##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:HPiP.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings HPiP_1.10.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck’
* using R version 4.4.1 (2024-06-14)
* using platform: aarch64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 12.2.0
* running under: macOS Ventura 13.6.6
* 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 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
corr_plot     52.090  2.866  55.804
FSmethod      52.245  2.667  55.544
var_imp       51.562  2.542  54.752
pred_ensembel 15.221  0.324  13.178
enrichfindP    0.539  0.084   7.941
* 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
  ‘/Users/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/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: aarch64-apple-darwin20

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 105.454741 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.660312 
final  value 94.354396 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.748822 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.864796 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.342427 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.099113 
iter  10 value 94.381465
final  value 94.381462 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.552697 
iter  10 value 94.405716
final  value 94.405650 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.057934 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.316041 
final  value 94.381462 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.731269 
iter  10 value 93.366879
iter  20 value 92.877566
iter  30 value 92.839029
final  value 92.838096 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.771778 
iter  10 value 94.382671
final  value 94.381462 
converged
Fitting Repeat 2 

# weights:  507
initial  value 118.210101 
final  value 94.381462 
converged
Fitting Repeat 3 

# weights:  507
initial  value 113.750574 
final  value 94.322897 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.940980 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.217860 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 108.996860 
iter  10 value 94.446619
iter  20 value 92.303930
iter  30 value 89.859077
iter  40 value 89.014346
iter  50 value 87.595492
iter  60 value 85.137973
iter  70 value 84.991412
iter  80 value 84.984028
iter  80 value 84.984027
iter  80 value 84.984027
final  value 84.984027 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.000384 
iter  10 value 94.492323
iter  20 value 94.410593
iter  30 value 90.918092
iter  40 value 87.019743
iter  50 value 86.659683
iter  60 value 83.974090
iter  70 value 83.970639
iter  80 value 83.965247
iter  90 value 83.956742
final  value 83.948098 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.775502 
iter  10 value 94.489302
iter  20 value 91.498114
iter  30 value 87.264497
iter  40 value 85.180003
iter  50 value 84.772490
iter  60 value 84.584756
iter  70 value 84.478108
iter  80 value 83.976376
iter  90 value 83.951681
final  value 83.948098 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.029705 
iter  10 value 94.460405
iter  20 value 86.894425
iter  30 value 86.105718
iter  40 value 85.014788
iter  50 value 84.988753
iter  60 value 84.968961
iter  70 value 84.965393
final  value 84.965272 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.326374 
iter  10 value 94.440187
iter  20 value 87.076825
iter  30 value 85.494676
iter  40 value 85.300338
iter  50 value 84.987027
final  value 84.984027 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.860258 
iter  10 value 94.171895
iter  20 value 93.347400
iter  30 value 92.875771
iter  40 value 92.629180
iter  50 value 85.275140
iter  60 value 85.007108
iter  70 value 82.834895
iter  80 value 81.421846
iter  90 value 80.086571
iter 100 value 79.724272
final  value 79.724272 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 121.704929 
iter  10 value 94.701683
iter  20 value 94.410645
iter  30 value 87.021072
iter  40 value 85.669731
iter  50 value 85.103765
iter  60 value 84.153499
iter  70 value 82.303812
iter  80 value 80.001945
iter  90 value 79.887462
iter 100 value 79.580463
final  value 79.580463 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.974871 
iter  10 value 94.444285
iter  20 value 92.760610
iter  30 value 87.872261
iter  40 value 86.641117
iter  50 value 83.159756
iter  60 value 82.823522
iter  70 value 82.527502
iter  80 value 82.469302
iter  90 value 82.383703
iter 100 value 82.043853
final  value 82.043853 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.113116 
iter  10 value 93.830441
iter  20 value 87.894464
iter  30 value 84.756574
iter  40 value 83.756454
iter  50 value 83.336926
iter  60 value 83.228268
iter  70 value 83.182947
iter  80 value 83.033219
iter  90 value 81.079427
iter 100 value 80.315741
final  value 80.315741 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 113.565789 
iter  10 value 94.292983
iter  20 value 89.736504
iter  30 value 85.950954
iter  40 value 81.776138
iter  50 value 79.868467
iter  60 value 79.717489
iter  70 value 79.605258
iter  80 value 79.367225
iter  90 value 79.302515
iter 100 value 79.220682
final  value 79.220682 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.868083 
iter  10 value 94.592365
iter  20 value 94.491667
iter  30 value 93.941537
iter  40 value 88.099744
iter  50 value 84.014071
iter  60 value 80.930117
iter  70 value 79.704424
iter  80 value 79.219400
iter  90 value 79.148629
iter 100 value 78.932570
final  value 78.932570 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 116.574577 
iter  10 value 94.322653
iter  20 value 92.585828
iter  30 value 90.360889
iter  40 value 87.194081
iter  50 value 85.420309
iter  60 value 82.461784
iter  70 value 80.567211
iter  80 value 80.200343
iter  90 value 79.610711
iter 100 value 79.393058
final  value 79.393058 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 137.196841 
iter  10 value 94.453051
iter  20 value 87.438174
iter  30 value 86.085904
iter  40 value 83.280617
iter  50 value 81.601781
iter  60 value 81.500093
iter  70 value 80.838946
iter  80 value 80.755583
iter  90 value 80.524548
iter 100 value 80.399217
final  value 80.399217 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.907371 
iter  10 value 94.521241
iter  20 value 87.573487
iter  30 value 86.729529
iter  40 value 84.272523
iter  50 value 81.990978
iter  60 value 81.703168
iter  70 value 81.549010
iter  80 value 81.299459
iter  90 value 80.142233
iter 100 value 79.895570
final  value 79.895570 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 117.306019 
iter  10 value 94.549494
iter  20 value 90.610060
iter  30 value 88.063841
iter  40 value 86.964695
iter  50 value 84.854999
iter  60 value 83.307358
iter  70 value 81.996710
iter  80 value 80.195659
iter  90 value 79.496329
iter 100 value 79.360501
final  value 79.360501 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.249517 
final  value 94.485740 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.222582 
final  value 94.485801 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.672244 
final  value 94.485936 
converged
Fitting Repeat 4 

