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


* using log directory ‘/Users/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck’
* using R version 4.4.1 (2024-06-14)
* using platform: x86_64-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 Monterey 12.7.1
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.11.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking 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       36.851  1.842  39.005
FSmethod      35.159  1.640  37.083
corr_plot     34.385  1.689  36.300
pred_ensembel 14.509  0.580  11.110
enrichfindP    0.497  0.059   7.667
* 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-3.20-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-x86_64/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: x86_64-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 99.722268 
iter  10 value 94.509190
iter  20 value 94.482609
final  value 94.482481 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.297491 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 108.111598 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.661162 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.161215 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.338237 
final  value 94.467391 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.079415 
iter  10 value 94.467230
iter  20 value 94.467038
final  value 94.467034 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.440668 
iter  10 value 94.470325
final  value 94.467391 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.906126 
iter  10 value 94.484211
iter  10 value 94.484211
iter  10 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.270085 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.886910 
iter  10 value 94.452257
final  value 94.301587 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.697838 
final  value 94.467391 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.427243 
iter  10 value 94.453333
iter  10 value 94.453333
iter  10 value 94.453333
final  value 94.453333 
converged
Fitting Repeat 4 

# weights:  507
initial  value 135.731249 
iter  10 value 93.675217
final  value 93.674286 
converged
Fitting Repeat 5 

# weights:  507
initial  value 111.684449 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.587519 
iter  10 value 94.315256
iter  20 value 89.146468
iter  30 value 85.486929
iter  40 value 84.098420
iter  50 value 82.397650
iter  60 value 82.231732
iter  70 value 82.186394
iter  70 value 82.186393
iter  70 value 82.186393
final  value 82.186393 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.004924 
iter  10 value 93.805335
iter  20 value 89.783091
iter  30 value 84.445121
iter  40 value 83.742685
iter  50 value 83.466877
iter  60 value 82.460897
iter  70 value 82.192629
iter  80 value 82.084539
final  value 82.084023 
converged
Fitting Repeat 3 

# weights:  103
initial  value 110.326282 
iter  10 value 94.475673
iter  20 value 94.279570
iter  30 value 88.049070
iter  40 value 87.116291
iter  50 value 86.393924
iter  60 value 83.596130
iter  70 value 83.509508
iter  80 value 83.322599
iter  90 value 82.600619
iter 100 value 82.508102
final  value 82.508102 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.810901 
iter  10 value 94.508734
iter  20 value 92.220236
iter  30 value 91.257658
iter  40 value 88.125765
iter  50 value 83.343982
iter  60 value 82.527294
iter  70 value 82.464946
iter  80 value 82.207479
final  value 82.186393 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.094784 
iter  10 value 94.255787
iter  20 value 85.976014
iter  30 value 84.906744
iter  40 value 83.575028
iter  50 value 83.289433
iter  60 value 82.461767
iter  70 value 82.356341
final  value 82.356338 
converged
Fitting Repeat 1 

