##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings HPiP_1.19.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.24-bioc/meat/HPiP.Rcheck’
* using R version 4.5.0 (2025-04-11)
* using platform: aarch64-unknown-linux-gnu
* R was compiled by
    aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0
    GNU Fortran (GCC) 14.2.0
* running under: openEuler 24.03 (LTS)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.19.0’
* 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
corr_plot     34.849  0.152  35.073
var_imp       33.667  0.369  34.201
FSmethod      32.988  0.423  33.472
pred_ensembel 17.412  0.164  16.390
enrichfindP    0.530  0.032  25.077
getFASTA       0.080  0.000   6.094
* 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: 2 NOTEs
See
  ‘/home/biocbuild/bbs-3.24-bioc/meat/HPiP.Rcheck/00check.log’
for details.

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/R/R-4.5.0/site-library’
* installing *source* package ‘HPiP’ ...
** this is package ‘HPiP’ version ‘1.19.0’
** 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 4.5.0 (2025-04-11) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu

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

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

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

> BiocGenerics:::testPackage('HPiP')
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
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 102.365867 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.966816 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.839023 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.725724 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.595378 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.216342 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.130784 
iter  10 value 94.320300
iter  10 value 94.320299
iter  10 value 94.320299
final  value 94.320299 
converged
Fitting Repeat 3 

# weights:  305
initial  value 111.391227 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.867347 
iter  10 value 86.794600
iter  20 value 85.005603
iter  30 value 84.996783
final  value 84.996734 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.993471 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 125.460247 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.383841 
final  value 94.484210 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.515895 
iter  10 value 94.354396
iter  10 value 94.354396
iter  10 value 94.354396
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.913179 
iter  10 value 87.587361
iter  20 value 85.868591
final  value 85.868378 
converged
Fitting Repeat 5 

# weights:  507
initial  value 110.616812 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.939883 
iter  10 value 94.486555
iter  20 value 93.793810
iter  30 value 93.712008
iter  40 value 93.521384
iter  50 value 93.490412
final  value 93.490241 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.798955 
iter  10 value 94.493933
iter  20 value 94.444990
iter  30 value 93.782903
iter  40 value 93.684828
iter  50 value 93.516026
iter  60 value 93.490603
iter  70 value 93.490243
final  value 93.490241 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.392229 
iter  10 value 94.486697
iter  20 value 84.036625
iter  30 value 83.893851
iter  40 value 83.537063
iter  50 value 83.429866
iter  60 value 83.212588
iter  70 value 83.209227
final  value 83.209213 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.896262 
iter  10 value 87.403122
iter  20 value 84.468458
iter  30 value 82.298758
iter  40 value 79.049991
iter  50 value 79.004422
final  value 79.001521 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.036842 
iter  10 value 93.881617
iter  20 value 87.348258
iter  30 value 83.652786
iter  40 value 83.397221
iter  50 value 83.242831
iter  60 value 83.209724
final  value 83.209212 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.975520 
iter  10 value 94.422684
iter  20 value 90.952490
iter  30 value 88.565960
iter  40 value 84.151248
iter  50 value 81.398037
iter  60 value 80.149116
iter  70 value 80.040431
iter  80 value 78.818677
iter  90 value 78.298921
iter 100 value 77.892175
final  value 77.892175 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 121.098575 
iter  10 value 94.602906
iter  20 value 93.572797
iter  30 value 93.361256
iter  40 value 87.342416
iter  50 value 84.627416
iter  60 value 83.702023
iter  70 value 83.446152
iter  80 value 83.364000
iter  90 value 83.221083
iter 100 value 81.216127
final  value 81.216127 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.270058 
iter  10 value 93.514940
iter  20 value 85.021990
iter  30 value 84.199796
iter  40 value 83.812674
iter  50 value 80.928015
iter  60 value 79.306680
iter  70 value 78.567364
iter  80 value 78.382362
iter  90 value 78.321158
iter 100 value 78.239199
final  value 78.239199 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 109.166360 
iter  10 value 94.461217
iter  20 value 92.013702
iter  30 value 84.230677
iter  40 value 81.428481
iter  50 value 79.780120
iter  60 value 79.644205
iter  70 value 79.177128
iter  80 value 78.948391
iter  90 value 78.852076
iter 100 value 78.694866
final  value 78.694866 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.099522 
iter  10 value 94.504268
iter  20 value 94.396682
iter  30 value 93.854129
iter  40 value 93.760229
iter  50 value 93.680033
iter  60 value 88.550767
iter  70 value 86.799695
iter  80 value 83.550698
iter  90 value 83.157824
iter 100 value 82.284985
final  value 82.284985 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 119.508631 
iter  10 value 94.420402
iter  20 value 89.452825
iter  30 value 82.462036
iter  40 value 81.393859
iter  50 value 79.645554
iter  60 value 78.577684
iter  70 value 78.269833
iter  80 value 77.893063
iter  90 value 77.716257
iter 100 value 77.704449
final  value 77.704449 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 114.227079 
iter  10 value 94.739958
iter  20 value 94.507864
iter  30 value 88.260301
iter  40 value 86.764693
iter  50 value 83.822044
iter  60 value 81.493075
iter  70 value 80.850702
iter  80 value 80.670361
iter  90 value 79.879334
iter 100 value 79.594866
final  value 79.594866 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 131.363144 
iter  10 value 94.445727
iter  20 value 91.343821
iter  30 value 86.178229
iter  40 value 84.787068
iter  50 value 83.947405
iter  60 value 83.743306
iter  70 value 82.218413
iter  80 value 81.293019
iter  90 value 80.061578
iter 100 value 79.928981
final  value 79.928981 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.381588 
iter  10 value 94.853253
iter  20 value 94.533395
iter  30 value 90.558463
iter  40 value 88.312757
iter  50 value 86.495420
iter  60 value 84.170850
iter  70 value 80.375515
iter  80 value 79.346733
iter  90 value 78.908939
iter 100 value 78.726695
final  value 78.726695 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 113.277526 
iter  10 value 96.501204
iter  20 value 87.942882
iter  30 value 82.131990
iter  40 value 79.485666
iter  50 value 78.387034
iter  60 value 78.211221
iter  70 value 78.002109
iter  80 value 77.821455
iter  90 value 77.684798
iter 100 value 77.618468
final  value 77.618468 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.993759 
final  value 94.485859 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.054986 
final  value 94.485981 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.932754 
final  value 94.485818 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.467278 
final  value 94.485760 
converged
Fitting Repeat 5 

