##############################################################################
##############################################################################
###
### Running command:
###
###   F:\biocbuild\bbs-3.20-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.20-bioc\R\library --no-vignettes --timings HPiP_1.11.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory 'F:/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck'
* using R version 4.4.1 (2024-06-14 ucrt)
* using platform: x86_64-w64-mingw32
* R was compiled by
    gcc.exe (GCC) 13.2.0
    GNU Fortran (GCC) 13.2.0
* running under: Windows Server 2022 x64 (build 20348)
* 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 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       34.93   1.50   36.44
FSmethod      34.02   2.22   36.38
corr_plot     34.72   1.51   36.26
pred_ensembel 15.51   0.70   11.92
enrichfindP    0.67   0.08   13.38
* 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
  'F:/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck/00check.log'
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   F:\biocbuild\bbs-3.20-bioc\R\bin\R.exe CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library 'F:/biocbuild/bbs-3.20-bioc/R/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 ucrt) -- "Race for Your Life"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64

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 106.910419 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.660615 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.456181 
final  value 94.113276 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.079943 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.725019 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.636455 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.837927 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.324411 
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.356284 
iter  10 value 87.567999
iter  20 value 85.454296
iter  30 value 85.286508
iter  40 value 84.571077
iter  50 value 84.458227
iter  60 value 84.446757
iter  70 value 83.768647
iter  80 value 83.537495
iter  90 value 83.503461
final  value 83.503357 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.273556 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.020952 
iter  10 value 91.668887
iter  20 value 90.521011
iter  30 value 90.258490
iter  40 value 90.254903
final  value 90.254775 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.177584 
iter  10 value 94.304609
iter  10 value 94.304608
iter  10 value 94.304608
final  value 94.304608 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.582606 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 122.462606 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 108.117055 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.381065 
iter  10 value 94.489403
iter  20 value 94.466919
iter  30 value 91.993972
iter  40 value 91.047188
iter  50 value 90.543859
iter  60 value 90.473083
iter  70 value 86.705470
iter  80 value 85.839641
iter  90 value 83.912201
iter 100 value 83.061738
final  value 83.061738 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 103.866229 
iter  10 value 94.502212
iter  20 value 94.487632
iter  30 value 94.486891
iter  40 value 93.108580
iter  50 value 91.122440
iter  60 value 90.799175
iter  70 value 90.588862
iter  80 value 90.478468
final  value 90.478444 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.685592 
iter  10 value 94.400247
iter  20 value 89.136952
iter  30 value 87.561620
iter  40 value 86.301920
iter  50 value 86.221686
iter  60 value 85.637208
iter  70 value 84.307074
iter  80 value 83.771958
iter  90 value 82.726892
iter 100 value 80.651899
final  value 80.651899 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 101.789017 
iter  10 value 94.483704
iter  20 value 93.097295
iter  30 value 90.117111
iter  40 value 83.322572
iter  50 value 82.670168
iter  60 value 82.641255
iter  70 value 82.639296
iter  80 value 82.638662
final  value 82.638641 
converged
Fitting Repeat 5 

