##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R-beta-2024-04-15_r86425/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/R/R-beta-2024-04-15_r86425/site-library --no-vignettes --timings HPiP_1.10.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck’
* using R version 4.4.0 beta (2024-04-15 r86425)
* using platform: aarch64-unknown-linux-gnu
* R was compiled by
    gcc (GCC) 10.3.1
    GNU Fortran (GCC) 10.3.1
* running under: openEuler 22.03 (LTS-SP1)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.10.0’
* 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       40.361  0.766  41.207
FSmethod      38.130  0.615  38.827
corr_plot     38.266  0.412  38.758
pred_ensembel 18.673  0.301  16.620
enrichfindP    0.524  0.028  29.054
getFASTA       0.086  0.008  14.316
* 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 running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 3 NOTEs
See
  ‘/home/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R-beta-2024-04-15_r86425/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/R/R-beta-2024-04-15_r86425/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 beta (2024-04-15 r86425) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-unknown-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 110.004492 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 93.230158 
iter  10 value 85.267561
iter  20 value 84.363772
final  value 84.363399 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.652439 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.094979 
final  value 94.291892 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.367261 
iter  10 value 94.481316
iter  20 value 93.615420
final  value 93.611986 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.144715 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.209408 
final  value 94.291892 
converged
Fitting Repeat 3 

# weights:  305
initial  value 110.221583 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.010319 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.848635 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.885163 
iter  10 value 94.242106
iter  10 value 94.242106
iter  10 value 94.242106
final  value 94.242106 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.803639 
final  value 94.291892 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.787424 
iter  10 value 94.040795
iter  20 value 92.272566
iter  30 value 92.007859
iter  40 value 91.973777
iter  50 value 91.893993
final  value 91.893524 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.985574 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.565360 
iter  10 value 88.502314
iter  20 value 87.976148
final  value 87.953872 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.134947 
iter  10 value 94.488600
iter  20 value 93.162095
iter  30 value 87.395700
iter  40 value 86.163243
iter  50 value 85.300751
iter  60 value 84.916582
iter  70 value 84.825157
final  value 84.820871 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.192908 
iter  10 value 94.392319
iter  20 value 91.940246
iter  30 value 87.174402
iter  40 value 86.198715
iter  50 value 85.314028
iter  60 value 84.457302
iter  70 value 83.776839
iter  80 value 83.404098
iter  90 value 83.336738
final  value 83.330640 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.104058 
iter  10 value 94.500957
iter  20 value 94.479703
iter  30 value 92.985424
iter  40 value 88.101567
iter  50 value 86.595665
iter  60 value 85.851576
iter  70 value 85.514956
iter  80 value 85.504950
final  value 85.504943 
converged
Fitting Repeat 4 

# weights:  103
initial  value 108.110017 
iter  10 value 94.294015
iter  20 value 92.342824
iter  30 value 91.769179
iter  40 value 90.662221
iter  50 value 86.570593
iter  60 value 84.962741
iter  70 value 84.299555
iter  80 value 83.525574
iter  90 value 83.331836
final  value 83.330640 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.815374 
iter  10 value 94.520903
iter  20 value 94.428218
iter  30 value 90.425952
iter  40 value 87.781357
iter  50 value 86.782903
iter  60 value 86.384987
iter  70 value 86.045191
iter  80 value 85.906243
iter  90 value 85.787966
final  value 85.786923 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.454405 
iter  10 value 94.251899
iter  20 value 92.728483
iter  30 value 89.286694
iter  40 value 87.016481
iter  50 value 86.347281
iter  60 value 84.562129
iter  70 value 83.113568
iter  80 value 82.811643
iter  90 value 82.717598
iter 100 value 82.676937
final  value 82.676937 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.316736 
iter  10 value 94.488933
iter  20 value 92.626389
iter  30 value 88.116720
iter  40 value 87.288607
iter  50 value 86.016222
iter  60 value 84.698517
iter  70 value 83.799976
iter  80 value 83.671456
iter  90 value 83.485467
iter 100 value 83.100768
final  value 83.100768 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.066508 
iter  10 value 94.382988
iter  20 value 89.966002
iter  30 value 86.728095
iter  40 value 84.097881
iter  50 value 83.333168
iter  60 value 82.760768
iter  70 value 82.494263
iter  80 value 82.319268
iter  90 value 82.243140
iter 100 value 82.207250
final  value 82.207250 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.671609 
iter  10 value 94.499007
iter  20 value 92.583854
iter  30 value 89.915147
iter  40 value 86.352614
iter  50 value 85.336207
iter  60 value 84.965660
iter  70 value 84.796621
iter  80 value 84.372257
iter  90 value 84.247847
iter 100 value 84.198944
final  value 84.198944 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.754843 
iter  10 value 94.529697
iter  20 value 94.242506
iter  30 value 92.601951
iter  40 value 89.684350
iter  50 value 89.109227
iter  60 value 88.846927
iter  70 value 86.609173
iter  80 value 84.427912
iter  90 value 83.974413
iter 100 value 83.547753
final  value 83.547753 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 130.694844 
iter  10 value 94.383941
iter  20 value 86.955185
iter  30 value 86.026440
iter  40 value 84.240996
iter  50 value 83.775804
iter  60 value 83.206455
iter  70 value 82.761820
iter  80 value 82.701016
iter  90 value 82.497797
iter 100 value 82.307955
final  value 82.307955 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 125.347449 
iter  10 value 94.586076
iter  20 value 91.859936
iter  30 value 87.879340
iter  40 value 86.664478
iter  50 value 85.437582
iter  60 value 85.151282
iter  70 value 85.078635
iter  80 value 84.937257
iter  90 value 84.930486
iter 100 value 84.834822
final  value 84.834822 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 115.195421 
iter  10 value 94.444192
iter  20 value 90.497496
iter  30 value 86.391504
iter  40 value 85.575148
iter  50 value 84.525940
iter  60 value 83.927714
iter  70 value 83.142132
iter  80 value 83.088630
iter  90 value 82.942428
iter 100 value 82.552405
final  value 82.552405 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.937548 
iter  10 value 94.529570
iter  20 value 94.334571
iter  30 value 90.008842
iter  40 value 85.860412
iter  50 value 83.403823
iter  60 value 82.920270
iter  70 value 82.509484
iter  80 value 82.166939
iter  90 value 81.952343
iter 100 value 81.858886
final  value 81.858886 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 114.965572 
iter  10 value 94.724860
iter  20 value 87.837644
iter  30 value 86.849862
iter  40 value 84.155487
iter  50 value 83.565602
iter  60 value 82.564387
iter  70 value 82.278767
iter  80 value 82.192892
iter  90 value 82.129336
iter 100 value 82.079220
final  value 82.079220 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.956180 
final  value 94.485814 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.280582 
iter  10 value 88.209405
iter  20 value 87.255006
final  value 87.254852 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.661296 
iter  10 value 94.485980
iter  20 value 94.483558
iter  30 value 88.680227
iter  40 value 88.448707
iter  50 value 85.939615
iter  60 value 85.745622
iter  70 value 85.627821
iter  80 value 85.622050
iter  90 value 85.360463
iter  90 value 85.360462
final  value 85.360457 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.040100 
final  value 94.485716 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.890811 
final  value 94.485956 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.306405 
iter  10 value 94.488596
iter  20 value 94.477471
final  value 94.292044 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.132445 
iter  10 value 94.530798
iter  20 value 94.497115
iter  30 value 88.432287
iter  40 value 86.293170
iter  50 value 86.257097
iter  60 value 86.237326
iter  70 value 85.349983
iter  80 value 85.051427
iter  90 value 85.046984
iter 100 value 85.046453
final  value 85.046453 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.353963 
iter  10 value 94.489243
iter  20 value 94.418134
iter  30 value 86.141383
iter  40 value 85.419803
iter  50 value 85.034331
final  value 84.999365 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.765210 
iter  10 value 94.467032
iter  20 value 87.263470
iter  30 value 87.167332
iter  40 value 87.069443
iter  50 value 86.617213
iter  60 value 86.602011
iter  70 value 86.601956
iter  80 value 86.601719
iter  90 value 86.601542
iter  90 value 86.601542
iter  90 value 86.601542
final  value 86.601542 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.041223 
iter  10 value 94.491699
iter  20 value 88.966752
iter  30 value 85.806967
iter  40 value 85.703158
iter  50 value 85.696108
iter  60 value 84.669025
iter  70 value 84.409039
iter  80 value 84.383057
iter  90 value 84.381927
iter 100 value 84.377107
final  value 84.377107 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 94.174313 
iter  10 value 93.932068
iter  20 value 93.873672
iter  30 value 93.872267
iter  40 value 93.728269
iter  50 value 92.178615
iter  60 value 92.000480
iter  70 value 91.322520
iter  80 value 91.260992
final  value 91.260771 
converged
Fitting Repeat 2 