# weights:  103
initial  value 110.350477 
final  value 94.485818 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.817109 
iter  10 value 94.488809
iter  20 value 93.662875
iter  30 value 93.022666
iter  40 value 82.927394
iter  50 value 82.523421
iter  60 value 82.522455
iter  70 value 82.521240
iter  80 value 82.520593
iter  90 value 82.503138
iter 100 value 82.477578
final  value 82.477578 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.967227 
iter  10 value 94.489147
iter  20 value 94.460511
iter  30 value 93.823168
iter  40 value 93.449635
iter  50 value 88.207390
iter  60 value 88.196194
final  value 88.196117 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.288355 
iter  10 value 94.488842
iter  20 value 93.551893
iter  30 value 85.426367
iter  40 value 85.423888
iter  50 value 84.651869
iter  60 value 84.535021
iter  70 value 84.532772
final  value 84.532120 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.289950 
iter  10 value 94.359278
iter  20 value 94.356381
iter  30 value 94.355706
iter  40 value 93.730271
iter  50 value 93.660033
final  value 93.624150 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.795640 
iter  10 value 94.488863
iter  20 value 94.484422
iter  30 value 94.484222
final  value 94.484213 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.889854 
iter  10 value 94.333428
iter  20 value 94.221676
iter  30 value 94.217264
iter  40 value 94.205053
iter  50 value 86.990238
iter  60 value 85.827307
iter  70 value 85.494869
iter  80 value 82.536075
iter  90 value 80.925123
iter 100 value 80.910003
final  value 80.910003 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.443587 
iter  10 value 93.696751
iter  20 value 93.689272
iter  30 value 93.624015
iter  40 value 85.572152
final  value 85.512956 
converged
Fitting Repeat 3 

# weights:  507
initial  value 114.321034 
iter  10 value 94.363236
iter  20 value 94.308734
iter  30 value 93.674307
iter  40 value 93.622406
iter  50 value 83.854715
iter  60 value 82.452258
iter  70 value 82.397111
iter  80 value 82.387816
iter  90 value 82.169482
iter 100 value 81.818078
final  value 81.818078 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 98.257330 
iter  10 value 94.362469
iter  20 value 94.362300
iter  30 value 94.355621
iter  40 value 93.594950
iter  50 value 92.173296
iter  60 value 91.795836
iter  70 value 91.680905
iter  80 value 91.680427
iter  90 value 91.677097
iter 100 value 91.676414
final  value 91.676414 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 100.545290 
iter  10 value 93.817443
iter  20 value 93.602494
iter  30 value 88.549582
iter  40 value 86.082240
iter  50 value 86.065727
iter  60 value 81.469380
iter  70 value 81.178381
iter  80 value 80.070715
iter  90 value 79.879243
iter 100 value 79.868046
final  value 79.868046 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.736870 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.115505 
final  value 94.052913 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.865539 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.562940 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.261930 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.937482 
final  value 93.628453 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.058276 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.736654 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.667561 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 112.069596 
iter  10 value 93.663393
final  value 93.628453 
converged
Fitting Repeat 1 

