##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.21-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.21-bioc/R/site-library --timings HPiP_1.13.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2024-10-21 r87258)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 13.2.0-23ubuntu4) 13.2.0
    GNU Fortran (Ubuntu 13.2.0-23ubuntu4) 13.2.0
* running under: Ubuntu 24.04.1 LTS
* using session charset: UTF-8
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.13.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
    29 | then the Kronecker product is the code{(pm × qn)} block matrix
       |                                       ^
* checking Rd metadata ... OK
* checking Rd cross-references ... INFO
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       35.186  0.431  35.617
FSmethod      33.632  0.401  34.034
corr_plot     33.272  0.513  33.794
pred_ensembel 12.625  0.227  11.604
enrichfindP    0.478  0.027   8.803
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE

Status: 2 NOTEs
See
  ‘/home/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.21-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.21-bioc/R/site-library’
* installing *source* package ‘HPiP’ ...
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R Under development (unstable) (2024-10-21 r87258) -- "Unsuffered Consequences"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> BiocGenerics:::testPackage('HPiP')
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
avNNet
Loading required package: ggplot2
Loading required package: lattice
Fitting Repeat 1 

# weights:  103
initial  value 101.039855 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 104.405487 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.367215 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.741547 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.547670 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.073336 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.676185 
iter  10 value 93.782087
iter  20 value 93.118336
iter  30 value 93.100579
iter  40 value 93.100530
final  value 93.100528 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.006489 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.719889 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.675518 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 110.510436 
iter  10 value 93.331343
iter  20 value 92.272572
iter  30 value 91.812808
iter  40 value 91.787120
final  value 91.786990 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.396326 
final  value 93.356643 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.919049 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.508127 
iter  10 value 93.836110
final  value 93.836066 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.246973 
iter  10 value 93.418684
iter  20 value 93.410445
final  value 93.410437 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.191993 
iter  10 value 94.053831
iter  20 value 92.476551
iter  30 value 89.157734
iter  40 value 88.279696
iter  50 value 86.047465
iter  60 value 85.533211
iter  70 value 84.562756
iter  80 value 84.395417
iter  90 value 84.385839
iter 100 value 84.374119
final  value 84.374119 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.648154 
iter  10 value 93.830577
iter  20 value 85.461815
iter  30 value 85.149200
iter  40 value 82.907623
iter  50 value 82.790442
iter  60 value 82.496405
iter  70 value 81.875731
iter  80 value 81.798855
iter  90 value 81.578934
iter 100 value 81.186922
final  value 81.186922 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.474670 
iter  10 value 94.056955
iter  20 value 94.056505
iter  30 value 94.054910
iter  40 value 93.689637
iter  50 value 93.506884
iter  60 value 93.266067
iter  70 value 89.052970
iter  80 value 88.832170
iter  90 value 87.237128
iter 100 value 85.174163
final  value 85.174163 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 102.957185 
iter  10 value 94.061071
iter  20 value 94.055066
iter  30 value 93.877616
iter  40 value 93.501714
iter  50 value 93.275780
iter  60 value 91.758080
iter  70 value 83.728847
iter  80 value 82.710082
iter  90 value 82.298071
iter 100 value 82.145601
final  value 82.145601 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 101.810136 
iter  10 value 93.700583
iter  20 value 93.533304
iter  30 value 93.216510
iter  40 value 91.410430
iter  50 value 88.679714
iter  60 value 82.736308
iter  70 value 81.736721
iter  80 value 81.352701
iter  90 value 81.020496
iter 100 value 80.993811
final  value 80.993811 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 113.861761 
iter  10 value 94.053387
iter  20 value 89.239007
iter  30 value 84.839329
iter  40 value 82.119796
iter  50 value 80.968426
iter  60 value 80.388244
iter  70 value 80.241831
iter  80 value 80.042137
iter  90 value 79.898248
iter 100 value 79.819133
final  value 79.819133 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.349023 
iter  10 value 93.926192
iter  20 value 86.836619
iter  30 value 86.133791
iter  40 value 84.573888
iter  50 value 83.939269
iter  60 value 83.624255
iter  70 value 83.422001
iter  80 value 82.186295
iter  90 value 80.044301
iter 100 value 79.665379
final  value 79.665379 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 108.450168 
iter  10 value 92.985514
iter  20 value 91.140776
iter  30 value 86.234679
iter  40 value 84.400355
iter  50 value 83.799121
iter  60 value 82.749908
iter  70 value 81.562668
iter  80 value 81.397688
iter  90 value 81.236948
iter 100 value 81.201748
final  value 81.201748 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.284722 
iter  10 value 94.195389
iter  20 value 89.473123
iter  30 value 85.347630
iter  40 value 85.037329
iter  50 value 84.718401
iter  60 value 84.407270
iter  70 value 83.887217
iter  80 value 83.275863
iter  90 value 81.882563
iter 100 value 81.638804
final  value 81.638804 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 110.693781 
iter  10 value 94.178053
iter  20 value 87.929727
iter  30 value 84.157746
iter  40 value 83.015466
iter  50 value 82.505395
iter  60 value 82.213598
iter  70 value 81.475897
iter  80 value 81.020888
iter  90 value 80.832651
iter 100 value 80.543896
final  value 80.543896 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.612055 
iter  10 value 93.719966
iter  20 value 89.237679
iter  30 value 83.908188
iter  40 value 83.173212
iter  50 value 82.310890
iter  60 value 82.217260
iter  70 value 81.652837
iter  80 value 81.530956
iter  90 value 81.437088
iter 100 value 81.359410
final  value 81.359410 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.435923 
iter  10 value 93.973115
iter  20 value 86.909599
iter  30 value 82.857043
iter  40 value 81.771079
iter  50 value 80.764300
iter  60 value 80.562369
iter  70 value 80.449819
iter  80 value 79.814776
iter  90 value 79.756447
iter 100 value 79.548174
final  value 79.548174 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 105.123730 
iter  10 value 92.452979
iter  20 value 88.383720
iter  30 value 85.647880
iter  40 value 85.257929
iter  50 value 84.861121
iter  60 value 84.084894
iter  70 value 81.376645
iter  80 value 80.321979
iter  90 value 80.117626
iter 100 value 79.690262
final  value 79.690262 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.868293 
iter  10 value 94.015200
iter  20 value 93.394916
iter  30 value 91.467276
iter  40 value 86.101990
iter  50 value 82.587397
iter  60 value 82.031342
iter  70 value 81.108223
iter  80 value 80.665992
iter  90 value 80.383171
iter 100 value 80.068490
final  value 80.068490 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 116.523043 
iter  10 value 94.182517
iter  20 value 93.502166
iter  30 value 93.338611
iter  40 value 87.129443
iter  50 value 83.048324
iter  60 value 82.177983
iter  70 value 80.647860
iter  80 value 80.220935
iter  90 value 79.976670
iter 100 value 79.882804
final  value 79.882804 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.047030 
iter  10 value 93.584425
iter  20 value 93.583598
iter  30 value 93.546787
iter  40 value 85.677790
iter  50 value 85.644300
iter  60 value 85.631763
iter  70 value 85.631707
iter  80 value 85.631601
iter  90 value 85.622265
iter 100 value 84.735570
final  value 84.735570 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 95.171072 
final  value 94.054721 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.119790 
final  value 94.054442 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.835064 
final  value 94.054484 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.873625 
iter  10 value 94.054593
iter  20 value 94.052966
final  value 94.052917 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.653719 
iter  10 value 94.057912
iter  20 value 94.052338
iter  30 value 93.603103
final  value 93.583359 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.938597 
iter  10 value 94.057054
iter  20 value 93.864617
iter  30 value 88.100521
iter  40 value 88.069533
iter  50 value 88.069319
iter  60 value 87.738446
iter  70 value 87.056877
iter  80 value 86.444258
iter  90 value 86.443857
iter 100 value 86.298254
final  value 86.298254 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.540398 
iter  10 value 93.899301
iter  20 value 93.539966
iter  30 value 93.269065
iter  40 value 84.007768
iter  50 value 82.151131
iter  60 value 81.398524
iter  70 value 81.079707
iter  80 value 81.072892
iter  90 value 81.071516
final  value 81.071511 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.632221 
iter  10 value 94.057589
iter  20 value 92.289964
iter  30 value 88.070655
iter  40 value 86.750177
iter  50 value 86.746370
iter  60 value 86.745637
iter  70 value 86.442940
iter  80 value 86.442312
final  value 86.442263 
converged
Fitting Repeat 5 