# weights:  103
initial  value 107.155530 
iter  10 value 94.446508
iter  20 value 92.701209
iter  30 value 90.967352
iter  40 value 90.583483
iter  50 value 90.480498
iter  60 value 90.478454
final  value 90.478443 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.359515 
iter  10 value 94.510815
iter  20 value 84.451645
iter  30 value 83.296933
iter  40 value 82.725421
iter  50 value 82.603339
iter  60 value 82.197323
iter  70 value 80.931663
iter  80 value 79.923601
iter  90 value 79.860567
iter 100 value 79.514251
final  value 79.514251 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.409956 
iter  10 value 91.669444
iter  20 value 83.869179
iter  30 value 81.903387
iter  40 value 80.567338
iter  50 value 80.204257
iter  60 value 80.069403
iter  70 value 79.470763
iter  80 value 79.160857
iter  90 value 79.103368
iter 100 value 78.966386
final  value 78.966386 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 109.384533 
iter  10 value 94.477778
iter  20 value 86.179938
iter  30 value 83.699898
iter  40 value 83.216371
iter  50 value 80.743566
iter  60 value 79.424546
iter  70 value 79.051713
iter  80 value 78.398545
iter  90 value 78.257675
iter 100 value 78.166099
final  value 78.166099 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.060206 
iter  10 value 93.841598
iter  20 value 87.724339
iter  30 value 86.457614
iter  40 value 85.242631
iter  50 value 83.866781
iter  60 value 81.025826
iter  70 value 79.382669
iter  80 value 79.016004
iter  90 value 78.730681
iter 100 value 78.463871
final  value 78.463871 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 123.241276 
iter  10 value 94.640292
iter  20 value 92.527715
iter  30 value 88.221658
iter  40 value 87.834325
iter  50 value 85.145512
iter  60 value 83.361020
iter  70 value 82.774257
iter  80 value 82.132161
iter  90 value 81.579470
iter 100 value 80.937777
final  value 80.937777 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 125.070446 
iter  10 value 94.832896
iter  20 value 90.178947
iter  30 value 83.681593
iter  40 value 82.863586
iter  50 value 82.137315
iter  60 value 81.694849
iter  70 value 81.131723
iter  80 value 79.066378
iter  90 value 78.894575
iter 100 value 78.774199
final  value 78.774199 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.819086 
iter  10 value 95.817814
iter  20 value 93.889268
iter  30 value 91.968237
iter  40 value 87.941919
iter  50 value 82.236007
iter  60 value 81.480882
iter  70 value 80.982684
iter  80 value 80.867372
iter  90 value 79.991593
iter 100 value 79.780989
final  value 79.780989 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.150691 
iter  10 value 94.570677
iter  20 value 93.449559
iter  30 value 91.526761
iter  40 value 83.790349
iter  50 value 81.170518
iter  60 value 80.304044
iter  70 value 80.103943
iter  80 value 79.556412
iter  90 value 79.145010
iter 100 value 78.911324
final  value 78.911324 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.311178 
iter  10 value 94.504241
iter  20 value 94.361739
iter  30 value 90.557949
iter  40 value 83.731847
iter  50 value 82.555193
iter  60 value 80.911699
iter  70 value 79.293896
iter  80 value 79.046360
iter  90 value 78.867156
iter 100 value 78.811902
final  value 78.811902 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.535802 
iter  10 value 94.660285
iter  20 value 86.949783
iter  30 value 82.246115
iter  40 value 80.554756
iter  50 value 80.275824
iter  60 value 79.255632
iter  70 value 78.724188
iter  80 value 78.239763
iter  90 value 77.935091
iter 100 value 77.767641
final  value 77.767641 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.022743 
final  value 94.485969 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.539761 
final  value 94.486064 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.789201 
final  value 94.485830 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.368627 
iter  10 value 94.485889
iter  20 value 94.479314
iter  30 value 94.400060
final  value 94.400049 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.546063 
final  value 94.485759 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.618870 
iter  10 value 92.101918
iter  20 value 92.087507
iter  30 value 91.767590
iter  40 value 91.758208
final  value 91.758119 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.159456 
iter  10 value 94.490744
iter  20 value 94.441620
iter  30 value 92.023242
iter  40 value 85.716408
iter  50 value 80.838725
iter  60 value 77.905249
iter  70 value 77.810148
iter  80 value 77.809376
iter  90 value 77.781124
iter 100 value 77.779836
final  value 77.779836 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.167041 
iter  10 value 94.487818
iter  20 value 92.290436
iter  30 value 88.504971
iter  40 value 87.291051
iter  50 value 87.056747
iter  50 value 87.056747
iter  50 value 87.056747
final  value 87.056747 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.332298 
iter  10 value 94.489457
iter  20 value 94.484265
iter  30 value 91.317291
final  value 90.639243 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.077408 
iter  10 value 94.489084
iter  20 value 94.298633
iter  30 value 83.903368
iter  40 value 82.289265
iter  50 value 80.437500
iter  60 value 80.180632
iter  70 value 80.179795
final  value 80.179712 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.826634 
iter  10 value 94.492435
iter  20 value 94.483322
iter  30 value 93.262952
iter  40 value 84.370281
iter  50 value 82.837266
iter  60 value 82.738184
final  value 82.737720 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.398643 
iter  10 value 94.492573
iter  20 value 92.730965
iter  30 value 84.910553
iter  40 value 82.963857
iter  50 value 82.693188
iter  60 value 81.416865
iter  70 value 81.330621
iter  80 value 81.158271
iter  90 value 80.862019
iter 100 value 80.808384
final  value 80.808384 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 120.686641 
iter  10 value 92.236069
iter  20 value 92.231250
iter  30 value 92.228199
iter  40 value 92.227657
iter  50 value 92.226532
iter  60 value 92.038153
iter  70 value 92.006556
iter  80 value 92.006165
final  value 92.006019 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.861250 
iter  10 value 92.287604
iter  20 value 83.655967
iter  30 value 82.414209
iter  40 value 81.945995
iter  50 value 81.937165
iter  60 value 81.934879
iter  70 value 81.933356
iter  80 value 81.868532
iter  90 value 80.295620
iter 100 value 77.143279
final  value 77.143279 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 129.577236 
iter  10 value 94.474722
iter  20 value 94.340936
iter  30 value 86.725320
iter  40 value 81.990088
iter  50 value 80.981068
iter  60 value 80.622907
iter  70 value 80.622293
iter  70 value 80.622293
final  value 80.622293 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.022804 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.412086 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.642764 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.769306 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.169356 
final  value 94.467391 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.495742 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.046017 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.707706 
iter  10 value 92.656395
final  value 92.468359 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.563327 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 127.281534 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 131.219795 
iter  10 value 87.919897
iter  20 value 82.417072
iter  30 value 81.038136
iter  40 value 80.949600
iter  50 value 80.949538
iter  50 value 80.949538
iter  50 value 80.949538
final  value 80.949538 
converged
Fitting Repeat 2 

# weights:  507
initial  value 112.325442 
final  value 94.467391 
converged
Fitting Repeat 3 

# weights:  507
initial  value 113.019266 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 114.374606 
final  value 94.467391 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.572299 
iter  10 value 94.467392
iter  10 value 94.467391
iter  10 value 94.467391
final  value 94.467391 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.986749 
iter  10 value 94.488926
iter  20 value 94.246887
iter  30 value 93.195644
iter  40 value 86.963847
iter  50 value 84.798812
iter  60 value 84.735332
iter  70 value 84.533923
iter  80 value 84.379056
iter  90 value 84.317088
iter 100 value 84.314736
final  value 84.314736 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 102.413123 
iter  10 value 94.554898
iter  20 value 93.101345
iter  30 value 89.960193
iter  40 value 82.646805
iter  50 value 82.462858
iter  60 value 82.401542
iter  70 value 82.381664
iter  80 value 82.230318
iter  90 value 81.648557
iter 100 value 81.443738
final  value 81.443738 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.081003 
iter  10 value 94.484940
iter  20 value 85.911542
iter  30 value 84.299350
iter  40 value 83.977541
iter  50 value 83.881372
iter  60 value 83.875081
final  value 83.875013 
converged
Fitting Repeat 4 