# weights:  305
initial  value 116.123914 
iter  10 value 94.388063
iter  20 value 85.288430
iter  30 value 81.944876
iter  40 value 79.830061
iter  50 value 79.544420
iter  60 value 79.522914
iter  70 value 79.437342
iter  80 value 79.401239
iter  90 value 79.357900
iter 100 value 79.104389
final  value 79.104389 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.910821 
iter  10 value 93.852310
iter  20 value 84.553842
iter  30 value 83.548655
iter  40 value 82.298241
iter  50 value 82.094494
iter  60 value 81.708919
iter  70 value 81.209481
iter  80 value 81.041759
iter  90 value 81.034045
iter 100 value 81.002872
final  value 81.002872 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 113.018593 
iter  10 value 94.458569
iter  20 value 86.934567
iter  30 value 83.582891
iter  40 value 82.749069
iter  50 value 82.717790
iter  60 value 82.524024
iter  70 value 82.344113
iter  80 value 82.246430
iter  90 value 82.081786
iter 100 value 81.495107
final  value 81.495107 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.284105 
iter  10 value 94.490923
iter  20 value 94.318814
iter  30 value 87.536504
iter  40 value 83.116494
iter  50 value 81.770722
iter  60 value 80.335800
iter  70 value 79.973829
iter  80 value 79.783690
iter  90 value 79.561098
iter 100 value 79.329257
final  value 79.329257 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.813955 
iter  10 value 94.312885
iter  20 value 87.613299
iter  30 value 85.316227
iter  40 value 84.256179
iter  50 value 83.368988
iter  60 value 82.622453
iter  70 value 81.849174
iter  80 value 81.378828
iter  90 value 81.296158
iter 100 value 81.166186
final  value 81.166186 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 129.006399 
iter  10 value 95.178826
iter  20 value 93.597163
iter  30 value 92.400224
iter  40 value 91.889818
iter  50 value 85.332555
iter  60 value 84.189438
iter  70 value 83.719601
iter  80 value 81.892403
iter  90 value 80.550226
iter 100 value 80.086792
final  value 80.086792 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 110.079739 
iter  10 value 94.618313
iter  20 value 83.827383
iter  30 value 82.797158
iter  40 value 82.720866
iter  50 value 81.786894
iter  60 value 80.590703
iter  70 value 79.678301
iter  80 value 79.579320
iter  90 value 79.498599
iter 100 value 79.309617
final  value 79.309617 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 122.234103 
iter  10 value 94.480277
iter  20 value 83.647299
iter  30 value 82.649752
iter  40 value 82.477362
iter  50 value 82.286596
iter  60 value 82.205879
iter  70 value 82.082118
iter  80 value 81.145358
iter  90 value 80.380931
iter 100 value 79.905812
final  value 79.905812 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.865353 
iter  10 value 96.106598
iter  20 value 92.463361
iter  30 value 85.832538
iter  40 value 82.376624
iter  50 value 82.199359
iter  60 value 82.022848
iter  70 value 81.879635
iter  80 value 81.410097
iter  90 value 80.015851
iter 100 value 79.795577
final  value 79.795577 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.947827 
iter  10 value 93.705744
iter  20 value 85.775371
iter  30 value 85.058058
iter  40 value 80.925563
iter  50 value 80.327545
iter  60 value 79.574721
iter  70 value 79.333038
iter  80 value 79.254412
iter  90 value 79.248498
iter 100 value 79.240665
final  value 79.240665 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.777396 
iter  10 value 94.469188
iter  20 value 94.467946
iter  30 value 91.442607
iter  40 value 91.233295
iter  50 value 90.868164
final  value 90.868053 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.251726 
final  value 94.485821 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.857441 
iter  10 value 94.469053
iter  20 value 94.468412
iter  30 value 94.467437
final  value 94.467424 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.111048 
final  value 94.450101 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.625057 
final  value 94.485722 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.912204 
iter  10 value 94.487777
iter  20 value 93.565772
iter  30 value 82.825728
iter  40 value 82.818597
iter  50 value 82.456764
iter  60 value 81.604875
iter  70 value 78.849810
iter  80 value 78.282929
iter  90 value 77.948884
iter 100 value 77.770857
final  value 77.770857 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 98.323159 
iter  10 value 94.488995
iter  20 value 94.430296
iter  30 value 85.528930
iter  40 value 81.942698
iter  50 value 81.843816
iter  60 value 81.843470
final  value 81.839878 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.726078 
iter  10 value 94.472370
iter  20 value 94.467470
iter  30 value 88.306920
iter  40 value 83.481280
iter  50 value 83.282972
iter  60 value 82.481421
iter  70 value 82.129229
iter  80 value 82.124545
iter  90 value 82.112490
iter 100 value 81.601606
final  value 81.601606 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 125.389771 
iter  10 value 94.473179
iter  20 value 94.467459
iter  30 value 83.883348
iter  40 value 82.813499
iter  50 value 82.811893
iter  60 value 82.811781
iter  60 value 82.811781
iter  60 value 82.811781
final  value 82.811781 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.234741 
iter  10 value 94.489289
iter  20 value 94.469486
iter  30 value 94.467503
iter  40 value 93.726363
iter  50 value 89.982260
iter  60 value 84.540580
iter  70 value 84.362524
iter  80 value 84.324268
iter  90 value 84.324080
iter 100 value 83.719262
final  value 83.719262 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 96.561267 
iter  10 value 94.475447
iter  20 value 94.473609
iter  30 value 94.470703
iter  40 value 93.708356
iter  50 value 93.677423
iter  60 value 89.009947
iter  70 value 86.831076
iter  80 value 85.799434
iter  90 value 85.791045
iter 100 value 84.083858
final  value 84.083858 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.055123 
iter  10 value 94.421469
iter  20 value 94.416675
iter  30 value 82.324464
iter  40 value 81.953350
iter  50 value 81.397679
iter  60 value 81.035545
final  value 81.035543 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.578284 
iter  10 value 94.444185
iter  20 value 94.436204
iter  30 value 89.651949
iter  40 value 85.087038
iter  50 value 83.813067
iter  60 value 83.742999
iter  70 value 83.248076
iter  80 value 82.968488
iter  90 value 82.809806
iter 100 value 82.804275
final  value 82.804275 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.206393 
iter  10 value 94.492494
iter  20 value 94.480615
final  value 94.467496 
converged
Fitting Repeat 5 

# weights:  507
initial  value 132.863651 
iter  10 value 91.473895
iter  20 value 91.444071
iter  30 value 91.375536
iter  40 value 91.369782
iter  50 value 91.298370
iter  60 value 90.870473
final  value 90.799645 
converged
Fitting Repeat 1 

# weights:  103
initial  value 94.315395 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.959942 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.946043 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.401292 
iter  10 value 92.962142
final  value 92.945355 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.098755 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.906633 
iter  10 value 92.945355
iter  20 value 86.357437
iter  30 value 77.961537
iter  40 value 73.504390
iter  50 value 73.477792
final  value 73.477709 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.016713 
iter  10 value 92.862806
final  value 92.690941 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.758577 
iter  10 value 92.530187
final  value 92.529794 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.457120 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 109.587477 
iter  10 value 92.563130
final  value 92.563128 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.911926 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.235462 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 134.400257 
iter  10 value 85.057275
iter  20 value 82.531979
iter  30 value 82.421720
iter  40 value 82.420778
final  value 82.420447 
converged
Fitting Repeat 4 