# weights:  305
initial  value 113.463462 
iter  10 value 94.057727
iter  20 value 93.690847
final  value 93.582586 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.514632 
iter  10 value 94.060181
iter  20 value 94.047976
iter  30 value 93.305114
final  value 93.279755 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.946593 
iter  10 value 93.591810
iter  20 value 93.585975
iter  30 value 93.584241
iter  40 value 93.582765
iter  50 value 92.569651
iter  60 value 87.806748
iter  70 value 87.543574
iter  80 value 87.258686
final  value 87.197936 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.214679 
iter  10 value 93.784400
iter  20 value 87.570511
iter  30 value 87.346566
iter  40 value 84.256904
iter  50 value 84.254180
iter  60 value 84.250823
iter  70 value 84.246360
iter  80 value 84.133746
iter  90 value 83.578770
iter 100 value 83.407550
final  value 83.407550 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.413407 
iter  10 value 93.688080
iter  20 value 93.590601
iter  30 value 93.346455
iter  40 value 87.640197
iter  50 value 85.152412
iter  60 value 84.949593
iter  70 value 84.874571
iter  80 value 84.873120
final  value 84.873096 
converged
Fitting Repeat 5 

# weights:  507
initial  value 117.195923 
iter  10 value 94.059066
iter  20 value 91.931436
iter  30 value 90.227531
iter  40 value 89.856686
iter  50 value 87.736385
iter  60 value 87.233534
final  value 87.116862 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.921998 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.384813 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.086336 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.525241 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.614434 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.209566 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.605076 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.267604 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.067816 
iter  10 value 93.398192
iter  20 value 89.280060
final  value 89.279552 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.733095 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.778420 
final  value 94.467391 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.971270 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 120.074764 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 112.477152 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.252849 
iter  10 value 93.735455
iter  20 value 92.896583
iter  30 value 92.896188
iter  30 value 92.896188
iter  30 value 92.896188
final  value 92.896188 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.922562 
iter  10 value 94.278718
iter  20 value 87.560197
iter  30 value 85.776521
iter  40 value 85.619606
iter  50 value 85.406184
iter  60 value 85.324886
final  value 85.309087 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.916653 
iter  10 value 94.488394
iter  20 value 94.475692
iter  30 value 94.392385
iter  40 value 90.791405
iter  50 value 89.970064
iter  60 value 88.172678
iter  70 value 86.567851
iter  80 value 83.889907
iter  90 value 83.513677
iter 100 value 83.512432
final  value 83.512432 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 102.623362 
iter  10 value 94.488708
iter  20 value 94.368598
iter  30 value 92.569903
iter  40 value 90.745003
iter  50 value 89.074513
iter  60 value 87.245873
iter  70 value 86.265172
iter  80 value 85.832381
iter  90 value 85.723168
final  value 85.722883 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.157706 
iter  10 value 94.486187
iter  20 value 92.962615
iter  30 value 89.797189
iter  40 value 88.825572
iter  50 value 87.126831
iter  60 value 86.517769
iter  70 value 85.902954
iter  80 value 84.443450
iter  90 value 84.194935
final  value 84.192681 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.473303 
iter  10 value 94.488496
iter  20 value 94.178872
iter  30 value 89.694737
iter  40 value 87.604984
iter  50 value 86.845663
iter  60 value 86.459536
final  value 86.457946 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.218533 
iter  10 value 94.528549
iter  20 value 94.496850
iter  30 value 94.485754
iter  40 value 90.028548
iter  50 value 87.552809
iter  60 value 86.106845
iter  70 value 85.662697
iter  80 value 85.467358
iter  90 value 85.182769
iter 100 value 84.981468
final  value 84.981468 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.213303 
iter  10 value 94.913425
iter  20 value 94.547908
iter  30 value 87.625812
iter  40 value 86.680517
iter  50 value 85.784523
iter  60 value 85.560842
iter  70 value 85.456203
iter  80 value 84.836865
iter  90 value 84.699986
iter 100 value 84.472718
final  value 84.472718 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 116.912926 
iter  10 value 94.835125
iter  20 value 90.582082
iter  30 value 88.151541
iter  40 value 87.455396
iter  50 value 86.746183
iter  60 value 86.129886
iter  70 value 85.946050
iter  80 value 85.907578
iter  90 value 85.388761
iter 100 value 84.270841
final  value 84.270841 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 114.236566 
iter  10 value 94.717613
iter  20 value 94.121812
iter  30 value 92.573764
iter  40 value 89.862902
iter  50 value 88.499966
iter  60 value 88.155747
iter  70 value 87.950061
iter  80 value 87.583570
iter  90 value 86.825324
iter 100 value 84.809584
final  value 84.809584 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.383469 
iter  10 value 94.634388
iter  20 value 94.487438
iter  30 value 87.864066
iter  40 value 86.261790
iter  50 value 85.784635
iter  60 value 85.400513
iter  70 value 84.443354
iter  80 value 83.763536
iter  90 value 83.050313
iter 100 value 82.105234
final  value 82.105234 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 115.142010 
iter  10 value 94.566982
iter  20 value 89.832090
iter  30 value 88.846329
iter  40 value 88.087586
iter  50 value 85.350348
iter  60 value 83.520309
iter  70 value 83.016437
iter  80 value 82.360592
iter  90 value 81.855326
iter 100 value 81.611871
final  value 81.611871 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 124.515144 
iter  10 value 99.173319
iter  20 value 95.983731
iter  30 value 87.817971
iter  40 value 85.950281
iter  50 value 84.460661
iter  60 value 83.225063
iter  70 value 82.397338
iter  80 value 82.155194
iter  90 value 82.030783
iter 100 value 81.885148
final  value 81.885148 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.725054 
iter  10 value 94.501677
iter  20 value 93.752254
iter  30 value 87.777067
iter  40 value 86.961359
iter  50 value 86.224940
iter  60 value 85.982997
iter  70 value 84.292884
iter  80 value 82.483748
iter  90 value 82.130432
iter 100 value 81.885356
final  value 81.885356 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 126.892831 
iter  10 value 94.459951
iter  20 value 88.039352
iter  30 value 87.491211
iter  40 value 87.065656
iter  50 value 85.110042
iter  60 value 83.176169
iter  70 value 82.398483
iter  80 value 82.103659
iter  90 value 81.989386
iter 100 value 81.891470
final  value 81.891470 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 121.017334 
iter  10 value 95.049214
iter  20 value 92.729676
iter  30 value 87.451703
iter  40 value 84.124592
iter  50 value 82.090042
iter  60 value 81.723552
iter  70 value 81.636222
iter  80 value 81.564716
iter  90 value 81.528051
iter 100 value 81.398983
final  value 81.398983 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.081811 
final  value 94.485904 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.070225 
iter  10 value 94.468991
iter  20 value 94.443926
iter  30 value 87.358707
iter  40 value 86.926188
iter  50 value 86.925261
iter  60 value 86.924339
iter  70 value 86.810923
iter  80 value 86.736174
iter  80 value 86.736174
iter  80 value 86.736174
final  value 86.736174 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.457944 
final  value 94.485437 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.113005 
final  value 94.485617 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.514564 
iter  10 value 93.473531
iter  20 value 92.955457
iter  30 value 92.475649
final  value 92.392875 
converged
Fitting Repeat 1 

