##############################################################################
##############################################################################
###
### 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_1.17.2.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2026-03-20 r89666)
* 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: 2026-03-26 23:58:24 UTC
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.17.2’
* 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
var_imp       17.424  0.183  17.761
corr_plot     17.170  0.122  17.445
FSmethod      16.812  0.119  17.289
pred_ensembel  6.265  0.162   5.728
enrichfindP    0.203  0.040   9.138
* 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-3.23-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 ‘1.17.2’
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (HPiP)

R Under development (unstable) (2026-03-20 r89666) -- "Unsuffered Consequences"
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
avNNet
Loading required package: ggplot2
Loading required package: lattice
Fitting Repeat 1 

# weights:  103
initial  value 98.705697 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.264713 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.846233 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.233846 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.652777 
final  value 94.467391 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.867608 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 96.146463 
iter  10 value 86.933947
iter  20 value 86.638708
iter  30 value 86.636722
final  value 86.636720 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.530142 
iter  10 value 92.970832
iter  20 value 90.946552
iter  30 value 90.939588
final  value 90.939556 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.393317 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 109.170483 
final  value 94.448052 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.918950 
final  value 94.387500 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.785020 
iter  10 value 89.792030
final  value 87.484376 
converged
Fitting Repeat 3 

# weights:  507
initial  value 134.648543 
iter  10 value 94.863962
iter  20 value 94.382560
iter  30 value 94.381618
final  value 94.381571 
converged
Fitting Repeat 4 

# weights:  507
initial  value 105.003136 
final  value 94.467391 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.282810 
final  value 94.467391 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.336766 
iter  10 value 94.502769
iter  20 value 94.405667
iter  30 value 94.163982
iter  40 value 94.133210
iter  50 value 90.800311
iter  60 value 86.870376
iter  70 value 86.130916
iter  80 value 85.655048
iter  90 value 85.239693
final  value 85.236494 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.292185 
iter  10 value 94.488893
iter  20 value 94.365247
iter  30 value 94.287999
iter  40 value 94.276717
iter  50 value 94.004870
iter  60 value 91.097829
iter  70 value 87.091210
iter  80 value 86.044063
iter  90 value 85.297588
iter 100 value 85.078128
final  value 85.078128 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.212517 
iter  10 value 93.803513
iter  20 value 88.193786
iter  30 value 87.120217
iter  40 value 87.010991
iter  50 value 86.614366
iter  60 value 86.102941
iter  70 value 84.541929
iter  80 value 82.791920
iter  90 value 82.212699
iter 100 value 82.180915
final  value 82.180915 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 109.476690 
iter  10 value 94.478243
iter  20 value 94.372121
iter  30 value 92.939857
iter  40 value 92.447789
iter  50 value 92.184601
iter  60 value 92.109069
iter  70 value 92.106722
iter  70 value 92.106721
iter  70 value 92.106721
final  value 92.106721 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.322238 
iter  10 value 92.264240
iter  20 value 89.080451
iter  30 value 86.768301
iter  40 value 85.993571
iter  50 value 85.326190
iter  60 value 85.015632
iter  70 value 84.911573
iter  80 value 83.982531
iter  90 value 82.949681
iter 100 value 82.608818
final  value 82.608818 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 101.032298 
iter  10 value 94.449987
iter  20 value 87.479931
iter  30 value 84.070045
iter  40 value 83.498747
iter  50 value 83.181293
iter  60 value 82.901518
iter  70 value 82.367987
iter  80 value 82.300375
iter  90 value 82.222059
iter 100 value 82.163604
final  value 82.163604 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 115.390453 
iter  10 value 95.468625
iter  20 value 89.409854
iter  30 value 88.476452
iter  40 value 87.142593
iter  50 value 85.645917
iter  60 value 83.970862
iter  70 value 83.136560
iter  80 value 82.730046
iter  90 value 82.435108
iter 100 value 82.412154
final  value 82.412154 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 103.089695 
iter  10 value 94.051026
iter  20 value 87.380098
iter  30 value 86.431841
iter  40 value 85.874469
iter  50 value 85.375792
iter  60 value 85.303024
iter  70 value 85.269761
iter  80 value 85.132920
iter  90 value 83.615779
iter 100 value 82.656516
final  value 82.656516 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.257924 
iter  10 value 94.896604
iter  20 value 93.777378
iter  30 value 93.472872
iter  40 value 87.081360
iter  50 value 84.792889
iter  60 value 83.811931
iter  70 value 83.560237
iter  80 value 83.465792
iter  90 value 83.125781
iter 100 value 82.501814
final  value 82.501814 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 113.228553 
iter  10 value 94.474326
iter  20 value 93.821394
iter  30 value 90.835128
iter  40 value 86.995515
iter  50 value 86.614530
iter  60 value 84.605245
iter  70 value 83.618220
iter  80 value 82.608772
iter  90 value 81.906937
iter 100 value 81.605602
final  value 81.605602 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 123.088243 
iter  10 value 94.614014
iter  20 value 93.691165
iter  30 value 92.310081
iter  40 value 89.306329
iter  50 value 87.476392
iter  60 value 87.104526
iter  70 value 86.284027
iter  80 value 83.273486
iter  90 value 82.452151
iter 100 value 81.391070
final  value 81.391070 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.595257 
iter  10 value 94.789368
iter  20 value 93.739028
iter  30 value 92.995324
iter  40 value 90.434680
iter  50 value 86.651761
iter  60 value 85.606531
iter  70 value 84.219397
iter  80 value 83.007570
iter  90 value 82.255276
iter 100 value 81.994646
final  value 81.994646 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 114.500998 
iter  10 value 94.727054
iter  20 value 94.515667
iter  30 value 94.377133
iter  40 value 92.609325
iter  50 value 85.987266
iter  60 value 85.147438
iter  70 value 84.754611
iter  80 value 84.046391
iter  90 value 82.597845
iter 100 value 81.974639
final  value 81.974639 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 102.875811 
iter  10 value 93.918867
iter  20 value 86.425761
iter  30 value 84.179130
iter  40 value 83.578147
iter  50 value 82.332927
iter  60 value 81.834664
iter  70 value 81.743586
iter  80 value 81.529051
iter  90 value 81.438231
iter 100 value 81.217406
final  value 81.217406 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.984298 
iter  10 value 95.479770
iter  20 value 87.061683
iter  30 value 86.444943
iter  40 value 85.718962
iter  50 value 85.464506
iter  60 value 84.254540
iter  70 value 83.651885
iter  80 value 83.256806
iter  90 value 82.848347
iter 100 value 82.346641
final  value 82.346641 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.414749 
final  value 94.485985 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.730933 
final  value 94.485813 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.444987 
final  value 94.468885 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.635104 
iter  10 value 94.469227
iter  20 value 94.467688
final  value 94.467541 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.032991 
final  value 94.485606 
converged
Fitting Repeat 1 

