iter  60 value 84.899645
iter  70 value 84.041066
iter  80 value 83.942103
final  value 83.941992 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.766460 
iter  10 value 87.488261
iter  20 value 85.970466
iter  30 value 85.654394
iter  40 value 85.576803
iter  50 value 84.109922
iter  60 value 83.139012
iter  70 value 83.085450
final  value 83.085437 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.644946 
iter  10 value 94.323549
iter  20 value 89.424568
iter  30 value 87.696627
iter  40 value 86.895441
iter  50 value 84.699259
iter  60 value 84.432204
iter  70 value 83.805653
iter  80 value 83.369156
iter  90 value 83.199574
iter 100 value 83.108805
final  value 83.108805 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.755811 
iter  10 value 90.706457
iter  20 value 85.883367
iter  30 value 85.623566
iter  40 value 85.378071
iter  50 value 84.246050
iter  60 value 83.706992
iter  70 value 83.112927
iter  80 value 83.085439
final  value 83.085437 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.817288 
iter  10 value 94.539156
iter  20 value 93.564658
iter  30 value 88.675076
iter  40 value 87.465166
iter  50 value 86.033553
iter  60 value 83.622677
iter  70 value 83.431082
iter  80 value 83.345744
iter  90 value 83.066945
iter 100 value 82.872101
final  value 82.872101 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 117.653615 
iter  10 value 94.276047
iter  20 value 93.038508
iter  30 value 89.724065
iter  40 value 87.952015
iter  50 value 85.366404
iter  60 value 84.499825
iter  70 value 83.511737
iter  80 value 83.412773
iter  90 value 83.178914
iter 100 value 82.256921
final  value 82.256921 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.069549 
iter  10 value 94.357485
iter  20 value 84.214168
iter  30 value 83.740056
iter  40 value 83.475481
iter  50 value 83.251696
iter  60 value 83.125138
iter  70 value 83.077239
iter  80 value 83.047601
iter  90 value 82.861653
iter 100 value 81.908003
final  value 81.908003 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 109.257148 
iter  10 value 94.440731
iter  20 value 92.076509
iter  30 value 87.763069
iter  40 value 86.362459
iter  50 value 84.706805
iter  60 value 83.806088
iter  70 value 83.504919
iter  80 value 83.119791
iter  90 value 82.871007
iter 100 value 82.464963
final  value 82.464963 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.327576 
iter  10 value 93.814438
iter  20 value 86.709164
iter  30 value 84.799795
iter  40 value 84.286947
iter  50 value 84.085897
iter  60 value 83.890117
iter  70 value 83.744680
iter  80 value 83.649808
iter  90 value 83.327919
iter 100 value 82.465877
final  value 82.465877 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.976698 
iter  10 value 94.474517
iter  20 value 87.713412
iter  30 value 86.637038
iter  40 value 86.393586
iter  50 value 85.574280
iter  60 value 84.295826
iter  70 value 83.623548
iter  80 value 82.701900
iter  90 value 82.229641
iter 100 value 82.128917
final  value 82.128917 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 102.845179 
iter  10 value 94.492525
iter  20 value 93.858756
iter  30 value 86.668205
iter  40 value 86.174311
iter  50 value 83.739175
iter  60 value 83.221168
iter  70 value 82.065687
iter  80 value 81.403723
iter  90 value 81.206297
iter 100 value 81.080081
final  value 81.080081 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.280415 
iter  10 value 94.736592
iter  20 value 94.494685
iter  30 value 91.262727
iter  40 value 84.842214
iter  50 value 84.339188
iter  60 value 83.920637
iter  70 value 83.083736
iter  80 value 82.187385
iter  90 value 81.722885
iter 100 value 81.615919
final  value 81.615919 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 132.307802 
iter  10 value 97.036487
iter  20 value 86.382373
iter  30 value 84.966053
iter  40 value 84.314135
iter  50 value 83.612950
iter  60 value 82.639538
iter  70 value 82.360096
iter  80 value 81.756943
iter  90 value 81.667934
iter 100 value 81.629517
final  value 81.629517 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 114.905705 
iter  10 value 88.500984
iter  20 value 87.009399