# weights:  507
initial  value 102.652651 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 147.272045 
iter  10 value 94.008731
final  value 94.008696 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.151430 
final  value 94.008696 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.411095 
iter  10 value 93.437748
iter  20 value 85.005047
iter  30 value 84.085559
iter  40 value 84.075077
final  value 84.075055 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.060408 
iter  10 value 93.046452
iter  20 value 91.691475
iter  30 value 83.728869
iter  30 value 83.728869
iter  30 value 83.728869
final  value 83.728869 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.360129 
iter  10 value 94.056675
iter  20 value 93.646881
iter  30 value 91.831159
iter  40 value 91.408398
iter  50 value 91.135603
iter  60 value 91.094085
iter  60 value 91.094085
final  value 91.094085 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.430643 
iter  10 value 94.056793
iter  20 value 93.195897
iter  30 value 85.625823
iter  40 value 84.545685
iter  50 value 83.788242
iter  60 value 83.373551
iter  70 value 83.321453
iter  80 value 83.290359
final  value 83.290330 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.472214 
iter  10 value 90.187834
iter  20 value 86.135726
iter  30 value 85.189826
iter  40 value 84.913766
iter  50 value 84.102680
iter  60 value 83.731594
final  value 83.703851 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.765671 
iter  10 value 89.215897
iter  20 value 87.022407
iter  30 value 86.517526
iter  40 value 84.016721
iter  50 value 83.775774
iter  60 value 83.389885
iter  70 value 83.356860
iter  80 value 83.096502
iter  90 value 83.055507
final  value 83.055470 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.851922 
iter  10 value 94.056688
iter  20 value 93.320621
iter  30 value 86.808410
iter  40 value 84.519758
iter  50 value 84.208219
iter  60 value 83.797261
iter  70 value 83.709089
iter  80 value 83.491194
iter  90 value 82.905816
iter 100 value 82.894494
final  value 82.894494 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 104.809359 
iter  10 value 94.049225
iter  20 value 91.962017
iter  30 value 88.586191
iter  40 value 88.108474
iter  50 value 86.248130
iter  60 value 84.490720
iter  70 value 84.071887
iter  80 value 83.026333
iter  90 value 82.310515
iter 100 value 82.132826
final  value 82.132826 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 109.576779 
iter  10 value 94.031741
iter  20 value 87.768691
iter  30 value 83.714610
iter  40 value 83.123059
iter  50 value 82.908692
iter  60 value 81.632045
iter  70 value 80.913109
iter  80 value 80.646303
iter  90 value 80.558275
iter 100 value 80.451017
final  value 80.451017 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.519604 
iter  10 value 92.092567
iter  20 value 91.324907
iter  30 value 87.511460
iter  40 value 84.939875
iter  50 value 84.347282
iter  60 value 82.788033
iter  70 value 81.960093
iter  80 value 81.652412
iter  90 value 81.211945
iter 100 value 80.765353
final  value 80.765353 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.200525 
iter  10 value 94.481459
iter  20 value 90.905496
iter  30 value 86.769612
iter  40 value 86.242757
iter  50 value 85.103479
iter  60 value 83.950158
iter  70 value 83.842405
iter  80 value 83.288064
iter  90 value 82.374750
iter 100 value 81.122999
final  value 81.122999 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.688967 
iter  10 value 93.682072
iter  20 value 88.034538
iter  30 value 86.156752
iter  40 value 85.724464
iter  50 value 85.463751
iter  60 value 84.151811
iter  70 value 83.667138
iter  80 value 83.479051
iter  90 value 82.948177
iter 100 value 81.623539
final  value 81.623539 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 114.032977 
iter  10 value 94.232201
iter  20 value 91.081661
iter  30 value 86.971974
iter  40 value 83.883352
iter  50 value 82.748710
iter  60 value 81.460894
iter  70 value 80.857527
iter  80 value 80.585240
iter  90 value 80.561657
iter 100 value 80.497895
final  value 80.497895 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 123.868567 
iter  10 value 92.713275
iter  20 value 86.574510
iter  30 value 82.924029
iter  40 value 81.784042
iter  50 value 81.344688
iter  60 value 80.615891
iter  70 value 80.308214
iter  80 value 80.183069
iter  90 value 80.054240
iter 100 value 79.918782
final  value 79.918782 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.861138 
iter  10 value 97.950774
iter  20 value 90.151184
iter  30 value 88.335960
iter  40 value 84.330498
iter  50 value 82.938139
iter  60 value 82.507919
iter  70 value 82.439005
iter  80 value 82.265001
iter  90 value 81.916939
iter 100 value 81.813488
final  value 81.813488 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 119.157898 
iter  10 value 93.945998
iter  20 value 87.186245
iter  30 value 85.850918
iter  40 value 84.369042
iter  50 value 83.410567
iter  60 value 81.581585
iter  70 value 81.247856
iter  80 value 80.938652
iter  90 value 80.761767
iter 100 value 80.534657
final  value 80.534657 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.767125 
iter  10 value 94.787186
iter  20 value 93.743886
iter  30 value 92.511028
iter  40 value 86.713095
iter  50 value 83.546703
iter  60 value 83.045162
iter  70 value 82.769188
iter  80 value 82.306344
iter  90 value 81.829140
iter 100 value 81.368678
final  value 81.368678 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.678727 
final  value 94.054640 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.226962 
final  value 94.054626 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.877655 
final  value 94.054466 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.345079 
iter  10 value 94.010313
iter  20 value 93.812943
iter  30 value 93.811456
iter  40 value 84.511034
iter  50 value 84.295445
iter  60 value 84.218285
iter  70 value 84.160306
iter  80 value 84.160132
final  value 84.158473 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.902637 
final  value 94.054597 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.748182 
iter  10 value 94.057675
iter  20 value 94.035549
iter  30 value 85.107639
iter  40 value 85.103190
iter  50 value 84.143532
final  value 83.638305 
converged
Fitting Repeat 2 

# weights:  305
initial  value 94.308255 
iter  10 value 94.057142
iter  20 value 94.036833
iter  30 value 93.535802
iter  40 value 93.348662
iter  50 value 93.120588
iter  60 value 93.107610
iter  70 value 93.098177
final  value 93.097395 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.177423 
iter  10 value 94.057452
iter  20 value 94.053036
iter  30 value 88.838167
iter  40 value 85.068122
iter  50 value 83.872308
iter  60 value 83.773460
iter  70 value 82.271707
iter  80 value 81.490823
iter  90 value 81.490480
iter 100 value 81.486449
final  value 81.486449 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.365802 
iter  10 value 94.057995
iter  20 value 94.052961
final  value 94.052954 
converged
Fitting Repeat 5 

