##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:HPiP.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings HPiP_1.19.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.24-bioc/meat/HPiP.Rcheck’
* using R version 4.6.0 Patched (2026-05-01 r89994)
* using platform: aarch64-apple-darwin23
* R was compiled by
    Apple clang version 17.0.0 (clang-1700.3.19.1)
    GNU Fortran (GCC) 14.2.0
* running under: macOS Tahoe 26.3.1
* using session charset: UTF-8
* current time: 2026-05-21 23:59:45 UTC
* 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 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     16.941  0.088  17.181
FSmethod      16.897  0.065  17.217
var_imp       16.813  0.079  16.905
pred_ensembel  6.039  0.107   5.438
enrichfindP    0.197  0.032   9.808
* 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
  ‘/Users/biocbuild/bbs-3.24-bioc/meat/HPiP.Rcheck/00check.log’
for details.

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


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.6/Resources/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 4.6.0 Patched (2026-05-01 r89994) -- "Because it was There"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin23

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 101.642498 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.456804 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.508837 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.450708 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.544829 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.453198 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.636622 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.702048 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.699163 
final  value 94.354396 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.655412 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.661993 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.594184 
final  value 94.354396 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.097789 
iter  10 value 89.980153
iter  20 value 89.622024
final  value 89.621533 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.283758 
iter  10 value 94.484215
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 125.159839 
iter  10 value 95.986179
iter  20 value 90.415665
iter  30 value 83.282235
iter  40 value 83.264529
final  value 83.264479 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.314319 
iter  10 value 94.364629
iter  20 value 93.944783
iter  30 value 93.909008
iter  40 value 83.679385
iter  50 value 82.905893
iter  60 value 81.940150
iter  70 value 81.452059
iter  80 value 80.798861
iter  90 value 80.758247
final  value 80.758242 
converged
Fitting Repeat 2 

# weights:  103
initial  value 114.197311 
iter  10 value 93.802033
iter  20 value 83.652552
iter  30 value 82.894549
iter  40 value 82.857037
iter  50 value 82.832405
iter  60 value 82.598727
iter  70 value 81.556361
iter  80 value 81.023523
iter  90 value 80.960415
final  value 80.960071 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.624422 
iter  10 value 94.488574
iter  20 value 88.445758
iter  30 value 87.486259
iter  40 value 86.103413
iter  50 value 85.563440
iter  60 value 85.345131
iter  70 value 81.217339
iter  80 value 81.043389
iter  90 value 80.977712
iter 100 value 80.834983
final  value 80.834983 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 102.545587 
iter  10 value 94.483375
iter  20 value 89.465243
iter  30 value 86.664367
iter  40 value 85.411331
iter  50 value 81.525664
iter  60 value 81.034865
iter  70 value 80.960126
final  value 80.960085 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.746690 
iter  10 value 94.487654
iter  20 value 94.374697
iter  30 value 94.154161
iter  40 value 94.043304
iter  50 value 94.022765
iter  60 value 92.465608
iter  70 value 86.397554
iter  80 value 85.784830
iter  90 value 82.013100
iter 100 value 81.631860
final  value 81.631860 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 124.734412 
iter  10 value 94.593120
iter  20 value 93.972148
iter  30 value 87.374920
iter  40 value 85.239629
iter  50 value 83.751144
iter  60 value 82.101781
iter  70 value 81.058838
iter  80 value 79.889246
iter  90 value 79.537923
iter 100 value 79.398144
final  value 79.398144 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 117.143845 
iter  10 value 94.486862
iter  20 value 92.912507
iter  30 value 86.438321
iter  40 value 84.328646
iter  50 value 83.409960
iter  60 value 82.785352
iter  70 value 82.649270
iter  80 value 81.931743
iter  90 value 81.608399
iter 100 value 81.525809
final  value 81.525809 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 114.773903 
iter  10 value 94.199289
iter  20 value 83.767809
iter  30 value 83.196453
iter  40 value 82.787707
iter  50 value 81.567342
iter  60 value 80.921165
iter  70 value 80.667526
iter  80 value 80.560399
iter  90 value 79.643415
iter 100 value 79.290201
final  value 79.290201 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.094561 
iter  10 value 95.824548
iter  20 value 84.098388
iter  30 value 82.001362
iter  40 value 81.589092
iter  50 value 80.738717
iter  60 value 79.522667
iter  70 value 79.129394
iter  80 value 78.903467
iter  90 value 78.794527
iter 100 value 78.720036
final  value 78.720036 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.244580 
iter  10 value 95.412009
iter  20 value 92.615316
iter  30 value 85.662202
iter  40 value 80.807075
iter  50 value 80.366987
iter  60 value 80.274112
iter  70 value 80.199506
iter  80 value 80.145907
iter  90 value 80.067602
iter 100 value 79.467764
final  value 79.467764 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.317715 
iter  10 value 94.534950
iter  20 value 91.853331
iter  30 value 87.439390
iter  40 value 84.182470
iter  50 value 83.024336
iter  60 value 82.138472
iter  70 value 81.740782
iter  80 value 80.824442
iter  90 value 80.313411
iter 100 value 79.682118
final  value 79.682118 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.371233 
iter  10 value 94.053539
iter  20 value 87.476830
iter  30 value 83.077708
iter  40 value 82.679453
iter  50 value 82.061565
iter  60 value 81.836870
iter  70 value 81.649841
iter  80 value 81.238752
iter  90 value 79.615767
iter 100 value 79.070706
final  value 79.070706 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 111.367246 
iter  10 value 94.486245
iter  20 value 86.216166
iter  30 value 83.513662
iter  40 value 80.475644
iter  50 value 79.666638
iter  60 value 79.342674
iter  70 value 79.210693
iter  80 value 78.935775
iter  90 value 78.730998
iter 100 value 78.718445
final  value 78.718445 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.093887 
iter  10 value 97.045640
iter  20 value 90.996452
iter  30 value 82.958751
iter  40 value 81.904571
iter  50 value 81.728675
iter  60 value 81.516137
iter  70 value 80.981315
iter  80 value 79.921387
iter  90 value 79.540867
iter 100 value 79.388154
final  value 79.388154 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.178519 
iter  10 value 94.358217
iter  20 value 87.974592
iter  30 value 86.367587
iter  40 value 82.282722
iter  50 value 80.282876
iter  60 value 80.029122
iter  70 value 79.398338
iter  80 value 79.193452
iter  90 value 78.956902
iter 100 value 78.767928
final  value 78.767928 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.871130 
iter  10 value 94.355833
iter  20 value 93.921433
iter  30 value 90.845941
iter  40 value 88.377875
iter  50 value 83.994981
iter  60 value 83.908318
iter  70 value 83.697428
iter  80 value 83.656280
final  value 83.656017 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.689237 
iter  10 value 89.223960
iter  20 value 87.508445
iter  30 value 86.609012
iter  40 value 86.509178
iter  50 value 86.344575
iter  60 value 86.189812
iter  70 value 86.185373
iter  80 value 86.182856
iter  90 value 85.216483
iter 100 value 84.055461
final  value 84.055461 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 100.036028 
final  value 94.485964 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.762040 
final  value 94.356034 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.244583 
iter  10 value 94.485777
iter  20 value 91.618120
final  value 86.701880 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.182096 
iter  10 value 94.174767
iter  20 value 94.171936
iter  30 value 93.828956
iter  40 value 82.640637
iter  50 value 82.018227
iter  60 value 81.602503
iter  70 value 79.973006
iter  80 value 79.930838
iter  90 value 79.919966
iter 100 value 79.917673
final  value 79.917673 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.935675 
iter  10 value 94.103970
iter  20 value 94.057655
final  value 94.053154 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.597721 
iter  10 value 94.488851
iter  20 value 93.830652
iter  30 value 86.962943
iter  40 value 86.694790
iter  50 value 86.693619
iter  60 value 83.834967
iter  70 value 83.802955
iter  80 value 83.494344
iter  90 value 83.327213
final  value 83.327081 
converged
Fitting Repeat 4 