# weights:  103
initial  value 108.026690 
iter  10 value 94.485901
iter  20 value 94.484237
final  value 94.484216 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.442334 
final  value 94.485730 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.728544 
iter  10 value 94.411368
iter  20 value 94.401352
iter  30 value 89.112739
iter  40 value 86.966710
iter  50 value 83.045565
iter  60 value 81.395914
iter  70 value 81.211649
iter  80 value 81.208287
iter  90 value 81.182133
iter 100 value 81.165798
final  value 81.165798 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.994150 
iter  10 value 94.488880
iter  20 value 94.481410
iter  30 value 87.182409
iter  40 value 84.699085
iter  50 value 83.532580
iter  60 value 83.087156
iter  70 value 80.055378
iter  80 value 77.911667
iter  90 value 77.563264
iter 100 value 77.170562
final  value 77.170562 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 98.776383 
iter  10 value 94.488743
iter  20 value 94.422766
iter  30 value 87.996060
iter  40 value 87.369571
iter  50 value 86.200842
iter  60 value 82.265476
iter  70 value 80.656743
iter  80 value 80.492879
iter  90 value 79.915143
iter 100 value 78.505846
final  value 78.505846 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.235176 
iter  10 value 94.488914
iter  20 value 94.484235
iter  30 value 88.015342
iter  40 value 86.153046
iter  50 value 86.062618
iter  60 value 85.909974
iter  70 value 85.904745
final  value 85.904422 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.026836 
iter  10 value 94.386878
iter  20 value 94.383065
iter  30 value 93.719824
iter  40 value 84.649968
iter  50 value 82.596990
iter  60 value 82.207448
iter  70 value 82.166932
final  value 82.166733 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.379257 
iter  10 value 94.392902
iter  20 value 92.972133
iter  30 value 86.095618
iter  40 value 86.022182
iter  50 value 85.873378
iter  60 value 85.872783
final  value 85.872495 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.157617 
iter  10 value 94.492302
iter  20 value 94.484004
iter  30 value 94.354929
iter  40 value 90.683765
iter  50 value 84.429261
iter  60 value 84.419354
final  value 84.419027 
converged
Fitting Repeat 3 

# weights:  507
initial  value 111.099923 
iter  10 value 94.491610
iter  20 value 94.409082
iter  30 value 86.771029
iter  40 value 83.730082
iter  50 value 83.559264
final  value 83.557352 
converged
Fitting Repeat 4 

# weights:  507
initial  value 119.338333 
iter  10 value 94.442638
iter  20 value 94.394649
iter  30 value 89.739553
iter  40 value 86.884510
iter  50 value 86.821563
iter  60 value 86.094747
iter  70 value 83.144021
iter  80 value 79.883801
iter  90 value 79.168941
iter 100 value 79.163423
final  value 79.163423 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 96.049953 
iter  10 value 94.491618
iter  20 value 93.583614
iter  30 value 91.650971
iter  30 value 91.650970
iter  40 value 85.151704
iter  50 value 84.751236
iter  60 value 84.748164
iter  70 value 84.746803
iter  80 value 84.730762
iter  90 value 84.247423
iter 100 value 82.072450
final  value 82.072450 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 105.239920 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.009049 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.775781 
final  value 93.637380 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.723339 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.567223 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.335518 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.254992 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.719969 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 111.058359 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 118.944750 
iter  10 value 94.484211
iter  10 value 94.484211
iter  10 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 95.492980 
iter  10 value 89.678543
iter  20 value 84.741986
iter  30 value 84.134428
iter  40 value 83.824010
iter  50 value 83.546509
iter  60 value 82.599032
iter  70 value 81.773328
iter  80 value 81.692320
iter  90 value 81.633929
iter 100 value 81.631545
final  value 81.631545 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 97.775793 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.928511 
iter  10 value 93.401047
iter  20 value 86.643690
iter  30 value 84.227035
iter  40 value 84.225557
final  value 84.225554 
converged
Fitting Repeat 4 

# weights:  507
initial  value 116.556740 
iter  10 value 94.012634
iter  20 value 93.704171
final  value 93.703974 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.752032 
iter  10 value 93.924678
iter  20 value 93.662855
iter  30 value 92.834313
iter  40 value 92.829467
final  value 92.829462 
converged
Fitting Repeat 1 

# weights:  103
initial  value 114.419779 
iter  10 value 94.162426
iter  20 value 86.468169
iter  30 value 85.030037
iter  40 value 84.339583
iter  50 value 83.491908
iter  60 value 83.272215
iter  70 value 82.911671
iter  80 value 82.480646
iter  90 value 82.339134
final  value 82.339011 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.138609 
iter  10 value 93.971810
iter  20 value 92.808682
iter  30 value 89.466938
iter  40 value 88.897354
iter  50 value 83.618059
iter  60 value 82.420303
iter  70 value 82.346095
iter  80 value 82.224764
final  value 82.222728 
converged
Fitting Repeat 3 

# weights:  103
initial  value 109.215090 
iter  10 value 94.114301
iter  20 value 89.783817
iter  30 value 85.995544
iter  40 value 83.932768
iter  50 value 83.136264
iter  60 value 82.964306
iter  70 value 82.901584
iter  80 value 82.792914
iter  90 value 82.339065
final  value 82.339011 
converged
Fitting Repeat 4 