# weights:  305
initial  value 113.193069 
iter  10 value 94.058174
iter  20 value 93.766056
iter  30 value 91.619026
iter  40 value 89.608220
iter  50 value 89.606074
iter  60 value 89.605709
iter  70 value 89.107068
iter  80 value 88.795107
iter  90 value 85.699510
iter 100 value 85.551933
final  value 85.551933 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 101.914117 
iter  10 value 94.061301
iter  20 value 94.009469
final  value 94.009453 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.241821 
iter  10 value 93.489757
iter  20 value 93.440341
iter  30 value 93.430078
iter  40 value 93.423069
iter  50 value 89.629996
iter  60 value 87.326794
iter  70 value 86.080103
iter  80 value 82.637890
iter  90 value 81.123010
iter 100 value 81.016835
final  value 81.016835 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 100.069107 
iter  10 value 94.016345
iter  20 value 93.887508
iter  30 value 84.957347
iter  40 value 83.766918
iter  50 value 83.298126
iter  60 value 83.296695
iter  70 value 83.296111
iter  80 value 83.275460
final  value 83.275002 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.238191 
iter  10 value 93.637311
iter  20 value 93.631827
iter  30 value 93.418768
iter  40 value 93.279358
iter  40 value 93.279358
iter  50 value 84.882527
iter  60 value 84.618906
iter  70 value 84.352504
iter  80 value 84.279876
iter  90 value 84.221974
iter 100 value 84.221648
final  value 84.221648 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 100.979038 
iter  10 value 85.862157
iter  20 value 84.579035
iter  30 value 83.850638
iter  40 value 83.180142
iter  50 value 83.175063
iter  60 value 83.147940
iter  70 value 83.129443
iter  80 value 83.129286
final  value 83.129280 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.119055 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.605059 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.803030 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.510059 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.473456 
final  value 94.467391 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.472484 
iter  10 value 91.986346
iter  20 value 91.568583
iter  30 value 91.544192
final  value 91.543902 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.942732 
iter  10 value 94.402619
final  value 93.508117 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.080071 
iter  10 value 94.134454
iter  10 value 94.134454
iter  10 value 94.134454
final  value 94.134454 
converged
Fitting Repeat 4 

# weights:  305
initial  value 125.378499 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 111.682129 
iter  10 value 94.467391
iter  10 value 94.467391
iter  10 value 94.467391
final  value 94.467391 
converged
Fitting Repeat 1 

# weights:  507
initial  value 107.358414 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.070831 
final  value 94.305882 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.671583 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 114.476125 
final  value 94.467391 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.962030 
final  value 94.467391 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.899133 
iter  10 value 94.346494
iter  20 value 94.302215
iter  30 value 87.322213
iter  40 value 86.463196
iter  50 value 86.022336
iter  60 value 84.960821
iter  70 value 83.830120
iter  80 value 83.091266
iter  90 value 83.052859
iter 100 value 82.880057
final  value 82.880057 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.932518 
iter  10 value 94.441891
iter  20 value 90.788721
iter  30 value 89.489253
iter  40 value 88.697976
iter  50 value 88.169299
iter  60 value 87.925869
iter  70 value 86.874536
iter  80 value 84.855543
iter  90 value 83.324175
iter 100 value 83.151817
final  value 83.151817 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 100.819874 
iter  10 value 94.486800
iter  20 value 94.420533
iter  30 value 93.281847
iter  40 value 92.383466
iter  50 value 92.118874
iter  60 value 91.706410
iter  70 value 90.450962
iter  80 value 89.065366
iter  90 value 88.012720
iter 100 value 87.543907
final  value 87.543907 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 103.210987 
iter  10 value 94.476096
iter  20 value 94.143770
iter  30 value 94.138559
iter  40 value 90.151999
iter  50 value 88.117140
iter  60 value 87.293478
iter  70 value 86.041782
iter  80 value 85.731556
iter  90 value 85.673554
final  value 85.673175 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.440274 
iter  10 value 93.598272
iter  20 value 89.259872
iter  30 value 87.622573
iter  40 value 85.572533
iter  50 value 85.124184
iter  60 value 84.877464
iter  70 value 84.713805
iter  80 value 84.007988
iter  90 value 83.188423
iter 100 value 83.001642
final  value 83.001642 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 102.644462 
iter  10 value 94.451730
iter  20 value 90.762527
iter  30 value 88.148428
iter  40 value 87.216665
iter  50 value 86.212707
iter  60 value 86.117938
iter  70 value 84.880179
iter  80 value 84.273320
iter  90 value 83.679140
iter 100 value 83.106942
final  value 83.106942 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.980262 
iter  10 value 94.522098
iter  20 value 94.332395
iter  30 value 93.304959
iter  40 value 92.598031
iter  50 value 87.796126
iter  60 value 87.056826
iter  70 value 86.202460
iter  80 value 85.832624
iter  90 value 84.001957
iter 100 value 83.293072
final  value 83.293072 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.554737 
iter  10 value 94.498252
iter  20 value 94.246680
iter  30 value 93.273922
iter  40 value 89.619280
iter  50 value 87.210658
iter  60 value 85.174151
iter  70 value 83.477599
iter  80 value 83.221638
iter  90 value 83.115890
iter 100 value 82.435726
final  value 82.435726 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 111.210674 
iter  10 value 94.738668
iter  20 value 94.488325
iter  30 value 89.792229
iter  40 value 88.271430
iter  50 value 87.342822
iter  60 value 86.359236
iter  70 value 85.831699
iter  80 value 85.570610
iter  90 value 85.452533
iter 100 value 85.405555
final  value 85.405555 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 120.443261 
iter  10 value 94.583751
iter  20 value 87.830852
iter  30 value 87.433541
iter  40 value 87.256469
iter  50 value 85.625340
iter  60 value 83.468288
iter  70 value 82.850088
iter  80 value 82.424377
iter  90 value 82.145121
iter 100 value 82.044929
final  value 82.044929 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.632752 
iter  10 value 94.903910
iter  20 value 93.755917
iter  30 value 89.033361
iter  40 value 86.310291
iter  50 value 83.686344
iter  60 value 83.316116
iter  70 value 82.938022
iter  80 value 82.457799
iter  90 value 81.517382
iter 100 value 81.279389
final  value 81.279389 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.671495 
iter  10 value 95.186768
iter  20 value 93.326991
iter  30 value 91.350595
iter  40 value 86.919435
iter  50 value 83.437790
iter  60 value 82.710217
iter  70 value 82.556595
iter  80 value 82.022569
iter  90 value 81.719010
iter 100 value 81.472155
final  value 81.472155 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 135.058364 
iter  10 value 95.060045
iter  20 value 89.842855
iter  30 value 87.163999
iter  40 value 85.385640
iter  50 value 85.044261
iter  60 value 84.332949
iter  70 value 82.777319
iter  80 value 82.171234
iter  90 value 81.860103
iter 100 value 81.841604
final  value 81.841604 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.419661 
iter  10 value 94.880341
iter  20 value 91.832355
iter  30 value 91.572432
iter  40 value 85.598781
iter  50 value 84.758487
iter  60 value 82.569514
iter  70 value 82.146030
iter  80 value 81.812670
iter  90 value 81.581815
iter 100 value 81.475206
final  value 81.475206 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 129.112740 
iter  10 value 96.332849
iter  20 value 94.215410
iter  30 value 88.491380
iter  40 value 87.203847
iter  50 value 85.973004
iter  60 value 84.360702
iter  70 value 84.269628
iter  80 value 83.688216
iter  90 value 83.510672
iter 100 value 83.205102
final  value 83.205102 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.215533 
final  value 94.485972 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.665800 
final  value 94.485609 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.266561 
final  value 94.485788 
converged
Fitting Repeat 4 