iter  30 value 85.204086
iter  40 value 83.330149
iter  50 value 82.835176
iter  60 value 81.834133
iter  70 value 81.521655
iter  80 value 81.306482
iter  90 value 81.142485
iter 100 value 81.067744
final  value 81.067744 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.180613 
iter  10 value 94.778768
iter  20 value 91.362276
iter  30 value 88.868536
iter  40 value 87.541433
iter  50 value 87.287692
iter  60 value 86.491409
iter  70 value 85.696176
iter  80 value 85.408048
iter  90 value 85.042367
iter 100 value 84.215121
final  value 84.215121 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.220276 
final  value 94.486264 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.634195 
final  value 94.485845 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.957227 
final  value 94.485641 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.320996 
final  value 94.485699 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.564452 
final  value 94.485736 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.036426 
iter  10 value 94.489761
iter  20 value 94.484706
iter  30 value 94.477609
iter  40 value 94.207824
iter  50 value 88.522443
iter  60 value 86.203118
iter  70 value 85.478321
iter  80 value 85.154251
final  value 85.152545 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.537527 
iter  10 value 94.472472
iter  20 value 94.467699
iter  30 value 94.449219
iter  40 value 91.700038
iter  50 value 85.827353
iter  60 value 83.603858
iter  70 value 83.292753
iter  80 value 83.089611
iter  90 value 83.089438
iter 100 value 83.089237
final  value 83.089237 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 95.618656 
iter  10 value 94.489022
iter  20 value 94.427812
iter  30 value 94.255703
iter  40 value 92.754403
iter  50 value 85.533764
iter  60 value 85.532311
iter  70 value 84.417321
iter  80 value 83.377080
iter  90 value 82.786280
iter 100 value 82.443400
final  value 82.443400 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 113.086441 
iter  10 value 94.488722
iter  20 value 94.476222
final  value 94.467576 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.323604 
iter  10 value 94.357082
iter  20 value 94.309486
iter  30 value 94.051253
iter  40 value 94.047953
iter  50 value 87.824178
iter  60 value 84.747406
iter  70 value 84.539842
iter  80 value 84.434322
final  value 84.429905 
converged
Fitting Repeat 1 

# weights:  507
initial  value 120.058680 
iter  10 value 94.492149
iter  20 value 94.000682
iter  30 value 86.568837
iter  40 value 86.567244
iter  50 value 86.371657
iter  60 value 84.713186
iter  70 value 84.026523
iter  80 value 84.023026
iter  90 value 83.988240
iter 100 value 83.080184
final  value 83.080184 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.921560 
iter  10 value 94.055446
iter  20 value 92.282950
iter  30 value 85.792573
iter  40 value 83.650070
iter  50 value 83.182494
iter  60 value 83.060504
iter  70 value 82.758814
iter  80 value 82.529749
iter  90 value 82.523120
final  value 82.523105 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.597345 
iter  10 value 90.982824
iter  20 value 87.667028
iter  30 value 86.347806
iter  40 value 86.125473
iter  50 value 85.504883
iter  60 value 85.301824
iter  70 value 83.035749
iter  80 value 83.030168
iter  90 value 82.838469
final  value 82.828235 
converged
Fitting Repeat 4 

# weights:  507
initial  value 117.130815 
iter  10 value 94.492262
iter  20 value 94.453496
iter  30 value 93.431874
iter  40 value 92.604839
iter  50 value 92.602445
iter  60 value 84.122597
iter  70 value 82.628562
iter  80 value 82.183135
iter  90 value 82.182122
iter 100 value 82.182032
final  value 82.182032 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 101.286451 
iter  10 value 94.328540
iter  20 value 93.348287
iter  30 value 85.596459
iter  40 value 85.561554
iter  50 value 85.505708
iter  50 value 85.505708