# weights:  507
initial  value 115.379517 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 122.879833 
final  value 94.052874 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.663025 
iter  10 value 93.487258
iter  20 value 88.292917
iter  30 value 80.401004
iter  40 value 79.784900
iter  50 value 79.246616
iter  60 value 78.623590
iter  70 value 78.605574
final  value 78.605571 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.208291 
iter  10 value 94.003616
iter  20 value 93.479928
iter  30 value 93.413467
iter  40 value 84.512791
iter  50 value 83.407830
iter  60 value 82.481638
iter  70 value 81.405621
iter  80 value 81.356414
iter  90 value 81.281595
iter 100 value 81.275448
final  value 81.275448 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 113.916603 
iter  10 value 97.895655
iter  20 value 94.054592
iter  30 value 93.083187
iter  40 value 92.749102
iter  50 value 87.727975
iter  60 value 85.990012
iter  70 value 81.933197
iter  80 value 80.799586
iter  90 value 78.931928
iter 100 value 78.658188
final  value 78.658188 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 106.303630 
iter  10 value 94.081255
iter  20 value 94.054525
iter  30 value 93.209633
iter  40 value 93.089074
iter  50 value 92.781096
iter  60 value 92.619468
iter  70 value 87.346120
iter  80 value 85.566926
iter  90 value 84.523541
iter 100 value 84.106852
final  value 84.106852 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 102.237266 
iter  10 value 94.296055
iter  20 value 94.062512
iter  30 value 94.041204
iter  40 value 93.073726
iter  50 value 92.715792
iter  60 value 90.813158
iter  70 value 88.024059
iter  80 value 87.228904
iter  90 value 84.817630
iter 100 value 76.256431
final  value 76.256431 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 111.939541 
iter  10 value 94.124243
iter  20 value 93.444580
iter  30 value 90.164321
iter  40 value 86.549884
iter  50 value 85.277818
iter  60 value 80.942398
iter  70 value 80.162786
iter  80 value 78.495685
iter  90 value 78.304994
iter 100 value 76.707998
final  value 76.707998 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.704196 
iter  10 value 93.882825
iter  20 value 86.556517
iter  30 value 84.914973
iter  40 value 82.619970
iter  50 value 82.030825
iter  60 value 81.949762
iter  70 value 81.656424
iter  80 value 81.256630
iter  90 value 80.758391
iter 100 value 77.739936
final  value 77.739936 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.766313 
iter  10 value 93.313494
iter  20 value 93.082316
iter  30 value 89.912078
iter  40 value 78.564831
iter  50 value 77.597601
iter  60 value 76.808113
iter  70 value 76.676828
iter  80 value 76.278284
iter  90 value 75.890587
iter 100 value 75.167091
final  value 75.167091 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.871919 
iter  10 value 93.296792
iter  20 value 91.272309
iter  30 value 86.967780
iter  40 value 78.915359
iter  50 value 76.541331
iter  60 value 75.538239
iter  70 value 75.479854
iter  80 value 75.292258
iter  90 value 74.997240
iter 100 value 74.839464
final  value 74.839464 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.437897 
iter  10 value 94.458538
iter  20 value 84.178524
iter  30 value 81.469600
iter  40 value 78.584614
iter  50 value 77.768209
iter  60 value 76.981862
iter  70 value 75.142859
iter  80 value 74.415836
iter  90 value 74.301705
iter 100 value 74.167188
final  value 74.167188 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.145247 
iter  10 value 93.601336
iter  20 value 81.723708
iter  30 value 76.114430
iter  40 value 75.065955
iter  50 value 74.629310
iter  60 value 74.416669
iter  70 value 74.007981
iter  80 value 73.883166
iter  90 value 73.858431
iter 100 value 73.793966
final  value 73.793966 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.034660 
iter  10 value 94.392614
iter  20 value 82.394822
iter  30 value 77.915722
iter  40 value 75.633135
iter  50 value 75.539347
iter  60 value 75.459901
iter  70 value 75.318139
iter  80 value 74.949702
iter  90 value 74.752192
iter 100 value 74.714360
final  value 74.714360 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 115.762054 
iter  10 value 93.999880
iter  20 value 93.478817
iter  30 value 92.640556
iter  40 value 86.535278
iter  50 value 80.998416
iter  60 value 78.736936
iter  70 value 77.900221
iter  80 value 76.664501
iter  90 value 76.140002
iter 100 value 75.354004
final  value 75.354004 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 125.811228 
iter  10 value 93.119693
iter  20 value 88.558763
iter  30 value 86.261943
iter  40 value 79.670417
iter  50 value 77.928679
iter  60 value 77.118458
iter  70 value 76.318922
iter  80 value 75.901708
iter  90 value 75.821007
iter 100 value 75.404038
final  value 75.404038 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.839923 
iter  10 value 93.943473
iter  20 value 86.536716
iter  30 value 80.052161
iter  40 value 78.602607
iter  50 value 77.462827
iter  60 value 76.001459
iter  70 value 75.102696
iter  80 value 74.683666
iter  90 value 74.606372
iter 100 value 74.591318
final  value 74.591318 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.712349 
final  value 94.054564 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.443697 
final  value 94.054510 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.123380 
final  value 94.054877 
converged
Fitting Repeat 4 

# weights:  103
initial  value 113.697434 
final  value 94.054288 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.188051 
final  value 94.054777 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.842044 
iter  10 value 92.950689
iter  20 value 92.946946
iter  30 value 90.663286
iter  40 value 90.461019
iter  50 value 90.460083
iter  60 value 90.430775
iter  70 value 80.038039
iter  80 value 78.470411
iter  90 value 78.343222
iter 100 value 78.297125
final  value 78.297125 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 116.643269 
iter  10 value 94.057632
iter  20 value 93.765306
iter  30 value 89.118143
iter  40 value 88.694830
iter  50 value 88.634303
iter  60 value 88.633885
iter  70 value 88.631715
iter  80 value 88.000609
iter  90 value 79.534442
iter 100 value 76.566951
final  value 76.566951 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 114.829754 
iter  10 value 94.057960
iter  20 value 94.050937
iter  30 value 92.506958
final  value 92.459029 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.828043 
iter  10 value 94.058201
iter  20 value 93.596407
iter  30 value 81.385558
iter  40 value 80.627831
iter  50 value 80.625580
iter  60 value 80.623403
iter  70 value 80.617295
iter  80 value 78.110488
iter  90 value 76.743268
iter 100 value 75.743552
final  value 75.743552 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 118.434318 
iter  10 value 94.063528
iter  20 value 93.993769
iter  30 value 90.751758
iter  40 value 86.347966
iter  50 value 86.342816
iter  60 value 86.117841
iter  70 value 86.100002
iter  80 value 84.919557
iter  90 value 84.334354
iter 100 value 77.920547
final  value 77.920547 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.484855 
iter  10 value 92.956539
iter  20 value 92.953611
iter  30 value 92.837802
iter  40 value 84.226991
iter  50 value 84.223951
iter  60 value 82.245346
iter  70 value 78.060272
iter  80 value 74.981463
iter  90 value 72.750901
iter 100 value 72.589630
final  value 72.589630 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.947815 
iter  10 value 92.991464
iter  20 value 92.954160
iter  30 value 92.950067
final  value 92.946172 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.393221 
iter  10 value 87.669995
iter  20 value 77.473583
iter  30 value 77.426048
iter  40 value 75.914700
iter  50 value 74.500656
iter  60 value 74.495345
iter  70 value 73.922409
iter  80 value 73.869261
iter  90 value 73.862401
final  value 73.856548 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.172879 
iter  10 value 93.121718
iter  20 value 92.433890
iter  30 value 92.433279
iter  40 value 91.327900
iter  50 value 85.459932
iter  60 value 81.854640
iter  70 value 78.206038
iter  80 value 77.478971
iter  90 value 77.470924
iter 100 value 77.470752
final  value 77.470752 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 127.231786 
iter  10 value 94.061259
final  value 94.053861 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.054497 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.769781 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.928195 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.051856 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.205608 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.803957 
final  value 94.032967 
converged
Fitting Repeat 2 