# weights:  305
initial  value 122.758612 
iter  10 value 94.488701
iter  20 value 94.441433
iter  30 value 90.002820
iter  40 value 89.829482
final  value 89.829044 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.156021 
iter  10 value 94.432803
iter  20 value 94.256420
iter  30 value 87.255530
iter  40 value 87.249457
iter  50 value 87.228100
iter  60 value 86.600602
iter  70 value 84.938302
iter  80 value 84.670516
iter  90 value 84.664884
iter 100 value 84.586801
final  value 84.586801 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 96.897160 
iter  10 value 94.105780
iter  20 value 93.115246
iter  30 value 93.113655
iter  40 value 93.113091
iter  50 value 93.111896
final  value 93.111098 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.864907 
iter  10 value 94.489119
iter  20 value 92.665052
iter  30 value 87.180843
final  value 86.699152 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.872665 
iter  10 value 94.488923
iter  20 value 94.483594
iter  30 value 93.087955
iter  40 value 84.899023
iter  50 value 83.093187
iter  60 value 82.810610
iter  70 value 82.791128
iter  80 value 82.783448
iter  90 value 82.782633
iter 100 value 82.155495
final  value 82.155495 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 95.940705 
iter  10 value 93.798751
iter  20 value 92.874597
iter  30 value 92.867307
iter  40 value 92.864154
iter  50 value 92.863075
iter  60 value 92.861438
iter  70 value 92.857189
iter  80 value 92.565599
iter  90 value 88.040971
iter 100 value 83.908473
final  value 83.908473 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.242210 
iter  10 value 94.492069
iter  20 value 86.719938
iter  30 value 86.624711
iter  40 value 86.620348
iter  50 value 86.600366
iter  60 value 86.597260
iter  70 value 86.585385
iter  80 value 85.203830
iter  90 value 85.036909
iter 100 value 84.749271
final  value 84.749271 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.358781 
iter  10 value 94.492685
iter  20 value 94.483960
iter  30 value 94.363889
iter  40 value 92.947657
iter  50 value 92.146333
iter  60 value 89.943722
iter  70 value 89.821534
iter  80 value 89.813065
iter  90 value 89.787856
iter 100 value 89.530739
final  value 89.530739 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.991959 
iter  10 value 93.112023
iter  20 value 92.796532
iter  30 value 92.792080
final  value 92.790388 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.696701 
iter  10 value 94.475421
iter  20 value 94.304571
iter  30 value 89.264613
iter  40 value 87.169208
iter  50 value 86.975204
iter  60 value 86.752218
iter  70 value 86.716198
iter  80 value 86.710833
iter  90 value 86.692230
iter 100 value 86.614417
final  value 86.614417 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.171986 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.683436 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 109.568132 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.949945 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.673834 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.132180 
iter  10 value 92.306670
iter  20 value 92.301840
iter  30 value 91.949407
iter  40 value 91.918815
iter  50 value 91.897321
iter  60 value 91.896491
iter  60 value 91.896490
iter  60 value 91.896490
final  value 91.896490 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.729500 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.243500 
final  value 93.701657 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.578768 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.276104 
iter  10 value 93.487546
final  value 93.459227 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.509536 
final  value 93.701657 
converged
Fitting Repeat 2 

# weights:  507
initial  value 110.337496 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.682251 
final  value 94.466821 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.595422 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  507
initial  value 110.723727 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.558747 
iter  10 value 92.891611
iter  20 value 83.621372
iter  30 value 82.261433
iter  40 value 82.027313
iter  50 value 81.954856
iter  60 value 79.912502
iter  70 value 79.440375
iter  80 value 79.329683
iter  90 value 79.306071
final  value 79.306068 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.643425 
iter  10 value 94.340848
iter  20 value 89.174872
iter  30 value 87.182394
iter  40 value 84.438426
iter  50 value 84.170871
iter  60 value 81.471740
iter  70 value 80.969332
iter  80 value 80.873212
final  value 80.867522 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.890553 
iter  10 value 94.441070
iter  20 value 87.352498
iter  30 value 86.139916
iter  40 value 85.705181
iter  50 value 85.693346