# weights:  305
initial  value 114.017197 
iter  10 value 94.489760
iter  20 value 94.484636
final  value 94.484631 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.750979 
iter  10 value 94.489143
iter  20 value 94.480739
iter  30 value 93.529882
iter  40 value 93.525200
iter  50 value 91.375115
iter  60 value 88.969067
iter  70 value 88.295112
iter  80 value 82.554920
iter  90 value 81.838649
iter 100 value 80.367254
final  value 80.367254 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 96.795670 
iter  10 value 94.331160
iter  20 value 90.673945
iter  30 value 83.292943
iter  40 value 79.713406
iter  50 value 77.747585
iter  60 value 77.721135
iter  70 value 77.720242
iter  80 value 77.719734
iter  90 value 77.718862
iter 100 value 77.716743
final  value 77.716743 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.888535 
iter  10 value 94.172761
iter  20 value 93.911124
iter  30 value 91.471411
iter  40 value 87.528835
iter  50 value 87.296536
iter  60 value 86.145194
iter  70 value 84.492202
iter  80 value 83.212205
iter  90 value 80.201882
iter 100 value 79.982950
final  value 79.982950 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.187170 
iter  10 value 94.172402
iter  20 value 94.168935
iter  30 value 93.840272
iter  40 value 93.839412
final  value 93.839359 
converged
Fitting Repeat 4 