# weights:  305
initial  value 121.873960 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.724172 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 108.939346 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.285043 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.950450 
iter  10 value 94.032967
iter  10 value 94.032967
iter  10 value 94.032967
final  value 94.032967 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.052506 
iter  10 value 93.188026
iter  20 value 89.504113
final  value 89.480427 
converged
Fitting Repeat 3 

# weights:  507
initial  value 124.856453 
iter  10 value 94.035088
iter  10 value 94.035088
iter  10 value 94.035088
final  value 94.035088 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.614518 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.929271 
final  value 94.032967 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.595029 
iter  10 value 94.034602
iter  20 value 92.503372
iter  30 value 91.362535
iter  40 value 87.309896
iter  50 value 86.362121
iter  60 value 85.708706
iter  70 value 85.351617
iter  80 value 85.285895
iter  90 value 85.265667
final  value 85.259240 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.496693 
iter  10 value 94.031236
iter  20 value 89.517134
iter  30 value 88.744084
iter  40 value 88.484723
iter  50 value 88.049255
iter  60 value 86.027199
iter  70 value 85.413939
iter  80 value 85.275822
iter  90 value 85.262811
final  value 85.259240 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.410615 
iter  10 value 91.501987
iter  20 value 87.187904
iter  30 value 85.869584
iter  40 value 85.189390
iter  50 value 84.257670
iter  60 value 84.033838
iter  70 value 83.871183
iter  80 value 83.755307
final  value 83.752556 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.197991 
iter  10 value 93.783434
iter  20 value 87.734360
iter  30 value 86.461179
iter  40 value 86.068901
iter  50 value 85.881585
final  value 85.879011 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.456688 
iter  10 value 94.076565
iter  20 value 94.039455
iter  30 value 93.120516
iter  40 value 89.804589
iter  50 value 87.685652
iter  60 value 87.220989
iter  70 value 86.581763
iter  80 value 85.624815
iter  90 value 84.801812
iter 100 value 84.289006
final  value 84.289006 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 101.617831 
iter  10 value 94.079595
iter  20 value 89.679018
iter  30 value 88.876274
iter  40 value 88.468963
iter  50 value 86.427671
iter  60 value 84.778504
iter  70 value 84.155231
iter  80 value 84.053765
iter  90 value 83.872722
iter 100 value 83.650489
final  value 83.650489 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.225653 
iter  10 value 94.077548
iter  20 value 93.217029
iter  30 value 87.965860
iter  40 value 85.841040
iter  50 value 84.505380
iter  60 value 84.376875
iter  70 value 84.319865
iter  80 value 84.258662
iter  90 value 84.204363
iter 100 value 83.940190
final  value 83.940190 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.459353 
iter  10 value 93.605613
iter  20 value 88.939084
iter  30 value 85.976366
iter  40 value 84.931695
iter  50 value 84.262003
iter  60 value 84.012559
iter  70 value 83.975656
iter  80 value 83.890953
iter  90 value 83.874552
iter 100 value 83.847694
final  value 83.847694 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 111.972731 
iter  10 value 94.134054
iter  20 value 93.946490
iter  30 value 92.123518
iter  40 value 88.112381
iter  50 value 86.762926
iter  60 value 85.549134
iter  70 value 85.172745
iter  80 value 84.258873
iter  90 value 83.203247
iter 100 value 82.644720
final  value 82.644720 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.161552 
iter  10 value 93.852258
iter  20 value 90.459141
iter  30 value 88.736511
iter  40 value 87.095114
iter  50 value 86.540695
iter  60 value 85.017424
iter  70 value 84.345857
iter  80 value 84.184154
iter  90 value 84.019498
iter 100 value 83.803491
final  value 83.803491 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.416596 
iter  10 value 93.666090
iter  20 value 88.548548
iter  30 value 85.964556
iter  40 value 85.234972
iter  50 value 84.198963
iter  60 value 83.698013
iter  70 value 83.361000
iter  80 value 83.199096
iter  90 value 83.178027
iter 100 value 83.071976
final  value 83.071976 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.508477 
iter  10 value 97.047533
iter  20 value 95.894277
iter  30 value 92.740798
iter  40 value 88.508361
iter  50 value 88.103146
iter  60 value 87.715035
iter  70 value 86.387151
iter  80 value 86.072893
iter  90 value 85.642550
iter 100 value 84.824878
final  value 84.824878 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 122.418649 
iter  10 value 94.748627
iter  20 value 93.924489
iter  30 value 91.336579