# weights:  103
initial  value 111.414022 
final  value 94.485663 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.894264 
final  value 94.141031 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.101227 
iter  10 value 94.488801
iter  20 value 94.483255
iter  30 value 90.674749
iter  40 value 89.152558
iter  50 value 89.150278
iter  60 value 88.478239
final  value 87.964235 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.236171 
iter  10 value 94.472284
iter  20 value 94.436630
iter  30 value 92.340900
iter  40 value 86.110892
iter  50 value 85.546454
iter  60 value 85.538732
iter  70 value 85.367816
iter  80 value 85.258172
iter  90 value 85.255414
iter 100 value 85.254720
final  value 85.254720 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 98.563939 
iter  10 value 94.489231
iter  20 value 94.107556
iter  30 value 94.091009
iter  40 value 94.065650
final  value 94.065375 
converged
Fitting Repeat 4 

# weights:  305
initial  value 108.924026 
iter  10 value 94.472873
iter  20 value 94.468414
iter  30 value 94.348360
iter  40 value 94.144442
final  value 94.135440 
converged
Fitting Repeat 5 

# weights:  305
initial  value 126.974167 
iter  10 value 94.472360
iter  20 value 94.170530
iter  30 value 86.758149
iter  40 value 86.067634
iter  50 value 84.616560
iter  60 value 84.177841
iter  70 value 84.176825
iter  80 value 84.175471
iter  90 value 83.097090
iter 100 value 81.523823
final  value 81.523823 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 96.579215 
iter  10 value 94.489913
iter  20 value 94.468174
iter  30 value 94.467747
final  value 94.467585 
converged
Fitting Repeat 2 

# weights:  507
initial  value 113.701280 
iter  10 value 94.452216
iter  20 value 94.448524
iter  30 value 93.431584
iter  40 value 91.558316
iter  50 value 91.486359
iter  60 value 91.358539
iter  70 value 91.356276
iter  80 value 91.214573
iter  90 value 90.621988
iter 100 value 90.611359
final  value 90.611359 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 98.707311 
iter  10 value 94.475395
iter  20 value 94.467451
iter  30 value 94.410041
iter  40 value 91.992923
iter  50 value 88.383545
iter  60 value 84.104758
iter  70 value 82.676490
iter  80 value 82.665397
iter  90 value 82.648146
iter 100 value 82.226364
final  value 82.226364 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.999700 
iter  10 value 94.481747
iter  20 value 93.735770
iter  30 value 88.800199
iter  40 value 86.724992
iter  50 value 85.813287
iter  60 value 85.810820
iter  70 value 85.294549
iter  80 value 85.082561
iter  90 value 85.067233
iter 100 value 84.944675
final  value 84.944675 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.288166 
iter  10 value 94.278572
iter  20 value 94.036144
iter  30 value 94.030872
iter  40 value 92.850776
iter  50 value 87.205494
iter  60 value 86.031730
iter  70 value 85.949719
iter  80 value 85.948547
iter  90 value 85.865948
iter 100 value 85.318117
final  value 85.318117 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 109.594995 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.373093 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.333487 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.897316 
iter  10 value 92.590760
final  value 92.515286 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.517675 
iter  10 value 92.945358
final  value 92.945355 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.075916 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.447236 
iter  10 value 85.067568
iter  20 value 82.533752
iter  30 value 82.302473
iter  40 value 82.234685
iter  50 value 82.136865
final  value 82.108314 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.652672 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.467213 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 93.616675 
iter  10 value 87.634877
final  value 87.634077 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.497485 
final  value 92.563129 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.929433 
iter  10 value 92.945454
final  value 92.945355 
converged
Fitting Repeat 3 