# weights:  103
initial  value 105.447376 
iter  10 value 94.488832
iter  20 value 87.655840
iter  30 value 85.481212
iter  40 value 83.699823
iter  50 value 82.179446
iter  60 value 82.046174
iter  70 value 81.359300
iter  80 value 81.030066
iter  90 value 80.951507
final  value 80.947733 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.664383 
iter  10 value 94.474880
iter  20 value 92.287263
iter  30 value 87.605557
iter  40 value 85.566913
iter  50 value 84.060249
iter  60 value 82.200052
iter  70 value 81.432253
iter  80 value 81.234760
iter  90 value 81.206043
final  value 81.206028 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.582679 
iter  10 value 93.972483
iter  20 value 85.184089
iter  30 value 83.386057
iter  40 value 81.316878
iter  50 value 80.981159
iter  60 value 80.883483
iter  70 value 80.854361
iter  80 value 80.851094
iter  90 value 80.846816
iter 100 value 80.443248
final  value 80.443248 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.061008 
iter  10 value 94.490909
iter  20 value 90.768706
iter  30 value 85.084034
iter  40 value 82.904261
iter  50 value 81.612459
iter  60 value 81.428669
iter  70 value 81.353238
iter  80 value 80.606249
iter  90 value 80.240762
iter 100 value 80.188630
final  value 80.188630 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.224076 
iter  10 value 94.497071
iter  20 value 94.378491
iter  30 value 94.069483
iter  40 value 93.962695
iter  50 value 87.626613
iter  60 value 86.938980
iter  70 value 85.779418
iter  80 value 82.661077
iter  90 value 82.242612
iter 100 value 81.981360
final  value 81.981360 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.652042 
iter  10 value 94.492399
iter  20 value 94.471503
iter  30 value 88.408327
iter  40 value 86.347225
iter  50 value 84.245858
iter  60 value 83.974784
iter  70 value 82.031722
iter  80 value 81.608189
iter  90 value 81.290930
iter 100 value 81.220238
final  value 81.220238 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.869134 
iter  10 value 92.007954
iter  20 value 84.938508
iter  30 value 84.661186
iter  40 value 84.522127
iter  50 value 84.070747
iter  60 value 82.359205
iter  70 value 81.885759
iter  80 value 81.305461
iter  90 value 81.174887
iter 100 value 80.646102
final  value 80.646102 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 130.603500 
iter  10 value 94.416786
iter  20 value 94.187303
iter  30 value 86.368503
iter  40 value 83.545868
iter  50 value 82.559958
iter  60 value 82.081102
iter  70 value 81.828419
iter  80 value 81.625944
iter  90 value 81.194389
iter 100 value 80.708324
final  value 80.708324 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.277772 
iter  10 value 94.515458
iter  20 value 94.442579
iter  30 value 90.131881
iter  40 value 88.131155
iter  50 value 85.298181
iter  60 value 84.871592
iter  70 value 82.994812
iter  80 value 82.022717
iter  90 value 81.036118
iter 100 value 80.292489
final  value 80.292489 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 112.615156 
iter  10 value 94.123060
iter  20 value 88.411295
iter  30 value 85.203419
iter  40 value 84.776746
iter  50 value 84.483252
iter  60 value 84.311567
iter  70 value 84.063662
iter  80 value 83.985000
iter  90 value 83.823887
iter 100 value 83.670170
final  value 83.670170 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.301083 
iter  10 value 94.318112
iter  20 value 88.825769
iter  30 value 87.950177
iter  40 value 86.900450
iter  50 value 86.599307
iter  60 value 84.849763
iter  70 value 82.191651
iter  80 value 81.714985
iter  90 value 81.136363
iter 100 value 81.003271
final  value 81.003271 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.674426 
iter  10 value 94.278751
iter  20 value 92.164343
iter  30 value 87.224176
iter  40 value 83.488670
iter  50 value 82.271486
iter  60 value 81.994981
iter  70 value 81.302855
iter  80 value 80.438255
iter  90 value 80.052818
iter 100 value 79.905559
final  value 79.905559 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.162164 
final  value 94.485851 
converged
Fitting Repeat 2 

# weights:  103
initial  value 105.774559 
final  value 94.485667 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.667039 
final  value 94.356016 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.267731 
iter  10 value 94.485953
iter  20 value 94.484229
final  value 94.484215 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.653809 
final  value 94.485755 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.310958 
iter  10 value 94.489246
iter  20 value 94.484114
iter  30 value 94.463958
iter  40 value 85.552453
iter  50 value 82.897103
iter  60 value 82.884417
iter  70 value 82.865945
iter  80 value 81.726876
iter  90 value 81.091748
iter 100 value 81.053675
final  value 81.053675 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 95.956126 
iter  10 value 87.402321
iter  20 value 87.338717
iter  30 value 85.956135
iter  40 value 85.955979
iter  50 value 85.954163
iter  60 value 85.868539
iter  70 value 85.866679
final  value 85.866674 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.553610 
iter  10 value 94.102806
iter  20 value 93.938405
iter  30 value 93.936947
iter  40 value 93.936535
iter  50 value 93.935852
iter  60 value 93.935123
iter  70 value 93.925182
iter  80 value 93.847655
iter  90 value 93.792050
iter 100 value 93.791924
final  value 93.791924 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.291159 
iter  10 value 94.491535
iter  20 value 94.278275
iter  30 value 86.049481
iter  40 value 85.238714
iter  50 value 85.218638
final  value 85.218502 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.709421 
iter  10 value 94.489311
iter  20 value 94.259450
iter  30 value 85.956499
iter  40 value 85.956180
iter  50 value 84.829550
iter  60 value 82.794422
iter  70 value 82.695308
iter  80 value 81.572157
iter  90 value 81.026864
iter 100 value 80.930892
final  value 80.930892 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 96.188782 
iter  10 value 94.177403
iter  20 value 89.058971
iter  30 value 82.912878
iter  40 value 82.717992
iter  50 value 82.514251
iter  60 value 82.344326
iter  70 value 82.342568
iter  80 value 82.336817
iter  90 value 82.336446
iter 100 value 82.332981
final  value 82.332981 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 102.803397 
iter  10 value 94.381945
iter  20 value 94.360774
iter  30 value 94.354356
iter  40 value 94.305519
iter  50 value 93.943379
iter  60 value 88.999305
iter  70 value 86.139652
iter  80 value 85.801910
iter  90 value 84.779167
iter 100 value 79.221015
final  value 79.221015 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.923250 
iter  10 value 94.492018
iter  20 value 92.518501
iter  30 value 84.098685
iter  40 value 83.969269
final  value 83.967966 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.128493 
iter  10 value 94.490903
iter  20 value 92.857455
iter  30 value 86.475676
iter  40 value 82.508667
iter  50 value 82.291989
iter  60 value 82.274283
iter  70 value 82.269992
iter  80 value 82.246675
iter  90 value 82.246534
iter 100 value 82.246241
final  value 82.246241 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.841971 
iter  10 value 94.492902
iter  20 value 93.842077
iter  30 value 86.763252
iter  40 value 84.750619
iter  50 value 84.750249
iter  60 value 84.329098
iter  70 value 83.533458
iter  80 value 83.472157
iter  80 value 83.472157
iter  80 value 83.472157
final  value 83.472157 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.261464 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.839480 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.046980 
iter  10 value 92.746701
iter  20 value 86.739808
final  value 86.726120 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.834072 
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  103
initial  value 113.132588 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 111.154674 
iter  10 value 94.484354
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.491985 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.377014 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.679448 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.253673 
iter  10 value 93.443179
iter  20 value 91.942865
iter  30 value 91.773525
iter  40 value 90.950296
iter  50 value 90.946670
final  value 90.946667 
converged
Fitting Repeat 1 