# weights:  305
initial  value 111.103637 
iter  10 value 94.147654
iter  20 value 94.144171
iter  30 value 91.797919
iter  40 value 89.428100
iter  50 value 89.415290
iter  60 value 89.390193
final  value 89.390158 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.152699 
iter  10 value 94.267855
iter  20 value 94.264126
final  value 94.263011 
converged
Fitting Repeat 3 

# weights:  305
initial  value 126.061493 
iter  10 value 94.489314
iter  20 value 93.714597
iter  30 value 87.978858
iter  40 value 87.970442
iter  50 value 87.939079
iter  60 value 87.476480
iter  70 value 87.425194
iter  80 value 87.422952
iter  90 value 87.418263
iter 100 value 86.275513
final  value 86.275513 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 98.433059 
iter  10 value 94.488700
iter  20 value 94.421054
iter  30 value 86.029711
iter  40 value 85.893032
iter  50 value 85.867382
iter  60 value 84.719380
iter  70 value 84.532196
iter  80 value 83.913124
iter  90 value 83.446586
iter 100 value 82.780032
final  value 82.780032 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 96.749919 
iter  10 value 94.489024
iter  20 value 94.484310
iter  30 value 92.480108
iter  40 value 92.417185
iter  50 value 92.416542
final  value 92.416540 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.474178 
iter  10 value 94.486150
iter  20 value 93.201078
iter  30 value 91.676459
iter  40 value 84.555652
iter  50 value 84.315037
iter  60 value 84.249364
iter  70 value 84.246604
iter  80 value 83.608098
iter  90 value 83.597159
iter 100 value 83.536136
final  value 83.536136 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 99.313467 
iter  10 value 94.490145
iter  20 value 94.388378
iter  30 value 86.091251
iter  40 value 85.133479
iter  50 value 81.520175
iter  60 value 80.690029
iter  70 value 79.908738
iter  80 value 79.698402
iter  90 value 79.437232
iter 100 value 79.367195
final  value 79.367195 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 97.454819 
iter  10 value 94.492118
iter  20 value 94.330726
iter  30 value 88.517374
iter  40 value 88.515820
iter  50 value 86.706188
iter  60 value 86.578237
iter  70 value 86.353361
iter  80 value 85.625986
iter  90 value 85.462822
iter 100 value 85.451945
final  value 85.451945 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 121.808951 
iter  10 value 94.475382
iter  20 value 94.406584
iter  30 value 94.219881
iter  40 value 94.215049
iter  50 value 93.569373
iter  60 value 88.866620
iter  70 value 87.464133
iter  80 value 87.155685
iter  90 value 86.936883
iter 100 value 86.915844
final  value 86.915844 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 100.556377 
iter  10 value 94.303427
iter  20 value 94.292709
iter  30 value 94.289918
iter  40 value 94.050564
iter  50 value 92.449391
iter  60 value 91.838825
iter  70 value 91.693426
iter  80 value 88.008468
iter  90 value 83.656783
iter 100 value 82.680806
final  value 82.680806 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 94.825192 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.734149 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.720060 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.726587 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.785194 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.432413 
iter  10 value 90.758109
iter  20 value 88.420711
iter  30 value 88.402710
iter  40 value 88.296958
final  value 88.295354 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.880382 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.236441 
iter  10 value 93.453027
iter  20 value 89.628516
final  value 89.622788 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.485403 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.086476 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 112.766840 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.123177 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 113.391513 
iter  10 value 94.101551
final  value 94.101525 
converged
Fitting Repeat 4 