# weights:  507
initial  value 112.742120 
iter  10 value 92.959555
iter  20 value 92.945415
final  value 92.945356 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.667451 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.186742 
iter  10 value 88.845802
iter  20 value 82.900117
iter  30 value 80.854873
iter  40 value 80.803177
final  value 80.799815 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.201519 
iter  10 value 93.230162
iter  20 value 91.598131
iter  30 value 87.518696
iter  40 value 87.244893
iter  50 value 86.510269
iter  60 value 83.680560
iter  70 value 82.984051
iter  80 value 82.910891
final  value 82.907582 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.702297 
iter  10 value 93.378788
iter  20 value 88.904662
iter  30 value 85.969337
iter  40 value 85.817186
iter  50 value 82.948100
iter  60 value 82.675288
iter  70 value 81.884750
iter  80 value 81.475560
final  value 81.472730 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.527978 
iter  10 value 93.964912
iter  20 value 89.722606
iter  30 value 85.420442
iter  40 value 84.438649
iter  50 value 83.351913
iter  60 value 82.944942
iter  70 value 82.907583
final  value 82.907582 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.918195 
iter  10 value 93.875202
iter  20 value 87.769948
iter  30 value 86.568259
iter  40 value 84.521428
iter  50 value 83.587870
iter  60 value 83.529999
iter  70 value 83.373927
final  value 83.369332 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.826011 
iter  10 value 93.735696
iter  20 value 92.856315
iter  30 value 92.827835
iter  40 value 91.572207
iter  50 value 85.645193
iter  60 value 85.204427
iter  70 value 84.514702
iter  80 value 81.365057
iter  90 value 81.271666
iter 100 value 81.247688
final  value 81.247688 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 101.037523 
iter  10 value 93.464161
iter  20 value 89.542719
iter  30 value 84.233736
iter  40 value 83.414494
iter  50 value 82.029596
iter  60 value 80.524693
iter  70 value 79.464136
iter  80 value 78.943152
iter  90 value 78.813929
iter 100 value 78.607947
final  value 78.607947 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.374293 
iter  10 value 94.116112
iter  20 value 93.683840
iter  30 value 92.944962
iter  40 value 88.441963
iter  50 value 85.917713
iter  60 value 85.074960
iter  70 value 81.568155
iter  80 value 80.055195
iter  90 value 79.555672
iter 100 value 79.399406
final  value 79.399406 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.661978 
iter  10 value 93.657245
iter  20 value 89.278146
iter  30 value 83.869183
iter  40 value 79.689796
iter  50 value 79.184469
iter  60 value 79.048954
iter  70 value 78.967820
iter  80 value 78.674802
iter  90 value 78.624610
iter 100 value 78.434568
final  value 78.434568 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 107.340877 
iter  10 value 93.230931
iter  20 value 88.589054
iter  30 value 85.745059
iter  40 value 84.943009
iter  50 value 81.322291
iter  60 value 80.656410
iter  70 value 79.232366
iter  80 value 78.582719
iter  90 value 78.147778
iter 100 value 77.993201
final  value 77.993201 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.517593 
iter  10 value 94.050290
iter  20 value 93.242728
iter  30 value 86.601566
iter  40 value 83.129594
iter  50 value 82.312057
iter  60 value 81.851710
iter  70 value 80.617806
iter  80 value 80.102466
iter  90 value 79.810142
iter 100 value 79.578334
final  value 79.578334 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 112.103838 
iter  10 value 94.070902
iter  20 value 85.254344
iter  30 value 83.844697
iter  40 value 81.964885
iter  50 value 80.331859
iter  60 value 79.985320
iter  70 value 79.775994
iter  80 value 79.523119
iter  90 value 79.292653
iter 100 value 79.083236
final  value 79.083236 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 132.958571 
iter  10 value 94.446540
iter  20 value 89.263993
iter  30 value 87.258766
iter  40 value 83.038934
iter  50 value 81.233932
iter  60 value 79.130608
iter  70 value 78.949980
iter  80 value 78.751254
iter  90 value 78.547775
iter 100 value 78.339194
final  value 78.339194 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 106.423942 
iter  10 value 93.120676
iter  20 value 92.166945
iter  30 value 87.691540
iter  40 value 85.330038
iter  50 value 84.410220
iter  60 value 81.320407
iter  70 value 79.824162
iter  80 value 78.718629
iter  90 value 78.128610
iter 100 value 77.849137
final  value 77.849137 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 109.209868 
iter  10 value 93.445920
iter  20 value 91.728059
iter  30 value 82.906958
iter  40 value 81.655132
iter  50 value 81.265972
iter  60 value 80.021665
iter  70 value 79.288471
iter  80 value 79.140448
iter  90 value 78.773618
iter 100 value 78.635992
final  value 78.635992 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.212576 
iter  10 value 92.332760
iter  20 value 84.702956
iter  30 value 83.879471
iter  40 value 83.656463
iter  50 value 81.962624
iter  60 value 81.330894
iter  70 value 80.738325
iter  80 value 80.032825
iter  90 value 79.589995
iter 100 value 78.939882
final  value 78.939882 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.936852 
final  value 93.630077 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.057963 
iter  10 value 94.054325
iter  20 value 94.018528
iter  30 value 94.017512
iter  40 value 92.201417
iter  50 value 89.325136
final  value 89.257667 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.734224 
final  value 94.054437 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.402944 
final  value 94.054446 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.346921 
final  value 94.054636 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.033865 
iter  10 value 94.057864
iter  20 value 94.047633
iter  30 value 92.946963
final  value 92.946955 
converged
Fitting Repeat 2 

# weights:  305
initial  value 95.142733 
iter  10 value 94.057999
iter  20 value 93.949205
iter  30 value 92.371722
iter  40 value 83.657396
iter  50 value 83.637233
iter  60 value 83.517030
iter  70 value 82.805730
iter  80 value 82.801647
iter  90 value 82.798843
iter 100 value 82.783701
final  value 82.783701 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 96.863311 
iter  10 value 92.576943
iter  20 value 92.576563
iter  30 value 92.318199
iter  40 value 89.999466
iter  50 value 89.986530
final  value 89.985460 
converged
Fitting Repeat 4 