# weights:  507
initial  value 118.766967 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.082052 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 113.322263 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.424373 
iter  10 value 94.275365
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.650904 
iter  10 value 94.275367
final  value 94.275362 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.113075 
iter  10 value 94.588565
iter  20 value 94.487254
iter  30 value 86.695802
iter  40 value 86.341619
iter  50 value 84.702856
iter  60 value 83.643346
iter  70 value 83.588677
iter  80 value 83.581441
final  value 83.581423 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.658151 
iter  10 value 94.433751
iter  20 value 92.357152
iter  30 value 92.293651
iter  40 value 91.996522
iter  50 value 91.758948
iter  60 value 91.747965
final  value 91.747634 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.657606 
iter  10 value 94.485463
iter  20 value 87.395916
iter  30 value 86.435772
iter  40 value 85.765781
iter  50 value 85.597611
iter  60 value 84.843353
iter  70 value 83.596494
iter  80 value 83.581383
final  value 83.581357 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.988633 
iter  10 value 94.495146
iter  20 value 94.310126
iter  30 value 87.817100
iter  40 value 85.796260
iter  50 value 85.391695
iter  60 value 83.930421
iter  70 value 82.832263
iter  80 value 82.647728
final  value 82.643794 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.088286 
iter  10 value 94.333781
iter  20 value 86.675647
iter  30 value 85.623412
iter  40 value 85.507069
iter  50 value 83.740676
iter  60 value 83.000170
iter  70 value 82.462520
iter  80 value 82.440342
final  value 82.440239 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.918055 
iter  10 value 94.439210
iter  20 value 90.311368
iter  30 value 88.241818
iter  40 value 87.534625
iter  50 value 86.395948
iter  60 value 84.781707
iter  70 value 83.817696
iter  80 value 82.278962
iter  90 value 81.929446
iter 100 value 81.620509
final  value 81.620509 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.045931 
iter  10 value 91.983599
iter  20 value 86.872380
iter  30 value 85.559552
iter  40 value 82.931346
iter  50 value 82.583274
iter  60 value 82.397070
iter  70 value 82.276332
iter  80 value 82.247629
iter  90 value 82.145083
iter 100 value 81.615754
final  value 81.615754 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.731663 
iter  10 value 94.543880
iter  20 value 94.490889
iter  30 value 94.379109
iter  40 value 90.009356
iter  50 value 86.998040
iter  60 value 85.782239
iter  70 value 83.359893
iter  80 value 82.817413
iter  90 value 82.376242
iter 100 value 81.919700
final  value 81.919700 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.090057 
iter  10 value 94.511323
iter  20 value 87.964733
iter  30 value 87.104557
iter  40 value 85.641436
iter  50 value 84.576925
iter  60 value 82.746222
iter  70 value 82.659014
iter  80 value 82.624078
iter  90 value 82.469411
iter 100 value 82.432832
final  value 82.432832 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.516855 
iter  10 value 93.868909
iter  20 value 92.143158
iter  30 value 91.717343
iter  40 value 89.142613
iter  50 value 87.576708
iter  60 value 87.075964
iter  70 value 86.131629
iter  80 value 83.950285
iter  90 value 83.539995
iter 100 value 83.347873
final  value 83.347873 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 124.033640 
iter  10 value 94.302516
iter  20 value 88.118243
iter  30 value 85.967113
iter  40 value 82.074599
iter  50 value 81.627353
iter  60 value 81.462457
iter  70 value 81.315772
iter  80 value 81.227030
iter  90 value 81.188252
iter 100 value 81.144893
final  value 81.144893 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 120.687798 
iter  10 value 94.276536
iter  20 value 92.541042
iter  30 value 91.812440
iter  40 value 91.243374
iter  50 value 83.169091
iter  60 value 81.621074
iter  70 value 81.365052
iter  80 value 81.337395
iter  90 value 81.290698
iter 100 value 81.279179
final  value 81.279179 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.078254 
iter  10 value 94.613230
iter  20 value 94.265244
iter  30 value 93.030450
iter  40 value 88.027644
iter  50 value 86.753268
iter  60 value 85.770933
iter  70 value 83.550689
iter  80 value 83.197353
iter  90 value 82.892487
iter 100 value 82.227768
final  value 82.227768 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.910964 
iter  10 value 94.304121
iter  20 value 93.310294
iter  30 value 89.800018
iter  40 value 85.563832
iter  50 value 83.124637
iter  60 value 82.119387
iter  70 value 81.594441
iter  80 value 81.395916
iter  90 value 81.293647
iter 100 value 81.220863
final  value 81.220863 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 116.172657 
iter  10 value 95.668045
iter  20 value 88.341235
iter  30 value 84.194714
iter  40 value 83.293489
iter  50 value 82.383901
iter  60 value 81.981982
iter  70 value 81.792176
iter  80 value 81.593064
iter  90 value 81.532263
iter 100 value 81.270677
final  value 81.270677 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 100.408268 
iter  10 value 94.276938
iter  20 value 93.089636
iter  30 value 89.932878
iter  40 value 89.885743
iter  50 value 89.884521
iter  50 value 89.884521
iter  50 value 89.884521
final  value 89.884521 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.141610 
iter  10 value 94.489377
iter  20 value 94.484222
final  value 94.484219 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.877753 
iter  10 value 93.111692
iter  20 value 93.110821
iter  20 value 93.110821
iter  20 value 93.110821
final  value 93.110821 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.570247 
final  value 94.485812 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.905846 
final  value 94.485998 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.492041 
iter  10 value 94.488814
iter  20 value 94.356901
iter  30 value 88.515150
iter  40 value 87.815450
iter  50 value 87.813437
iter  60 value 87.812051
final  value 87.811475 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.729004 
iter  10 value 94.488346
final  value 94.484223 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.475128 
iter  10 value 93.757153
iter  20 value 93.737367
iter  30 value 93.642626
iter  40 value 93.449534
iter  50 value 93.344686
iter  60 value 93.343572
final  value 93.343455 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.663662 
iter  10 value 94.488546
iter  20 value 94.481669
iter  30 value 93.339482
iter  40 value 88.476492
iter  50 value 87.735090
iter  60 value 84.352208
iter  70 value 83.634161
iter  80 value 83.252508
iter  90 value 82.396376
iter 100 value 80.787169
final  value 80.787169 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 97.920907 
iter  10 value 94.280596
iter  20 value 93.772141
iter  30 value 92.114286
iter  40 value 92.107275
iter  50 value 92.097823
final  value 92.097812 
converged
Fitting Repeat 1 