# weights:  507
initial  value 100.053521 
iter  10 value 94.354396
iter  10 value 94.354396
iter  10 value 94.354396
final  value 94.354396 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.127411 
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.184153 
iter  10 value 94.476428
iter  20 value 94.039188
iter  30 value 93.921100
iter  40 value 93.910512
iter  50 value 91.705294
iter  60 value 88.123582
iter  70 value 87.155999
iter  80 value 84.715842
iter  90 value 83.987333
iter 100 value 83.746387
final  value 83.746387 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 101.659554 
iter  10 value 94.398083
iter  20 value 89.313517
iter  30 value 86.745039
iter  40 value 86.106684
iter  50 value 85.970415
iter  60 value 85.965290
iter  70 value 85.965020
final  value 85.965013 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.438775 
iter  10 value 94.495637
iter  20 value 94.484687
iter  30 value 93.856773
iter  40 value 89.433633
iter  50 value 87.361157
iter  60 value 87.228924
iter  70 value 86.956013
iter  80 value 86.432763
iter  90 value 86.374504
iter 100 value 86.349328
final  value 86.349328 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.326581 
iter  10 value 94.495364
iter  20 value 94.164734
iter  30 value 93.852744
iter  40 value 93.847352
iter  50 value 93.361122
iter  60 value 87.765924
iter  70 value 85.317217
iter  80 value 84.872351
iter  90 value 84.521573
iter 100 value 84.287661
final  value 84.287661 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.804824 
iter  10 value 94.487983
iter  20 value 94.401533
iter  30 value 94.373458
iter  40 value 90.206774
iter  50 value 86.254198
iter  60 value 84.859125
iter  70 value 84.156937
iter  80 value 83.929513
iter  90 value 83.844323
iter 100 value 83.756970
final  value 83.756970 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 109.173980 
iter  10 value 94.593689
iter  20 value 90.028661
iter  30 value 89.222297
iter  40 value 88.923893
iter  50 value 86.774754
iter  60 value 85.377715
iter  70 value 85.038800
iter  80 value 84.645792
iter  90 value 84.058382
iter 100 value 83.877463
final  value 83.877463 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.086655 
iter  10 value 94.525840
iter  20 value 94.087211
iter  30 value 93.839318
iter  40 value 93.504015
iter  50 value 91.069406
iter  60 value 88.040106
iter  70 value 87.240403
iter  80 value 86.927985
iter  90 value 86.665979
iter 100 value 85.965945
final  value 85.965945 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.110903 
iter  10 value 94.634767
iter  20 value 94.335534
iter  30 value 93.873434
iter  40 value 87.158100
iter  50 value 84.128344
iter  60 value 83.485396
iter  70 value 83.325052
iter  80 value 83.113100
iter  90 value 82.917560
iter 100 value 82.758890
final  value 82.758890 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 99.925640 
iter  10 value 94.595393
iter  20 value 92.960454
iter  30 value 87.693413
iter  40 value 87.532229
iter  50 value 86.165739
iter  60 value 85.627534
iter  70 value 85.108862
iter  80 value 84.792304
iter  90 value 84.286350
iter 100 value 84.131517
final  value 84.131517 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.051549 
iter  10 value 94.454739
iter  20 value 91.600610
iter  30 value 88.294040
iter  40 value 87.113138
iter  50 value 86.298768
iter  60 value 86.169736
iter  70 value 85.600417
iter  80 value 84.269150
iter  90 value 84.182245
iter 100 value 84.035654
final  value 84.035654 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 115.005550 
iter  10 value 94.012201
iter  20 value 89.137274
iter  30 value 86.588891
iter  40 value 86.280795
iter  50 value 85.853646
iter  60 value 85.573682
iter  70 value 85.463201
iter  80 value 85.210578
iter  90 value 85.041064
iter 100 value 84.449374
final  value 84.449374 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 115.685837 
iter  10 value 94.156831
iter  20 value 88.699331
iter  30 value 86.748136
iter  40 value 85.601691
iter  50 value 84.264724
iter  60 value 83.883425
iter  70 value 83.218720
iter  80 value 82.755114
iter  90 value 82.672530
iter 100 value 82.632204
final  value 82.632204 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.298111 
iter  10 value 94.620908
iter  20 value 94.080824
iter  30 value 93.852360
iter  40 value 93.076953
iter  50 value 91.582830
iter  60 value 90.600080
iter  70 value 89.286663
iter  80 value 87.626398
iter  90 value 84.280483
iter 100 value 83.743694
final  value 83.743694 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 117.401382 
iter  10 value 94.992524
iter  20 value 93.529888
iter  30 value 87.051335
iter  40 value 84.853031
iter  50 value 83.633412
iter  60 value 83.508644
iter  70 value 82.957570
iter  80 value 82.741353
iter  90 value 82.662260
iter 100 value 82.510995
final  value 82.510995 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 107.947314 
iter  10 value 96.024799
iter  20 value 93.954917
iter  30 value 93.711698
iter  40 value 92.140027
iter  50 value 87.693340
iter  60 value 85.992880
iter  70 value 85.608130
iter  80 value 85.248648
iter  90 value 85.106536
iter 100 value 84.527527
final  value 84.527527 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.310353 
final  value 94.485714 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.852717 
iter  10 value 94.324502
iter  20 value 94.323851
iter  30 value 91.032199
iter  40 value 89.229477
iter  50 value 89.204567
final  value 89.204347 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.002664 
final  value 94.485960 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.004643 
final  value 94.485679 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.196802 
iter  10 value 94.485828
iter  20 value 94.483670
iter  30 value 93.003821
iter  40 value 90.118693
iter  50 value 90.118280
iter  60 value 90.026823
iter  70 value 90.026207
final  value 90.025702 
converged
Fitting Repeat 1 

# weights:  305
initial  value 111.903572 
iter  10 value 94.489484
final  value 94.484848 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.940563 
iter  10 value 93.793020
iter  20 value 93.785336
iter  30 value 93.780216
iter  40 value 93.752085
iter  50 value 93.694660
final  value 93.694655 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.067981 
iter  10 value 94.488807
iter  20 value 94.484400
iter  30 value 94.389908
iter  40 value 93.611372
iter  50 value 90.296831
iter  60 value 85.721278
iter  70 value 83.499973
iter  80 value 82.558421
iter  90 value 82.499951
iter 100 value 82.465894
final  value 82.465894 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.610905 
iter  10 value 94.360019
iter  20 value 94.104571
iter  30 value 94.006099
iter  40 value 92.060073
iter  50 value 87.863547
iter  60 value 87.623013
iter  70 value 87.622408
iter  80 value 87.621366
iter  80 value 87.621366
iter  80 value 87.621366
final  value 87.621366 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.683187 
iter  10 value 94.359503
iter  20 value 93.833329
iter  30 value 93.788103
iter  40 value 93.777702
final  value 93.777685 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.139425 
iter  10 value 94.491328
iter  20 value 91.231480
iter  30 value 86.492434
iter  40 value 86.486790
final  value 86.486574 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.769545 
iter  10 value 94.362635
iter  20 value 93.972421
iter  30 value 93.770264
iter  40 value 93.698111
final  value 93.694622 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.256353 
iter  10 value 94.117681
iter  20 value 94.112339
iter  30 value 94.110857
iter  40 value 94.110284
iter  50 value 94.104293
iter  60 value 88.179768
iter  70 value 87.686009
iter  80 value 86.918673
final  value 86.698141 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.176150 
iter  10 value 93.002398
iter  20 value 92.999249
iter  30 value 92.996642
iter  40 value 92.552743
iter  50 value 89.130843
iter  60 value 88.998168
iter  70 value 88.966866
iter  80 value 88.958732
iter  90 value 88.958125
iter 100 value 88.957733
final  value 88.957733 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.772743 
iter  10 value 94.492141
iter  20 value 89.093716
iter  30 value 86.362288
iter  40 value 86.332782
iter  50 value 86.327389
final  value 86.327301 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.765985 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.749410 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.854831 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.098159 
iter  10 value 92.949473
final  value 92.945355 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.423737 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.984734 
iter  10 value 92.835520
final  value 92.835473 
converged
Fitting Repeat 2 