# weights:  305
initial  value 112.476007 
iter  10 value 92.567535
iter  20 value 92.535839
iter  30 value 92.533674
iter  40 value 92.530280
final  value 92.530269 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.236353 
iter  10 value 94.057768
iter  20 value 93.669608
iter  30 value 84.752516
iter  40 value 83.388985
iter  50 value 80.818282
iter  60 value 80.277503
iter  70 value 80.222377
iter  80 value 80.193752
iter  90 value 80.192571
final  value 80.192176 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.937363 
iter  10 value 92.873019
iter  20 value 92.527416
iter  30 value 92.525426
iter  40 value 90.113001
iter  50 value 89.103155
iter  60 value 83.800441
iter  70 value 79.649490
iter  80 value 79.160780
iter  90 value 78.791001
iter 100 value 77.861195
final  value 77.861195 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 116.408428 
iter  10 value 94.070166
iter  20 value 93.922601
iter  30 value 92.956624
iter  40 value 92.952571
iter  50 value 88.917522
iter  60 value 88.841550
iter  70 value 86.510962
iter  80 value 84.392172
iter  90 value 84.201650
iter 100 value 84.200848
final  value 84.200848 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 104.303597 
iter  10 value 94.061019
iter  20 value 94.022878
iter  30 value 93.732233
iter  40 value 85.358150
iter  50 value 82.983317
iter  60 value 82.238117
iter  70 value 82.201018
iter  80 value 82.093516
iter  90 value 81.288930
iter 100 value 80.904212
final  value 80.904212 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 115.719164 
iter  10 value 94.061197
iter  20 value 94.041853
iter  30 value 85.062245
iter  40 value 84.896108
iter  50 value 84.841239
iter  60 value 84.104952
iter  70 value 84.103227
iter  80 value 84.102461
iter  90 value 82.451824
iter 100 value 81.696828
final  value 81.696828 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 96.250629 
iter  10 value 83.095053
iter  20 value 81.965322
iter  30 value 80.921744
iter  40 value 80.916308
iter  40 value 80.916308
final  value 80.916308 
converged
Fitting Repeat 1 

# weights:  103
initial  value 104.519885 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.956102 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.304977 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.022463 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.357452 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.722977 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.005676 
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.297475 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.787707 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 117.096600 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.907396 
iter  10 value 91.657957
iter  20 value 83.036323
iter  30 value 81.783097
iter  40 value 81.164438
iter  50 value 81.146210
iter  60 value 80.937690
iter  70 value 80.819776
iter  80 value 80.818978
final  value 80.818510 
converged
Fitting Repeat 2 

# weights:  507
initial  value 125.853577 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 139.779332 
iter  10 value 94.466823
iter  10 value 94.466823
iter  10 value 94.466823
final  value 94.466823 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.426814 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.267281 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.739082 
iter  10 value 94.488857
iter  20 value 94.456296
iter  30 value 93.462774
iter  40 value 87.073007
iter  50 value 85.606907
iter  60 value 84.786392
iter  70 value 84.763754
iter  80 value 84.719635
final  value 84.718987 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.925869 
iter  10 value 94.490665
iter  20 value 94.488572
iter  30 value 94.461889
iter  40 value 93.218887
iter  50 value 92.516132
iter  60 value 92.086002
iter  70 value 85.387023
iter  80 value 85.175733
iter  90 value 84.917051
iter 100 value 84.807415
final  value 84.807415 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 100.499464 
iter  10 value 94.109063
iter  20 value 92.732404
iter  30 value 92.180135
iter  40 value 87.558096
iter  50 value 85.195003
iter  60 value 85.143544
iter  70 value 85.072515
iter  80 value 84.772542
iter  90 value 84.753641
iter 100 value 84.737904
final  value 84.737904 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 98.296348 
iter  10 value 94.453659
iter  20 value 88.806551
iter  30 value 87.470411
iter  40 value 87.117284
iter  50 value 87.050087
iter  60 value 85.190863
iter  70 value 84.868680
iter  80 value 84.766517
iter  90 value 84.724525
final  value 84.724457 
converged
Fitting Repeat 5 

# weights:  103
initial  value 108.280685 
iter  10 value 94.406216
iter  20 value 92.786751
iter  30 value 92.145328
iter  40 value 91.975235
iter  50 value 91.972153
final  value 91.972130 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.338330 
iter  10 value 90.635179
iter  20 value 86.400280
iter  30 value 85.027554
iter  40 value 84.378596
iter  50 value 83.593112
iter  60 value 82.577094
iter  70 value 82.420103
iter  80 value 82.305716
iter  90 value 82.276775
iter 100 value 82.057841
final  value 82.057841 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 116.723045 
iter  10 value 94.615523
iter  20 value 94.325409
iter  30 value 94.304852
iter  40 value 94.189407
iter  50 value 93.248624
iter  60 value 91.626523
iter  70 value 90.789128
iter  80 value 86.586812
iter  90 value 85.690894
iter 100 value 83.762817
final  value 83.762817 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.179933 
iter  10 value 94.614767
iter  20 value 87.704765
iter  30 value 86.835896
iter  40 value 84.783998
iter  50 value 84.652197
iter  60 value 84.431398
iter  70 value 84.344451
iter  80 value 84.321757
iter  90 value 83.936186
iter 100 value 82.812292
final  value 82.812292 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.185195 
iter  10 value 94.171248
iter  20 value 85.616247
iter  30 value 85.170010
iter  40 value 84.871440
iter  50 value 84.768518
iter  60 value 84.689396
iter  70 value 84.052255
iter  80 value 82.943222
iter  90 value 82.184417
iter 100 value 81.521459
final  value 81.521459 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.052317 
iter  10 value 94.179456
iter  20 value 92.918859
iter  30 value 92.594705
iter  40 value 85.735175
iter  50 value 84.252648
iter  60 value 82.895609
iter  70 value 82.531941
iter  80 value 82.267864
iter  90 value 82.250007
iter 100 value 82.205500
final  value 82.205500 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 117.489123 
iter  10 value 94.530884
iter  20 value 88.334881
iter  30 value 87.950748
iter  40 value 85.578120
iter  50 value 83.446226
iter  60 value 82.461171
iter  70 value 82.081228
iter  80 value 81.941811
iter  90 value 81.842105
iter 100 value 81.738695
final  value 81.738695 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 121.963511 
iter  10 value 94.471434
iter  20 value 90.164771
iter  30 value 86.876624
iter  40 value 86.213531
iter  50 value 85.135805
iter  60 value 83.665342
iter  70 value 82.126936
iter  80 value 81.852000
iter  90 value 81.518625
iter 100 value 81.379036
final  value 81.379036 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 117.503957 
iter  10 value 94.305375
iter  20 value 89.553325
iter  30 value 85.502694
iter  40 value 84.972698
iter  50 value 83.927240
iter  60 value 83.120604
iter  70 value 82.154742
iter  80 value 81.969064
iter  90 value 81.732380
iter 100 value 81.563682
final  value 81.563682 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.686324 
iter  10 value 93.216127
iter  20 value 92.656820
iter  30 value 91.236677
iter  40 value 88.336390
iter  50 value 85.174900
iter  60 value 84.856363
iter  70 value 83.456165
iter  80 value 82.597348
iter  90 value 82.232745
iter 100 value 81.990284
final  value 81.990284 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 103.933129 
iter  10 value 94.670216
iter  20 value 94.492471
iter  30 value 94.421170
iter  40 value 87.987181
iter  50 value 86.559120
iter  60 value 84.977577
iter  70 value 83.651924
iter  80 value 82.525450
iter  90 value 82.201179
iter 100 value 81.901331
final  value 81.901331 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.234705 
final  value 94.485973 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.463025 
final  value 94.485932 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.485595 
final  value 94.485827 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.425911 
final  value 94.485770 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.121795 
final  value 94.485705 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.779551 
iter  10 value 94.489092
iter  20 value 94.483890
iter  30 value 86.344286
iter  40 value 86.324758
iter  50 value 84.449630
iter  60 value 84.333192
iter  70 value 84.320385
iter  80 value 84.320115
final  value 84.319976 
converged
Fitting Repeat 2 