# weights:  507
initial  value 111.369684 
iter  10 value 94.437362
iter  20 value 94.429902
iter  30 value 93.793261
iter  40 value 91.764120
iter  50 value 91.520627
iter  60 value 91.389031
iter  70 value 87.810995
iter  80 value 87.723680
iter  90 value 87.706883
iter 100 value 86.117027
final  value 86.117027 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.092772 
iter  10 value 94.299874
iter  20 value 94.292836
iter  30 value 90.955603
iter  40 value 88.339076
final  value 88.335946 
converged
Fitting Repeat 4 

# weights:  507
initial  value 110.088521 
iter  10 value 94.493745
iter  20 value 94.485495
iter  30 value 93.886166
iter  40 value 92.828594
iter  50 value 92.798962
iter  60 value 92.798637
iter  70 value 92.798384
iter  80 value 92.798016
iter  90 value 92.618882
iter 100 value 92.548441
final  value 92.548441 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 112.957617 
iter  10 value 94.492325
iter  20 value 94.469622
iter  30 value 88.968816
iter  40 value 87.052842
iter  50 value 87.045575
iter  60 value 87.043384
final  value 87.043357 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.970715 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.949767 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 114.953761 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.530433 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.097169 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.163418 
iter  10 value 88.967868
iter  20 value 86.301393
iter  30 value 86.300497
final  value 86.300463 
converged
Fitting Repeat 2 

# weights:  305
initial  value 118.580371 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.570693 
iter  10 value 93.375684
iter  10 value 93.375684
iter  10 value 93.375684
final  value 93.375684 
converged
Fitting Repeat 4 

# weights:  305
initial  value 130.535135 
iter  10 value 94.423530
iter  10 value 94.423529
iter  10 value 94.423529
final  value 94.423529 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.223054 
iter  10 value 94.484219
final  value 94.484212 
converged
Fitting Repeat 1 

# weights:  507
initial  value 114.462662 
iter  10 value 87.174944
iter  20 value 84.639566
iter  30 value 84.019469
iter  40 value 83.992948
final  value 83.992913 
converged
Fitting Repeat 2 