# weights:  305
initial  value 111.604957 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.643913 
iter  10 value 92.945356
final  value 92.945355 
converged
Fitting Repeat 4 

# weights:  305
initial  value 113.075219 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.895971 
final  value 94.052911 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.015228 
final  value 93.578659 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.509648 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.779267 
iter  10 value 87.261389
iter  20 value 85.984071
final  value 85.981926 
converged
Fitting Repeat 4 

# weights:  507
initial  value 102.135538 
iter  10 value 92.945355
iter  10 value 92.945355
iter  10 value 92.945355
final  value 92.945355 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.056146 
iter  10 value 93.999280
iter  20 value 93.628893
iter  30 value 93.628455
iter  30 value 93.628454
iter  30 value 93.628454
final  value 93.628454 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.295409 
iter  10 value 94.030087
iter  20 value 93.241790
iter  30 value 93.230890
iter  40 value 93.230497
iter  50 value 93.175292
iter  60 value 92.402176
iter  70 value 91.037200
iter  80 value 85.631529
iter  90 value 85.184426
iter 100 value 84.354949
final  value 84.354949 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.100733 
iter  10 value 87.469747
iter  20 value 85.757864
iter  30 value 84.579476
iter  40 value 83.782156
iter  50 value 83.440990
iter  60 value 83.312324
iter  70 value 83.284586
iter  80 value 83.280506
iter  80 value 83.280506
iter  80 value 83.280506
final  value 83.280506 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.348846 
iter  10 value 94.207483
iter  20 value 94.060662
iter  30 value 94.004812
iter  40 value 93.342468
iter  50 value 93.182451
iter  60 value 93.165814
iter  70 value 91.828986
iter  80 value 86.697877
iter  90 value 85.896507
iter 100 value 84.642462
final  value 84.642462 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 98.023421 
iter  10 value 94.095699
iter  20 value 93.993631
iter  30 value 93.450164
iter  40 value 93.212207
iter  50 value 92.007152
iter  60 value 86.801773
iter  70 value 86.149418
iter  80 value 85.499318
iter  90 value 84.556019
iter 100 value 84.364328
final  value 84.364328 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 96.330037 
iter  10 value 94.055864
iter  20 value 93.254560
iter  30 value 93.230499
iter  40 value 91.575084
iter  50 value 85.572436
iter  60 value 84.267005
iter  70 value 83.198233
iter  80 value 82.924339
iter  90 value 82.759979
iter 100 value 82.727827
final  value 82.727827 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 106.145396 
iter  10 value 95.076253
iter  20 value 87.898448
iter  30 value 85.363869
iter  40 value 84.846157
iter  50 value 84.737635
iter  60 value 84.669220
iter  70 value 84.285232
iter  80 value 82.374702
iter  90 value 81.174306
iter 100 value 80.773512
final  value 80.773512 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.657555 
iter  10 value 94.069583
iter  20 value 88.039609
iter  30 value 85.851705
iter  40 value 84.219961
iter  50 value 83.851087
iter  60 value 83.485561
iter  70 value 83.292359
iter  80 value 82.923628
iter  90 value 80.799119
iter 100 value 80.387997
final  value 80.387997 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 116.317185 
iter  10 value 93.378878
iter  20 value 92.411236
iter  30 value 91.005365
iter  40 value 85.370350
iter  50 value 82.392074
iter  60 value 81.212279
iter  70 value 80.799575
iter  80 value 80.345116
iter  90 value 80.319595
iter 100 value 80.314764
final  value 80.314764 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 110.041153 
iter  10 value 92.918183
iter  20 value 87.247293
iter  30 value 85.490322
iter  40 value 82.627819
iter  50 value 80.943377
iter  60 value 80.521225
iter  70 value 80.225662
iter  80 value 80.110503
iter  90 value 80.081436
iter 100 value 80.073248
final  value 80.073248 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 125.883550 
iter  10 value 94.214336
iter  20 value 93.981418
iter  30 value 89.362429
iter  40 value 87.928803
iter  50 value 84.144952
iter  60 value 82.772245
iter  70 value 81.764630
iter  80 value 80.923457
iter  90 value 80.766470
iter 100 value 80.731526
final  value 80.731526 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 114.342873 
iter  10 value 94.649935
iter  20 value 93.744480
iter  30 value 93.035262
iter  40 value 90.129471
iter  50 value 85.654639
iter  60 value 83.034998
iter  70 value 81.103703
iter  80 value 80.549311
iter  90 value 80.079111
iter 100 value 79.804626
final  value 79.804626 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.610175 
iter  10 value 94.154414
iter  20 value 91.699342
iter  30 value 84.060260
iter  40 value 82.998445
iter  50 value 81.858975
iter  60 value 80.976748
iter  70 value 80.435946
iter  80 value 80.345757
iter  90 value 80.212321
iter 100 value 80.179057
final  value 80.179057 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 119.585175 
iter  10 value 93.960065
iter  20 value 89.704402
iter  30 value 85.795397
iter  40 value 83.924165
iter  50 value 82.811005
iter  60 value 82.325146
iter  70 value 81.391975
iter  80 value 81.110296
iter  90 value 80.442720
iter 100 value 80.045289
final  value 80.045289 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 108.770305 
iter  10 value 93.439141
iter  20 value 92.719760
iter  30 value 90.183914
iter  40 value 87.936193
iter  50 value 86.091558
iter  60 value 85.437505
iter  70 value 83.613735
iter  80 value 81.411561
iter  90 value 80.951434
iter 100 value 80.503024
final  value 80.503024 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 102.643894 
iter  10 value 88.270779
iter  20 value 84.805030
iter  30 value 84.219690
iter  40 value 82.849291
iter  50 value 82.308929
iter  60 value 81.603983
iter  70 value 80.659007
iter  80 value 80.338821
iter  90 value 80.251094
iter 100 value 80.231979
final  value 80.231979 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 105.384360 
final  value 94.054395 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.842136 
final  value 94.054461 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.564141 
iter  10 value 94.054318
iter  20 value 94.051539
iter  30 value 85.273903
iter  40 value 85.031146
iter  50 value 85.030634
final  value 85.030632 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.732062 
iter  10 value 94.052941
final  value 94.052914 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.513777 
iter  10 value 94.054630
final  value 94.052946 
converged
Fitting Repeat 1 