iter  60 value 85.367003
iter  70 value 82.198571
iter  80 value 80.881344
iter  90 value 80.868477
final  value 80.867522 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.809405 
iter  10 value 94.494561
iter  20 value 94.424985
iter  30 value 94.081375
iter  40 value 91.426528
iter  50 value 91.229737
iter  60 value 91.153749
iter  70 value 90.743433
iter  80 value 82.179720
iter  90 value 81.582597
iter 100 value 81.037791
final  value 81.037791 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 104.548902 
iter  10 value 94.396767
iter  20 value 92.443644
iter  30 value 90.105309
iter  40 value 90.036593
iter  50 value 89.849685
iter  60 value 89.563503
iter  70 value 89.562867
final  value 89.562841 
converged
Fitting Repeat 1 

# weights:  305
initial  value 122.520470 
iter  10 value 93.490141
iter  20 value 91.214438
iter  30 value 83.120459
iter  40 value 81.329914
iter  50 value 79.616645
iter  60 value 79.317387
iter  70 value 79.199535
iter  80 value 79.022733
iter  90 value 77.676517
iter 100 value 77.329823
final  value 77.329823 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 111.241511 
iter  10 value 87.676989
iter  20 value 84.476855
iter  30 value 82.304701
iter  40 value 82.054036
iter  50 value 80.985894
iter  60 value 80.297904
iter  70 value 80.180674
iter  80 value 80.108790
iter  90 value 79.979006
iter 100 value 79.749540
final  value 79.749540 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.571445 
iter  10 value 94.485462
iter  20 value 92.277779
iter  30 value 86.081982
iter  40 value 81.543061
iter  50 value 80.306028
iter  60 value 80.121512
iter  70 value 79.167657
iter  80 value 78.316327
iter  90 value 77.648020
iter 100 value 77.356435
final  value 77.356435 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.777746 
iter  10 value 95.213593
iter  20 value 91.904862
iter  30 value 87.811320
iter  40 value 86.910023
iter  50 value 84.116243
iter  60 value 83.943006
iter  70 value 82.639778
iter  80 value 81.283170
iter  90 value 80.627196
iter 100 value 78.888822
final  value 78.888822 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.452044 
iter  10 value 94.350552
iter  20 value 91.852722
iter  30 value 85.169009
iter  40 value 84.934194
iter  50 value 84.745275
iter  60 value 84.199558
iter  70 value 79.982646
iter  80 value 79.394750
iter  90 value 78.618851
iter 100 value 78.000713
final  value 78.000713 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 104.608166 
iter  10 value 88.985259
iter  20 value 82.553856
iter  30 value 82.062552
iter  40 value 81.507611
iter  50 value 81.406660
iter  60 value 79.473251
iter  70 value 78.869551
iter  80 value 77.382506
iter  90 value 76.828620
iter 100 value 76.674484
final  value 76.674484 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 127.719497 
iter  10 value 94.488700
iter  20 value 89.742123
iter  30 value 85.405984
iter  40 value 82.382827
iter  50 value 81.291953
iter  60 value 79.498211
iter  70 value 79.306123
iter  80 value 78.649637
iter  90 value 77.513727
iter 100 value 76.977290
final  value 76.977290 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 101.854470 
iter  10 value 88.643503
iter  20 value 82.738425
iter  30 value 81.912432
iter  40 value 79.785841
iter  50 value 78.290476
iter  60 value 78.178014
iter  70 value 77.931303
iter  80 value 77.380662
iter  90 value 77.026162
iter 100 value 76.709331
final  value 76.709331 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 105.139327 
iter  10 value 95.762647
iter  20 value 86.655743
iter  30 value 83.692150
iter  40 value 81.360117
iter  50 value 78.611304
iter  60 value 77.255545
iter  70 value 76.976035
iter  80 value 76.953398
iter  90 value 76.944140
iter 100 value 76.926540
final  value 76.926540 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 136.312876 
iter  10 value 97.983831
iter  20 value 94.664013
iter  30 value 88.978018
iter  40 value 85.917192
iter  50 value 85.390111
iter  60 value 84.892619
iter  70 value 79.764588
iter  80 value 78.095184
iter  90 value 77.608699
iter 100 value 77.138777
final  value 77.138777 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 117.572586 
final  value 94.485684 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.563337 
final  value 94.485586 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.471787 
final  value 94.486296 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.512683 
iter  10 value 94.485720
iter  20 value 94.483630
iter  30 value 84.642920
iter  40 value 83.562937
iter  40 value 83.562937
iter  40 value 83.562937
final  value 83.562937 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.810274 
iter  10 value 88.687119
iter  20 value 88.676767
iter  20 value 88.676767
final  value 88.676767 
converged
Fitting Repeat 1 