# weights:  103
initial  value 109.708068 
iter  10 value 94.610538
iter  20 value 94.504587
iter  30 value 88.561995
iter  40 value 86.192221
iter  50 value 85.503581
iter  60 value 84.961171
iter  70 value 84.790432
final  value 84.790239 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.212795 
iter  10 value 87.185362
iter  20 value 85.166994
iter  30 value 84.693608
iter  40 value 83.680621
iter  50 value 83.119062
iter  60 value 82.673074
iter  70 value 82.339215
final  value 82.339011 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.309838 
iter  10 value 93.869275
iter  20 value 86.054069
iter  30 value 83.515575
iter  40 value 82.905369
iter  50 value 82.748515
iter  60 value 82.546152
iter  70 value 82.229431
iter  80 value 82.197601
iter  90 value 81.867784
iter 100 value 81.208156
final  value 81.208156 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 114.346246 
iter  10 value 94.265562
iter  20 value 89.502141
iter  30 value 88.913423
iter  40 value 86.034494
iter  50 value 83.695863
iter  60 value 82.312730
iter  70 value 81.281059
iter  80 value 80.944174
iter  90 value 80.787132
iter 100 value 80.755992
final  value 80.755992 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 118.138266 
iter  10 value 94.600934
iter  20 value 87.421885
iter  30 value 85.189624
iter  40 value 84.082523
iter  50 value 82.734941
iter  60 value 82.113333
iter  70 value 81.879662
iter  80 value 81.582436
iter  90 value 81.432562
iter 100 value 81.295852
final  value 81.295852 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.187878 
iter  10 value 94.520700
iter  20 value 91.750698
iter  30 value 88.281606
iter  40 value 83.591744
iter  50 value 82.315532
iter  60 value 82.254700
iter  70 value 82.050074
iter  80 value 81.578047
iter  90 value 81.364477
iter 100 value 81.338600
final  value 81.338600 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.576574 
iter  10 value 94.591803
iter  20 value 94.508672
iter  30 value 93.784525
iter  40 value 91.304250
iter  50 value 85.953945
iter  60 value 85.243688
iter  70 value 85.071871
iter  80 value 84.660181
iter  90 value 83.800567
iter 100 value 83.112042
final  value 83.112042 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 120.067729 
iter  10 value 94.434038
iter  20 value 87.515742
iter  30 value 87.129722
iter  40 value 85.995674
iter  50 value 82.721832
iter  60 value 82.387759
iter  70 value 82.122176
iter  80 value 81.328906
iter  90 value 81.151727
iter 100 value 81.029747
final  value 81.029747 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.069981 
iter  10 value 94.611456
iter  20 value 87.108177
iter  30 value 86.789132
iter  40 value 86.318035
iter  50 value 83.776843
iter  60 value 82.089288
iter  70 value 81.468587
iter  80 value 81.388171
iter  90 value 81.331172
iter 100 value 81.189039
final  value 81.189039 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.541171 
iter  10 value 93.437730
iter  20 value 87.399460
iter  30 value 83.243330
iter  40 value 83.005371
iter  50 value 82.820091
iter  60 value 82.630554
iter  70 value 82.090783
iter  80 value 81.905602
iter  90 value 81.758881
iter 100 value 81.586753
final  value 81.586753 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 122.616725 
iter  10 value 95.318427
iter  20 value 93.995558
iter  30 value 91.038977
iter  40 value 88.425544
iter  50 value 85.335764
iter  60 value 83.874108
iter  70 value 83.484043
iter  80 value 82.703052
iter  90 value 82.353274
iter 100 value 81.985920
final  value 81.985920 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.187113 
iter  10 value 94.462694
iter  20 value 90.287755
iter  30 value 85.257010
iter  40 value 84.845451
iter  50 value 84.053175
iter  60 value 83.626147
iter  70 value 82.563660
iter  80 value 81.815442
iter  90 value 81.492764
iter 100 value 81.459184
final  value 81.459184 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.739073 
final  value 94.485724 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.194979 
final  value 94.486019 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.672664 
iter  10 value 94.486091
iter  20 value 94.409328
iter  30 value 90.710338
iter  40 value 87.811986
iter  50 value 87.164660
iter  60 value 86.638297
iter  70 value 85.475833
final  value 85.390397 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.558496 
final  value 94.485814 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.427395 
final  value 94.486012 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.440312 
iter  10 value 94.489599
iter  20 value 94.425318
iter  30 value 93.258801
iter  40 value 93.212051
iter  50 value 92.664748
iter  60 value 92.605844
iter  70 value 92.598088
iter  80 value 87.732350
iter  90 value 87.261130
iter 100 value 87.259441
final  value 87.259441 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 123.460119 
iter  10 value 94.489461
iter  20 value 94.484745
iter  30 value 94.282428
iter  40 value 91.693926
iter  50 value 91.573531
iter  60 value 91.573250
iter  70 value 91.572576
final  value 91.572558 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.710995 
iter  10 value 93.646370
iter  20 value 93.640557
iter  30 value 88.791322
iter  40 value 86.741110
iter  50 value 86.233607
iter  60 value 86.182652
final  value 86.182296 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.518571 
iter  10 value 94.489706
iter  20 value 93.783507
iter  30 value 86.834408
iter  40 value 86.546294
iter  50 value 86.545858
iter  60 value 86.545248
iter  70 value 86.544777
iter  80 value 86.544583
final  value 86.544580 
converged
Fitting Repeat 5 

# weights:  305
initial  value 114.134972 
iter  10 value 94.484523
iter  20 value 89.339930
iter  30 value 89.076268
iter  40 value 88.186736
final  value 87.952614 
converged
Fitting Repeat 1 