# weights:  507
initial  value 111.044084 
iter  10 value 90.022914
iter  20 value 89.908125
iter  30 value 89.008173
iter  40 value 89.005861
final  value 89.005856 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.873961 
iter  10 value 92.331692
iter  20 value 89.116424
iter  30 value 88.894611
iter  40 value 88.893651
final  value 88.893647 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.320139 
iter  10 value 93.373169
final  value 93.372595 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.539356 
iter  10 value 89.988282
final  value 89.988263 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.442379 
iter  10 value 94.453477
iter  20 value 83.644059
iter  30 value 83.175950
iter  40 value 82.890118
iter  50 value 82.675011
iter  60 value 80.587831
iter  70 value 80.307392
iter  80 value 80.279656
final  value 80.270362 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.868830 
iter  10 value 94.488041
iter  20 value 90.872072
iter  30 value 89.283351
iter  40 value 87.238974
iter  50 value 84.865275
iter  60 value 82.298974
iter  70 value 81.948436
iter  80 value 81.649001
iter  90 value 81.638476
iter  90 value 81.638476
iter  90 value 81.638476
final  value 81.638476 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.542372 
iter  10 value 94.486642
iter  20 value 87.133566
iter  30 value 85.744209
iter  40 value 84.638973
iter  50 value 82.203519
iter  60 value 80.128899
iter  70 value 78.720883
iter  80 value 78.708040
iter  90 value 78.704822
iter 100 value 78.704755
final  value 78.704755 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 108.523862 
iter  10 value 94.491331
iter  20 value 90.037004
iter  30 value 85.339216
iter  40 value 85.047096
iter  50 value 82.605109
iter  60 value 81.628554
iter  70 value 81.493237
final  value 81.492237 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.854359 
iter  10 value 94.209692
iter  20 value 86.210608
iter  30 value 83.287971
iter  40 value 82.835353
iter  50 value 82.206302
iter  60 value 81.727497
iter  70 value 81.638476
iter  70 value 81.638476
iter  70 value 81.638476
final  value 81.638476 
converged
Fitting Repeat 1 

# weights:  305
initial  value 127.025624 
iter  10 value 94.498033
iter  20 value 86.232514
iter  30 value 85.802554
iter  40 value 84.052649
iter  50 value 82.338907
iter  60 value 79.729385
iter  70 value 79.385494
iter  80 value 78.526387
iter  90 value 77.447860
iter 100 value 77.308449
final  value 77.308449 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 120.938988 
iter  10 value 96.612580
iter  20 value 95.036932
iter  30 value 89.428992
iter  40 value 83.805582
iter  50 value 83.272225
iter  60 value 82.837363
iter  70 value 82.180142
iter  80 value 81.884306
iter  90 value 80.343786
iter 100 value 78.577566
final  value 78.577566 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 118.698347 
iter  10 value 94.575968
iter  20 value 92.061626
iter  30 value 90.381847
iter  40 value 90.199622
iter  50 value 81.261225
iter  60 value 80.140262
iter  70 value 80.098200
iter  80 value 79.073116
iter  90 value 78.669711
iter 100 value 77.665037
final  value 77.665037 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.916524 
iter  10 value 94.557091
iter  20 value 94.488199
iter  30 value 93.653080
iter  40 value 92.430722
iter  50 value 83.870053
iter  60 value 82.481612
iter  70 value 81.734495
iter  80 value 81.618860
iter  90 value 81.303905
iter 100 value 81.163950
final  value 81.163950 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 113.257620 
iter  10 value 93.973390
iter  20 value 90.692995
iter  30 value 85.787737
iter  40 value 83.288508
iter  50 value 80.175739
iter  60 value 78.213461
iter  70 value 77.958071
iter  80 value 77.782685
iter  90 value 77.623326
iter 100 value 77.382861
final  value 77.382861 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 113.004021 
iter  10 value 93.453591
iter  20 value 84.448339
iter  30 value 83.578219
iter  40 value 82.810779
iter  50 value 82.598784
iter  60 value 80.910279
iter  70 value 80.276028
iter  80 value 79.843784
iter  90 value 78.039114
iter 100 value 77.371272
final  value 77.371272 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.264305 
iter  10 value 94.404900
iter  20 value 93.771353
iter  30 value 87.827774
iter  40 value 85.974324
iter  50 value 85.563545
iter  60 value 84.444369
iter  70 value 82.465711
iter  80 value 82.039094
iter  90 value 80.013857
iter 100 value 78.536219
final  value 78.536219 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.647695 
iter  10 value 94.622743
iter  20 value 83.408596
iter  30 value 82.585394
iter  40 value 79.818791
iter  50 value 78.387323
iter  60 value 77.828191
iter  70 value 77.459903
iter  80 value 77.347710
iter  90 value 77.286349
iter 100 value 77.146885
final  value 77.146885 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.412955 
iter  10 value 94.477274
iter  20 value 94.200288
iter  30 value 93.442322
iter  40 value 88.873013
iter  50 value 84.099670
iter  60 value 80.466607
iter  70 value 79.996825
iter  80 value 78.843700
iter  90 value 77.898451
iter 100 value 77.583508
final  value 77.583508 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.812027 
iter  10 value 94.528081
iter  20 value 92.950492
iter  30 value 90.826646
iter  40 value 83.206581
iter  50 value 81.972885
iter  60 value 80.462242
iter  70 value 78.863350
iter  80 value 78.328075
iter  90 value 77.804950
iter 100 value 77.440107
final  value 77.440107 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.745741 
final  value 94.485843 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.419833 
final  value 94.485503 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.529514 
final  value 94.485725 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.727478 
final  value 94.486045 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.922464 
iter  10 value 94.485774
iter  20 value 93.947313
iter  30 value 93.406083
iter  40 value 93.365268
iter  50 value 93.365105
final  value 93.365103 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.912305 
iter  10 value 94.489123
iter  20 value 94.484236
iter  30 value 92.873869
iter  40 value 91.210523
iter  50 value 85.064900
iter  60 value 82.801315
iter  70 value 82.786190
iter  80 value 82.780495
iter  90 value 82.444431
iter 100 value 82.071758
final  value 82.071758 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 114.742191 
iter  10 value 94.489107
iter  20 value 94.325898
iter  30 value 91.507729
iter  40 value 79.976928
iter  50 value 79.592696
iter  60 value 79.464781
iter  70 value 78.938882
iter  80 value 78.521071
iter  90 value 77.940958
iter 100 value 77.867234
final  value 77.867234 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.530923 
iter  10 value 94.489006
iter  20 value 94.234383
iter  30 value 82.460359
iter  40 value 79.308355
iter  50 value 78.553784
iter  60 value 77.979917
iter  70 value 77.955711
final  value 77.955679 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.878776 
iter  10 value 94.471969
iter  20 value 94.131978
iter  30 value 83.737527
iter  40 value 81.455028
iter  50 value 81.428380
iter  60 value 81.423650
iter  60 value 81.423649
iter  60 value 81.423649
final  value 81.423649 
converged
Fitting Repeat 5 