# weights:  305
initial  value 109.781405 
iter  10 value 85.000298
iter  20 value 84.978504
iter  30 value 82.197233
iter  40 value 81.936317
iter  50 value 81.933656
iter  60 value 81.277792
final  value 81.264567 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.626902 
iter  10 value 94.492248
iter  20 value 94.480626
iter  30 value 87.493354
iter  40 value 83.791062
iter  50 value 83.568077
iter  60 value 83.564851
iter  70 value 83.530152
iter  80 value 82.121331
iter  90 value 81.923096
iter 100 value 81.921074
final  value 81.921074 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 95.978700 
iter  10 value 94.471572
iter  20 value 94.456185
final  value 93.702861 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.328695 
iter  10 value 94.488878
iter  20 value 94.484338
iter  30 value 94.063011
iter  40 value 89.659048
iter  50 value 89.555403
final  value 89.554429 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.803847 
iter  10 value 94.489186
iter  20 value 94.479296
final  value 94.467067 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.870595 
iter  10 value 94.320318
iter  20 value 94.221558
iter  30 value 94.219337
iter  40 value 94.162386
iter  50 value 94.161883
iter  60 value 94.159814
final  value 94.157337 
converged
Fitting Repeat 2 

# weights:  507
initial  value 106.860687 
iter  10 value 94.320178
iter  20 value 91.289950
iter  30 value 81.464599
iter  40 value 81.441071
iter  50 value 77.862034
iter  60 value 77.479716
iter  70 value 77.479141
iter  80 value 77.478823
iter  90 value 77.478660
final  value 77.478591 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.795678 
iter  10 value 94.492033
iter  20 value 94.365425
iter  30 value 82.997844
iter  40 value 80.668335
iter  50 value 80.332020
iter  60 value 79.767979
iter  70 value 79.703993
iter  80 value 79.617188
iter  90 value 79.583717
iter 100 value 79.582319
final  value 79.582319 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.880545 
iter  10 value 94.277756
iter  20 value 92.403371
iter  30 value 92.169135
iter  40 value 92.158887
iter  50 value 92.158612
iter  60 value 92.157750
iter  70 value 89.868048
iter  80 value 88.827387
iter  90 value 88.807163
final  value 88.805889 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.705069 
iter  10 value 93.359031
iter  20 value 93.271798
iter  30 value 93.054483
iter  40 value 93.052231
iter  40 value 93.052230
final  value 93.052230 
converged
Fitting Repeat 1 

# weights:  103
initial  value 94.538378 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 113.939178 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.134455 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.331940 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.794927 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.158374 
iter  10 value 92.173831
final  value 92.043182 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.094375 
iter  10 value 93.289481
iter  20 value 93.088853
final  value 93.087180 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.082976 
final  value 94.052909 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.746086 
iter  10 value 92.701658
iter  10 value 92.701658
iter  10 value 92.701658
final  value 92.701658 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.511618 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.092342 
iter  10 value 93.328303
final  value 93.328261 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.117421 
final  value 93.332522 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.527863 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 111.586007 
iter  10 value 93.328379
final  value 93.328261 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.228118 
final  value 94.052911 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.966578 
iter  10 value 94.027521
iter  20 value 93.553360
iter  30 value 91.302614
iter  40 value 86.525889
iter  50 value 84.431150
iter  60 value 82.945406
iter  70 value 82.852618
iter  80 value 82.326286
iter  90 value 81.675174
iter 100 value 81.523607
final  value 81.523607 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.857757 
iter  10 value 94.055059
iter  20 value 93.793815
iter  30 value 93.103585
iter  40 value 89.368631
iter  50 value 88.776666
iter  60 value 88.715190
iter  70 value 86.460970
iter  80 value 82.511541
iter  90 value 82.098840
iter 100 value 81.587202
final  value 81.587202 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.627688 
iter  10 value 93.858102
iter  20 value 85.282371
iter  30 value 84.825310
iter  40 value 83.253165
iter  50 value 82.970777
iter  60 value 82.944700
iter  70 value 82.904538
iter  80 value 82.871170
iter  90 value 82.851597
iter  90 value 82.851597
iter  90 value 82.851597
final  value 82.851597 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.844875 
iter  10 value 94.123819
iter  20 value 87.416069
iter  30 value 85.152080
iter  40 value 83.942363
iter  50 value 81.907114
iter  60 value 81.681441
iter  70 value 81.492508
final  value 81.492161 
converged
Fitting Repeat 5 