# weights:  507
initial  value 95.403692 
iter  10 value 90.881732
iter  20 value 83.273902
iter  30 value 83.268557
iter  40 value 82.915636
iter  50 value 82.529746
iter  60 value 81.916933
iter  70 value 81.453450
iter  80 value 81.308635
iter  90 value 81.308424
iter 100 value 81.304310
final  value 81.304310 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 102.171920 
iter  10 value 94.362048
iter  20 value 94.210152
iter  30 value 94.179401
iter  40 value 92.552735
iter  50 value 90.394924
iter  60 value 90.335240
iter  70 value 90.267014
iter  80 value 90.245366
iter  90 value 89.754385
iter 100 value 81.555959
final  value 81.555959 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.063009 
final  value 94.052911 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.545262 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.375708 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 113.086429 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.579790 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.891993 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 115.035218 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 113.716347 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.568191 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.951060 
final  value 94.038251 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.504027 
iter  10 value 85.604232
iter  20 value 79.946322
iter  30 value 78.389573
iter  40 value 78.358168
iter  50 value 78.356890
iter  60 value 78.356382
final  value 78.356381 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.232692 
iter  10 value 93.894167
iter  20 value 93.893852
final  value 93.893850 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.586910 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 113.989032 
final  value 94.038251 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.374660 
iter  10 value 86.426778
iter  20 value 84.667199
final  value 84.664401 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.774135 
iter  10 value 94.059659
iter  20 value 94.054949
iter  30 value 93.965793
iter  40 value 91.713323
iter  50 value 90.844733
iter  60 value 84.272536
iter  70 value 82.962831
iter  80 value 82.549228
iter  90 value 82.413230
iter 100 value 82.387573
final  value 82.387573 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.137547 
iter  10 value 94.056805
iter  20 value 93.055896
iter  30 value 91.403061
iter  40 value 90.938808
iter  50 value 90.789312
iter  60 value 90.195915
iter  70 value 90.084568
iter  80 value 90.077572
iter  80 value 90.077572
iter  80 value 90.077572
final  value 90.077572 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.025293 
iter  10 value 94.040343
iter  20 value 91.099387
iter  30 value 86.355625
iter  40 value 82.942901
iter  50 value 82.645924
iter  60 value 82.494734
iter  70 value 82.268496
iter  80 value 82.029922
iter  90 value 81.969981
final  value 81.969979 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.020427 
iter  10 value 94.093753
iter  20 value 94.052167
iter  30 value 93.912616
iter  40 value 87.498033
iter  50 value 86.732046
iter  60 value 86.667831
iter  70 value 86.505365
iter  80 value 86.466594
iter  90 value 83.839431
iter 100 value 81.874383
final  value 81.874383 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 100.737163 
iter  10 value 93.693723
iter  20 value 88.336846
iter  30 value 86.462522
iter  40 value 86.292587
iter  50 value 86.112874
iter  60 value 86.012753
iter  70 value 85.973100
iter  80 value 83.868945
iter  90 value 82.477763
iter 100 value 82.403200
final  value 82.403200 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 119.928397 
iter  10 value 93.912001
iter  20 value 91.873245
iter  30 value 85.094368
iter  40 value 83.821563
iter  50 value 82.554981
iter  60 value 81.235296
iter  70 value 80.996359
iter  80 value 80.305162
iter  90 value 79.385237
iter 100 value 79.179975
final  value 79.179975 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 111.793826 
iter  10 value 94.086956
iter  20 value 92.600595
iter  30 value 90.267668
iter  40 value 86.630328
iter  50 value 86.195892
iter  60 value 84.518548
iter  70 value 82.786417
iter  80 value 82.202178
iter  90 value 82.182481
iter 100 value 81.662147
final  value 81.662147 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.474344 
iter  10 value 94.071117
iter  20 value 89.232012
iter  30 value 84.897570
iter  40 value 84.401566
iter  50 value 84.235311
iter  60 value 82.978903
iter  70 value 80.887266
iter  80 value 79.889983
iter  90 value 78.791922
iter 100 value 78.487792
final  value 78.487792 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 119.377951 
iter  10 value 94.094428
iter  20 value 92.220263
iter  30 value 83.537748
iter  40 value 79.952654
iter  50 value 79.299755
iter  60 value 78.937405
iter  70 value 78.733692
iter  80 value 78.682866
iter  90 value 78.627771
iter 100 value 78.619851
final  value 78.619851 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.666169 
iter  10 value 94.017950
iter  20 value 91.076200
iter  30 value 86.050986
iter  40 value 85.376181
iter  50 value 81.143507
iter  60 value 80.172460
iter  70 value 79.089474
iter  80 value 78.223747
iter  90 value 78.083399
iter 100 value 78.073927
final  value 78.073927 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 102.643571 
iter  10 value 94.242628
iter  20 value 91.204865
iter  30 value 84.599273
iter  40 value 80.048812
iter  50 value 79.340026
iter  60 value 78.796546
iter  70 value 78.621874
iter  80 value 78.455524
iter  90 value 78.369833
iter 100 value 78.279193
final  value 78.279193 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.756751 
iter  10 value 94.341348
iter  20 value 83.951444
iter  30 value 82.440354
iter  40 value 79.823498
iter  50 value 79.057428
iter  60 value 78.474511
iter  70 value 78.102111
iter  80 value 77.562384
iter  90 value 77.448256
iter 100 value 77.422183
final  value 77.422183 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 123.227551 
iter  10 value 93.951611
iter  20 value 84.528223
iter  30 value 82.869922
iter  40 value 80.121447
iter  50 value 78.983623
iter  60 value 78.233080
iter  70 value 77.860371
iter  80 value 77.658350
iter  90 value 77.616876
iter 100 value 77.561351
final  value 77.561351 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.906576 
iter  10 value 93.267893
iter  20 value 84.377538
iter  30 value 80.822964
iter  40 value 79.491007
iter  50 value 78.673087
iter  60 value 78.433893
iter  70 value 77.989777
iter  80 value 77.736889
iter  90 value 77.690430
iter 100 value 77.642741
final  value 77.642741 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.768352 
iter  10 value 94.197925
iter  20 value 92.555195
iter  30 value 85.875251
iter  40 value 85.028073
iter  50 value 82.849699
iter  60 value 81.124319
iter  70 value 79.293441
iter  80 value 78.460605
iter  90 value 78.199470
iter 100 value 78.173926
final  value 78.173926 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.633998 
final  value 94.054806 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.831217 
final  value 94.039666 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.990143 
final  value 94.054797 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.355067 
iter  10 value 94.054518
iter  20 value 94.052966
iter  30 value 92.253654
iter  40 value 86.606891
iter  50 value 86.483025
iter  60 value 86.480612
final  value 86.478670 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.728117 
iter  10 value 94.039893
iter  20 value 94.038410
final  value 94.038273 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.099957 
iter  10 value 94.043911
iter  20 value 93.989410
iter  30 value 93.984486
iter  40 value 93.980355
iter  50 value 91.777798
iter  60 value 88.009408
iter  70 value 86.084191
iter  80 value 85.720271
final  value 85.719739 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.377678 
iter  10 value 94.043091
iter  20 value 94.038433
final  value 94.038293 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.433700 
iter  10 value 94.057971
iter  20 value 94.033656
iter  30 value 93.763065
iter  40 value 86.837566
iter  50 value 82.309844
iter  60 value 81.714043
iter  70 value 79.213690
iter  80 value 79.077983
iter  90 value 78.862295
iter 100 value 78.853229
final  value 78.853229 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 96.355033 
iter  10 value 94.057699
iter  20 value 90.179463
iter  30 value 85.509295
final  value 85.509283 
converged
Fitting Repeat 5 

# weights:  305
initial  value 110.616966 
iter  10 value 94.043389
iter  20 value 94.039734
iter  30 value 93.571737
iter  40 value 90.481174
iter  50 value 88.534852
iter  60 value 88.129406
iter  70 value 87.513406
iter  80 value 85.610357
iter  90 value 85.408538
iter 100 value 85.407466
final  value 85.407466 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 117.072544 
iter  10 value 94.061092
iter  20 value 94.051701
iter  30 value 93.847185
iter  40 value 90.780160
iter  50 value 87.590462
iter  60 value 87.570003
final  value 87.569273 
converged
Fitting Repeat 2 