# weights:  305
initial  value 118.703147 
iter  10 value 94.489022
iter  20 value 94.484509
iter  30 value 94.334965
iter  40 value 86.461077
iter  50 value 86.310355
final  value 86.309547 
converged
Fitting Repeat 3 

# weights:  305
initial  value 106.528506 
iter  10 value 94.445133
iter  20 value 93.586679
iter  30 value 86.319302
iter  40 value 86.268874
iter  50 value 85.467923
iter  60 value 85.467600
iter  70 value 85.465323
iter  70 value 85.465323
iter  70 value 85.465323
final  value 85.465323 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.538006 
iter  10 value 94.471314
iter  20 value 94.427028
iter  30 value 88.503738
iter  40 value 87.552232
final  value 87.551168 
converged
Fitting Repeat 5 

# weights:  305
initial  value 108.610407 
iter  10 value 94.489077
iter  20 value 94.484421
final  value 94.484229 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.298592 
iter  10 value 94.475255
iter  20 value 94.457349
iter  30 value 94.099658
iter  40 value 94.095573
iter  50 value 94.010181
iter  60 value 93.797926
iter  70 value 93.697736
final  value 93.697731 
converged
Fitting Repeat 2 

# weights:  507
initial  value 114.083669 
iter  10 value 94.492278
iter  20 value 93.682292
iter  30 value 92.633895
iter  40 value 92.632532
iter  50 value 92.631258
iter  60 value 92.631030
iter  70 value 92.629923
iter  80 value 92.629452
final  value 92.629371 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.365082 
iter  10 value 94.492360
iter  20 value 94.449526
iter  30 value 86.536788
iter  40 value 86.510708
iter  50 value 84.521300
iter  60 value 84.360694
iter  70 value 84.329551
iter  80 value 84.325415
iter  90 value 84.315896
iter 100 value 84.313852
final  value 84.313852 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.091594 
iter  10 value 94.491535
iter  20 value 94.474770
iter  30 value 86.311035
final  value 86.310504 
converged
Fitting Repeat 5 

# weights:  507
initial  value 128.925413 
iter  10 value 94.494208
iter  20 value 94.180627
iter  30 value 84.399607
iter  40 value 84.336390
iter  50 value 83.202323
iter  60 value 83.035160
iter  70 value 82.937954
iter  80 value 82.937046
iter  90 value 82.872209
iter 100 value 82.837672
final  value 82.837672 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 141.130028 
iter  10 value 117.763574
iter  20 value 117.759643
iter  30 value 117.564502
iter  40 value 117.282063
iter  50 value 114.249990
iter  60 value 114.036756
iter  70 value 114.032249
iter  80 value 114.019319
final  value 114.019088 
converged
Fitting Repeat 2 

# weights:  305
initial  value 132.581334 
iter  10 value 117.893796
final  value 117.892059 
converged
Fitting Repeat 3 

# weights:  305
initial  value 133.420982 
iter  10 value 117.895784
iter  20 value 117.881178
iter  30 value 107.057848
iter  40 value 106.778886
iter  40 value 106.778886
final  value 106.778886 
converged
Fitting Repeat 4 

# weights:  305
initial  value 121.743096 
iter  10 value 117.774870
iter  20 value 117.733224
iter  30 value 117.730423
iter  40 value 109.640676
iter  50 value 106.984719
iter  60 value 106.957871
iter  70 value 105.273013
iter  80 value 105.097998
iter  90 value 105.052383
iter 100 value 105.043906
final  value 105.043906 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 132.946651 
iter  10 value 117.895636
iter  20 value 117.890432
iter  30 value 117.749630
iter  40 value 108.546554
iter  50 value 108.530803
final  value 108.528145 
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 -- Tue May  5 11:16:25 2026 
*********************************************** 
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 
 53.940   1.490 135.766