# weights:  103
initial  value 106.702802 
iter  10 value 93.448478
iter  20 value 91.291817
iter  30 value 88.223616
iter  40 value 83.466754
iter  50 value 83.110697
iter  60 value 82.714309
iter  70 value 82.518118
iter  80 value 82.485168
iter  90 value 82.462708
final  value 82.453624 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.784751 
iter  10 value 94.001293
iter  20 value 87.666346
iter  30 value 85.286022
iter  40 value 84.855784
iter  50 value 84.473656
iter  60 value 82.161351
iter  70 value 81.851897
iter  80 value 81.751795
iter  90 value 81.460168
iter 100 value 80.939665
final  value 80.939665 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.707411 
iter  10 value 94.120638
iter  20 value 91.353124
iter  30 value 86.190568
iter  40 value 83.865374
iter  50 value 83.467133
iter  60 value 82.439664
iter  70 value 81.714034
iter  80 value 81.269519
iter  90 value 80.593345
iter 100 value 80.319987
final  value 80.319987 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.321118 
iter  10 value 93.129535
iter  20 value 85.637353
iter  30 value 83.517748
iter  40 value 82.614833
iter  50 value 82.375757
iter  60 value 81.121906
iter  70 value 80.620020
iter  80 value 80.416822
iter  90 value 80.331751
iter 100 value 80.264507
final  value 80.264507 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.842205 
iter  10 value 89.398881
iter  20 value 85.831260
iter  30 value 84.308395
iter  40 value 82.588822
iter  50 value 82.033823
iter  60 value 81.942479
iter  70 value 81.898994
iter  80 value 81.329747
iter  90 value 80.397326
iter 100 value 80.260141
final  value 80.260141 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.732379 
iter  10 value 94.004536
iter  20 value 85.614335
iter  30 value 83.305780
iter  40 value 83.097222
iter  50 value 82.650437
iter  60 value 82.622085
iter  70 value 82.404079
iter  80 value 81.650170
iter  90 value 80.877787
iter 100 value 80.499933
final  value 80.499933 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.402261 
iter  10 value 96.011801
iter  20 value 93.826053
iter  30 value 93.127831
iter  40 value 91.738497
iter  50 value 83.489533
iter  60 value 83.319175
iter  70 value 82.584302
iter  80 value 82.348667
iter  90 value 81.769794
iter 100 value 81.015267
final  value 81.015267 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 115.365838 
iter  10 value 94.081360
iter  20 value 93.313791
iter  30 value 91.097942
iter  40 value 87.513243
iter  50 value 85.792545
iter  60 value 83.736533
iter  70 value 81.437830
iter  80 value 81.132333
iter  90 value 80.715710
iter 100 value 80.386940
final  value 80.386940 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 125.716508 
iter  10 value 93.712181
iter  20 value 88.400951
iter  30 value 87.747317
iter  40 value 85.450960
iter  50 value 83.654009
iter  60 value 82.223064
iter  70 value 81.632716
iter  80 value 81.104664
iter  90 value 80.584426
iter 100 value 80.523803
final  value 80.523803 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 121.260040 
iter  10 value 94.393336
iter  20 value 87.523633
iter  30 value 84.755280
iter  40 value 82.938061
iter  50 value 82.676344
iter  60 value 82.630827
iter  60 value 82.630826
iter  70 value 81.530481
iter  80 value 80.819401
iter  90 value 80.659731
iter 100 value 80.597762
final  value 80.597762 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 138.670426 
iter  10 value 94.076228
iter  20 value 90.052775
iter  30 value 85.240316
iter  40 value 84.047606
iter  50 value 83.189847
iter  60 value 82.974799
iter  70 value 82.766356
iter  80 value 81.666592
iter  90 value 81.149462
iter 100 value 80.905468
final  value 80.905468 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.344678 
iter  10 value 94.054427
iter  20 value 94.031151
iter  30 value 92.704574
final  value 92.702597 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.189217 
final  value 94.054588 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.417540 
iter  10 value 94.054493
iter  20 value 93.706511
iter  30 value 93.226294
final  value 93.226291 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.841230 
final  value 94.054771 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.967134 
final  value 94.054701 
converged
Fitting Repeat 1 

# weights:  305
initial  value 121.731515 
iter  10 value 94.057609
iter  20 value 94.036668
iter  30 value 84.407682
iter  40 value 84.224039
iter  50 value 83.805974
iter  60 value 83.783222
iter  70 value 83.606107
iter  80 value 83.363242
iter  90 value 83.362625
iter 100 value 83.319671
final  value 83.319671 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.947046 
iter  10 value 94.058226
iter  20 value 93.980063
final  value 93.329195 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.324970 
iter  10 value 94.057981
iter  20 value 94.049818
iter  30 value 93.334006
iter  40 value 93.305814
iter  50 value 89.244629
iter  60 value 89.167350
iter  70 value 89.166834
iter  80 value 88.495111
iter  90 value 88.092393
final  value 88.092390 
converged
Fitting Repeat 4 

# weights:  305
initial  value 95.718041 
iter  10 value 93.334141
iter  20 value 93.330446
final  value 93.328839 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.255721 
iter  10 value 93.333325
iter  20 value 93.281969
iter  30 value 93.062331
iter  40 value 85.942599
iter  50 value 81.989713
iter  60 value 81.984286
iter  70 value 81.816832
iter  80 value 81.782840
iter  90 value 81.775686
iter 100 value 81.775341
final  value 81.775341 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 96.378474 
iter  10 value 94.060092
iter  20 value 85.714571
iter  30 value 84.127653
iter  40 value 83.967553
iter  50 value 81.374887
iter  60 value 80.871331
iter  70 value 80.129389
iter  80 value 79.472177
iter  90 value 78.771518
iter 100 value 78.578961
final  value 78.578961 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 109.535711 
iter  10 value 94.060320
iter  20 value 94.021099
iter  30 value 92.305787
iter  40 value 92.301777
iter  50 value 92.301411
iter  60 value 92.296816
iter  70 value 91.712304
iter  70 value 91.712304
iter  70 value 91.712304
final  value 91.712304 
converged
Fitting Repeat 3 