# weights:  305
initial  value 113.887167 
iter  10 value 94.488862
iter  20 value 94.310769
iter  30 value 85.122655
final  value 85.122653 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.848109 
iter  10 value 93.463281
iter  20 value 93.206403
iter  30 value 93.204200
iter  40 value 93.200176
iter  50 value 93.199857
iter  60 value 93.199719
iter  70 value 93.081068
iter  80 value 81.673067
iter  90 value 80.720460
iter 100 value 80.719612
final  value 80.719612 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 99.141444 
iter  10 value 94.099017
iter  20 value 94.098021
iter  30 value 94.059632
iter  40 value 91.834926
iter  50 value 90.401675
iter  60 value 85.059180
iter  70 value 84.810668
iter  80 value 82.048487
iter  90 value 80.327629
iter 100 value 80.021279
final  value 80.021279 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.186689 
iter  10 value 94.492287
iter  20 value 94.269206
iter  30 value 91.963650
iter  40 value 91.962373
iter  50 value 90.429998
iter  60 value 90.420735
iter  70 value 90.416979
final  value 90.415860 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.395429 
iter  10 value 86.100519
iter  20 value 86.042801
iter  30 value 84.667970
iter  40 value 84.218422
iter  50 value 84.206806
iter  60 value 83.960574
iter  70 value 83.957758
iter  80 value 83.933116
iter  90 value 83.932443
iter  90 value 83.932442
final  value 83.932442 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.574326 
iter  10 value 85.754967
iter  20 value 85.658195
iter  30 value 85.655722
final  value 85.652069 
converged
Fitting Repeat 1 

# weights:  103
initial  value 106.725732 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.915200 
final  value 93.869755 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.023499 
final  value 92.945355 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.647942 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.255329 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.895976 
iter  10 value 93.531367
final  value 93.531283 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.784566 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.521277 
iter  10 value 92.945396
final  value 92.945355 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.951721 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 111.111831 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.624669 
iter  10 value 94.052954
final  value 94.052911 
converged
Fitting Repeat 2 

# weights:  507
initial  value 124.942374 
iter  10 value 92.945374
final  value 92.945355 
converged
Fitting Repeat 3 

# weights:  507
initial  value 112.904494 
iter  10 value 92.945355
iter  10 value 92.945355
iter  10 value 92.945355
final  value 92.945355 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.298487 
iter  10 value 94.099366
iter  20 value 93.592241
iter  30 value 91.253677
iter  40 value 91.252791
final  value 91.252787 
converged
Fitting Repeat 5 

# weights:  507
initial  value 114.126737 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.919323 
iter  10 value 93.930464
iter  20 value 88.797971
iter  30 value 86.915059
iter  40 value 86.433648
iter  50 value 84.686812
iter  60 value 83.985319
iter  70 value 83.801158
final  value 83.801120 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.163115 
iter  10 value 94.080807
iter  20 value 93.255918
iter  30 value 93.083313
iter  40 value 92.998152
iter  50 value 90.592739
iter  60 value 88.167597
iter  70 value 84.907880
iter  80 value 82.268105
iter  90 value 81.640310
iter 100 value 81.251025
final  value 81.251025 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 99.250080 
iter  10 value 93.231818
iter  20 value 91.002991
iter  30 value 85.671943
iter  40 value 84.529345
iter  50 value 84.124174
iter  60 value 83.791651
iter  70 value 83.527662
final  value 83.519879 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.645745 
iter  10 value 86.483869
iter  20 value 84.731883
iter  30 value 83.636132
iter  40 value 83.284692
final  value 83.281501 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.839590 
iter  10 value 94.056469
iter  20 value 84.057413
iter  30 value 82.992798
iter  40 value 82.465803
iter  50 value 81.496187
iter  60 value 80.929058
iter  70 value 80.588854
iter  80 value 80.295814
iter  90 value 80.286770
final  value 80.275434 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.212462 
iter  10 value 93.593621
iter  20 value 92.055829
iter  30 value 87.248424
iter  40 value 85.906882
iter  50 value 84.853737
iter  60 value 82.083704
iter  70 value 80.329658
iter  80 value 79.839523
iter  90 value 78.953793
iter 100 value 78.681670
final  value 78.681670 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.628542 
iter  10 value 94.446292
iter  20 value 85.838935
iter  30 value 85.361185
iter  40 value 84.922931
iter  50 value 84.858943
iter  60 value 84.809982
iter  70 value 84.157664
iter  80 value 83.277948
iter  90 value 81.339330
iter 100 value 80.416095
final  value 80.416095 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 120.706983 
iter  10 value 96.677816
iter  20 value 90.910802
iter  30 value 89.722312
iter  40 value 89.261163
iter  50 value 83.357441
iter  60 value 83.046370
iter  70 value 82.831366
iter  80 value 82.474592
iter  90 value 81.164919
iter 100 value 80.076332
final  value 80.076332 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.867752 
iter  10 value 94.138156
iter  20 value 90.426054
iter  30 value 85.637831
iter  40 value 84.990536
iter  50 value 83.141378
iter  60 value 80.733014
iter  70 value 80.343648
iter  80 value 80.226807
iter  90 value 79.602780
iter 100 value 79.375786
final  value 79.375786 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.649812 
iter  10 value 94.046213
iter  20 value 93.128421
iter  30 value 92.450778
iter  40 value 87.404552
iter  50 value 84.699186
iter  60 value 83.151142
iter  70 value 82.142139
iter  80 value 80.521839
iter  90 value 79.890013
iter 100 value 79.635173
final  value 79.635173 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 114.317577 
iter  10 value 93.539594
iter  20 value 91.258949
iter  30 value 87.132821
iter  40 value 84.501003
iter  50 value 82.072568
iter  60 value 81.550085
iter  70 value 81.280934
iter  80 value 80.740615
iter  90 value 80.512454
iter 100 value 80.404401
final  value 80.404401 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.345395 
iter  10 value 96.984432
iter  20 value 83.558172
iter  30 value 81.939222
iter  40 value 81.481147
iter  50 value 80.579188
iter  60 value 80.215400
iter  70 value 79.984530
iter  80 value 79.889766
iter  90 value 79.826868
iter 100 value 79.120120
final  value 79.120120 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.267945 
iter  10 value 94.354042
iter  20 value 93.833621
iter  30 value 87.945201
iter  40 value 84.785137
iter  50 value 84.012750
iter  60 value 83.796078
iter  70 value 83.158027
iter  80 value 82.112203
iter  90 value 80.151570
iter 100 value 78.913018
final  value 78.913018 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.766811 
iter  10 value 94.560716
iter  20 value 93.535903
iter  30 value 87.716472
iter  40 value 83.953709
iter  50 value 80.554298
iter  60 value 79.637870
iter  70 value 79.226529
iter  80 value 78.785727
iter  90 value 78.651505
iter 100 value 78.433978
final  value 78.433978 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.677175 
iter  10 value 94.714412
iter  20 value 85.429845
iter  30 value 84.327656
iter  40 value 83.681456
iter  50 value 83.180266
iter  60 value 82.957383
iter  70 value 82.196228
iter  80 value 80.992950
iter  90 value 80.791884
iter 100 value 80.032003
final  value 80.032003 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.950078 
iter  10 value 92.947643
iter  20 value 92.947284
final  value 92.945830 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.952710 
final  value 93.947883 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.537256 
iter  10 value 94.054633
final  value 94.052923 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.985921 
final  value 94.054555 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.506738 
final  value 94.054655 
converged
Fitting Repeat 1 