final  value 85.505708 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.867238 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.163485 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.421329 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.982989 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.676246 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.704239 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.495557 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.545493 
iter  10 value 94.300217
final  value 94.298189 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.837316 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 116.142880 
iter  10 value 94.466823
iter  10 value 94.466823
iter  10 value 94.466823
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.705822 
iter  10 value 92.093355
iter  20 value 91.607356
final  value 91.486613 
converged
Fitting Repeat 2 

# weights:  507
initial  value 112.966474 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.245267 
final  value 94.483810 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.380905 
iter  10 value 94.367881
iter  20 value 94.253973
final  value 94.253431 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.336840 
iter  10 value 89.988291
iter  20 value 89.845280
iter  30 value 89.637352
iter  40 value 89.636707
final  value 89.636705 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.916207 
iter  10 value 94.467082
iter  20 value 92.384859
iter  30 value 87.184539
iter  40 value 85.632046
iter  50 value 84.616293
iter  60 value 81.381904
iter  70 value 80.068247
iter  80 value 79.898669
iter  90 value 79.726518
final  value 79.725535 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.663902 
iter  10 value 94.264149
iter  20 value 87.575256
iter  30 value 87.115043
iter  40 value 86.547944
iter  50 value 85.625291
iter  60 value 85.287368
iter  70 value 84.598227
iter  80 value 84.124979
iter  90 value 84.112809
iter  90 value 84.112808
iter  90 value 84.112808
final  value 84.112808 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.174612 
iter  10 value 94.488541
iter  20 value 87.317474
iter  30 value 87.093151
iter  40 value 85.551072
iter  50 value 84.552999
iter  60 value 84.276011
iter  70 value 84.151189
iter  80 value 84.112810
final  value 84.112809 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.533321 
iter  10 value 94.244933
iter  20 value 91.690332
iter  30 value 91.416481
iter  40 value 84.708068
iter  50 value 84.262611
iter  60 value 83.947822
iter  70 value 82.927979
iter  80 value 82.633048
iter  90 value 82.540005
iter 100 value 82.456042
final  value 82.456042 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 102.286868 
iter  10 value 94.486470
iter  20 value 92.467690
iter  30 value 89.751516
iter  40 value 86.112114
iter  50 value 85.473707
iter  60 value 85.320618
iter  70 value 85.200100
iter  80 value 84.688787
iter  90 value 80.967572
iter 100 value 80.635289
final  value 80.635289 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 99.435970 
iter  10 value 94.577399
iter  20 value 93.589200
iter  30 value 92.560773
iter  40 value 90.972234
iter  50 value 90.268583
iter  60 value 87.767067
iter  70 value 86.192090
iter  80 value 84.392291
iter  90 value 83.250703
iter 100 value 82.957330
final  value 82.957330 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 115.692438 
iter  10 value 94.560497
iter  20 value 94.321124
iter  30 value 87.003717
iter  40 value 85.134605
iter  50 value 84.313892
iter  60 value 82.483646
iter  70 value 82.111811
iter  80 value 79.833720
iter  90 value 78.801028
iter 100 value 78.665610
final  value 78.665610 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 115.749323 
iter  10 value 94.476992
iter  20 value 90.685057
iter  30 value 87.698584
iter  40 value 86.770378
iter  50 value 82.563180
iter  60 value 81.219882
iter  70 value 80.278280
iter  80 value 80.030484
iter  90 value 79.487166
iter 100 value 79.222063
final  value 79.222063 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.959754 
iter  10 value 94.524798
iter  20 value 90.734601
iter  30 value 87.084616
iter  40 value 85.790349
iter  50 value 85.153795
iter  60 value 84.719562
iter  70 value 83.802968
iter  80 value 81.695279
iter  90 value 81.043266
iter 100 value 80.926621
final  value 80.926621 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.845050 