# weights:  507
initial  value 118.332864 
iter  10 value 94.283428
iter  20 value 93.697557
final  value 93.637993 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.623969 
iter  10 value 92.769973
iter  20 value 92.029557
iter  30 value 91.958297
iter  40 value 91.932931
iter  50 value 91.291304
iter  60 value 91.238696
iter  70 value 91.236127
iter  80 value 91.233533
iter  90 value 91.157074
iter 100 value 83.812090
final  value 83.812090 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 98.694357 
iter  10 value 94.491995
iter  20 value 94.464764
iter  30 value 92.655620
final  value 92.613027 
converged
Fitting Repeat 4 

# weights:  507
initial  value 107.173169 
iter  10 value 94.283242
iter  20 value 94.276790
iter  30 value 93.652994
iter  40 value 93.638100
final  value 93.637899 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.679408 
iter  10 value 94.492581
iter  20 value 93.628973
iter  30 value 86.328571
iter  40 value 81.903733
iter  50 value 80.845615
iter  60 value 80.259502
iter  70 value 79.741051
iter  80 value 79.675124
iter  90 value 79.538613
iter 100 value 79.488637
final  value 79.488637 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.467348 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.510565 
iter  10 value 94.484213
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.299330 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.182242 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.591786 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.750591 
final  value 93.860350 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.717130 
final  value 94.484210 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.496346 
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.234102 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.700365 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.335465 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  507
initial  value 132.666500 
iter  10 value 89.662809
iter  20 value 81.298014
final  value 81.298004 
converged
Fitting Repeat 3 

# weights:  507
initial  value 110.832724 
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.448229 
iter  10 value 94.484653
iter  20 value 94.484212
iter  20 value 94.484211
iter  20 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.298194 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.629265 
iter  10 value 94.659332
iter  20 value 94.205234
iter  30 value 94.195287
iter  40 value 90.966632
iter  50 value 89.331202
iter  60 value 87.101237
iter  70 value 86.494917
iter  80 value 86.334891
iter  90 value 82.573196
iter 100 value 82.549834
final  value 82.549834 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.715062 
iter  10 value 94.488479
iter  20 value 92.524027
iter  30 value 84.856251
iter  40 value 82.792186
iter  50 value 82.693506
iter  60 value 82.643488
iter  70 value 82.572834
iter  80 value 82.544102
final  value 82.544030 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.214525 
iter  10 value 94.482471
iter  20 value 92.861385
iter  30 value 92.405282
iter  40 value 85.275969
iter  50 value 85.018918
iter  60 value 84.931439
iter  70 value 83.048369
iter  80 value 82.751089
iter  90 value 82.675518
iter 100 value 82.670987
final  value 82.670987 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.526050 
iter  10 value 94.479570
iter  20 value 92.641498
iter  30 value 92.491127
iter  40 value 85.408974
iter  50 value 82.978581
iter  60 value 82.772335
iter  70 value 82.710167
iter  80 value 82.680660
iter  90 value 82.563931
iter 100 value 82.544205
final  value 82.544205 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 102.159657 
iter  10 value 94.459712
iter  20 value 86.519760
iter  30 value 85.113820
iter  40 value 84.866284
iter  50 value 82.780600
iter  60 value 82.260740
iter  70 value 82.213959
iter  80 value 82.114863
iter  90 value 82.089260
final  value 82.088782 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.036947 
iter  10 value 94.302369
iter  20 value 87.221570
iter  30 value 86.650638
iter  40 value 86.535593
iter  50 value 83.692998
iter  60 value 82.208787
iter  70 value 81.573572
iter  80 value 80.796483
iter  90 value 80.524915
iter 100 value 80.184607
final  value 80.184607 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.338236 
iter  10 value 95.124644
iter  20 value 85.431927
iter  30 value 84.708467
iter  40 value 83.038029
iter  50 value 81.252871
iter  60 value 80.669062
iter  70 value 80.289916
iter  80 value 80.245469
iter  90 value 80.235239
iter 100 value 80.208408
final  value 80.208408 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 109.033380 
iter  10 value 94.456576
iter  20 value 89.197057
iter  30 value 86.207050
iter  40 value 85.330609
iter  50 value 85.074978
iter  60 value 84.902537
iter  70 value 84.701632
iter  80 value 82.722601
iter  90 value 82.434141
iter 100 value 82.348106
final  value 82.348106 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 116.604069 
iter  10 value 92.030870
iter  20 value 86.346274
iter  30 value 81.862595
iter  40 value 81.313688
iter  50 value 80.722904