# weights:  305
initial  value 115.503667 
iter  10 value 92.951084
iter  20 value 92.949187
iter  30 value 92.779586
iter  40 value 89.841116
iter  50 value 82.351741
iter  60 value 81.943620
iter  70 value 80.845356
iter  80 value 80.470900
iter  90 value 80.277055
final  value 80.276882 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.890361 
iter  10 value 94.090534
iter  20 value 94.053978
iter  30 value 94.052930
final  value 94.052913 
converged
Fitting Repeat 3 

# weights:  305
initial  value 108.781430 
iter  10 value 94.063262
iter  20 value 94.058266
iter  30 value 92.960653
iter  40 value 92.843424
iter  50 value 92.596394
iter  60 value 92.584896
iter  70 value 92.573109
iter  80 value 83.049187
iter  90 value 81.478541
iter 100 value 81.227003
final  value 81.227003 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 115.621190 
iter  10 value 94.057434
iter  20 value 94.052939
iter  30 value 94.008187
iter  40 value 92.930230
iter  50 value 82.212892
iter  60 value 82.056336
iter  70 value 81.648439
iter  80 value 81.397324
final  value 81.392364 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.538672 
iter  10 value 92.950972
iter  20 value 92.948032
iter  30 value 92.946149
final  value 92.946038 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.582286 
iter  10 value 93.975772
iter  20 value 93.955022
iter  30 value 93.954789
iter  40 value 92.216746
iter  50 value 87.472224
iter  60 value 87.394094
iter  70 value 84.344018
iter  80 value 84.221160
iter  90 value 82.293008
iter 100 value 80.305670
final  value 80.305670 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 101.978487 
iter  10 value 92.773673
iter  20 value 92.589734
iter  30 value 92.584481
iter  40 value 87.476439
iter  50 value 86.527446
iter  60 value 86.304661
iter  70 value 86.298462
final  value 86.298460 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.832899 
iter  10 value 92.959463
iter  20 value 92.841438
iter  30 value 92.830109
iter  40 value 92.825340
iter  50 value 92.824271
iter  60 value 92.761274
iter  70 value 82.014244
iter  80 value 81.174666
final  value 81.173740 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.160374 
iter  10 value 92.941830
iter  20 value 92.864704
final  value 92.823093 
converged
Fitting Repeat 5 

# weights:  507
initial  value 109.559433 
iter  10 value 94.061547
iter  20 value 94.053628
iter  30 value 93.679589
iter  40 value 92.121104
iter  50 value 85.496624
iter  60 value 85.476820
iter  70 value 83.969397
iter  80 value 83.763724
iter  90 value 83.666798
iter 100 value 83.664440
final  value 83.664440 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.608051 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.900129 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.035324 
final  value 93.288889 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.790552 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.654579 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.385327 
final  value 93.836066 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.313162 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.871532 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.885572 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.804215 
final  value 93.836066 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.433179 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.162861 
final  value 93.836066 
converged
Fitting Repeat 3 

# weights:  507
initial  value 117.954509 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 118.554617 
iter  10 value 94.052910
iter  10 value 94.052910
iter  10 value 94.052910
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.599737 
iter  10 value 88.933811
iter  20 value 84.458720
iter  30 value 83.505099
iter  40 value 83.334915
iter  50 value 83.334634
final  value 83.334625 
converged
Fitting Repeat 1 