# weights:  507
initial  value 119.636008 
iter  10 value 91.674186
iter  20 value 85.634763
iter  30 value 84.982073
iter  40 value 84.880585
iter  50 value 84.830204
iter  60 value 84.815660
iter  70 value 84.803692
iter  80 value 84.616014
iter  90 value 84.366387
iter 100 value 82.696443
final  value 82.696443 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 121.343411 
iter  10 value 94.046496
iter  20 value 94.039069
iter  30 value 85.991377
iter  40 value 83.604914
final  value 83.603899 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.216135 
iter  10 value 93.970124
iter  20 value 93.956736
iter  30 value 93.890992
iter  40 value 92.397265
iter  50 value 90.392506
iter  60 value 90.201793
final  value 90.201554 
converged
Fitting Repeat 5 

# weights:  507
initial  value 117.874082 
iter  10 value 93.599308
iter  20 value 93.539828
iter  30 value 93.533429
iter  40 value 93.492387
iter  50 value 93.489492
iter  60 value 93.489008
iter  70 value 93.488588
iter  80 value 93.488330
final  value 93.488305 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.146336 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.765758 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.538308 
final  value 94.484137 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.611448 
iter  10 value 94.276734
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.739255 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 115.853963 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.168803 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.977499 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 106.106829 
iter  10 value 94.460483
iter  20 value 94.275363
iter  20 value 94.275362
iter  20 value 94.275362
final  value 94.275362 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.812579 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.133090 
iter  10 value 89.581647
iter  20 value 87.229529
iter  30 value 87.227787
final  value 87.227601 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.251594 
iter  10 value 94.275358
iter  10 value 94.275358
iter  10 value 94.275358
final  value 94.275358 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.326172 
final  value 94.409357 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.532268 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 109.737539 
final  value 94.484137 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.941146 
iter  10 value 94.333179
iter  20 value 93.345913
iter  30 value 90.640972
iter  40 value 90.422339
iter  50 value 89.479988
iter  60 value 86.783873
iter  70 value 84.117672
iter  80 value 83.751253
iter  90 value 83.456117
iter 100 value 83.398126
final  value 83.398126 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.249322 
iter  10 value 94.490411
iter  20 value 94.389322
iter  30 value 94.333782
iter  40 value 94.327060
iter  50 value 89.720820
iter  60 value 86.579200
iter  70 value 85.644143
iter  80 value 84.766580
iter  90 value 84.180088
iter 100 value 83.754996
final  value 83.754996 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 104.460823 
iter  10 value 94.455326
iter  20 value 94.227977
iter  30 value 89.192367
iter  40 value 88.731835
iter  50 value 86.086867
iter  60 value 85.486746
iter  70 value 85.106970
iter  80 value 84.765135
final  value 84.764951 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.536685 
iter  10 value 94.377613
iter  20 value 87.941810
iter  30 value 87.328652
iter  40 value 86.085797
iter  50 value 85.378230
iter  60 value 84.494605
iter  70 value 83.865464
iter  80 value 83.856183
iter  90 value 83.476068
iter 100 value 83.054898
final  value 83.054898 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.352324 
iter  10 value 94.487094
iter  20 value 94.296671
iter  30 value 91.707061
iter  40 value 88.188485
iter  50 value 87.245587
iter  60 value 85.997606
iter  70 value 84.335918
iter  80 value 83.379400
iter  90 value 83.223339
iter 100 value 83.188908
final  value 83.188908 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 115.810740 
iter  10 value 94.498450
iter  20 value 91.609154
iter  30 value 87.093252
iter  40 value 84.602872
iter  50 value 82.629927
iter  60 value 82.043104
iter  70 value 81.831558
iter  80 value 81.752613
iter  90 value 81.722065
iter 100 value 81.626495
final  value 81.626495 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.123942 
iter  10 value 94.208186
iter  20 value 87.246434
iter  30 value 85.811737
iter  40 value 84.311344
iter  50 value 83.337178
iter  60 value 82.936237
iter  70 value 82.600889
iter  80 value 82.206634
iter  90 value 82.156686
iter 100 value 82.151722
final  value 82.151722 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.706288 
iter  10 value 94.310732
iter  20 value 93.119396
iter  30 value 87.834626
iter  40 value 85.047157
iter  50 value 84.674457
iter  60 value 84.231931
iter  70 value 82.935882
iter  80 value 82.397492
iter  90 value 82.178782
iter 100 value 82.086740
final  value 82.086740 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 114.872578 
iter  10 value 94.423924
iter  20 value 91.227400
iter  30 value 87.870318
iter  40 value 84.664143
iter  50 value 83.748140
iter  60 value 83.245486
iter  70 value 82.263392
iter  80 value 81.861404
iter  90 value 81.497520
iter 100 value 81.349655
final  value 81.349655 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 102.703321 
iter  10 value 94.587063
iter  20 value 93.873877
iter  30 value 90.211690
iter  40 value 87.143805
iter  50 value 84.648194
iter  60 value 84.089671
iter  70 value 83.776636
iter  80 value 83.041193
iter  90 value 82.214308
iter 100 value 81.585738
final  value 81.585738 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.025023 
iter  10 value 94.469845
iter  20 value 88.757243
iter  30 value 86.927893
iter  40 value 84.682696
iter  50 value 83.440242
iter  60 value 83.082985
iter  70 value 82.755729
iter  80 value 82.082176
iter  90 value 81.651777
iter 100 value 81.357368
final  value 81.357368 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.593790 
iter  10 value 94.552217
iter  20 value 93.573106
iter  30 value 88.326301
iter  40 value 87.480449
iter  50 value 86.859026
iter  60 value 86.623189
iter  70 value 86.019929
iter  80 value 84.539776
iter  90 value 83.715135
iter 100 value 83.111921
final  value 83.111921 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 113.450592 
iter  10 value 94.465057
iter  20 value 90.127558
iter  30 value 87.797398
iter  40 value 86.670706
iter  50 value 86.051301
iter  60 value 84.006471
iter  70 value 82.949804
iter  80 value 82.902717
iter  90 value 82.841455
iter 100 value 82.820628
final  value 82.820628 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.430821 
iter  10 value 94.771009
iter  20 value 88.841727
iter  30 value 83.695897
iter  40 value 81.968751
iter  50 value 81.763516
iter  60 value 81.667104
iter  70 value 81.636850
iter  80 value 81.630157
iter  90 value 81.598068
iter 100 value 81.550678
final  value 81.550678 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 115.956523 
iter  10 value 94.235960
iter  20 value 90.019645
iter  30 value 86.180967
iter  40 value 85.912218
iter  50 value 85.025106
iter  60 value 83.652990
iter  70 value 82.808868
iter  80 value 82.193774
iter  90 value 81.666123
iter 100 value 81.497140
final  value 81.497140 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.905035 
final  value 94.355822 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.001445 
iter  10 value 91.115848
iter  20 value 87.336773
iter  30 value 87.325835
iter  40 value 86.737024
iter  50 value 85.122293
iter  60 value 84.413575
iter  70 value 84.402911
iter  80 value 84.398039
iter  90 value 84.395111
final  value 84.395105 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.812598 
iter  10 value 94.277194
iter  20 value 94.275807
iter  30 value 94.062931
iter  40 value 94.049646
final  value 94.049609 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.156242 
final  value 94.485655 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.994040 
iter  10 value 94.486143
iter  20 value 94.484227
final  value 94.484215 
converged
Fitting Repeat 1 