# weights:  507
initial  value 106.693950 
iter  10 value 94.283845
iter  20 value 94.234114
iter  30 value 92.346398
iter  40 value 91.936632
iter  50 value 91.931709
final  value 91.931622 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.865595 
iter  10 value 94.282929
iter  20 value 94.275534
iter  30 value 87.807495
iter  40 value 86.886776
iter  50 value 84.038967
iter  60 value 83.984033
iter  70 value 83.857551
iter  80 value 83.695004
iter  90 value 83.345309
iter 100 value 83.251957
final  value 83.251957 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 98.811974 
iter  10 value 94.491869
iter  20 value 93.986083
iter  30 value 86.262351
iter  40 value 86.121632
iter  50 value 85.932939
iter  60 value 85.927680
iter  70 value 85.722812
iter  80 value 83.024673
iter  90 value 81.928360
iter 100 value 81.708668
final  value 81.708668 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.691103 
iter  10 value 94.489808
iter  20 value 94.150454
iter  30 value 89.866930
iter  40 value 88.712195
final  value 88.711026 
converged
Fitting Repeat 5 

# weights:  507
initial  value 112.506055 
iter  10 value 94.236997
iter  20 value 94.234176
iter  30 value 94.229935
iter  40 value 94.229755
iter  50 value 94.229240
iter  60 value 94.228995
iter  70 value 94.228915
iter  80 value 94.035755
iter  90 value 92.108204
iter 100 value 92.099199
final  value 92.099199 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.185365 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.787221 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.255802 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.239641 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.762812 
final  value 93.860355 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.166806 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.502658 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 108.906513 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.701992 
iter  10 value 93.356510
iter  20 value 93.341991
iter  20 value 93.341991
iter  20 value 93.341991
final  value 93.341991 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.204607 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.375183 
iter  10 value 93.588180
final  value 93.582418 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.717375 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 110.024393 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 110.789961 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 127.258454 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.604374 
iter  10 value 93.626509
iter  20 value 87.930644
iter  30 value 87.041369
iter  40 value 86.761076
iter  50 value 84.970163
iter  60 value 84.053528
iter  70 value 83.367134
iter  80 value 83.362826
iter  90 value 82.995437
iter 100 value 82.618412
final  value 82.618412 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 98.959744 
iter  10 value 93.991365
iter  20 value 93.459575
iter  30 value 93.347329
iter  40 value 93.156451
iter  50 value 88.177845
iter  60 value 87.660445
iter  70 value 85.597573
iter  80 value 84.622234
iter  90 value 83.896810
iter 100 value 83.813727
final  value 83.813727 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 107.736163 
iter  10 value 94.072698
iter  20 value 89.866665
iter  30 value 87.497123
iter  40 value 87.134784
iter  50 value 85.546518
iter  60 value 84.333873
iter  70 value 83.761027
iter  80 value 83.641205
final  value 83.640637 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.763721 
iter  10 value 94.047774
iter  20 value 92.957247
iter  30 value 84.962527
iter  40 value 83.662903
iter  50 value 83.616791
iter  60 value 83.610565
final  value 83.610268 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.552353 
iter  10 value 94.055905
iter  20 value 93.788322
iter  30 value 93.247093
iter  40 value 92.937015
iter  50 value 89.207287
iter  60 value 87.201292
iter  70 value 86.808009
iter  80 value 84.766918
iter  90 value 83.393164
iter 100 value 82.892404
final  value 82.892404 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 120.237623 
iter  10 value 92.367945
iter  20 value 88.192225
iter  30 value 86.623623
iter  40 value 85.148501
iter  50 value 83.556960
iter  60 value 83.190562
iter  70 value 82.894672
iter  80 value 82.593015
iter  90 value 82.359845
iter 100 value 82.330142
final  value 82.330142 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 107.520831 
iter  10 value 93.832027
iter  20 value 88.257113
iter  30 value 85.405848
iter  40 value 82.989141
iter  50 value 82.074457
iter  60 value 82.005260
iter  70 value 81.923898
iter  80 value 81.907650
iter  80 value 81.907650
final  value 81.907650 
converged
Fitting Repeat 3 