iter  60 value 80.470845
iter  70 value 79.998055
iter  80 value 79.952658
iter  90 value 79.781222
iter 100 value 79.677194
final  value 79.677194 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.464940 
iter  10 value 86.675312
iter  20 value 84.754239
iter  30 value 82.750106
iter  40 value 82.236315
iter  50 value 81.372489
iter  60 value 80.944854
iter  70 value 80.637981
iter  80 value 80.589261
iter  90 value 80.549307
iter 100 value 80.480602
final  value 80.480602 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.771764 
iter  10 value 94.378627
iter  20 value 92.634711
iter  30 value 92.424061
iter  40 value 86.017271
iter  50 value 85.411888
iter  60 value 85.181087
iter  70 value 82.979533
iter  80 value 80.943684
iter  90 value 80.381978
iter 100 value 79.623433
final  value 79.623433 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.137541 
iter  10 value 95.520778
iter  20 value 94.914626
iter  30 value 92.503963
iter  40 value 85.131282
iter  50 value 83.148640
iter  60 value 80.896742
iter  70 value 80.251707
iter  80 value 80.150694
iter  90 value 79.649491
iter 100 value 79.452037
final  value 79.452037 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 102.309553 
iter  10 value 95.829069
iter  20 value 87.949828
iter  30 value 85.128295
iter  40 value 83.963967
iter  50 value 81.469361
iter  60 value 81.211243
iter  70 value 80.904446
iter  80 value 80.684625
iter  90 value 80.161807
iter 100 value 79.629314
final  value 79.629314 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 132.215750 
iter  10 value 94.684679
iter  20 value 94.083682
iter  30 value 87.096707
iter  40 value 84.107772
iter  50 value 83.227366
iter  60 value 82.581200
iter  70 value 82.427393
iter  80 value 82.315278
iter  90 value 82.257420
iter 100 value 82.198717
final  value 82.198717 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.463797 
iter  10 value 94.760708
iter  20 value 90.933738
iter  30 value 83.358653
iter  40 value 82.238236
iter  50 value 81.729207
iter  60 value 81.664860
iter  70 value 81.150664
iter  80 value 81.019990
iter  90 value 80.796052
iter 100 value 80.692072
final  value 80.692072 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.255266 
final  value 94.486042 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.113125 
final  value 94.355945 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.395904 
final  value 94.485875 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.054362 
final  value 94.486088 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.321657 
iter  10 value 94.485853
iter  20 value 93.747148
iter  30 value 92.226276
iter  30 value 92.226276
iter  30 value 92.226276
final  value 92.226276 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.707828 
iter  10 value 94.489539
iter  20 value 94.471953
iter  30 value 91.653932
iter  40 value 91.653160
iter  40 value 91.653159
final  value 91.653155 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.049187 
iter  10 value 94.486424
iter  20 value 94.477912
iter  30 value 90.391288
iter  40 value 90.151981
iter  50 value 83.194493
iter  60 value 83.190926
iter  70 value 83.188953
final  value 83.188926 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.512893 
iter  10 value 94.359150
iter  20 value 93.847585
iter  30 value 92.170070
final  value 92.156658 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.633152 
iter  10 value 94.488879
iter  20 value 94.484309
iter  30 value 85.392861
iter  40 value 84.146755
iter  50 value 84.014544
iter  60 value 82.288472
iter  70 value 81.190399
iter  80 value 81.005572
iter  90 value 80.310266
iter 100 value 80.270851
final  value 80.270851 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.004443 
iter  10 value 94.489282
iter  20 value 94.371476
iter  30 value 88.963993
iter  40 value 88.825797
iter  50 value 86.808339
iter  60 value 83.788130
iter  70 value 83.106736
iter  80 value 83.103455
iter  90 value 83.078407
iter 100 value 80.956244
final  value 80.956244 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 115.503352 
iter  10 value 94.492343
iter  20 value 94.483698
iter  30 value 94.363158
final  value 94.354617 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.189926 
iter  10 value 94.488172
iter  20 value 88.994416
iter  30 value 87.704891
iter  40 value 87.701462
iter  50 value 87.652474
iter  60 value 87.612371
iter  70 value 86.165717
iter  80 value 86.155402
iter  90 value 86.031727
iter 100 value 85.440560
final  value 85.440560 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 132.120141 
iter  10 value 94.492741
iter  20 value 94.461627
iter  30 value 86.353934
iter  40 value 85.711137
iter  50 value 83.164013
iter  60 value 83.100972
iter  70 value 83.099096
iter  80 value 83.061817
iter  90 value 82.621535
iter 100 value 82.010419
final  value 82.010419 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.894626 
iter  10 value 94.492247
iter  20 value 94.455744
iter  30 value 82.541687
iter  40 value 81.787177
iter  50 value 81.463877
iter  60 value 81.110127
iter  70 value 81.105120
final  value 81.100240 
converged
Fitting Repeat 5 