# weights:  305
initial  value 106.047662 
iter  10 value 93.710014
iter  20 value 93.708248
iter  30 value 93.704982
iter  40 value 91.887138
iter  50 value 84.720117
iter  60 value 83.924938
iter  70 value 83.266978
iter  80 value 83.238591
iter  90 value 82.525565
iter 100 value 81.303396
final  value 81.303396 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 98.620604 
iter  10 value 94.488945
iter  20 value 94.484415
iter  30 value 94.077607
iter  40 value 86.322727
iter  50 value 86.101528
iter  60 value 86.094495
iter  70 value 86.076259
final  value 86.075303 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.648593 
iter  10 value 94.488937
iter  20 value 94.288390
final  value 94.275561 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.532708 
iter  10 value 94.073955
iter  20 value 94.057360
iter  30 value 94.054245
iter  40 value 94.052748
final  value 94.052746 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.509739 
iter  10 value 94.488660
iter  20 value 94.391725
final  value 93.835047 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.161104 
iter  10 value 90.520716
iter  20 value 87.038301
iter  30 value 85.527861
iter  40 value 85.306258
iter  50 value 85.288423
iter  60 value 85.061855
iter  70 value 85.004030
iter  80 value 84.972230
iter  90 value 82.850761
iter 100 value 82.477089
final  value 82.477089 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 116.714506 
iter  10 value 94.282051
iter  20 value 94.277639
iter  30 value 94.276203
iter  40 value 94.246144
iter  50 value 85.428842
iter  60 value 85.021155
final  value 85.019288 
converged
Fitting Repeat 3 

# weights:  507
initial  value 102.213240 
iter  10 value 90.783236
iter  20 value 87.733485
iter  30 value 85.609533
iter  40 value 84.154774
iter  50 value 83.744559
iter  60 value 83.736932
final  value 83.735586 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.188562 
iter  10 value 94.491649
iter  20 value 94.289045
iter  30 value 94.276563
iter  40 value 94.213873
iter  50 value 87.385837
iter  60 value 87.238146
iter  70 value 87.237728
iter  80 value 86.920125
iter  90 value 86.919637
iter 100 value 86.906192
final  value 86.906192 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.389698 
iter  10 value 94.512373
iter  20 value 94.503881
iter  30 value 87.939178
iter  40 value 87.372914
iter  50 value 86.920045
iter  60 value 86.748160
iter  70 value 83.485982
iter  80 value 83.412602
iter  90 value 83.395976
iter 100 value 81.987893
final  value 81.987893 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.875363 
iter  10 value 87.080207
iter  20 value 86.622075
iter  30 value 86.618367
final  value 86.618336 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.086714 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.152079 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.817160 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 119.578642 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.389770 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.568244 
final  value 94.050155 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.651502 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.785189 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.821145 
iter  10 value 92.943920
iter  20 value 88.337110
iter  30 value 88.336263
final  value 88.336206 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.676544 
iter  10 value 94.009990
final  value 94.009967 
converged
Fitting Repeat 2 

# weights:  507
initial  value 103.978034 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 109.281583 
iter  10 value 92.007912
iter  20 value 87.727148
iter  30 value 86.023867
final  value 86.023447 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.300416 
iter  10 value 92.825147
iter  20 value 92.359216
final  value 92.085795 
converged
Fitting Repeat 5 