# weights:  305
initial  value 121.003317 
iter  10 value 93.576412
iter  20 value 92.842281
iter  30 value 89.865639
iter  40 value 85.586369
iter  50 value 84.304755
iter  60 value 84.190467
iter  70 value 83.343540
iter  80 value 83.065718
iter  90 value 81.867628
iter 100 value 81.247610
final  value 81.247610 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 118.585847 
iter  10 value 94.041442
iter  20 value 87.688684
iter  30 value 86.893384
iter  40 value 85.894469
iter  50 value 84.408469
iter  60 value 82.525746
iter  70 value 81.921779
iter  80 value 81.727298
iter  90 value 81.612145
iter 100 value 81.363594
final  value 81.363594 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.342367 
iter  10 value 94.059597
iter  20 value 93.738621
iter  30 value 93.162336
iter  40 value 90.095375
iter  50 value 86.664603
iter  60 value 85.561380
iter  70 value 84.077875
iter  80 value 83.897430
iter  90 value 83.515900
iter 100 value 83.159936
final  value 83.159936 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.421968 
iter  10 value 94.027916
iter  20 value 93.379553
iter  30 value 86.205441
iter  40 value 84.590186
iter  50 value 83.634598
iter  60 value 83.366029
iter  70 value 82.645342
iter  80 value 81.931718
iter  90 value 81.698359
iter 100 value 81.460751
final  value 81.460751 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 130.993303 
iter  10 value 94.492750
iter  20 value 92.864895
iter  30 value 85.674796
iter  40 value 83.598337
iter  50 value 82.351651
iter  60 value 81.822263
iter  70 value 81.433788
iter  80 value 81.067599
iter  90 value 80.986529
iter 100 value 80.957188
final  value 80.957188 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 119.712193 
iter  10 value 93.785269
iter  20 value 86.517838
iter  30 value 86.096732
iter  40 value 85.668783
iter  50 value 82.966412
iter  60 value 82.004343
iter  70 value 81.743636
iter  80 value 81.580937
iter  90 value 81.465327
iter 100 value 81.441513
final  value 81.441513 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.890469 
iter  10 value 94.388418
iter  20 value 93.613966
iter  30 value 87.351963
iter  40 value 84.649322
iter  50 value 83.015142
iter  60 value 82.899616
iter  70 value 82.765910
iter  80 value 82.157633
iter  90 value 81.870622
iter 100 value 81.749153
final  value 81.749153 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 119.616086 
iter  10 value 92.430616
iter  20 value 88.221681
iter  30 value 85.844544
iter  40 value 85.040943
iter  50 value 83.057622
iter  60 value 82.843506
iter  70 value 82.785590
iter  80 value 82.412416
iter  90 value 81.739500
iter 100 value 81.408638
final  value 81.408638 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.531217 
final  value 94.054851 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.846799 
final  value 94.054645 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.185252 
final  value 94.054490 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.037270 
iter  10 value 93.659091
iter  10 value 93.659090
iter  10 value 93.659090
final  value 93.659090 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.554570 
final  value 94.054587 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.490920 
iter  10 value 88.810469
iter  20 value 83.872352
iter  30 value 83.411068
final  value 83.393773 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.722298 
iter  10 value 93.767871
iter  20 value 93.552589
iter  30 value 93.342347
iter  40 value 93.339905
iter  50 value 93.308601
iter  60 value 87.255379
iter  70 value 86.577037
iter  80 value 86.542623
final  value 86.542520 
converged
Fitting Repeat 3 

# weights:  305
initial  value 109.956269 
iter  10 value 94.058163
iter  20 value 94.052967
final  value 94.052912 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.495440 
iter  10 value 94.057425
iter  20 value 92.180521
iter  30 value 89.656961
iter  40 value 89.542430
iter  50 value 87.238610
iter  60 value 87.045945
iter  70 value 86.627860
iter  80 value 86.625980
iter  90 value 86.621805
iter 100 value 86.465702
final  value 86.465702 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 95.292168 
iter  10 value 94.056960
iter  20 value 93.912029
iter  30 value 89.598683
iter  40 value 86.649243
iter  50 value 86.542276
iter  60 value 86.007366
final  value 85.985603 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.531743 
iter  10 value 93.590521
iter  20 value 93.321305
iter  30 value 86.770833
iter  40 value 86.328053
iter  50 value 83.201442
iter  60 value 82.207009
iter  70 value 81.765063
iter  80 value 81.326707
iter  90 value 80.975639
iter 100 value 80.567545
final  value 80.567545 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.252180 
iter  10 value 93.590402
iter  20 value 93.191645
iter  30 value 92.960603
iter  40 value 92.946185
iter  50 value 92.924035
iter  60 value 92.921026
iter  70 value 92.920064
final  value 92.920042 
converged
Fitting Repeat 3 