# weights:  103
initial  value 108.866998 
iter  10 value 94.019349
iter  20 value 93.729400
iter  30 value 89.969779
iter  40 value 89.415629
iter  50 value 87.016035
iter  60 value 86.093189
iter  70 value 85.769819
iter  80 value 83.482744
iter  90 value 82.918590
iter 100 value 82.856273
final  value 82.856273 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 102.283845 
iter  10 value 92.416857
iter  20 value 87.742824
iter  30 value 85.888570
iter  40 value 85.539601
iter  50 value 85.448984
iter  60 value 85.221402
iter  70 value 85.075164
iter  80 value 85.025748
final  value 85.025735 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.534334 
iter  10 value 94.056057
iter  20 value 94.034053
iter  30 value 94.002179
iter  40 value 93.784719
iter  50 value 87.468225
iter  60 value 87.072173
iter  70 value 86.962835
iter  80 value 84.012236
iter  90 value 82.723450
iter 100 value 82.604890
final  value 82.604890 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 103.534018 
iter  10 value 94.057351
iter  20 value 93.549390
iter  30 value 88.404529
iter  40 value 87.203406
iter  50 value 85.891105
iter  60 value 85.415967
iter  70 value 85.246130
iter  80 value 85.201417
iter  90 value 85.051906
final  value 85.025735 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.917055 
iter  10 value 91.812964
iter  20 value 87.477593
iter  30 value 86.717761
iter  40 value 85.158903
iter  50 value 85.009427
iter  60 value 85.008867
final  value 85.008729 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.477816 
iter  10 value 93.910613
iter  20 value 89.099912
iter  30 value 87.693522
iter  40 value 85.716127
iter  50 value 84.335906
iter  60 value 83.906395
iter  70 value 83.602217
iter  80 value 83.024235
iter  90 value 82.501714
iter 100 value 81.827997
final  value 81.827997 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.992827 
iter  10 value 94.045945
iter  20 value 89.131500
iter  30 value 85.844973
iter  40 value 85.264263
iter  50 value 85.216810
iter  60 value 85.175519
iter  70 value 84.809782
iter  80 value 84.252807
iter  90 value 84.062581
iter 100 value 83.277894
final  value 83.277894 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 106.351343 
iter  10 value 94.220714
iter  20 value 92.729625
iter  30 value 88.208802
iter  40 value 85.846047
iter  50 value 85.613370
iter  60 value 83.909944
iter  70 value 82.650414
iter  80 value 82.255606
iter  90 value 82.162137
iter 100 value 82.055491
final  value 82.055491 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.726345 
iter  10 value 93.877453
iter  20 value 93.240068
iter  30 value 87.331067
iter  40 value 85.472355
iter  50 value 85.326398
iter  60 value 84.438911
iter  70 value 83.340659
iter  80 value 83.141935
iter  90 value 82.727502
iter 100 value 82.229872
final  value 82.229872 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 117.223923 
iter  10 value 94.025902
iter  20 value 93.751464
iter  30 value 90.359810
iter  40 value 87.612806
iter  50 value 86.510070
iter  60 value 84.673251
iter  70 value 84.196233
iter  80 value 83.548875
iter  90 value 82.210898
iter 100 value 81.413576
final  value 81.413576 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 135.599174 
iter  10 value 96.785451
iter  20 value 94.273222
iter  30 value 93.379679
iter  40 value 88.129990
iter  50 value 87.703632
iter  60 value 87.271093
iter  70 value 85.863508
iter  80 value 83.677023
iter  90 value 83.156918
iter 100 value 82.636463
final  value 82.636463 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.262955 
iter  10 value 92.645344
iter  20 value 87.714509
iter  30 value 85.948454
iter  40 value 84.257396
iter  50 value 82.727870
iter  60 value 82.139227
iter  70 value 81.903895
iter  80 value 81.740561
iter  90 value 81.624288
iter 100 value 81.578283
final  value 81.578283 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.478082 
iter  10 value 94.223173
iter  20 value 93.800637
iter  30 value 88.732531
iter  40 value 86.691085
iter  50 value 86.363879
iter  60 value 85.153859
iter  70 value 83.897413
iter  80 value 83.417890
iter  90 value 83.278603
iter 100 value 83.243832
final  value 83.243832 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.217406 
iter  10 value 93.971304
iter  20 value 93.647225
iter  30 value 89.312849
iter  40 value 85.943612
iter  50 value 85.427074
iter  60 value 83.718111
iter  70 value 82.809555
iter  80 value 82.354053
iter  90 value 82.165165
iter 100 value 82.003880
final  value 82.003880 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.567703 
iter  10 value 93.982449
iter  20 value 93.086036
iter  30 value 86.876679
iter  40 value 84.348822
iter  50 value 82.555520
iter  60 value 81.671710
iter  70 value 81.266818
iter  80 value 81.146557
iter  90 value 81.120424
iter 100 value 81.080994
final  value 81.080994 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.766855 
iter  10 value 94.054447
iter  20 value 94.052921
final  value 94.052912 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.811909 
iter  10 value 94.054700
iter  20 value 94.039940
iter  30 value 93.605418
iter  40 value 93.604919
final  value 93.604879 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.734243 
final  value 94.054957 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.845874 
final  value 94.054369 
converged
Fitting Repeat 5 

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

# weights:  305
initial  value 95.732631 
iter  10 value 93.294054
iter  20 value 93.292826
iter  30 value 88.293421
iter  40 value 86.424107
iter  50 value 86.409748
iter  60 value 86.399004
iter  70 value 86.398367
iter  80 value 86.397186
iter  80 value 86.397186
iter  80 value 86.397185
final  value 86.397185 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.280089 
iter  10 value 93.811904
iter  20 value 93.807830
iter  30 value 93.606271
final  value 93.605756 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.464514 
iter  10 value 93.809801
iter  20 value 93.805280
iter  30 value 86.818541
iter  40 value 86.176898
iter  50 value 85.990114
final  value 85.990032 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.375371 
iter  10 value 93.352251
iter  20 value 93.109234
iter  30 value 93.095959
iter  40 value 91.672391
iter  50 value 91.659736
iter  60 value 91.659051
iter  70 value 91.643066
iter  80 value 87.452124
iter  90 value 84.186399
iter 100 value 83.590026
final  value 83.590026 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.032423 
iter  10 value 94.057531
iter  20 value 94.050088
iter  30 value 91.950046
iter  40 value 86.641708
iter  50 value 86.597109
iter  60 value 86.482298
iter  70 value 85.735649
iter  80 value 85.735322
final  value 85.735307 
converged
Fitting Repeat 1 