# weights:  305
initial  value 126.839488 
iter  10 value 93.583502
iter  20 value 93.370727
iter  30 value 86.412170
iter  40 value 85.825308
iter  50 value 85.814555
iter  60 value 85.433744
iter  70 value 85.294652
final  value 85.293939 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.725123 
iter  10 value 94.136653
iter  20 value 92.619138
iter  30 value 92.597802
iter  40 value 92.528036
iter  50 value 91.979775
iter  60 value 91.974514
iter  70 value 91.929463
iter  80 value 91.726350
iter  90 value 91.283439
iter 100 value 91.282021
final  value 91.282021 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 97.429545 
iter  10 value 92.950830
iter  20 value 92.947644
iter  30 value 92.936801
final  value 92.935899 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.113171 
iter  10 value 94.057430
final  value 94.053368 
converged
Fitting Repeat 5 

# weights:  305
initial  value 101.713759 
iter  10 value 93.663989
iter  20 value 92.954650
iter  30 value 92.948920
iter  40 value 92.602107
iter  50 value 85.014829
iter  60 value 83.951793
iter  70 value 80.330584
iter  80 value 79.940689
iter  90 value 79.933150
iter 100 value 79.900894
final  value 79.900894 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.664581 
iter  10 value 89.771629
iter  20 value 82.371526
iter  30 value 82.136423
iter  40 value 82.122679
iter  50 value 82.118279
iter  60 value 82.092028
iter  70 value 82.081447
iter  80 value 82.081193
iter  90 value 82.013609
iter 100 value 81.768915
final  value 81.768915 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 97.085195 
iter  10 value 94.061048
iter  20 value 94.052122
iter  30 value 90.176687
iter  40 value 89.704542
iter  50 value 85.479576
final  value 85.462022 
converged
Fitting Repeat 3 

# weights:  507
initial  value 114.927290 
iter  10 value 92.954922
iter  20 value 92.950673
iter  30 value 92.882718
iter  40 value 91.559044
iter  50 value 85.118113
iter  60 value 83.911701
final  value 83.866248 
converged
Fitting Repeat 4 

# weights:  507
initial  value 110.390980 
iter  10 value 94.060600
iter  20 value 86.459496
iter  30 value 85.023351
iter  40 value 83.723022
iter  50 value 83.077149
iter  60 value 82.620762
iter  70 value 82.620379
final  value 82.620372 
converged
Fitting Repeat 5 