# weights:  507
initial  value 122.224612 
iter  10 value 94.061595
iter  20 value 94.042743
iter  30 value 85.500079
iter  40 value 82.754467
iter  50 value 80.915256
iter  60 value 80.621934
iter  70 value 80.610524
iter  80 value 80.603861
iter  90 value 80.564425
iter 100 value 80.440531
final  value 80.440531 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.433038 
iter  10 value 93.590862
iter  20 value 93.583539
iter  30 value 93.451233
iter  40 value 86.843048
iter  50 value 82.594033
iter  60 value 80.866002
iter  70 value 80.659972
iter  80 value 80.551690
iter  90 value 80.534954
iter 100 value 80.533722
final  value 80.533722 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.632180 
iter  10 value 93.587537
iter  20 value 93.584350
iter  30 value 93.342414
iter  40 value 93.336120
iter  50 value 93.335488
final  value 93.335407 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.739655 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.477874 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.663770 
iter  10 value 82.751756
iter  20 value 82.224927
iter  30 value 81.761835
iter  40 value 81.645211
iter  50 value 81.616556
final  value 81.616367 
converged
Fitting Repeat 4 

# weights:  103
initial  value 110.074264 
final  value 92.954173 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.318097 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.865602 
iter  10 value 92.683978
final  value 92.677297 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.657175 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.450447 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.135864 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.156564 
iter  10 value 93.605237
final  value 93.604520 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.764937 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 112.633040 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.519981 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.579859 
iter  10 value 88.360597
iter  20 value 85.980238
iter  30 value 85.911634
iter  40 value 85.594346
iter  50 value 85.284046
iter  60 value 83.885276
iter  70 value 83.824341
iter  80 value 83.821948
final  value 83.821894 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.194738 
iter  10 value 93.600524
iter  20 value 93.057534
final  value 92.954172 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.739263 
iter  10 value 88.528014
iter  20 value 85.805332
iter  30 value 85.567626
iter  40 value 85.536427
iter  50 value 85.135518
iter  60 value 85.039701
iter  70 value 84.976758
final  value 84.976696 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.884754 
iter  10 value 93.829158
iter  20 value 92.842833
iter  30 value 92.804848
iter  40 value 89.767604
iter  50 value 82.604153
iter  60 value 81.919849
iter  70 value 81.190328
iter  80 value 80.820832
iter  90 value 80.679494
iter 100 value 80.332263
final  value 80.332263 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 95.978354 
iter  10 value 94.007592
iter  20 value 89.697809
iter  30 value 85.249307
iter  40 value 82.174580
iter  50 value 81.094501
iter  60 value 80.643760
iter  70 value 80.219285
iter  80 value 80.187278
final  value 80.166515 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.242266 
iter  10 value 93.749909
iter  20 value 89.568441
iter  30 value 86.650425
iter  40 value 84.866827
iter  50 value 82.378378
iter  60 value 82.303773
iter  70 value 82.261616
final  value 82.260764 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.980049 
iter  10 value 94.002463
iter  20 value 93.093150
iter  30 value 92.801144
iter  40 value 87.286222
iter  50 value 83.494332
iter  60 value 82.460766
iter  70 value 81.115761
iter  80 value 80.460536
iter  90 value 80.194912
iter 100 value 80.180559
final  value 80.180559 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 104.961538 
iter  10 value 95.053932
iter  20 value 93.501363
iter  30 value 89.670479
iter  40 value 82.331581
iter  50 value 81.160799
iter  60 value 80.985644
iter  70 value 80.546091
iter  80 value 80.377845
iter  90 value 79.999628
iter 100 value 79.949261
final  value 79.949261 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.082250 
iter  10 value 94.688895
iter  20 value 83.057379
iter  30 value 81.153847
iter  40 value 80.447253
iter  50 value 80.201940
iter  60 value 79.786044
iter  70 value 79.540245
iter  80 value 79.410251
iter  90 value 79.161111
iter 100 value 79.019019
final  value 79.019019 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 109.779751 
iter  10 value 92.951874
iter  20 value 88.383132
iter  30 value 82.177861
iter  40 value 80.310437
iter  50 value 79.242643
iter  60 value 78.998868
iter  70 value 78.933550
iter  80 value 78.878891
iter  90 value 78.825511
iter 100 value 78.801420
final  value 78.801420 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.929121 
iter  10 value 94.017183
iter  20 value 93.140948
iter  30 value 91.026194
iter  40 value 86.430344
iter  50 value 84.836281
iter  60 value 81.590778
iter  70 value 80.265272
iter  80 value 79.649129
iter  90 value 79.551625
iter 100 value 79.278234
final  value 79.278234 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.908181 
iter  10 value 93.975848
iter  20 value 83.625937
iter  30 value 82.904761
iter  40 value 80.871614
iter  50 value 80.658990
iter  60 value 80.510092
iter  70 value 80.032930
iter  80 value 79.038823
iter  90 value 78.902228
iter 100 value 78.588214
final  value 78.588214 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 102.429527 
iter  10 value 89.107260
iter  20 value 82.809432
iter  30 value 81.578689
iter  40 value 80.639347
iter  50 value 79.580431
iter  60 value 79.194354
iter  70 value 78.629803
iter  80 value 78.525768
iter  90 value 78.435396
iter 100 value 78.360740
final  value 78.360740 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.372336 
iter  10 value 96.594808
iter  20 value 94.099850
iter  30 value 85.554142
iter  40 value 84.684606
iter  50 value 82.767548
iter  60 value 81.515441
iter  70 value 80.285238
iter  80 value 79.694793
iter  90 value 79.410649
iter 100 value 79.285467
final  value 79.285467 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.656164 
iter  10 value 94.009233
iter  20 value 91.714188
iter  30 value 85.676101
iter  40 value 83.842807
iter  50 value 79.775578
iter  60 value 78.894269
iter  70 value 78.635172
iter  80 value 78.461053
iter  90 value 78.452739
iter 100 value 78.429937
final  value 78.429937 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 116.886549 
iter  10 value 94.040241
iter  20 value 92.794000
iter  30 value 84.053910
iter  40 value 82.983619
iter  50 value 81.827447
iter  60 value 81.181372
iter  70 value 80.644342
iter  80 value 79.863283
iter  90 value 79.437690
iter 100 value 79.268683
final  value 79.268683 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 133.612222 
iter  10 value 93.800278
iter  20 value 83.537592
iter  30 value 81.358125
iter  40 value 80.891551
iter  50 value 80.354574
iter  60 value 79.911015
iter  70 value 79.674529
iter  80 value 79.476323
iter  90 value 79.017992
iter 100 value 78.783996
final  value 78.783996 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.186680 
final  value 94.054559 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.509231 
iter  10 value 93.185982
iter  20 value 93.184668
iter  30 value 93.184262
iter  30 value 93.184262
iter  30 value 93.184261
final  value 93.184261 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.495760 
iter  10 value 91.080944
iter  20 value 91.080461
iter  30 value 89.109075
iter  40 value 85.840262
iter  50 value 85.447433
iter  60 value 85.200536
iter  70 value 85.200272
final  value 85.200189 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.314366 
final  value 94.054487 
converged
Fitting Repeat 5 