# weights:  507
initial  value 110.712456 
iter  10 value 94.060501
iter  20 value 94.054145
iter  30 value 93.985852
iter  40 value 93.193583
iter  50 value 85.243856
iter  60 value 84.601621
final  value 84.601533 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.149551 
iter  10 value 94.061096
iter  20 value 93.986038
final  value 93.836688 
converged
Fitting Repeat 3 

# weights:  507
initial  value 111.770880 
iter  10 value 94.061066
iter  20 value 93.870367
iter  30 value 91.901538
iter  40 value 89.203903
iter  50 value 89.165315
iter  60 value 88.820238
iter  70 value 88.781328
iter  80 value 88.757111
iter  90 value 88.666969
iter 100 value 88.652871
final  value 88.652871 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.642150 
iter  10 value 93.844312
iter  20 value 93.836204
iter  30 value 87.170425
iter  40 value 86.009801
iter  50 value 85.868280
iter  60 value 85.865113
final  value 85.865085 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.754059 
iter  10 value 94.059667
iter  20 value 92.587009
iter  30 value 88.944493
iter  40 value 88.943310
final  value 88.942504 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.309869 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.003139 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 115.137004 
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.266734 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.316292 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.964749 
iter  10 value 93.928539
iter  20 value 93.701839
final  value 93.701658 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.273572 
iter  10 value 93.942751
iter  20 value 93.942287
iter  20 value 93.942286
iter  20 value 93.942286
final  value 93.942286 
converged
Fitting Repeat 3 

# weights:  305
initial  value 108.683220 
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.144565 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.426087 
iter  10 value 94.354396
iter  10 value 94.354396
iter  10 value 94.354396
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.599670 
final  value 94.484208 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.521203 
iter  10 value 87.013000
iter  20 value 84.435619
iter  30 value 84.252095
iter  40 value 84.107129
final  value 84.107012 
converged
Fitting Repeat 3 

# weights:  507
initial  value 105.789449 
iter  10 value 94.334955
iter  20 value 93.352385
iter  30 value 93.315871
final  value 93.315658 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.833606 
iter  10 value 94.275432
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.364587 
final  value 93.701658 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.033403 
iter  10 value 94.373644
iter  20 value 88.915173
iter  30 value 84.862054
iter  40 value 84.549170
iter  50 value 84.018772
iter  60 value 83.822379
iter  70 value 83.765549
final  value 83.762623 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.517752 
iter  10 value 94.427260
iter  20 value 87.763217
iter  30 value 86.426390
iter  40 value 84.749459
iter  50 value 84.211278
iter  60 value 84.073021
iter  70 value 84.026976
final  value 84.026859 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.815412 
iter  10 value 94.420721
iter  20 value 91.767786
iter  30 value 87.635060
iter  40 value 86.032867
iter  50 value 85.686930
iter  60 value 84.151904
iter  70 value 84.026936
final  value 84.026859 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.011333 
iter  10 value 94.239102
iter  20 value 86.700556
iter  30 value 84.982863
iter  40 value 84.803941
iter  50 value 84.028169
iter  60 value 83.971560
final  value 83.971403 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.881887 
iter  10 value 94.486700
iter  20 value 94.041127
iter  30 value 93.981068
iter  40 value 86.667603
iter  50 value 85.574870
iter  60 value 84.871602
iter  70 value 84.285222
iter  80 value 84.088450
iter  90 value 84.027122
final  value 84.026859 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.167430 
iter  10 value 94.457812
iter  20 value 91.845621
iter  30 value 88.030944
iter  40 value 87.718312
iter  50 value 87.142319
iter  60 value 86.377090
iter  70 value 84.680092
iter  80 value 83.869348
iter  90 value 82.848651
iter 100 value 80.960534
final  value 80.960534 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.534846 
iter  10 value 94.596384
iter  20 value 92.446693
iter  30 value 86.023651
iter  40 value 84.773957
iter  50 value 84.649166
iter  60 value 84.445108
iter  70 value 82.875665
iter  80 value 80.966530
iter  90 value 80.776424
iter 100 value 80.647293
final  value 80.647293 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.862483 
iter  10 value 93.992318
iter  20 value 86.372094
iter  30 value 83.265858
iter  40 value 82.365270
iter  50 value 82.209180
iter  60 value 81.289155
iter  70 value 80.558814
iter  80 value 80.403176
iter  90 value 80.398111
iter 100 value 80.396013
final  value 80.396013 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.129348 
iter  10 value 94.132542
iter  20 value 90.119215
iter  30 value 84.461541
iter  40 value 82.041849
iter  50 value 81.895321
iter  60 value 81.584594
iter  70 value 81.168077
iter  80 value 80.979479
iter  90 value 80.948154
iter 100 value 80.916962
final  value 80.916962 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.669892 
iter  10 value 94.527397
iter  20 value 94.488739
iter  30 value 94.428046
iter  40 value 93.513415
iter  50 value 88.608693
iter  60 value 85.699480
iter  70 value 85.294852
iter  80 value 85.065336
iter  90 value 83.250585
iter 100 value 82.335584
final  value 82.335584 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.462072 
iter  10 value 95.179234
iter  20 value 92.950767
iter  30 value 89.730149
iter  40 value 87.981693
iter  50 value 87.162592
iter  60 value 83.884893
iter  70 value 81.643074
iter  80 value 80.799623
iter  90 value 80.717196
iter 100 value 80.677904
final  value 80.677904 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.657772 
iter  10 value 94.380617
iter  20 value 85.746484
iter  30 value 85.147202
iter  40 value 84.270654
iter  50 value 83.991913
iter  60 value 82.233688
iter  70 value 81.127302
iter  80 value 80.839878
iter  90 value 80.704480
iter 100 value 80.525677
final  value 80.525677 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.608371 
iter  10 value 96.056689
iter  20 value 94.584565
iter  30 value 89.560861
iter  40 value 86.998262
iter  50 value 85.401723
iter  60 value 82.888837
iter  70 value 82.501221
iter  80 value 82.205185
iter  90 value 81.058901
iter 100 value 80.684547
final  value 80.684547 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.348701 
iter  10 value 94.612805
iter  20 value 93.972112
iter  30 value 88.268812
iter  40 value 87.915293
iter  50 value 87.569817
iter  60 value 86.821155
iter  70 value 83.730497
iter  80 value 82.409556
iter  90 value 81.837713
iter 100 value 80.943590
final  value 80.943590 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.927294 
iter  10 value 94.201365
iter  20 value 85.424157
iter  30 value 84.357696
iter  40 value 83.817433
iter  50 value 83.685815
iter  60 value 82.092654
iter  70 value 81.499446
iter  80 value 81.064832
iter  90 value 80.941015
iter 100 value 80.905614
final  value 80.905614 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.770592 
final  value 94.485752 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.387056 
final  value 94.485753 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.993619 
iter  10 value 94.485665
iter  20 value 94.385862
iter  30 value 85.653259
iter  40 value 85.650183
iter  50 value 84.766330
iter  60 value 84.765452
iter  70 value 84.764131
iter  80 value 84.764028
final  value 84.763988 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.499859 
final  value 94.485786 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.233661 
final  value 94.485844 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.718890 
iter  10 value 94.170475
iter  20 value 94.165837
iter  30 value 86.846704
iter  40 value 83.570820
iter  50 value 83.555736
iter  60 value 83.178534
iter  70 value 82.789091
iter  80 value 82.572025
iter  90 value 82.571926
final  value 82.571914 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.109664 
iter  10 value 94.488838
iter  20 value 94.061242
iter  30 value 85.019317
iter  40 value 84.876527
iter  50 value 84.762423
final  value 84.483804 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.615422 
iter  10 value 94.487127
final  value 94.484228 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.622834 
iter  10 value 94.317116
iter  20 value 93.840498
iter  30 value 87.199302
iter  40 value 86.522652
final  value 86.522463 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.177336 
iter  10 value 94.488390
iter  20 value 94.477174
iter  30 value 93.702373
final  value 93.702372 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.723586 
iter  10 value 94.173085
iter  20 value 93.960269
iter  30 value 87.817220
iter  40 value 87.263060
iter  50 value 87.258919
iter  60 value 85.910567
final  value 85.899643 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.750267 
iter  10 value 92.198021
iter  20 value 84.332560
iter  30 value 83.016912
iter  40 value 81.720491
iter  50 value 81.710960
iter  60 value 81.552774
iter  70 value 81.118836
iter  80 value 80.892456
iter  90 value 80.469554
iter 100 value 80.446991
final  value 80.446991 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 98.092034 
iter  10 value 94.362673
iter  20 value 93.966710
iter  30 value 93.933013
iter  40 value 93.932601
final  value 93.932566 
converged
Fitting Repeat 4 