iter  10 value 94.466547
iter  20 value 86.066055
iter  30 value 82.524090
iter  40 value 82.159629
iter  50 value 80.321174
iter  60 value 79.383991
iter  70 value 79.134692
iter  80 value 78.817843
iter  90 value 78.740307
iter 100 value 78.579914
final  value 78.579914 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.546197 
iter  10 value 94.496974
iter  20 value 87.765068
iter  30 value 86.210940
iter  40 value 83.098116
iter  50 value 80.958553
iter  60 value 80.034585
iter  70 value 79.426404
iter  80 value 79.347757
iter  90 value 78.979081
iter 100 value 78.229548
final  value 78.229548 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 110.437111 
iter  10 value 94.511965
iter  20 value 87.728337
iter  30 value 85.572296
iter  40 value 85.183642
iter  50 value 81.749151
iter  60 value 80.661387
iter  70 value 80.303569
iter  80 value 79.238667
iter  90 value 78.592360
iter 100 value 78.167175
final  value 78.167175 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.398675 
iter  10 value 94.694258
iter  20 value 89.731320
iter  30 value 84.692205
iter  40 value 82.441512
iter  50 value 81.506531
iter  60 value 79.716403
iter  70 value 79.177949
iter  80 value 79.010156
iter  90 value 78.973135
iter 100 value 78.909719
final  value 78.909719 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 118.080043 
iter  10 value 93.620160
iter  20 value 88.022237
iter  30 value 86.420859
iter  40 value 83.290911
iter  50 value 81.274585
iter  60 value 80.141014
iter  70 value 79.472021
iter  80 value 79.066029
iter  90 value 78.956010
iter 100 value 78.937382
final  value 78.937382 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.425196 
iter  10 value 94.470735
iter  20 value 88.764769
iter  30 value 82.807983
iter  40 value 81.274393
iter  50 value 80.734620
iter  60 value 79.902853
iter  70 value 79.441159
iter  80 value 78.788496
iter  90 value 78.393403
iter 100 value 78.176414
final  value 78.176414 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.798303 
final  value 94.486021 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.522591 
final  value 94.485903 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.316518 
final  value 94.485728 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.078064 
final  value 94.488350 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.777360 
final  value 94.486018 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.676822 
iter  10 value 94.488253
iter  20 value 91.502904
iter  30 value 83.445119
iter  40 value 82.105462
iter  50 value 81.868683
iter  60 value 81.865740
iter  70 value 81.835899
iter  80 value 81.835478
final  value 81.831287 
converged
Fitting Repeat 2 

# weights:  305
initial  value 109.370498 
iter  10 value 94.489982
iter  20 value 94.484599
iter  30 value 94.383358
iter  40 value 84.663703
iter  50 value 84.601294
iter  60 value 82.204743
iter  70 value 82.164649
iter  80 value 81.690742
iter  90 value 80.773763
iter 100 value 80.740592
final  value 80.740592 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 125.303607 
iter  10 value 94.471375
iter  20 value 94.467536
iter  30 value 94.466912
final  value 94.466911 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.554168 
iter  10 value 94.487501
iter  20 value 94.476797
iter  30 value 91.032892
iter  40 value 88.277622
iter  50 value 88.204872
iter  60 value 88.027523
iter  70 value 87.514406
iter  80 value 87.496010
final  value 87.495978 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.645945 
iter  10 value 94.488504
iter  20 value 94.483062
iter  30 value 92.383115
iter  40 value 92.288805
iter  50 value 92.286008
iter  60 value 92.257645
iter  70 value 90.314043
iter  80 value 90.309695
iter  90 value 90.274616
iter 100 value 90.274468
final  value 90.274468 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.069532 
iter  10 value 94.086578
iter  20 value 93.225602
iter  30 value 86.115152
iter  40 value 85.696378
iter  50 value 85.344834
iter  60 value 79.262819
iter  70 value 78.911979
iter  80 value 78.910017
iter  90 value 78.909406
iter 100 value 78.905006