# weights:  103
initial  value 120.787188 
iter  10 value 93.837868
iter  20 value 93.836599
iter  30 value 92.168983
iter  40 value 85.231129
iter  50 value 85.219544
iter  60 value 85.217808
iter  70 value 85.217643
final  value 85.217614 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.235357 
iter  10 value 93.189224
iter  20 value 92.959330
iter  30 value 92.931934
iter  40 value 92.928866
iter  50 value 92.925885
iter  60 value 85.366370
final  value 82.288578 
converged
Fitting Repeat 2 

# weights:  305
initial  value 114.616909 
iter  10 value 94.057793
iter  20 value 92.019686
iter  30 value 91.992829
iter  40 value 91.991962
iter  50 value 91.991097
iter  60 value 91.115974
iter  70 value 89.218289
iter  80 value 89.142599
iter  90 value 89.141547
iter 100 value 89.140169
final  value 89.140169 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 97.138898 
iter  10 value 90.973281
iter  20 value 86.776360
iter  30 value 86.763428
iter  40 value 83.269144
iter  50 value 82.293669
iter  60 value 82.281949
iter  70 value 82.266449
iter  80 value 82.248812
iter  90 value 81.750312
final  value 81.749912 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.753254 
iter  10 value 92.740556
iter  20 value 92.733445
iter  30 value 91.806610
iter  40 value 81.704226
iter  50 value 78.279979
iter  60 value 77.513715
iter  70 value 77.370633
iter  80 value 77.053961
iter  90 value 77.049052
iter 100 value 77.048800
final  value 77.048800 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.849250 
iter  10 value 92.662568
iter  20 value 92.653915
iter  30 value 92.650223
final  value 92.649787 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.996372 
iter  10 value 88.789302
iter  20 value 81.938780
iter  30 value 81.048981
iter  40 value 80.584095
iter  50 value 80.065415
iter  60 value 79.925623
iter  70 value 79.909822
iter  80 value 79.751145
iter  90 value 79.617842
iter 100 value 79.614977
final  value 79.614977 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.328680 
iter  10 value 93.793069
iter  20 value 93.784812
iter  30 value 92.356556
iter  40 value 92.177440
iter  50 value 92.164212
iter  60 value 92.163125
iter  70 value 92.159648
iter  80 value 84.381884
iter  90 value 81.623769
iter 100 value 79.835580
final  value 79.835580 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.533678 
iter  10 value 91.018747
iter  20 value 90.246494
iter  30 value 82.749412
iter  40 value 82.710988
iter  50 value 82.694323
iter  60 value 82.687860
iter  70 value 82.687474
iter  80 value 82.659592
iter  90 value 82.652857
iter 100 value 82.652173
final  value 82.652173 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.580132 
iter  10 value 94.060790
iter  20 value 94.019448
iter  30 value 92.688553
iter  40 value 85.775723
iter  50 value 85.192307
iter  60 value 84.186950
iter  70 value 84.186633
iter  80 value 84.186452
iter  90 value 83.413035
iter 100 value 83.383856
final  value 83.383856 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.015999 
iter  10 value 94.060812
iter  20 value 94.009832
final  value 93.836272 
converged
Fitting Repeat 1 

# weights:  305
initial  value 142.742679 
iter  10 value 117.720057
iter  20 value 117.199264
iter  30 value 117.009899
iter  40 value 117.007792
iter  50 value 111.332887
iter  60 value 105.779927
iter  70 value 104.490740
iter  80 value 103.007159
iter  90 value 101.555294
iter 100 value 101.117740
final  value 101.117740 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 156.619450 
iter  10 value 117.895762
iter  20 value 117.890984
iter  30 value 111.409913
iter  40 value 105.802165
iter  50 value 105.406049
iter  60 value 105.249920
iter  70 value 104.417764
final  value 104.417761 
converged
Fitting Repeat 3 

# weights:  305
initial  value 118.317194 
iter  10 value 117.574688
iter  20 value 117.573208
iter  30 value 116.955742
iter  40 value 114.212456
iter  50 value 109.171178
iter  60 value 108.498318
iter  70 value 106.311409
iter  80 value 106.297798
iter  90 value 106.293951
iter 100 value 106.290404
final  value 106.290404 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 118.482964 
iter  10 value 117.871032
iter  20 value 117.695298
iter  30 value 109.708637
iter  40 value 106.778825
final  value 106.778717 
converged
Fitting Repeat 5 

# weights:  305
initial  value 119.026623 
iter  10 value 117.562270
iter  20 value 117.263904
iter  30 value 115.541738
iter  40 value 115.537673
iter  50 value 107.636015
final  value 106.943938 
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 Aug 16 01:45:53 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 
  48.32    2.31   50.01