# weights:  507
initial  value 99.618547 
iter  10 value 92.994996
iter  20 value 92.956694
iter  30 value 92.895836
iter  40 value 92.890788
iter  50 value 90.314983
iter  60 value 87.254830
iter  70 value 87.250436
final  value 87.250226 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.852682 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.251715 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.953590 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.070499 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 103.018788 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.241885 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 98.821428 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.572945 
final  value 94.038251 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.598014 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 103.653614 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.026713 
final  value 94.038251 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.520864 
iter  10 value 93.202792
iter  20 value 85.614702
final  value 85.614286 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.666339 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 97.031613 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 123.623281 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.303634 
iter  10 value 93.999356
iter  20 value 92.286450
iter  30 value 90.853086
iter  40 value 83.751671
iter  50 value 83.185639
iter  60 value 82.192101
iter  70 value 80.324897
iter  80 value 79.750058
final  value 79.749938 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.053126 
iter  10 value 94.058348
iter  20 value 93.927365
iter  30 value 91.475679
iter  40 value 90.954817
iter  50 value 89.674516
iter  60 value 88.690418
iter  70 value 87.282120
iter  80 value 80.730983
iter  90 value 80.537505
iter 100 value 80.080438
final  value 80.080438 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.849995 
iter  10 value 93.999604
iter  20 value 92.214102
iter  30 value 86.452770
iter  40 value 84.649951
iter  50 value 83.607399
iter  60 value 82.439909
iter  70 value 82.237670
iter  80 value 80.926637
iter  90 value 80.106695
iter 100 value 79.750234
final  value 79.750234 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 98.737244 
iter  10 value 93.553388
iter  20 value 84.008931
iter  30 value 82.226306
iter  40 value 81.794195
iter  50 value 80.507096
iter  60 value 79.564746
iter  70 value 79.341384
final  value 79.339922 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.920396 
iter  10 value 94.033136
iter  20 value 89.539700
iter  30 value 83.140609
iter  40 value 82.738472
iter  50 value 82.289179
iter  60 value 81.609341
iter  70 value 78.731170
iter  80 value 78.560124
iter  90 value 78.354669
iter 100 value 78.322185
final  value 78.322185 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 110.932557 
iter  10 value 94.082509
iter  20 value 90.423932
iter  30 value 90.223606
iter  40 value 81.001100
iter  50 value 80.243843
iter  60 value 79.632884
iter  70 value 79.438925
iter  80 value 79.426406
iter  90 value 79.351309
iter 100 value 78.711752
final  value 78.711752 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.730746 
iter  10 value 94.068571
iter  20 value 93.113340
iter  30 value 83.400372
iter  40 value 82.774447
iter  50 value 81.595486
iter  60 value 79.809656
iter  70 value 79.074919
iter  80 value 78.766104
iter  90 value 77.803557
iter 100 value 77.405849
final  value 77.405849 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 110.189229 
iter  10 value 94.088907
iter  20 value 93.659844
iter  30 value 80.736615
iter  40 value 80.545184
iter  50 value 80.112913
iter  60 value 78.389562
iter  70 value 77.439468
iter  80 value 76.867084
iter  90 value 76.678642
iter 100 value 76.522302
final  value 76.522302 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 111.016853 
iter  10 value 94.063246
iter  20 value 83.293138
iter  30 value 79.732583
iter  40 value 79.616479
iter  50 value 79.583303
iter  60 value 78.998303
iter  70 value 77.834388
iter  80 value 77.725721
iter  90 value 77.503970
iter 100 value 77.056437
final  value 77.056437 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.708906 
iter  10 value 93.933826
iter  20 value 83.678792
iter  30 value 81.153998
iter  40 value 80.942698
iter  50 value 80.843057
iter  60 value 80.548948
iter  70 value 78.477770
iter  80 value 78.241048
iter  90 value 77.277427
iter 100 value 77.045940
final  value 77.045940 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.728825 
iter  10 value 95.824335
iter  20 value 90.574720
iter  30 value 84.366586
iter  40 value 82.875961
iter  50 value 79.588832
iter  60 value 77.600673
iter  70 value 77.102804
iter  80 value 76.759926
iter  90 value 76.714574
iter 100 value 76.621344
final  value 76.621344 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 111.963536 
iter  10 value 90.845640
iter  20 value 82.366589
iter  30 value 80.299696
iter  40 value 79.622685
iter  50 value 78.702240
iter  60 value 77.555902
iter  70 value 77.278616
iter  80 value 76.758824
iter  90 value 76.689902
iter 100 value 76.681913
final  value 76.681913 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 127.707215 
iter  10 value 94.116241
iter  20 value 91.135238
iter  30 value 89.478744
iter  40 value 88.835636
iter  50 value 85.895876
iter  60 value 84.367714
iter  70 value 83.174295
iter  80 value 79.992616
iter  90 value 77.305263
iter 100 value 76.784618
final  value 76.784618 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 107.846579 
iter  10 value 94.733104
iter  20 value 92.935966
iter  30 value 92.269122
iter  40 value 89.566712
iter  50 value 83.872916
iter  60 value 82.449208
iter  70 value 81.425540
iter  80 value 79.725221
iter  90 value 79.544379
iter 100 value 78.922646
final  value 78.922646 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 110.015022 
iter  10 value 94.844973
iter  20 value 90.472538
iter  30 value 84.942998
iter  40 value 83.888416
iter  50 value 80.134243
iter  60 value 79.190641
iter  70 value 78.957178
iter  80 value 78.551002
iter  90 value 78.389641
iter 100 value 77.982667
final  value 77.982667 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.307193 
iter  10 value 91.255235
iter  20 value 91.254428
iter  30 value 90.871551
iter  40 value 88.163747
iter  50 value 82.061031
iter  60 value 81.906556
iter  70 value 81.414134
iter  80 value 80.721842
iter  90 value 80.456026
iter 100 value 80.453972
final  value 80.453972 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 104.312074 
final  value 94.054360 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.434568 
final  value 94.054909 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.906907 
final  value 94.054729 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.819207 
final  value 94.054496 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.614085 
iter  10 value 94.045327
iter  20 value 94.040550
iter  30 value 93.929819
iter  40 value 91.054578
iter  50 value 90.912296
iter  60 value 90.910054
iter  70 value 90.908339
iter  80 value 90.908137
iter  90 value 90.907722
iter 100 value 90.144437
final  value 90.144437 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.366291 
iter  10 value 94.057447
iter  20 value 91.325369
iter  30 value 87.547968
iter  40 value 87.497221
iter  50 value 82.280279
iter  60 value 82.276681
iter  70 value 82.275893
final  value 82.275861 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.514406 
iter  10 value 93.840636
iter  20 value 93.416447
iter  30 value 85.432622
iter  40 value 84.227385
iter  50 value 84.223514
final  value 84.223486 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.071088 
iter  10 value 94.058170
iter  20 value 94.053108
iter  30 value 93.976658
iter  40 value 90.946172
iter  50 value 90.930968
iter  60 value 90.462128
iter  70 value 88.480947
iter  80 value 88.477964
iter  90 value 88.461350
iter 100 value 88.406750
final  value 88.406750 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 105.346688 
iter  10 value 91.258674
iter  20 value 91.256871
iter  30 value 91.253917
iter  30 value 91.253917
iter  30 value 91.253917
final  value 91.253917 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.481260 
iter  10 value 94.060958
iter  20 value 94.052720
iter  30 value 91.080792
iter  40 value 91.063253
iter  50 value 83.097680
iter  60 value 82.761487
iter  70 value 82.682761
iter  80 value 81.857926
iter  90 value 81.126917
iter 100 value 81.120913
final  value 81.120913 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 101.763653 
iter  10 value 94.060455
iter  20 value 93.700942
iter  30 value 89.860977
iter  40 value 89.856564
iter  50 value 89.734740
iter  60 value 89.729834
iter  70 value 82.200213
iter  80 value 81.158618
iter  90 value 81.144441
iter 100 value 80.216600
final  value 80.216600 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 101.220147 
iter  10 value 92.745093
iter  20 value 92.277710
iter  30 value 82.444731
iter  40 value 78.464081
iter  50 value 77.345613
iter  60 value 76.779239
iter  70 value 76.574265
iter  80 value 76.569576
final  value 76.568863 
converged
Fitting Repeat 4 