final  value 78.905006 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 126.280742 
iter  10 value 94.492529
iter  20 value 94.385269
iter  30 value 92.260588
iter  40 value 92.188691
iter  50 value 92.183261
final  value 92.183247 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.598529 
iter  10 value 94.474663
iter  20 value 89.831999
iter  30 value 86.301613
final  value 86.300806 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.021813 
iter  10 value 94.474918
iter  20 value 94.467499
final  value 94.466989 
converged
Fitting Repeat 5 

# weights:  507
initial  value 121.782862 
iter  10 value 94.492473
iter  20 value 94.484501
iter  30 value 89.441642
iter  40 value 84.217161
iter  50 value 83.337409
iter  60 value 82.886788
iter  70 value 82.873851
iter  80 value 82.872700
iter  90 value 82.870956
final  value 82.869148 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.081770 
final  value 94.284001 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.241577 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.682029 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.161915 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.661162 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 115.527389 
iter  10 value 92.716653
iter  20 value 90.451228
iter  30 value 85.416082
iter  30 value 85.416082
final  value 85.416057 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.840286 
iter  10 value 87.936882
iter  20 value 86.902107
final  value 86.899567 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.907580 
iter  10 value 90.412219
final  value 90.350215 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.979704 
iter  10 value 93.394938
final  value 93.394928 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.765104 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.663358 
iter  10 value 93.394928
iter  10 value 93.394928
iter  10 value 93.394928
final  value 93.394928 
converged
Fitting Repeat 2 

# weights:  507
initial  value 111.738396 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.784852 
iter  10 value 93.394932
final  value 93.394928 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.164596 
iter  10 value 93.221714
final  value 93.221696 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.258720 
iter  10 value 92.110244
iter  20 value 82.108583
iter  30 value 81.492460
iter  40 value 81.483978
iter  50 value 81.483362
final  value 81.483361 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.171594 
iter  10 value 94.486928
iter  20 value 93.862218
iter  30 value 93.710492
iter  40 value 93.512232
iter  50 value 87.061148
iter  60 value 84.974714
iter  70 value 82.047757
iter  80 value 81.156338
iter  90 value 81.129967
iter 100 value 79.869519
final  value 79.869519 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.324591 
iter  10 value 94.497175
iter  20 value 94.483308
iter  30 value 93.684947
iter  40 value 93.676670
iter  40 value 93.676669
iter  50 value 93.611703
iter  60 value 92.794904
iter  70 value 85.270523
iter  80 value 84.733833
iter  90 value 84.149163
iter 100 value 83.814439
final  value 83.814439 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 105.887454 
iter  10 value 94.318231
iter  20 value 88.730471
iter  30 value 86.781180
iter  40 value 86.426783
iter  50 value 84.617681
iter  60 value 83.881907
iter  70 value 82.307856
iter  80 value 81.894361
iter  90 value 81.718023
iter 100 value 81.392480
final  value 81.392480 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 99.779451 
iter  10 value 94.469229
iter  20 value 90.396698
iter  30 value 88.345538
iter  40 value 87.746549
iter  50 value 87.253378
iter  60 value 84.963055
iter  70 value 84.739311
iter  80 value 84.246298
iter  90 value 83.365672
iter 100 value 82.915885
final  value 82.915885 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 100.533066 
iter  10 value 92.102253
iter  20 value 87.763195
iter  30 value 87.227506
iter  40 value 86.626615
iter  50 value 86.441494
iter  60 value 83.929392
iter  70 value 82.949822
iter  80 value 82.906903