# weights:  507
initial  value 128.359102 
iter  10 value 93.337205
iter  20 value 93.333144
iter  30 value 93.328780
iter  40 value 91.724337
iter  50 value 87.099455
iter  60 value 84.392157
iter  70 value 83.666917
iter  80 value 83.627151
iter  90 value 83.624030
iter 100 value 83.598740
final  value 83.598740 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 96.586963 
iter  10 value 93.954132
iter  20 value 93.234042
iter  30 value 93.172435
iter  40 value 93.161014
final  value 93.159499 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.752217 
iter  10 value 93.125727
iter  20 value 93.118642
iter  30 value 93.111588
iter  40 value 93.053986
iter  50 value 86.048064
iter  60 value 81.456351
iter  70 value 79.644614
iter  80 value 79.368087
iter  90 value 79.219389
iter 100 value 79.211836
final  value 79.211836 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.046020 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.973025 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.914361 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.482383 
iter  10 value 92.687135
iter  20 value 92.683717
final  value 92.683636 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.511633 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.839547 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 116.591459 
iter  10 value 94.155895
final  value 94.090583 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.895552 
final  value 94.288571 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.749582 
final  value 94.484210 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.323668 
final  value 94.252920 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.470644 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.641391 
iter  10 value 88.991998
iter  20 value 87.601262
iter  30 value 86.846250
iter  40 value 86.836186
final  value 86.835714 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.006825 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.139527 
iter  10 value 93.556545
iter  20 value 85.776421
iter  30 value 84.781299
iter  40 value 84.587587
iter  50 value 84.069153
iter  60 value 82.749590
iter  70 value 82.736927
final  value 82.736766 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.330769 
iter  10 value 88.557226
iter  20 value 85.002948
iter  30 value 84.781060
final  value 84.768209 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.502835 
iter  10 value 94.472713
iter  20 value 93.914991
iter  30 value 93.886097
iter  40 value 91.854782
iter  50 value 84.123937
iter  60 value 83.214027
iter  70 value 82.995596
iter  80 value 82.191864
iter  90 value 82.094031
final  value 82.093673 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.517438 
iter  10 value 94.429057
iter  20 value 94.312196
iter  30 value 93.938323
iter  40 value 89.236102
iter  50 value 87.901135
iter  60 value 87.892664
iter  70 value 87.766124
iter  80 value 85.427093
iter  90 value 85.100167
final  value 85.097820 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.373275 
iter  10 value 93.866694
iter  20 value 90.386845
iter  30 value 89.920542
iter  40 value 88.965950
iter  50 value 88.935811
iter  60 value 88.921824
iter  70 value 88.737420
iter  80 value 86.413575
iter  90 value 83.924981
iter 100 value 83.425418
final  value 83.425418 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 96.584701 
iter  10 value 94.493431
iter  20 value 93.311048
iter  30 value 93.047231
iter  40 value 91.819009
iter  50 value 91.427030
iter  60 value 90.884082
iter  70 value 90.762498
iter  80 value 90.717131
final  value 90.714345 
converged
Fitting Repeat 5 