# weights:  507
initial  value 111.789616 
iter  10 value 94.060550
iter  20 value 92.363879
iter  30 value 85.886422
iter  40 value 85.627043
iter  50 value 85.626537
iter  60 value 84.994274
iter  70 value 84.062083
iter  80 value 84.059315
iter  90 value 84.058295
iter 100 value 84.058139
final  value 84.058139 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 98.322102 
iter  10 value 94.061217
iter  20 value 90.632111
iter  30 value 86.625405
iter  40 value 79.988902
iter  50 value 78.820774
iter  60 value 78.815929
final  value 78.815750 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.169654 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.909866 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 119.232743 
iter  10 value 94.482197
iter  20 value 94.480526
final  value 94.480521 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.102608 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.791653 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.436487 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.442766 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 111.931208 
final  value 94.275362 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.753767 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 110.510942 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.671417 
iter  10 value 92.268563
iter  20 value 91.323787
iter  30 value 91.321541
iter  40 value 91.320835
iter  40 value 91.320835
iter  40 value 91.320835
final  value 91.320835 
converged
Fitting Repeat 2 

# weights:  507
initial  value 121.230515 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.994374 
final  value 94.338745 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.646050 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.907290 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.758552 
iter  10 value 88.981266
iter  20 value 85.328012
iter  30 value 85.144913
iter  40 value 84.783856
iter  50 value 84.167348
iter  60 value 83.207569
iter  70 value 81.788027
iter  80 value 80.417539
iter  90 value 80.289006
iter 100 value 80.287866
final  value 80.287866 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 99.192491 
iter  10 value 93.614495
iter  20 value 85.145831
iter  30 value 84.171179
iter  40 value 83.839492
iter  50 value 83.103163
iter  60 value 82.766864
iter  70 value 81.123473
iter  80 value 80.324484
iter  90 value 80.261057
iter 100 value 80.190712
final  value 80.190712 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 103.507176 
iter  10 value 94.489558
iter  20 value 94.476919
iter  30 value 94.247873
iter  40 value 94.233029
iter  50 value 94.214705
iter  60 value 86.922887
iter  70 value 82.421843
iter  80 value 82.194038
iter  90 value 81.594341
iter 100 value 80.984947
final  value 80.984947 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.569679 
iter  10 value 94.416413
iter  20 value 92.288734
iter  30 value 90.130819
iter  40 value 89.631141
iter  50 value 89.568961
iter  60 value 85.226895
iter  70 value 83.604638
iter  80 value 83.054904
iter  90 value 82.691630
iter 100 value 80.916730
final  value 80.916730 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 118.113058 
iter  10 value 93.852439
iter  20 value 85.103347
iter  30 value 83.748967
iter  40 value 81.980305
iter  50 value 80.735587
iter  60 value 80.438694
iter  70 value 80.203293
final  value 80.190682 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.772952 
iter  10 value 94.018519
iter  20 value 87.946835
iter  30 value 85.308165
iter  40 value 83.891797
iter  50 value 81.273515
iter  60 value 80.313141
iter  70 value 79.453894
iter  80 value 79.182304
iter  90 value 78.832480
iter 100 value 78.733212
final  value 78.733212 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 109.859083 
iter  10 value 94.679640
iter  20 value 94.484992
iter  30 value 93.876599
iter  40 value 88.779712
iter  50 value 86.055777
iter  60 value 84.197761
iter  70 value 82.348586
iter  80 value 81.594427
iter  90 value 80.881230
iter 100 value 80.316772
final  value 80.316772 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 104.461445 
iter  10 value 94.490132
iter  20 value 93.418795
iter  30 value 86.616402
iter  40 value 85.114325
iter  50 value 81.535342
iter  60 value 79.991481
iter  70 value 79.689403
iter  80 value 79.234022
iter  90 value 78.573726
iter 100 value 78.400830
final  value 78.400830 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.398354 
iter  10 value 94.606608
iter  20 value 94.270815
iter  30 value 92.650890
iter  40 value 90.603138
iter  50 value 85.531055
iter  60 value 84.179250
iter  70 value 82.121272
iter  80 value 81.243881
iter  90 value 79.559588
iter 100 value 79.094083
final  value 79.094083 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 103.895952 
iter  10 value 94.514890
iter  20 value 89.059290
iter  30 value 87.345470
iter  40 value 85.291349
iter  50 value 84.476836
iter  60 value 83.226508
iter  70 value 81.583727
iter  80 value 80.526633
iter  90 value 79.500501
iter 100 value 78.969953
final  value 78.969953 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 114.312180 
iter  10 value 94.536802
iter  20 value 94.351254
iter  30 value 93.751512
iter  40 value 85.810206
iter  50 value 84.389126
iter  60 value 82.835897
iter  70 value 81.717756
iter  80 value 81.462636
iter  90 value 81.401093
iter 100 value 81.108262
final  value 81.108262 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.599490 
iter  10 value 94.581459
iter  20 value 89.827769
iter  30 value 85.942772
iter  40 value 84.575837
iter  50 value 84.224921
iter  60 value 84.091961
iter  70 value 83.097424
iter  80 value 80.700722
iter  90 value 80.049897
iter 100 value 79.795158
final  value 79.795158 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 121.489265 
iter  10 value 94.891223
iter  20 value 94.501332
iter  30 value 92.502213
iter  40 value 91.779182
iter  50 value 87.818824
iter  60 value 82.276222
iter  70 value 81.612440
iter  80 value 81.106163
iter  90 value 80.722304
iter 100 value 80.611618
final  value 80.611618 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.479586 
iter  10 value 93.188175
iter  20 value 92.415161
iter  30 value 87.365193
iter  40 value 86.012838
iter  50 value 84.951960
iter  60 value 82.703911
iter  70 value 81.834465
iter  80 value 81.488746
iter  90 value 80.708382
iter 100 value 80.460559
final  value 80.460559 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 118.823078 
iter  10 value 91.338670
iter  20 value 82.058194
iter  30 value 81.338770
iter  40 value 80.080961
iter  50 value 79.206143
iter  60 value 78.806545
iter  70 value 78.763036
iter  80 value 78.286376
iter  90 value 78.098470
iter 100 value 78.005666
final  value 78.005666 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.830872 
final  value 94.485561 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.985679 
final  value 94.485727 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.975788 
final  value 94.276832 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.233200 
final  value 94.485764 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.793317 
iter  10 value 94.277314
iter  20 value 94.276642
iter  30 value 90.394763
iter  40 value 85.802196
final  value 85.786323 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.047655 
iter  10 value 94.489273
iter  20 value 94.261302
iter  30 value 88.294314
iter  40 value 87.243718
iter  50 value 87.200238
iter  60 value 86.239509
iter  70 value 86.089387
iter  80 value 85.244482
iter  90 value 85.244121
iter 100 value 83.343414
final  value 83.343414 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.888992 
iter  10 value 94.280197
iter  20 value 94.278871
iter  30 value 94.276995
iter  40 value 92.730177
iter  50 value 90.116492
iter  60 value 85.291630
iter  70 value 85.262642
final  value 85.262600 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.115147 
iter  10 value 94.488656
iter  20 value 94.484223
iter  30 value 90.077389
iter  40 value 85.090933
iter  50 value 85.085789
iter  60 value 85.084103
iter  70 value 85.081944
iter  80 value 84.852889
iter  90 value 83.157086
iter 100 value 82.851914
final  value 82.851914 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 95.934562 
iter  10 value 94.280792
iter  20 value 94.195109
final  value 94.164258 
converged
Fitting Repeat 5 