# weights:  507
initial  value 102.517440 
iter  10 value 91.294465
iter  20 value 90.864919
final  value 90.864664 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.053346 
iter  10 value 94.036761
iter  20 value 92.289313
iter  30 value 88.170097
iter  40 value 85.922422
iter  50 value 84.956610
iter  60 value 84.281876
iter  70 value 83.778267
iter  80 value 83.726864
final  value 83.726858 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.429278 
iter  10 value 94.062869
iter  20 value 93.614775
iter  30 value 93.088146
iter  40 value 88.563004
iter  50 value 88.399743
iter  60 value 88.280914
iter  70 value 86.461049
iter  80 value 86.197827
iter  90 value 86.073448
iter 100 value 86.048378
final  value 86.048378 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 103.423973 
iter  10 value 93.924346
iter  20 value 85.993931
iter  30 value 85.546868
iter  40 value 85.284152
iter  50 value 84.564759
iter  60 value 84.145398
iter  70 value 83.894948
final  value 83.894872 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.435974 
iter  10 value 94.059768
iter  20 value 93.005006
iter  30 value 89.555795
iter  40 value 87.410301
iter  50 value 86.048445
iter  60 value 85.055177
iter  70 value 84.625759
final  value 84.624380 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.781195 
iter  10 value 93.986357
iter  20 value 88.348670
iter  30 value 85.660973
iter  40 value 85.188495
iter  50 value 84.270225
iter  60 value 83.896841
iter  70 value 83.894183
iter  80 value 83.775091
iter  90 value 83.727165
final  value 83.726857 
converged
Fitting Repeat 1 

# weights:  305
initial  value 113.011524 
iter  10 value 94.619338
iter  20 value 94.039450
iter  30 value 86.937757
iter  40 value 85.526911
iter  50 value 84.727933
iter  60 value 83.552431
iter  70 value 82.825961
iter  80 value 82.743834
iter  90 value 82.577990
iter 100 value 82.498425
final  value 82.498425 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 114.527502 
iter  10 value 94.022902
iter  20 value 92.696078
iter  30 value 87.935957
iter  40 value 84.733338
iter  50 value 83.389633
iter  60 value 82.961087
iter  70 value 82.719722
iter  80 value 81.877515
iter  90 value 81.680110
iter 100 value 81.536432
final  value 81.536432 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.577238 
iter  10 value 94.024735
iter  20 value 93.746938
iter  30 value 91.782377
iter  40 value 89.458400
iter  50 value 86.502936
iter  60 value 86.351800
iter  70 value 86.334118
iter  80 value 86.314503
iter  90 value 86.241814
iter 100 value 85.229602
final  value 85.229602 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.559432 
iter  10 value 94.093751
iter  20 value 88.833168
iter  30 value 86.713243
iter  40 value 86.406956
iter  50 value 86.297655
iter  60 value 86.277572
iter  70 value 86.256788
iter  80 value 85.908235
iter  90 value 84.570848
iter 100 value 83.591630
final  value 83.591630 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.069287 
iter  10 value 94.129672
iter  20 value 93.910733
iter  30 value 91.942234
iter  40 value 86.669664
iter  50 value 85.598887
iter  60 value 85.229318
iter  70 value 84.789899
iter  80 value 84.048686
iter  90 value 83.118317
iter 100 value 81.499557
final  value 81.499557 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 129.924980 
iter  10 value 95.783844
iter  20 value 95.568082
iter  30 value 88.220223
iter  40 value 86.336924
iter  50 value 85.577908
iter  60 value 85.003279
iter  70 value 83.978904
iter  80 value 82.991812
iter  90 value 82.723452
iter 100 value 82.600775
final  value 82.600775 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.371885 
iter  10 value 94.030240
iter  20 value 92.057232
iter  30 value 89.935308
iter  40 value 87.251301
iter  50 value 86.004207
iter  60 value 84.659487
iter  70 value 84.229123
iter  80 value 84.101616
iter  90 value 83.653000
iter 100 value 83.314432
final  value 83.314432 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.249211 
iter  10 value 92.943908
iter  20 value 90.724991
iter  30 value 89.311140
iter  40 value 86.678917
iter  50 value 85.921468
iter  60 value 83.508230
iter  70 value 82.516220
iter  80 value 82.140354
iter  90 value 81.838170
iter 100 value 81.648321
final  value 81.648321 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.523192 
iter  10 value 93.025087
iter  20 value 87.450796
iter  30 value 86.334723
iter  40 value 84.595995
iter  50 value 83.189118
iter  60 value 82.326939
iter  70 value 82.006842
iter  80 value 81.889966
iter  90 value 81.667780
iter 100 value 81.455666
final  value 81.455666 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 116.823314 
iter  10 value 98.134617
iter  20 value 95.550117
iter  30 value 94.701742
iter  40 value 94.219910
iter  50 value 92.453373
iter  60 value 88.257414
iter  70 value 83.994105
iter  80 value 83.676444
iter  90 value 83.303637
iter 100 value 82.243756
final  value 82.243756 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 97.967970 
iter  10 value 93.837681
iter  20 value 93.836959
iter  30 value 93.821177
iter  40 value 93.811391
final  value 93.811357 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.161969 
iter  10 value 94.034996
iter  20 value 94.034467
final  value 94.033076 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.298339 
final  value 94.054368 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.918532 
final  value 94.054311 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.823507 
final  value 94.054629 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.813653 
iter  10 value 94.037720
iter  20 value 94.033823
iter  30 value 93.960876
iter  40 value 89.361856
iter  50 value 86.298861
iter  60 value 85.983125
iter  70 value 85.928494
iter  80 value 85.916023
iter  90 value 85.854356
iter 100 value 83.976333
final  value 83.976333 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 101.233524 
iter  10 value 94.057734
iter  20 value 90.584889
iter  30 value 90.366881
iter  40 value 90.361913
iter  50 value 90.351307
iter  60 value 89.021918
iter  70 value 84.768437
iter  80 value 82.121740
iter  90 value 81.714095
iter 100 value 81.703709
final  value 81.703709 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 95.473675 
iter  10 value 91.441446
iter  20 value 91.438089
iter  30 value 91.426338
iter  40 value 90.529149
final  value 90.498445 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.199132 
iter  10 value 94.056844
iter  20 value 86.954865
iter  30 value 86.445989
iter  40 value 85.830789
iter  50 value 84.682596
iter  60 value 81.858078
iter  70 value 81.840149
iter  80 value 81.824182
iter  90 value 81.694718
iter 100 value 81.621095
final  value 81.621095 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 120.288618 
iter  10 value 94.058039
iter  20 value 94.053202
iter  30 value 87.491230
iter  40 value 87.233789
iter  50 value 87.232783
iter  60 value 87.229721
final  value 87.229332 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.116277 
iter  10 value 94.040271
iter  20 value 94.033039
iter  30 value 92.384466
iter  40 value 88.405375
iter  50 value 88.163717
iter  60 value 85.550735
iter  70 value 85.381423
iter  80 value 85.379450
iter  90 value 85.335170
iter 100 value 85.182642
final  value 85.182642 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.294680 
iter  10 value 94.060782
iter  20 value 94.005441
iter  30 value 93.334858
iter  40 value 93.333500
final  value 93.333478 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.056884 
iter  10 value 92.892881
iter  20 value 90.811719
iter  30 value 87.547250
iter  40 value 85.617583
iter  50 value 85.112780
iter  60 value 84.212978
iter  70 value 83.633423
iter  80 value 83.457637
iter  90 value 83.409950
final  value 83.409608 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.517994 
iter  10 value 94.041150
iter  20 value 94.033158
iter  30 value 93.911361
iter  40 value 92.347516
iter  50 value 92.034455
iter  60 value 91.958133
iter  70 value 87.038945
iter  80 value 87.024831
iter  90 value 87.019405
iter 100 value 87.014878
final  value 87.014878 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 95.395194 
iter  10 value 94.023389
iter  20 value 93.733769
iter  30 value 92.217917
iter  40 value 92.202393
iter  50 value 92.098678
iter  60 value 90.915025
iter  70 value 90.500160
iter  80 value 90.498723
final  value 90.498685 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.599279 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.676424 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.304145 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.265514 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.127981 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.347694 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.367197 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.507177 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 110.803741 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.031096 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.082997 
iter  10 value 93.555988
iter  20 value 90.105480
iter  30 value 89.874056
iter  40 value 89.870290
final  value 89.870271 
converged
Fitting Repeat 2 