final  value 82.906842 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.296805 
iter  10 value 94.374144
iter  20 value 91.411840
iter  30 value 88.281977
iter  40 value 88.039570
iter  50 value 84.435647
iter  60 value 80.536962
iter  70 value 80.133873
iter  80 value 79.783307
iter  90 value 79.697896
iter 100 value 79.537072
final  value 79.537072 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.280340 
iter  10 value 94.499324
iter  20 value 93.854195
iter  30 value 93.676666
iter  40 value 93.621748
iter  50 value 92.710720
iter  60 value 89.611028
iter  70 value 89.235231
iter  80 value 89.166858
iter  90 value 86.172993
iter 100 value 81.369057
final  value 81.369057 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.667385 
iter  10 value 93.851604
iter  20 value 92.331257
iter  30 value 86.843304
iter  40 value 81.716121
iter  50 value 81.445050
iter  60 value 80.250084
iter  70 value 80.034430
iter  80 value 79.912581
iter  90 value 79.471405
iter 100 value 79.173657
final  value 79.173657 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.328853 
iter  10 value 94.388098
iter  20 value 84.786227
iter  30 value 82.916708
iter  40 value 81.890162
iter  50 value 80.082264
iter  60 value 79.345184
iter  70 value 78.867269
iter  80 value 78.681469
iter  90 value 78.557506
iter 100 value 78.388329
final  value 78.388329 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.000951 
iter  10 value 93.164991
iter  20 value 87.639680
iter  30 value 86.473982
iter  40 value 85.428878
iter  50 value 81.890790
iter  60 value 79.933576
iter  70 value 79.379552
iter  80 value 79.275556
iter  90 value 79.238771
iter 100 value 79.229507
final  value 79.229507 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.712412 
iter  10 value 94.493325
iter  20 value 93.525365
iter  30 value 83.944490
iter  40 value 82.603873
iter  50 value 80.474883
iter  60 value 79.842489
iter  70 value 79.453917
iter  80 value 78.849601
iter  90 value 78.487376
iter 100 value 78.143768
final  value 78.143768 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.952859 
iter  10 value 94.577765
iter  20 value 89.571545
iter  30 value 85.219973
iter  40 value 82.263931
iter  50 value 80.788343
iter  60 value 79.808740
iter  70 value 79.256470
iter  80 value 78.766364
iter  90 value 78.474000
iter 100 value 78.354124
final  value 78.354124 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 141.150974 
iter  10 value 96.826300
iter  20 value 94.050878
iter  30 value 91.810731
iter  40 value 91.025630
iter  50 value 90.153544
iter  60 value 86.252595
iter  70 value 82.189440
iter  80 value 80.045562
iter  90 value 79.336246
iter 100 value 79.016598
final  value 79.016598 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 129.372229 
iter  10 value 94.020678
iter  20 value 89.069483
iter  30 value 88.398435
iter  40 value 85.791366
iter  50 value 83.808618
iter  60 value 83.182303
iter  70 value 82.059372
iter  80 value 81.648886
iter  90 value 81.233175
iter 100 value 81.129875
final  value 81.129875 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.685686 
iter  10 value 94.602397
iter  20 value 88.577546
iter  30 value 86.996093
iter  40 value 85.701085
iter  50 value 81.074785
iter  60 value 80.074334
iter  70 value 79.827819
iter  80 value 79.784346
iter  90 value 78.883532
iter 100 value 78.827934
final  value 78.827934 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 110.475888 
final  value 94.486083 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.777594 
iter  10 value 94.486055
iter  20 value 94.484273
iter  30 value 93.728057
final  value 93.688549 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.930167 
iter  10 value 94.485732
iter  20 value 93.759779
iter  30 value 84.193875
iter  30 value 84.193875
iter  30 value 84.193875
final  value 84.193875 
converged
Fitting Repeat 4 

# weights:  103
initial  value 113.002993 
final  value 94.486024 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.579824 
final  value 94.355749 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.895360 
iter  10 value 94.488764
iter  20 value 94.461849
iter  30 value 93.395981
final  value 93.395412 