# weights:  305
initial  value 104.601890 
iter  10 value 94.280342
iter  20 value 94.275805
iter  30 value 94.197235
iter  40 value 85.363341
iter  50 value 83.803089
iter  60 value 83.747900
iter  70 value 83.571254
final  value 83.571084 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.201174 
iter  10 value 94.492274
iter  20 value 86.711300
iter  30 value 84.548805
iter  40 value 81.853297
iter  50 value 76.894364
iter  60 value 76.751728
iter  70 value 76.745168
final  value 76.744008 
converged
Fitting Repeat 2 

# weights:  507
initial  value 112.926735 
iter  10 value 90.708604
iter  20 value 86.342451
iter  30 value 86.329497
iter  40 value 82.617608
iter  50 value 81.560231
iter  60 value 78.995334
iter  70 value 78.954420
iter  80 value 78.953764
iter  90 value 78.952163
iter 100 value 78.952065
final  value 78.952065 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 119.421395 
iter  10 value 94.492285
iter  20 value 94.427426
iter  30 value 84.325172
iter  40 value 82.937619
iter  50 value 81.800044
iter  60 value 80.907015
iter  70 value 79.896160
iter  80 value 79.882962
final  value 79.882111 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.604394 
iter  10 value 94.492328
iter  20 value 94.487787
iter  30 value 94.468675
iter  40 value 89.290698
iter  50 value 87.940802
iter  60 value 85.301029
iter  70 value 85.290443
iter  80 value 85.264273
iter  90 value 85.201438
iter 100 value 83.475809
final  value 83.475809 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 112.111460 
iter  10 value 94.173571
iter  20 value 92.673046
iter  30 value 84.680406
iter  40 value 83.078678
iter  50 value 80.855046
iter  60 value 80.083931
iter  70 value 78.151128
iter  80 value 77.617443
iter  90 value 77.591674
iter 100 value 77.591308
final  value 77.591308 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 121.070211 
iter  10 value 117.894951
iter  20 value 117.881414
iter  30 value 110.458448
iter  40 value 107.379618
iter  50 value 107.170439
iter  60 value 105.351340
iter  70 value 105.258517
final  value 105.258333 
converged
Fitting Repeat 2 

# weights:  103
initial  value 125.557588 
iter  10 value 117.875327
iter  20 value 117.790447
iter  30 value 117.786892
iter  40 value 117.563076
iter  50 value 115.808551
iter  60 value 115.015219
iter  70 value 114.399619
iter  80 value 114.085680
iter  90 value 113.980108
iter 100 value 113.972538
final  value 113.972538 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 128.984773 
iter  10 value 117.871356
iter  20 value 111.057631
iter  30 value 107.430689
iter  40 value 107.233998
iter  50 value 105.135302
iter  60 value 104.780845
iter  70 value 104.775485
final  value 104.775465 
converged
Fitting Repeat 4 

# weights:  103
initial  value 121.710908 
iter  10 value 117.885304
iter  20 value 116.332508
iter  30 value 115.605411
iter  40 value 115.086720
iter  50 value 105.503766
iter  60 value 104.770119
iter  70 value 103.212834
iter  80 value 103.065528
iter  90 value 102.605295
iter 100 value 102.327545
final  value 102.327545 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 133.648694 
iter  10 value 117.767271
iter  20 value 112.595179
iter  30 value 111.063765
iter  40 value 110.399027
iter  50 value 108.036992
iter  60 value 106.781841
iter  70 value 106.762718
final  value 106.762713 
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 Mar 26 20:01:43 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 
 20.116   0.764  84.997