# weights:  103
initial  value 108.828931 
iter  10 value 94.419921
iter  20 value 87.718082
iter  30 value 86.689496
iter  40 value 85.541896
iter  50 value 85.039445
iter  60 value 85.028124
final  value 85.028094 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.250922 
iter  10 value 94.618215
iter  20 value 94.478785
iter  30 value 87.110448
iter  40 value 86.928032
iter  50 value 85.713988
iter  60 value 85.366395
iter  70 value 84.520785
iter  80 value 84.184497
iter  90 value 83.342236
iter 100 value 82.803109
final  value 82.803109 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 103.795695 
iter  10 value 94.491961
iter  20 value 94.416913
iter  30 value 89.663229
iter  40 value 85.776272
iter  50 value 85.099363
iter  60 value 82.467458
iter  70 value 81.887161
iter  80 value 81.506861
iter  90 value 81.428554
iter 100 value 80.987484
final  value 80.987484 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 109.852474 
iter  10 value 94.457081
iter  20 value 93.250328
iter  30 value 89.891723
iter  40 value 88.207304
iter  50 value 84.752015
iter  60 value 82.595721
iter  70 value 81.896829
iter  80 value 81.476370
iter  90 value 81.336188
iter 100 value 81.299319
final  value 81.299319 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.812844 
iter  10 value 94.225202
iter  20 value 91.200609
iter  30 value 89.693059
iter  40 value 85.659175
iter  50 value 84.020923
iter  60 value 82.995100
iter  70 value 82.516640
iter  80 value 82.011099
iter  90 value 81.406985
iter 100 value 81.206002
final  value 81.206002 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.017132 
iter  10 value 94.502270
iter  20 value 93.924855
iter  30 value 88.698340
iter  40 value 85.242986
iter  50 value 84.548675
iter  60 value 82.890943
iter  70 value 82.628195
iter  80 value 82.295268
iter  90 value 82.000305
iter 100 value 81.938705
final  value 81.938705 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.622121 
iter  10 value 95.155624
iter  20 value 94.413975
iter  30 value 92.293820
iter  40 value 91.989527
iter  50 value 91.126729
iter  60 value 83.356012
iter  70 value 82.477892
iter  80 value 82.009890
iter  90 value 81.300216
iter 100 value 80.862615
final  value 80.862615 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 122.553081 
iter  10 value 94.738632
iter  20 value 94.344761
iter  30 value 91.457439
iter  40 value 87.151747
iter  50 value 85.526377
iter  60 value 84.077547
iter  70 value 83.845913
iter  80 value 82.602049
iter  90 value 82.122464
iter 100 value 81.995493
final  value 81.995493 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.455823 
iter  10 value 96.001900
iter  20 value 94.579112
iter  30 value 93.330937
iter  40 value 88.518656
iter  50 value 85.381720
iter  60 value 83.869905
iter  70 value 83.659878
iter  80 value 83.056976
iter  90 value 82.662592
iter 100 value 82.178358
final  value 82.178358 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.000943 
iter  10 value 94.633209
iter  20 value 93.998647
iter  30 value 91.276641
iter  40 value 90.010719
iter  50 value 89.413663
iter  60 value 88.863115
iter  70 value 85.663331
iter  80 value 82.817163
iter  90 value 81.942380
iter 100 value 80.926647
final  value 80.926647 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.401093 
iter  10 value 94.551759
iter  20 value 92.894004
iter  30 value 91.114691
iter  40 value 89.766737
iter  50 value 87.498947
iter  60 value 85.174048
iter  70 value 83.281609
iter  80 value 82.958325
iter  90 value 82.511308
iter 100 value 82.162666
final  value 82.162666 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.838869 
final  value 94.485735 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.961338 
final  value 94.485693 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.542172 
final  value 94.485838 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.249342 
final  value 94.485985 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.629358 
final  value 94.485747 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.970700 
iter  10 value 94.488684
iter  20 value 94.477018
iter  30 value 91.203354
iter  40 value 91.196252
iter  50 value 88.382494
iter  60 value 86.311559
iter  70 value 86.015187
iter  80 value 84.677555
iter  90 value 84.676061
iter 100 value 82.670822
final  value 82.670822 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 97.173189 
iter  10 value 94.489136
iter  20 value 94.391098
iter  30 value 93.751507
iter  40 value 93.326888
iter  50 value 89.684547
iter  60 value 88.438925
iter  70 value 88.353796
iter  80 value 88.352739
final  value 88.352669 
converged
Fitting Repeat 3 

# weights:  305
initial  value 109.847667 
iter  10 value 94.471836
iter  20 value 94.467467
final  value 94.467223 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.835255 
iter  10 value 94.488863
iter  20 value 94.481420
iter  30 value 94.288742
final  value 94.288649 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.579296 
iter  10 value 89.191232
iter  20 value 87.595265
iter  30 value 87.593455
iter  40 value 87.592304
iter  50 value 87.460302
iter  60 value 83.581840
iter  70 value 82.931661
iter  80 value 82.931316
iter  80 value 82.931316
final  value 82.931316 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.897712 
iter  10 value 93.847361
iter  20 value 93.801126
iter  30 value 93.796734
iter  40 value 92.610364
iter  50 value 92.563968
iter  60 value 92.286982
iter  70 value 84.872367
iter  80 value 84.537323
iter  90 value 84.300972
iter 100 value 84.238568
final  value 84.238568 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 95.097891 
iter  10 value 87.632547
iter  20 value 86.171443
iter  30 value 86.168141
iter  40 value 86.167021
iter  50 value 86.157109
iter  60 value 86.081526
iter  70 value 86.071741
iter  80 value 86.047919
iter  90 value 85.972689
final  value 85.971873 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.596152 
iter  10 value 94.488182
iter  20 value 94.474053
iter  30 value 94.301767
iter  40 value 90.498313
iter  50 value 88.619938
iter  60 value 85.238225
iter  70 value 83.795208
iter  80 value 83.503677
iter  90 value 83.469560
final  value 83.469113 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.882062 
iter  10 value 94.475216
iter  20 value 94.424199
iter  30 value 92.943711
iter  40 value 91.556948
iter  50 value 91.354023
final  value 91.278345 
converged
Fitting Repeat 5 

# weights:  507
initial  value 100.161281 
iter  10 value 94.474300
iter  20 value 94.374219
iter  30 value 91.646510
iter  40 value 88.813226
iter  50 value 87.620907
iter  60 value 83.565410
iter  70 value 83.413840
iter  80 value 83.175903
iter  90 value 83.120923
iter 100 value 83.099285
final  value 83.099285 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 140.080889 
iter  10 value 117.895540
iter  20 value 117.886941
iter  30 value 116.741643
iter  40 value 115.472219
iter  50 value 109.600513
iter  60 value 108.517414
iter  70 value 108.506700
iter  80 value 108.505596
iter  90 value 108.503276
iter 100 value 108.503010
final  value 108.503010 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 127.196042 
iter  10 value 117.735280
iter  20 value 111.829438
iter  30 value 110.818829
iter  40 value 108.724716
iter  50 value 108.164304
iter  60 value 108.163225
iter  70 value 107.193963
iter  80 value 104.521034
iter  90 value 103.501832
iter 100 value 102.720571
final  value 102.720571 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 121.394956 
iter  10 value 117.895170
iter  20 value 117.890711
final  value 117.890700 
converged
Fitting Repeat 4 

# weights:  305
initial  value 122.310615 
iter  10 value 117.895029
iter  20 value 117.689549
iter  30 value 116.034160
iter  40 value 114.636281
iter  50 value 114.418930
final  value 114.418902 
converged
Fitting Repeat 5 

# weights:  305
initial  value 142.834456 
iter  10 value 117.895245
iter  20 value 116.341638
iter  30 value 116.196677
iter  40 value 116.146691
final  value 116.114076 
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 Jan 13 23:00:01 2025 
*********************************************** 
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 
 39.242   1.111 132.624