iter  40 value 87.426911
iter  50 value 84.824485
iter  60 value 84.687876
iter  70 value 84.090261
iter  80 value 83.683434
iter  90 value 83.516232
iter 100 value 83.260098
final  value 83.260098 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 120.236223 
iter  10 value 93.852188
iter  20 value 87.377946
iter  30 value 86.648565
iter  40 value 84.342438
iter  50 value 83.461661
iter  60 value 83.254505
iter  70 value 83.118242
iter  80 value 82.931916
iter  90 value 82.673507
iter 100 value 82.598118
final  value 82.598118 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.185071 
iter  10 value 96.085686
iter  20 value 88.957326
iter  30 value 84.557527
iter  40 value 83.859473
iter  50 value 83.488567
iter  60 value 83.277621
iter  70 value 83.213257
iter  80 value 83.162929
iter  90 value 83.031174
iter 100 value 82.754428
final  value 82.754428 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.880771 
final  value 94.054643 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.662550 
iter  10 value 94.054825
iter  20 value 94.053029
final  value 94.053014 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.774295 
final  value 94.054672 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.515528 
final  value 94.054447 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.591416 
final  value 94.054607 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.911040 
iter  10 value 91.983898
iter  20 value 88.647872
iter  30 value 88.182602
iter  40 value 87.987761
iter  50 value 87.335564
iter  60 value 87.135835
iter  70 value 87.062121
iter  80 value 86.981035
iter  90 value 86.895139
iter 100 value 86.774279
final  value 86.774279 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 97.507853 
iter  10 value 94.057253
iter  20 value 93.998429
iter  30 value 92.469024
iter  40 value 92.379391
final  value 92.379387 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.302098 
iter  10 value 94.057717
iter  20 value 93.791926
iter  30 value 90.460164
final  value 90.460160 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.098679 
iter  10 value 94.057280
iter  20 value 94.026115
iter  30 value 93.185412
iter  40 value 92.785106
iter  50 value 89.627442
iter  60 value 88.889859
iter  70 value 87.049312
iter  80 value 86.927575
iter  90 value 86.677104
iter 100 value 86.584046
final  value 86.584046 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 96.861118 
iter  10 value 94.057217
iter  20 value 94.051627
iter  30 value 89.263817
iter  40 value 88.454354
iter  50 value 88.358930
iter  60 value 88.190292
iter  70 value 88.146274
iter  80 value 88.139292
iter  90 value 88.132243
final  value 88.132103 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.810114 
iter  10 value 94.041688
iter  20 value 94.038665
iter  30 value 94.034171
iter  40 value 94.017048
iter  50 value 92.353878
iter  60 value 86.783491
iter  70 value 86.777184
final  value 86.776936 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.372880 
iter  10 value 94.058364
iter  20 value 94.041680
iter  30 value 94.040633
iter  40 value 94.034324
iter  50 value 93.550076
iter  60 value 88.914930
iter  70 value 85.350273
iter  80 value 83.834094
iter  90 value 82.612809
iter 100 value 81.948288
final  value 81.948288 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.665361 
iter  10 value 93.857102
iter  20 value 93.812804
iter  30 value 93.811569
iter  40 value 93.799121
iter  50 value 92.140648
iter  60 value 91.478886
iter  70 value 91.478539
iter  80 value 91.478306
iter  90 value 91.449734
iter 100 value 91.404435
final  value 91.404435 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.817979 
iter  10 value 94.040398
iter  20 value 92.717690
iter  30 value 92.380756
iter  40 value 92.007445
iter  50 value 92.002811
iter  60 value 91.993290
iter  70 value 91.935551
final  value 91.935386 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.129559 
iter  10 value 91.253092
iter  20 value 87.801194
iter  30 value 87.644517
iter  40 value 87.517311
iter  50 value 87.453124
iter  60 value 87.341090
iter  70 value 87.092343
iter  80 value 86.900178
iter  90 value 85.300825
iter 100 value 84.358729
final  value 84.358729 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 109.158613 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.189802 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.376817 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.364358 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.307840 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 116.543845 
final  value 94.476190 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.289972 
final  value 94.354396 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.423111 
final  value 94.147186 
converged
Fitting Repeat 4 