converged
Fitting Repeat 2 

# weights:  305
initial  value 123.972195 
iter  10 value 94.489067
iter  20 value 94.406413
iter  30 value 88.842553
iter  40 value 88.154641
iter  50 value 87.280391
iter  60 value 86.351677
iter  70 value 86.324737
iter  80 value 86.323404
iter  90 value 86.321791
iter 100 value 86.190922
final  value 86.190922 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 96.715312 
iter  10 value 94.493472
iter  20 value 93.584668
iter  30 value 93.400182
iter  40 value 93.395853
iter  50 value 93.181132
iter  60 value 86.344391
iter  70 value 86.323067
iter  80 value 86.320946
iter  90 value 86.320151
iter 100 value 86.319676
final  value 86.319676 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.136154 
iter  10 value 93.647899
iter  20 value 93.415426
iter  30 value 87.688754
iter  40 value 79.170504
iter  50 value 78.925765
final  value 78.921650 
converged
Fitting Repeat 5 

# weights:  305
initial  value 111.166581 
iter  10 value 93.400793
iter  20 value 93.398750
iter  30 value 84.936159
iter  40 value 81.204526
iter  50 value 79.927751
iter  60 value 79.783847
final  value 79.783178 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.464106 
iter  10 value 93.514108
iter  20 value 93.230018
iter  30 value 93.229277
iter  40 value 93.222730
iter  50 value 93.222657
iter  60 value 93.222268
iter  70 value 93.221984
iter  80 value 93.154955
iter  90 value 87.228618
iter 100 value 83.283086
final  value 83.283086 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.347161 
iter  10 value 93.423575
iter  20 value 93.231724
iter  30 value 93.225425
iter  40 value 93.222736
final  value 93.222621 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.293509 
iter  10 value 93.230124
iter  20 value 93.229734
iter  30 value 93.224130
iter  40 value 93.223684
iter  50 value 93.223343
iter  60 value 93.180380
iter  70 value 91.569812
iter  80 value 89.507099
iter  90 value 89.503740
iter 100 value 89.503419
final  value 89.503419 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 100.859738 
iter  10 value 93.230193
iter  20 value 93.225934
iter  30 value 93.222414
iter  40 value 93.136585
iter  50 value 90.912038
iter  60 value 89.677345
iter  70 value 89.627154
iter  80 value 89.318694
iter  90 value 88.639501
iter 100 value 87.808646
final  value 87.808646 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 97.603760 
iter  10 value 91.752717
iter  20 value 88.376758
iter  30 value 88.373958
iter  40 value 88.352618
final  value 88.351849 
converged
Fitting Repeat 1 

# weights:  507
initial  value 121.341274 
iter  10 value 117.898674
iter  20 value 117.888818
iter  30 value 112.934809
iter  40 value 108.680889
iter  50 value 108.272715
iter  60 value 107.247768
iter  70 value 102.844576
iter  80 value 102.512829
iter  90 value 102.512103
iter 100 value 102.231604
final  value 102.231604 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 119.344951 
iter  10 value 117.749300
iter  20 value 117.748390
iter  30 value 117.747801
iter  40 value 117.127303
iter  50 value 110.846023
iter  60 value 109.230882
iter  70 value 107.222421
iter  80 value 107.160996
iter  90 value 107.160960
iter 100 value 107.135398
final  value 107.135398 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 144.056761 
iter  10 value 117.546427
iter  20 value 117.543035
iter  30 value 117.541422
iter  40 value 117.539932
iter  50 value 117.529352
iter  60 value 117.254708
iter  70 value 115.607938
iter  80 value 114.538008
iter  90 value 114.532408
iter 100 value 114.529870
final  value 114.529870 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 123.714843 
iter  10 value 116.911953
final  value 116.911156 
converged
Fitting Repeat 5 

# weights:  507
initial  value 137.233308 
iter  10 value 117.539526
iter  20 value 117.532727
iter  30 value 115.889337
iter  40 value 108.535644
iter  50 value 108.528891
iter  50 value 108.528890
iter  50 value 108.528890
final  value 108.528890 
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 -- Sat Nov  2 01:27:04 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 
 42.660   1.749  41.474