# weights:  507
initial  value 108.642475 
iter  10 value 93.608719
iter  20 value 93.601675
iter  30 value 85.644008
iter  40 value 84.418604
iter  50 value 84.400987
iter  60 value 84.380196
iter  70 value 84.379801
iter  80 value 84.377255
iter  90 value 84.376904
iter 100 value 84.376494
final  value 84.376494 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 99.575451 
iter  10 value 94.491825
iter  20 value 93.956220
iter  30 value 89.788913
iter  40 value 89.774012
iter  50 value 89.735190
iter  60 value 84.004561
iter  70 value 83.216507
iter  80 value 82.610930
iter  90 value 82.333976
iter 100 value 82.262891
final  value 82.262891 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 132.677321 
iter  10 value 117.875795
iter  20 value 114.676234
iter  30 value 107.718955
iter  40 value 106.692748
iter  50 value 105.985042
iter  60 value 105.402592
iter  70 value 105.160153
iter  80 value 104.929391
iter  90 value 104.894820
iter 100 value 104.676891
final  value 104.676891 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 125.829967 
iter  10 value 117.255513
iter  20 value 107.761298
iter  30 value 106.728854
iter  40 value 106.109281
iter  50 value 103.409841
iter  60 value 102.982953
iter  70 value 102.450476
iter  80 value 102.087771
final  value 102.065847 
converged
Fitting Repeat 3 

# weights:  305
initial  value 124.041053 
iter  10 value 118.023193
iter  20 value 117.715963
iter  30 value 112.310562
iter  40 value 106.679761
iter  50 value 105.713337
iter  60 value 105.666590
iter  70 value 104.015303
iter  80 value 102.408974
iter  90 value 101.532952
iter 100 value 101.286806
final  value 101.286806 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 123.902911 
iter  10 value 117.746842
iter  20 value 112.954985
iter  30 value 110.306998
iter  40 value 109.751369
iter  50 value 109.645648
iter  60 value 107.978992
iter  70 value 104.876741
iter  80 value 102.921625
iter  90 value 102.154467
iter 100 value 102.095201
final  value 102.095201 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 131.979456 
iter  10 value 118.052676
iter  20 value 117.856275
iter  30 value 110.872009
iter  40 value 107.529867
iter  50 value 106.439816
iter  60 value 106.089912
iter  70 value 104.891490
iter  80 value 103.310151
iter  90 value 102.057725
iter 100 value 100.963289
final  value 100.963289 
stopped after 100 iterations
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Thu May  9 08:30:50 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 
 54.870   2.200  72.581