# weights:  507
initial  value 130.699882 
iter  10 value 94.493600
iter  20 value 94.485652
iter  30 value 85.627649
iter  40 value 84.188060
final  value 84.187932 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.394859 
iter  10 value 94.010903
iter  20 value 93.869755
iter  20 value 93.869755
iter  20 value 93.869755
final  value 93.869755 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.322978 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.353526 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.577208 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.306655 
iter  10 value 93.977641
iter  20 value 88.528563
iter  30 value 88.513778
final  value 88.513753 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.946134 
final  value 93.244970 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.690655 
final  value 93.869755 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.433329 
final  value 93.915746 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.412124 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.806341 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.245355 
iter  10 value 93.349101
iter  20 value 92.438981
iter  30 value 92.397830
final  value 92.397465 
converged
Fitting Repeat 2 

# weights:  507
initial  value 120.755257 
final  value 93.714286 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.122465 
final  value 93.915746 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.512244 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.434728 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.245023 
iter  10 value 94.300010
iter  20 value 94.036073
iter  30 value 93.982196
iter  40 value 93.946406
iter  50 value 92.825293
iter  60 value 87.362767
iter  70 value 86.801880
iter  80 value 86.498508
iter  90 value 85.628914
iter 100 value 84.914727
final  value 84.914727 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 108.894932 
iter  10 value 94.060949
iter  20 value 93.670500
iter  30 value 93.454354
iter  40 value 93.445292
iter  50 value 91.841871
iter  60 value 85.199830
iter  70 value 84.682937
iter  80 value 83.731917
iter  90 value 81.941183
iter 100 value 81.788872
final  value 81.788872 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.057227 
iter  10 value 93.490254
iter  20 value 93.266661
iter  30 value 91.019530
iter  40 value 89.618555
iter  50 value 86.340399
iter  60 value 85.022964
iter  70 value 82.832801
iter  80 value 82.288210
iter  90 value 81.960473
iter 100 value 81.828424
final  value 81.828424 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 102.075923 
iter  10 value 94.064593
iter  20 value 94.053227
iter  30 value 93.493521
iter  40 value 93.466963
iter  50 value 93.446901
iter  60 value 93.446377
iter  60 value 93.446376
iter  70 value 89.972869
iter  80 value 88.400600
iter  90 value 86.485450
iter 100 value 83.763267
final  value 83.763267 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 108.308338 
iter  10 value 94.054884
iter  20 value 93.591369
iter  30 value 93.456293
iter  40 value 93.284102
iter  50 value 87.343704
iter  60 value 86.761681
iter  70 value 85.405918
iter  80 value 84.622118
iter  90 value 84.508002
iter 100 value 83.601897
final  value 83.601897 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 121.602031 
iter  10 value 94.059829
iter  20 value 93.481979
iter  30 value 85.983994
iter  40 value 85.494657
iter  50 value 84.736196
iter  60 value 84.484188
iter  70 value 83.329335
iter  80 value 82.539601
iter  90 value 81.535168
iter 100 value 81.500129
final  value 81.500129 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 113.482046 
iter  10 value 93.797604
iter  20 value 92.913816
iter  30 value 89.965138
iter  40 value 89.151525
iter  50 value 88.216399
iter  60 value 87.517196
iter  70 value 83.121627
iter  80 value 81.840277
iter  90 value 81.552638
iter 100 value 81.112517
final  value 81.112517 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.097755 
iter  10 value 93.928826
iter  20 value 87.308419
iter  30 value 84.684252
iter  40 value 83.111673
iter  50 value 82.311716
iter  60 value 81.965699
iter  70 value 81.271923
iter  80 value 81.121547
iter  90 value 80.886977
iter 100 value 80.802048
final  value 80.802048 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.907623 
iter  10 value 94.029258
iter  20 value 93.744739
iter  30 value 93.635748
iter  40 value 93.548598
iter  50 value 93.505866
iter  60 value 92.659372
iter  70 value 88.184269
iter  80 value 83.858528
iter  90 value 82.940508
iter 100 value 82.697445
final  value 82.697445 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.852562 
iter  10 value 94.452117
iter  20 value 94.060905
iter  30 value 93.579472
iter  40 value 93.422649
iter  50 value 87.498803
iter  60 value 86.299561
iter  70 value 86.092556
iter  80 value 85.927899
iter  90 value 85.488826
iter 100 value 83.729552
final  value 83.729552 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 128.587100 
iter  10 value 96.695074
iter  20 value 91.874622
iter  30 value 90.165699
iter  40 value 84.966408
iter  50 value 82.421091
iter  60 value 81.787725
iter  70 value 81.540319
iter  80 value 81.177623
iter  90 value 80.777954
iter 100 value 80.607430
final  value 80.607430 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.242426 
iter  10 value 94.055639
iter  20 value 86.230886
iter  30 value 85.611697
iter  40 value 84.441284
iter  50 value 81.350970
iter  60 value 80.805351
iter  70 value 80.675323
iter  80 value 80.573141
iter  90 value 80.486753
iter 100 value 80.353760
final  value 80.353760 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.068797 
iter  10 value 93.788041
iter  20 value 89.625021
iter  30 value 87.122988
iter  40 value 82.623364
iter  50 value 81.266807
iter  60 value 80.840631
iter  70 value 80.442181
iter  80 value 80.191943
iter  90 value 80.091027
iter 100 value 80.024162
final  value 80.024162 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 122.665674 
iter  10 value 93.766491
iter  20 value 93.022705
iter  30 value 85.232192
iter  40 value 83.463669
iter  50 value 83.071770
iter  60 value 82.592395
iter  70 value 82.168795
iter  80 value 81.728101
iter  90 value 81.262996
iter 100 value 80.614691
final  value 80.614691 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.813752 
iter  10 value 93.988689
iter  20 value 90.537898
iter  30 value 88.414523
iter  40 value 88.213726
iter  50 value 86.737096
iter  60 value 84.854574
iter  70 value 84.350637
iter  80 value 83.992046
iter  90 value 82.785925
iter 100 value 82.416764
final  value 82.416764 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 107.967654 
final  value 93.606027 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.991504 
iter  10 value 93.951110
iter  20 value 93.715792
iter  30 value 93.714784
iter  40 value 93.713842
iter  50 value 93.422994
iter  60 value 93.377718
final  value 93.377618 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.746974 
final  value 94.054700 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.260259 
final  value 94.054480 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.256115 
iter  10 value 94.054449
iter  20 value 93.921431
iter  30 value 93.671981
iter  40 value 84.738586
final  value 84.737204 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.251255 
iter  10 value 93.415749
iter  20 value 93.380833
final  value 93.378660 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.696199 
iter  10 value 93.920661
iter  20 value 93.705108
iter  30 value 90.224302
iter  40 value 90.000481
iter  50 value 89.999502
iter  60 value 89.989281
iter  70 value 89.988906
iter  80 value 84.414870
iter  90 value 84.388546
final  value 84.388254 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.279710 
iter  10 value 94.057267
iter  20 value 93.967887
iter  30 value 85.721224
final  value 85.720020 
converged
Fitting Repeat 4 

# weights:  305
initial  value 111.789841 
iter  10 value 94.057658
iter  20 value 93.949797
iter  30 value 91.594916
iter  40 value 89.744629
iter  50 value 86.164046
iter  60 value 83.528477
iter  70 value 83.434266
iter  80 value 83.431294
iter  90 value 83.267493
iter 100 value 83.262478
final  value 83.262478 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 97.303790 
iter  10 value 93.920966
iter  20 value 93.917468
final  value 93.917395 
converged
Fitting Repeat 1 