# weights:  305
initial  value 108.461762 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.150261 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 109.479318 
iter  10 value 94.354920
final  value 94.354397 
converged
Fitting Repeat 2 

# weights:  507
initial  value 112.196763 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.950087 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 126.966267 
iter  10 value 94.354396
iter  10 value 94.354396
iter  10 value 94.354396
final  value 94.354396 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.304616 
iter  10 value 92.770118
iter  20 value 90.355328
iter  30 value 90.186126
iter  40 value 89.769658
final  value 89.769598 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.562843 
iter  10 value 94.140852
iter  20 value 89.089102
iter  30 value 87.263123
iter  40 value 86.490694
iter  50 value 86.407406
iter  60 value 86.320398
iter  70 value 86.308401
final  value 86.307926 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.802936 
iter  10 value 94.490929
iter  20 value 94.454544
iter  30 value 93.513353
iter  40 value 93.228579
iter  50 value 87.764258
iter  60 value 87.374349
iter  70 value 86.994413
iter  80 value 86.747722
iter  90 value 85.937031
iter 100 value 84.727733
final  value 84.727733 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 107.134252 
iter  10 value 94.488413
iter  20 value 94.486749
iter  30 value 94.476597
iter  40 value 93.953572
iter  50 value 89.756718
iter  60 value 89.283175
iter  70 value 86.688966
iter  80 value 85.611377
iter  90 value 85.037139
iter 100 value 84.955917
final  value 84.955917 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 100.352633 
iter  10 value 94.489727
iter  20 value 90.366878
iter  30 value 88.030535
iter  40 value 87.346638
iter  50 value 87.255121
iter  60 value 85.863229
iter  70 value 85.834862
final  value 85.834860 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.021077 
iter  10 value 94.498265
iter  20 value 94.471805
iter  30 value 91.984870
iter  40 value 87.468728
iter  50 value 86.617072
iter  60 value 86.339614
iter  70 value 86.229655
iter  80 value 86.027163
iter  90 value 85.217723
iter 100 value 84.905381
final  value 84.905381 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 106.442131 
iter  10 value 94.562380
iter  20 value 92.613823
iter  30 value 89.618131
iter  40 value 89.179572
iter  50 value 87.883396
iter  60 value 86.335495
iter  70 value 86.159883
iter  80 value 85.845969
iter  90 value 83.968906
iter 100 value 83.713131
final  value 83.713131 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.120779 
iter  10 value 92.119041
iter  20 value 89.497409
iter  30 value 87.656751
iter  40 value 85.084081
iter  50 value 84.613604
iter  60 value 84.489406
iter  70 value 84.379925
iter  80 value 83.881154
iter  90 value 83.428451
iter 100 value 83.102468
final  value 83.102468 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 107.298859 
iter  10 value 94.377013
iter  20 value 90.921747
iter  30 value 87.996557
iter  40 value 87.120118
iter  50 value 86.838545
iter  60 value 86.576127
iter  70 value 85.402854
iter  80 value 84.892938
iter  90 value 84.492375
iter 100 value 83.244521
final  value 83.244521 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.733613 
iter  10 value 94.409212
iter  20 value 92.555695
iter  30 value 90.683950
iter  40 value 87.238321
iter  50 value 85.436361
iter  60 value 84.679486
iter  70 value 83.748389
iter  80 value 83.441770
iter  90 value 83.367148
iter 100 value 83.135942
final  value 83.135942 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.291099 
iter  10 value 94.758789
iter  20 value 94.522892
iter  30 value 94.371349
iter  40 value 93.898249
iter  50 value 87.308893
iter  60 value 87.106278
iter  70 value 87.011198
iter  80 value 86.541099
iter  90 value 85.575084
iter 100 value 85.118229
final  value 85.118229 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.044831 
iter  10 value 94.531754
iter  20 value 93.567585
iter  30 value 90.366611
iter  40 value 87.351316
iter  50 value 86.383117
iter  60 value 84.711941
iter  70 value 83.625353
iter  80 value 83.368936
iter  90 value 83.268475
iter 100 value 83.143645
final  value 83.143645 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 130.763908 
iter  10 value 93.177240
iter  20 value 89.035756
iter  30 value 87.062409
iter  40 value 85.889839
iter  50 value 84.707597
iter  60 value 83.227022
iter  70 value 82.985172
iter  80 value 82.543337
iter  90 value 82.469057
iter 100 value 82.435014
final  value 82.435014 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.911504 
iter  10 value 99.899485
iter  20 value 92.826265
iter  30 value 92.582790
iter  40 value 86.824955
iter  50 value 85.920400
iter  60 value 85.581539
iter  70 value 84.954797
iter  80 value 84.887446
iter  90 value 84.767317
iter 100 value 84.364696
final  value 84.364696 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 141.510158 
iter  10 value 96.258983
iter  20 value 89.303220
iter  30 value 87.635185
iter  40 value 85.880310
iter  50 value 85.185797
iter  60 value 84.970368
iter  70 value 84.640189
iter  80 value 83.935245
iter  90 value 82.998117
iter 100 value 82.683183
final  value 82.683183 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.026605 
iter  10 value 94.509849
iter  20 value 88.363392
iter  30 value 85.478313
iter  40 value 84.737064
iter  50 value 83.947975
iter  60 value 82.852685
iter  70 value 82.738976
iter  80 value 82.479092
iter  90 value 82.255929
iter 100 value 82.151233
final  value 82.151233 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 106.031396 
final  value 94.485831 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.483812 
iter  10 value 94.485920
iter  20 value 90.020648
iter  30 value 87.748168
final  value 87.747458 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.043870 
final  value 94.485979 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.610788 
iter  10 value 94.485781
iter  20 value 94.484242
final  value 94.484216 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.300072 
final  value 94.485977 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.108103 
iter  10 value 94.487716
iter  20 value 93.784744
iter  30 value 88.233337
iter  40 value 87.961148
iter  50 value 87.273242
iter  60 value 86.542983
iter  70 value 86.437798
iter  80 value 86.431207
iter  90 value 86.331049
iter 100 value 86.075994
final  value 86.075994 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.000463 
iter  10 value 94.489192
iter  20 value 94.484252
final  value 94.484216 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.354326 
iter  10 value 93.819726
iter  20 value 93.801956
iter  30 value 93.799324
iter  40 value 93.682675
iter  50 value 88.367337
iter  60 value 86.751963
iter  70 value 86.561242
iter  80 value 86.557440
iter  90 value 86.551084
iter 100 value 86.316643
final  value 86.316643 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.225016 
iter  10 value 94.488569
iter  20 value 94.485120
final  value 94.485114 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.320996 
iter  10 value 94.491381
iter  20 value 94.484237
final  value 94.484232 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.965209 
iter  10 value 88.414442
iter  20 value 86.070700
iter  30 value 85.001332
iter  40 value 84.965818
iter  50 value 84.933951
iter  60 value 84.929019
iter  70 value 84.926317
final  value 84.925646 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.004421 
iter  10 value 90.161642
iter  20 value 89.949274
iter  30 value 89.945268
iter  40 value 89.844814
iter  50 value 88.015358
iter  60 value 86.068146
iter  70 value 85.793550
iter  80 value 85.776584
iter  90 value 85.776311
iter 100 value 85.774370
final  value 85.774370 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.596482 
iter  10 value 93.654605
iter  20 value 93.576230
iter  30 value 93.573612
iter  40 value 93.571547
iter  50 value 93.571250
iter  60 value 92.745480
iter  70 value 88.355661
iter  80 value 88.347794
iter  90 value 88.193831
iter 100 value 87.990437
final  value 87.990437 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 100.547222 
iter  10 value 94.362652
iter  20 value 94.355956
iter  30 value 94.355716
iter  40 value 94.352004
iter  50 value 91.307909
iter  60 value 87.853819
iter  70 value 87.640461
iter  80 value 87.636997
final  value 87.635593 
converged
Fitting Repeat 5 