# weights:  507
initial  value 109.027181 
iter  10 value 93.751993
final  value 93.720301 
converged
Fitting Repeat 3 

# weights:  507
initial  value 117.753223 
iter  10 value 93.777020
final  value 93.746369 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.543411 
final  value 93.772974 
converged
Fitting Repeat 5 

# weights:  507
initial  value 96.795131 
iter  10 value 93.918868
final  value 93.911201 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.105865 
iter  10 value 90.808498
iter  20 value 84.994288
iter  30 value 82.992143
iter  40 value 81.766233
iter  50 value 81.382741
final  value 81.381535 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.247955 
iter  10 value 94.495848
iter  20 value 92.355979
iter  30 value 87.295855
iter  40 value 86.470871
iter  50 value 85.370885
iter  60 value 82.653025
iter  70 value 82.439474
iter  80 value 82.360364
iter  90 value 82.218103
iter 100 value 81.779350
final  value 81.779350 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 102.202643 
iter  10 value 94.440132
iter  20 value 94.110918
iter  30 value 91.887725
iter  40 value 90.180749
iter  50 value 89.985171
iter  60 value 86.489652
iter  70 value 84.674309
iter  80 value 84.548167
iter  90 value 84.482616
final  value 84.478553 
converged
Fitting Repeat 4 