# weights:  507
initial  value 117.059561 
iter  10 value 93.923975
iter  20 value 93.916527
final  value 93.916509 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.031948 
iter  10 value 94.060467
iter  20 value 94.041801
iter  30 value 86.554183
iter  40 value 84.016597
iter  50 value 83.692359
final  value 83.692083 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.585742 
iter  10 value 93.417910
iter  20 value 93.414027
iter  30 value 93.403377
iter  40 value 93.378076
iter  50 value 88.017764
iter  60 value 83.046735
iter  70 value 82.138231
iter  80 value 81.927782
iter  90 value 80.906727
iter 100 value 80.838067
final  value 80.838067 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.423163 
iter  10 value 94.060943
iter  20 value 92.134765
iter  30 value 85.991420
iter  40 value 84.907086
iter  50 value 84.674758
iter  60 value 84.488401
iter  70 value 84.316725
final  value 84.313667 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.956351 
iter  10 value 94.000267
iter  20 value 93.721911
iter  30 value 93.653139
iter  40 value 93.412776
iter  50 value 93.410683
iter  60 value 93.376411
iter  70 value 85.694807
iter  80 value 85.416654
iter  90 value 85.415214
iter 100 value 83.818173
final  value 83.818173 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.088112 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.732302 
final  value 93.988095 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.949985 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.011555 
iter  10 value 94.052117
iter  20 value 94.049101
iter  30 value 94.041464
iter  40 value 94.039658
iter  50 value 94.039337
iter  60 value 94.039264
final  value 94.039236 
converged
Fitting Repeat 5 

# weights:  103
initial  value 114.641573 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.124837 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.706109 
iter  10 value 93.817712
final  value 93.813458 
converged
Fitting Repeat 3 

# weights:  305
initial  value 109.928152 
iter  10 value 89.503358
iter  20 value 87.563267
final  value 87.548526 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.217002 
final  value 94.032967 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.101155 
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.839699 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.332012 
iter  10 value 93.839508
final  value 93.839506 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.269051 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 111.684432 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.259188 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.209988 
iter  10 value 94.066303
iter  20 value 94.023698
iter  30 value 87.477822
iter  40 value 84.740062
iter  50 value 83.969528
iter  60 value 83.198244
iter  70 value 81.973657
iter  80 value 81.569421
iter  90 value 81.520766
final  value 81.520540 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.915969 
iter  10 value 94.067458
iter  20 value 92.452093
iter  30 value 91.049382
iter  40 value 84.198937
iter  50 value 81.761151
iter  60 value 81.303632
iter  70 value 81.228874
iter  80 value 81.175388
final  value 81.175304 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.614284 
iter  10 value 94.055080
iter  20 value 88.981470
iter  30 value 84.403409
iter  40 value 84.166982
iter  50 value 83.864189
iter  60 value 82.428410
iter  70 value 81.799109
iter  80 value 81.716219
iter  90 value 81.665775
iter 100 value 81.551188
final  value 81.551188 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 104.529822 
iter  10 value 94.024150
iter  20 value 88.010257
iter  30 value 87.798778
iter  40 value 86.956153
iter  50 value 86.797792
iter  60 value 83.983825
iter  70 value 83.147836
iter  80 value 81.909692
iter  90 value 81.537840
iter 100 value 81.520556
final  value 81.520556 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 115.401372 
iter  10 value 93.919918
iter  20 value 87.051466
iter  30 value 84.166532
iter  40 value 83.993514
iter  50 value 83.854139
final  value 83.854033 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.540116 
iter  10 value 94.074349
iter  20 value 93.622283
iter  30 value 88.884620
iter  40 value 83.754328
iter  50 value 82.872339
iter  60 value 82.263036
iter  70 value 82.089495
iter  80 value 81.504176
iter  90 value 81.334366
iter 100 value 81.266990
final  value 81.266990 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.705613 
iter  10 value 93.956077
iter  20 value 87.157801
iter  30 value 86.105660
iter  40 value 84.057607
iter  50 value 83.694204
iter  60 value 83.541945
iter  70 value 83.262195
iter  80 value 82.370040
iter  90 value 81.315537
iter 100 value 80.520040
final  value 80.520040 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.882483 
iter  10 value 93.809155
iter  20 value 86.935110
iter  30 value 86.288779
iter  40 value 85.963622
iter  50 value 85.349776
iter  60 value 84.558259
iter  70 value 82.549864
iter  80 value 81.704043
iter  90 value 81.649367
iter 100 value 81.491289
final  value 81.491289 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.348240 
iter  10 value 93.201823
iter  20 value 86.598045
iter  30 value 82.903231
iter  40 value 82.165082
iter  50 value 80.994965
iter  60 value 80.487347
iter  70 value 80.431497
iter  80 value 80.340283
iter  90 value 80.300332
iter 100 value 80.256671
final  value 80.256671 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 132.305564 
iter  10 value 93.988150
iter  20 value 88.970171
iter  30 value 88.752734
iter  40 value 87.718738
iter  50 value 84.255710
iter  60 value 82.152754
iter  70 value 81.810080
iter  80 value 81.510961
iter  90 value 81.097350
iter 100 value 80.798065
final  value 80.798065 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.899165 
iter  10 value 97.543385
iter  20 value 88.794763
iter  30 value 86.375507
iter  40 value 84.497821
iter  50 value 82.440155
iter  60 value 81.287511
iter  70 value 80.857112
iter  80 value 80.711731
iter  90 value 80.609704
iter 100 value 80.560923
final  value 80.560923 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.025387 
iter  10 value 97.166143
iter  20 value 91.116528
iter  30 value 87.100913
iter  40 value 85.689716
iter  50 value 84.039077
iter  60 value 82.651205
iter  70 value 82.413327
iter  80 value 81.997595
iter  90 value 81.227024
iter 100 value 80.783731
final  value 80.783731 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.563139 
iter  10 value 94.018303
iter  20 value 85.710749
iter  30 value 84.682242
iter  40 value 84.184018
iter  50 value 81.738332
iter  60 value 80.922666
iter  70 value 80.687177
iter  80 value 80.338081
iter  90 value 80.157440
iter 100 value 80.102062
final  value 80.102062 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.843643 
iter  10 value 94.074643
iter  20 value 89.358573
iter  30 value 86.663630
iter  40 value 84.025655
iter  50 value 82.206638
iter  60 value 81.384588
iter  70 value 81.047211
iter  80 value 80.846756
iter  90 value 80.759401
iter 100 value 80.484498
final  value 80.484498 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.669506 
iter  10 value 94.060704
iter  20 value 89.781050
iter  30 value 88.280500
iter  40 value 85.987893
iter  50 value 81.337774
iter  60 value 80.690107
iter  70 value 80.658992
iter  80 value 80.575908
iter  90 value 80.421651
iter 100 value 80.184436
final  value 80.184436 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.023399 
iter  10 value 93.816051
iter  20 value 93.815026
iter  30 value 93.813969
final  value 93.813909 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.697929 
final  value 94.054497 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.575269 
final  value 94.054650 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.152606 
final  value 94.054749 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.688840 
final  value 94.054369 
converged
Fitting Repeat 1 