# weights:  507
initial  value 118.682104 
iter  10 value 94.362858
iter  20 value 94.354991
iter  30 value 94.161712
iter  40 value 92.058089
iter  50 value 88.049731
iter  60 value 86.328378
iter  70 value 84.791031
iter  80 value 82.975127
iter  90 value 81.639817
iter 100 value 81.623719
final  value 81.623719 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.211020 
final  value 93.783647 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.975576 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.143447 
final  value 94.443243 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.292582 
final  value 94.443243 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.342473 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.317377 
iter  10 value 94.347383
iter  20 value 94.120680
iter  30 value 93.884007
iter  40 value 93.883345
final  value 93.883342 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.928152 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.264385 
final  value 94.484212 
converged
Fitting Repeat 4 

# weights:  305
initial  value 108.786978 
final  value 94.443243 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.449929 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 110.632876 
iter  10 value 93.722383
final  value 93.722222 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.563268 
iter  10 value 94.443246
final  value 94.443243 
converged
Fitting Repeat 3 

# weights:  507
initial  value 137.968089 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 116.372089 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 113.074738 
iter  10 value 94.203858
final  value 94.144481 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.725427 
iter  10 value 94.005963
iter  20 value 93.632667
iter  30 value 85.331943
iter  40 value 84.571523
iter  50 value 84.255597
iter  60 value 84.228317
iter  70 value 83.696710
final  value 83.694483 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.459061 
iter  10 value 94.488699
iter  20 value 92.540980
iter  30 value 85.461489
iter  40 value 83.595130
iter  50 value 83.342319
iter  60 value 83.202274
iter  70 value 82.404879
iter  80 value 81.400141
iter  90 value 80.940467
iter 100 value 80.822614
final  value 80.822614 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 96.612608 
iter  10 value 87.902547
iter  20 value 87.555558
iter  30 value 84.665562
iter  40 value 84.513663
iter  50 value 84.012444
iter  60 value 83.702735
final  value 83.701541 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.612674 
iter  10 value 94.432298
iter  20 value 93.671411
iter  30 value 93.636560
iter  40 value 93.622187
iter  50 value 92.821301
iter  60 value 89.803160
iter  70 value 87.608333
iter  80 value 83.489478
iter  90 value 82.673835
iter 100 value 81.523859
final  value 81.523859 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 100.454346 
iter  10 value 93.702040
iter  20 value 86.784489
iter  30 value 85.833151
iter  40 value 85.067930
iter  50 value 84.812249
iter  60 value 83.683434
iter  70 value 82.118930
iter  80 value 81.298772
iter  90 value 81.291343
iter  90 value 81.291342
final  value 81.291342 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.574395 
iter  10 value 94.369620
iter  20 value 89.975961
iter  30 value 83.242249
iter  40 value 82.641460
iter  50 value 82.398452
iter  60 value 80.881371
iter  70 value 80.091098
iter  80 value 79.454396
iter  90 value 79.379515
iter 100 value 79.278909
final  value 79.278909 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.777749 
iter  10 value 94.716901
iter  20 value 88.839331
iter  30 value 87.748507
iter  40 value 87.365639
iter  50 value 83.086260
iter  60 value 81.575749
iter  70 value 81.060715
iter  80 value 80.793741
iter  90 value 80.177691
iter 100 value 79.905080
final  value 79.905080 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 113.061520 
iter  10 value 94.489969
iter  20 value 94.220359
iter  30 value 93.648605
iter  40 value 93.440057
iter  50 value 86.849965
iter  60 value 85.979104
iter  70 value 83.485526
iter  80 value 83.244751
iter  90 value 82.587403
iter 100 value 82.144235
final  value 82.144235 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.590875 
iter  10 value 94.340965
iter  20 value 91.163758
iter  30 value 89.378851
iter  40 value 87.537925
final  value 87.439852 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.775883 
iter  10 value 94.319584
iter  20 value 88.195500
iter  30 value 87.436331
iter  40 value 87.374680
iter  50 value 87.180285
iter  60 value 86.562407
iter  70 value 85.708811
iter  80 value 82.132253
iter  90 value 81.116407
iter 100 value 80.555453
final  value 80.555453 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 119.187536 
iter  10 value 94.719588
iter  20 value 93.772878
iter  30 value 93.342840
iter  40 value 86.638203
iter  50 value 85.183597
iter  60 value 83.718704
iter  70 value 81.304830
iter  80 value 79.955599
iter  90 value 79.752105
iter 100 value 79.684534
final  value 79.684534 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 130.951205 
iter  10 value 94.390417
iter  20 value 93.916496
iter  30 value 86.540898
iter  40 value 84.872490
iter  50 value 83.833375
iter  60 value 83.360287
iter  70 value 83.110221
iter  80 value 83.023343
iter  90 value 82.446296
iter 100 value 81.288206
final  value 81.288206 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 121.454000 
iter  10 value 94.484507
iter  20 value 89.382434
iter  30 value 85.008647
iter  40 value 83.632621
iter  50 value 83.367827
iter  60 value 82.002472
iter  70 value 80.874874
iter  80 value 80.548946
iter  90 value 80.255396
iter 100 value 79.878239
final  value 79.878239 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.780460 
iter  10 value 94.417380
iter  20 value 88.507143
iter  30 value 83.877001
iter  40 value 81.231642
iter  50 value 80.390783
iter  60 value 80.069118
iter  70 value 79.782371
iter  80 value 79.562663
iter  90 value 79.489183
iter 100 value 79.278321
final  value 79.278321 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 116.086774 
iter  10 value 94.525344
iter  20 value 94.188145
iter  30 value 91.765595
iter  40 value 84.958219
iter  50 value 83.998441
iter  60 value 83.013443
iter  70 value 81.789604
iter  80 value 81.505518
iter  90 value 81.418440
iter 100 value 80.998453
final  value 80.998453 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 99.235029 
iter  10 value 94.150053
final  value 94.107162 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.346986 
iter  10 value 94.486055
final  value 94.484235 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.314975 
iter  10 value 94.486003
final  value 94.484252 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.381884 
iter  10 value 94.445344
iter  20 value 94.114560
iter  30 value 93.558608
iter  40 value 93.558513
final  value 93.558500 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.530583 
final  value 94.485756 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.084365 
iter  10 value 93.328900
iter  20 value 92.997088
iter  30 value 92.963084
iter  40 value 92.369576
iter  50 value 87.082249
iter  60 value 84.749408
iter  70 value 84.608223
iter  80 value 84.606943
iter  90 value 84.481895
iter 100 value 84.472411
final  value 84.472411 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 97.513490 
iter  10 value 94.489426
iter  20 value 94.425935
iter  30 value 84.864982
iter  40 value 84.622187
iter  50 value 84.611910
iter  60 value 84.610433
final  value 84.610374 
converged
Fitting Repeat 3 