# weights:  103
initial  value 104.826616 
iter  10 value 94.040897
iter  20 value 91.856681
iter  30 value 86.758366
iter  40 value 85.889842
iter  50 value 85.472915
iter  60 value 85.155943
iter  70 value 85.042025
iter  80 value 84.980331
final  value 84.980328 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.289363 
iter  10 value 94.407368
iter  20 value 94.125121
iter  30 value 93.915295
iter  40 value 85.884497
iter  50 value 85.569883
iter  60 value 85.521154
iter  70 value 85.497427
iter  80 value 85.435493
iter  90 value 84.909635
iter 100 value 84.514395
final  value 84.514395 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 107.105769 
iter  10 value 93.768263
iter  20 value 92.051601
iter  30 value 91.131732
iter  40 value 90.963868
iter  50 value 87.687583
iter  60 value 85.034067
iter  70 value 83.846927
iter  80 value 82.997043
iter  90 value 82.518775
iter 100 value 81.058856
final  value 81.058856 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.847957 
iter  10 value 94.487476
iter  20 value 93.979275
iter  30 value 92.999422
iter  40 value 89.176179
iter  50 value 85.924935
iter  60 value 84.772549
iter  70 value 83.023561
iter  80 value 81.800394
iter  90 value 81.404191
iter 100 value 80.951979
final  value 80.951979 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 107.444851 
iter  10 value 94.458885
iter  20 value 93.162569
iter  30 value 85.379629
iter  40 value 83.883564
iter  50 value 83.717755
iter  60 value 83.505422
iter  70 value 82.927753
iter  80 value 82.274929
iter  90 value 81.082354
iter 100 value 80.739445
final  value 80.739445 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.875118 
iter  10 value 94.045843
iter  20 value 86.987652
iter  30 value 84.600111
iter  40 value 83.212696
iter  50 value 82.435749
iter  60 value 81.958156
iter  70 value 81.780851
iter  80 value 81.699296
iter  90 value 81.570187
iter 100 value 81.477945
final  value 81.477945 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 124.232824 
iter  10 value 94.864398
iter  20 value 90.777562
iter  30 value 87.216286
iter  40 value 86.366021
iter  50 value 84.751142
iter  60 value 83.998022
iter  70 value 83.219695
iter  80 value 82.751001
iter  90 value 82.569304
iter 100 value 82.038344
final  value 82.038344 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.483069 
iter  10 value 93.984750
iter  20 value 90.541356
iter  30 value 87.279273
iter  40 value 84.767432
iter  50 value 83.231922
iter  60 value 82.391801
iter  70 value 81.750770
iter  80 value 81.133167
iter  90 value 80.986075
iter 100 value 80.714629
final  value 80.714629 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 137.766760 
iter  10 value 91.919512
iter  20 value 90.023182
iter  30 value 87.064029
iter  40 value 84.705936
iter  50 value 83.426579
iter  60 value 81.863905
iter  70 value 81.558847
iter  80 value 80.505391
iter  90 value 80.223090
iter 100 value 80.128037
final  value 80.128037 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.247038 
iter  10 value 94.612441
iter  20 value 88.549540
iter  30 value 87.609953
iter  40 value 86.839876
iter  50 value 83.293618
iter  60 value 81.034308
iter  70 value 80.813116
iter  80 value 80.624013
iter  90 value 80.438032
iter 100 value 80.032351
final  value 80.032351 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.394584 
iter  10 value 94.527472
iter  20 value 91.954682
iter  30 value 86.146570
iter  40 value 84.026630
iter  50 value 82.541001
iter  60 value 82.012367
iter  70 value 81.926754
iter  80 value 81.618112
iter  90 value 81.099583
iter 100 value 80.494255
final  value 80.494255 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.578841 
iter  10 value 94.890724
iter  20 value 89.405419
iter  30 value 85.241776
iter  40 value 84.713751
iter  50 value 84.301003
iter  60 value 83.813669
iter  70 value 82.335892
iter  80 value 81.953466
iter  90 value 81.855871
iter 100 value 81.748495
final  value 81.748495 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.134683 
final  value 94.485873 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.474586 
iter  10 value 94.485647
iter  20 value 93.172818
iter  30 value 86.841858
iter  40 value 85.670212
iter  50 value 85.212541
final  value 85.211922 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.647240 
iter  10 value 93.775012
iter  20 value 93.773993
iter  30 value 93.759473
iter  40 value 92.979399
final  value 88.240912 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.692059 
final  value 94.485990 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.511428 
final  value 94.486035 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.923662 
iter  10 value 93.028125
iter  20 value 90.080852
iter  30 value 89.952694
final  value 89.873245 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.365966 
iter  10 value 94.488782
iter  20 value 94.484051
iter  30 value 93.814884
iter  40 value 85.906042
iter  50 value 83.482144
iter  60 value 83.230238
iter  70 value 83.218839
final  value 83.218463 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.369422 
iter  10 value 94.457491
iter  20 value 94.452000
iter  30 value 94.450686
iter  40 value 94.448069
iter  50 value 87.101806
iter  60 value 86.152608
iter  70 value 86.150958
iter  80 value 86.023005
iter  90 value 85.988187
iter 100 value 85.988047
final  value 85.988047 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 124.023480 
iter  10 value 94.489338
iter  20 value 94.467523
iter  30 value 93.934930
final  value 93.774009 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.023722 
iter  10 value 94.489248
iter  20 value 94.212078
iter  30 value 92.020520
iter  40 value 89.804453
iter  50 value 89.778294
iter  60 value 89.751878
iter  70 value 89.590747
iter  80 value 87.648595
iter  90 value 85.729849
iter 100 value 85.587522
final  value 85.587522 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 116.415409 
iter  10 value 93.040922
iter  20 value 93.036616
iter  30 value 92.882231
iter  40 value 89.891847
iter  50 value 89.332213
iter  60 value 89.076542
iter  70 value 89.076187
iter  80 value 89.076033
final  value 89.075977 
converged
Fitting Repeat 2 

# weights:  507
initial  value 112.276072 
iter  10 value 93.728925
iter  20 value 93.726053
iter  30 value 93.723600
iter  40 value 93.723242
iter  50 value 93.720967
iter  60 value 93.620787
iter  70 value 86.978320
iter  80 value 85.599947
iter  90 value 85.594920
final  value 85.594900 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.510291 
iter  10 value 94.492660
iter  20 value 93.057606
iter  30 value 85.903474
iter  40 value 85.659547
iter  50 value 85.653965
iter  60 value 85.653007
final  value 85.652482 
converged
Fitting Repeat 4 

# weights:  507
initial  value 118.215135 
iter  10 value 93.433336
iter  20 value 92.125244
iter  30 value 91.720300
iter  40 value 91.711586
iter  50 value 91.694900
iter  60 value 91.675275
iter  70 value 91.664328
iter  80 value 89.876864
iter  90 value 89.143167
iter 100 value 89.110026
final  value 89.110026 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.804500 
iter  10 value 94.491493
iter  20 value 94.339797
iter  30 value 89.898812
iter  40 value 89.849214
iter  50 value 89.383504
iter  60 value 89.140620
final  value 89.139858 
converged
Fitting Repeat 1 

# weights:  305
initial  value 135.903104 
iter  10 value 117.870646
iter  20 value 117.690564
iter  30 value 114.829823
final  value 114.740920 
converged
Fitting Repeat 2 

# weights:  305
initial  value 121.057219 
iter  10 value 117.735656
iter  20 value 115.663227
iter  30 value 106.943595
iter  40 value 106.921394
iter  50 value 106.789322
iter  60 value 106.355994
iter  70 value 106.152619
iter  80 value 106.121402
iter  90 value 106.121012
iter 100 value 105.455432
final  value 105.455432 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 119.037347 
iter  10 value 117.763733
iter  20 value 117.758993
iter  30 value 117.758788
final  value 117.758782 
converged
Fitting Repeat 4 

# weights:  305
initial  value 127.045695 
iter  10 value 117.892889
final  value 117.890304 
converged
Fitting Repeat 5 

# weights:  305
initial  value 133.755968 
iter  10 value 117.895193
iter  20 value 117.851732
iter  30 value 116.175396
iter  40 value 114.761261
iter  50 value 111.858086
iter  60 value 109.067041
iter  70 value 107.765477
final  value 107.765350 
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 -- Thu May 21 20:02:52 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 
 19.797   0.645  74.282