# weights:  305
initial  value 115.817169 
iter  10 value 94.098324
iter  20 value 94.089895
iter  30 value 91.483639
iter  40 value 86.477000
iter  50 value 86.466032
iter  60 value 86.413545
iter  70 value 85.932766
iter  80 value 85.929317
iter  90 value 85.628287
iter 100 value 85.533400
final  value 85.533400 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 116.215135 
iter  10 value 93.816410
iter  20 value 93.785317
iter  30 value 93.755927
iter  40 value 93.755551
iter  50 value 92.372540
iter  60 value 91.461849
iter  70 value 91.007070
iter  80 value 90.948838
final  value 90.945848 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.350929 
iter  10 value 94.030396
iter  20 value 94.029733
iter  30 value 90.204508
iter  40 value 85.789240
iter  50 value 85.610211
iter  60 value 85.608731
iter  70 value 85.501796
iter  80 value 85.491381
iter  90 value 85.491311
final  value 85.491305 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.509864 
iter  10 value 94.057971
iter  20 value 94.001141
iter  30 value 89.433587
iter  40 value 85.445789
iter  50 value 85.443056
iter  60 value 85.441084
iter  70 value 85.439909
iter  80 value 85.439444
iter  90 value 85.439128
iter 100 value 85.438921
final  value 85.438921 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.417063 
iter  10 value 94.056947
iter  20 value 89.708079
iter  30 value 85.639558
iter  40 value 85.639440
iter  50 value 85.392472
iter  60 value 83.516193
iter  70 value 83.499883
iter  80 value 83.486058
iter  90 value 83.435145
iter 100 value 83.433741
final  value 83.433741 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.697384 
iter  10 value 94.055253
iter  20 value 94.051780
iter  30 value 92.226789
iter  40 value 89.938368
iter  50 value 89.862568
iter  60 value 89.856821
iter  70 value 89.856171
iter  80 value 89.344909
iter  90 value 89.259709
iter 100 value 87.381243
final  value 87.381243 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 136.603299 
iter  10 value 94.056734
iter  20 value 93.959685
iter  30 value 93.895090
iter  40 value 91.681635
iter  50 value 85.002084
iter  60 value 83.483830
iter  70 value 82.013684
iter  80 value 81.569737
iter  90 value 81.562642
final  value 81.562132 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.049132 
iter  10 value 86.701179
iter  20 value 86.491643
iter  30 value 86.490918
iter  40 value 86.487954
iter  50 value 84.965819
iter  60 value 83.189355
iter  70 value 82.923088
iter  80 value 82.918787
iter  90 value 82.916196
iter 100 value 81.992709
final  value 81.992709 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.152830 
iter  10 value 94.041013
iter  20 value 94.033389
final  value 94.033332 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.406098 
iter  10 value 94.041386
iter  20 value 91.473992
iter  30 value 87.706323
iter  40 value 83.123686
iter  50 value 83.039088
iter  60 value 83.038266
iter  70 value 82.522244
iter  80 value 82.127069
iter  90 value 82.096282
iter 100 value 82.077158
final  value 82.077158 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 145.051814 
iter  10 value 117.763995
iter  20 value 117.714740
iter  30 value 117.503948
iter  40 value 112.396768
iter  50 value 107.733588
iter  60 value 104.288780
iter  70 value 102.230785
iter  80 value 102.215411
iter  90 value 102.160342
iter 100 value 101.802812
final  value 101.802812 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 128.809324 
iter  10 value 117.894401
iter  20 value 117.813019
iter  30 value 111.698465
iter  40 value 111.659943
iter  50 value 111.658015
iter  60 value 110.867033
iter  70 value 110.422614
iter  80 value 110.422284
iter  90 value 107.823226
iter 100 value 107.049541
final  value 107.049541 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 120.204188 
iter  10 value 117.894871
iter  20 value 117.890432
iter  30 value 109.809358
iter  40 value 106.904788
final  value 106.903908 
converged
Fitting Repeat 4 

# weights:  305
initial  value 140.722479 
iter  10 value 112.723861
iter  20 value 112.653390
iter  30 value 111.034588
iter  40 value 109.197342
iter  50 value 108.244954
iter  60 value 108.174561
iter  70 value 108.174221
iter  70 value 108.174220
iter  70 value 108.174220
final  value 108.174220 
converged
Fitting Repeat 5 

# weights:  305
initial  value 121.146968 
iter  10 value 117.715012
iter  20 value 116.969294
iter  30 value 116.912749
iter  40 value 116.911549
iter  50 value 116.831462
iter  60 value 116.823955
iter  70 value 116.821193
iter  80 value 116.820305
iter  80 value 116.820304
iter  80 value 116.820304
final  value 116.820304 
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 -- Fri Oct 18 00:51:03 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 
 48.726   1.399  50.922