# weights:  305
initial  value 118.176031 
iter  10 value 94.601010
iter  20 value 93.689110
iter  30 value 84.963642
iter  40 value 83.659201
iter  50 value 80.924122
iter  60 value 79.541380
iter  70 value 79.443110
iter  80 value 79.440074
iter  90 value 79.424539
iter 100 value 79.421929
final  value 79.421929 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 98.056882 
iter  10 value 94.448387
iter  20 value 94.372518
iter  30 value 84.086542
iter  40 value 83.896817
iter  50 value 83.895088
iter  60 value 83.859985
final  value 83.859946 
converged
Fitting Repeat 5 

# weights:  305
initial  value 110.178004 
iter  10 value 94.487808
iter  20 value 93.999977
iter  30 value 83.459471
final  value 83.370979 
converged
Fitting Repeat 1 

# weights:  507
initial  value 128.082113 
iter  10 value 94.451473
iter  20 value 94.315553
iter  30 value 93.651642
iter  40 value 91.287113
iter  50 value 90.678724
iter  60 value 89.761993
iter  70 value 89.623914
iter  80 value 89.620220
iter  90 value 89.601969
iter 100 value 89.305417
final  value 89.305417 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.909544 
iter  10 value 94.493118
iter  20 value 94.484280
iter  30 value 93.559208
iter  40 value 84.834468
iter  50 value 82.648486
iter  60 value 81.332916
iter  70 value 80.127299
iter  80 value 78.681049
iter  90 value 78.402463
iter 100 value 78.059022
final  value 78.059022 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 123.191803 
iter  10 value 94.492996
iter  20 value 94.055186
iter  30 value 93.376664
iter  40 value 93.362927
iter  50 value 93.317520
iter  60 value 92.979415
iter  70 value 90.207062
iter  80 value 89.895112
iter  90 value 89.894398
iter 100 value 89.893816
final  value 89.893816 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 135.453440 
iter  10 value 94.492642
iter  20 value 91.311914
iter  30 value 90.954005
iter  40 value 90.942146
iter  50 value 90.422723
iter  60 value 90.389138
iter  70 value 90.380667
iter  80 value 90.284904
iter  90 value 89.623473
iter 100 value 83.322798
final  value 83.322798 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.642375 
iter  10 value 94.451115
iter  20 value 94.390977
iter  30 value 88.873826
iter  40 value 85.005023
iter  50 value 83.254484
iter  60 value 82.285246
iter  70 value 82.283837
iter  80 value 82.283234
iter  80 value 82.283234
final  value 82.283234 
converged
Fitting Repeat 1 

# weights:  305
initial  value 127.789793 
iter  10 value 117.894739
iter  20 value 117.255651
iter  30 value 117.211023
final  value 117.206415 
converged
Fitting Repeat 2 

# weights:  305
initial  value 123.498344 
iter  10 value 117.895487
iter  20 value 117.823491
iter  30 value 117.406106
iter  40 value 109.356273
iter  50 value 109.328499
iter  60 value 109.239151
iter  70 value 106.734645
iter  80 value 106.707151
iter  90 value 104.811829
iter 100 value 104.262187
final  value 104.262187 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 123.761065 
iter  10 value 117.895720
iter  20 value 117.760556
iter  30 value 117.758768
iter  30 value 117.758768
iter  30 value 117.758768
final  value 117.758768 
converged
Fitting Repeat 4 

# weights:  305
initial  value 125.032119 
iter  10 value 117.895657
iter  20 value 117.890763
iter  30 value 116.109003
iter  40 value 105.377737
iter  50 value 103.420513
iter  60 value 102.672859
iter  70 value 102.634799
final  value 102.634685 
converged
Fitting Repeat 5 

# weights:  305
initial  value 132.826651 
iter  10 value 117.425735
iter  20 value 117.103297
iter  30 value 117.101185
iter  40 value 117.100400
iter  50 value 117.100237
iter  60 value 117.099485
iter  70 value 116.917175
iter  80 value 116.893266
iter  90 value 116.883640
iter  90 value 116.883639
iter  90 value 116.883639
final  value 116.883639 
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 -- Mon Aug 26 21:13:29 2024 
*********************************************** 
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 
Warning messages:
1: `repeats` has no meaning for this resampling method. 
2: executing %dopar% sequentially: no parallel backend registered 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
 42.301   1.927  42.483