• using R version 2.8.1 beta (2008-12-12 r47183)
  • using session charset: ISO8859-1
  • checking for file 'stepPlr/DESCRIPTION' ... OK
  • this is package 'stepPlr' version '0.91'
  • checking package name space information ... OK
  • checking package dependencies ... OK
  • checking if this is a source package ... OK
  • checking whether package 'stepPlr' can be installed ... OK
  • checking package directory ... OK
  • checking for portable file names ... OK
  • checking DESCRIPTION meta-information ... OK
  • checking top-level files ... OK
  • checking index information ... OK
  • checking package subdirectories ... OK
  • checking R 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 name space can be loaded with stated dependencies ... OK
  • checking for unstated 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 ... OK
  • checking Rd cross-references ... OK
  • checking for missing documentation entries ... OK
  • checking for code/documentation mismatches ... OK
  • checking Rd \usage sections ... OK
  • checking line endings in C/C++/Fortran sources/headers ... OK
  • checking line endings in Makefiles ... OK
  • checking for portable use of $BLAS_LIBS ... OK
  • creating stepPlr-Ex.R ... OK
  • checking examples ... ERROR
    Running examples in 'stepPlr-Ex.R' failed.
    The error most likely occurred in:

    > ### * cv.step.plr
    >
    > flush(stderr()); flush(stdout())
    >
    > ### Name: cv.step.plr
    > ### Title: Computes cross-validated deviance or prediction errors for
    > ### step.plr
    > ### Aliases: cv.step.plr
    > ### Keywords: models regression
    >
    > ### ** Examples
    >
    > n <- 100
    > p <- 5
    > x <- matrix(sample(seq(3),n*p,replace=TRUE),nrow=n)
    > y <- sample(c(0,1),n,replace=TRUE)
    > level <- vector("list",length=p)
    > for (i in 1:p) level[[i]] <- seq(3)
    > cvfit1 <- cv.step.plr(x,y,level=level,lambda=c(1e-4,1e-2,1),cp="bic")
    *** forward addition ***
    x5 added df= 2.999931 score= 117.8231
    x3 added df= 4.999846 score= 121.1096
    x1 added df= 6.999756 score= 127.5945
    x2 added df= 8.999662 score= 134.3927
    x5 x3 added df= 12.99896 score= 140.6840

    *** backward deletion ***
    x5 x3 deleted df= 8.999662 score= 134.3927
    x2 deleted df= 6.999756 score= 127.5945
    x1 deleted df= 4.999846 score= 121.1096
    x3 deleted df= 2.999931 score= 117.8231
    x5 deleted df= 1 score= 114.8352
    *** forward addition ***
    x5 added df= 2.993156 score= 117.7935
    x3 added df= 4.984667 score= 121.0433
    x1 added df= 6.975783 score= 127.4897
    x2 added df= 8.9664 score= 134.2473
    x5 x3 added df= 12.89850 score= 140.2473

    *** backward deletion ***
    x5 x3 deleted df= 8.9664 score= 134.2473
    x2 deleted df= 6.975783 score= 127.4897
    x1 deleted df= 4.984667 score= 121.0433
    x3 deleted df= 2.993156 score= 117.7935
    x5 deleted df= 1 score= 114.8352
    *** forward addition ***
    x5 added df= 2.508282 score= 116.0509
    x3 added df= 3.960439 score= 117.3763
    x5 x3 added df= 5.991096 score= 119.3122
    x2 added df= 7.381948 score= 122.7997
    x3 x2 added df= 9.188368 score= 125.7508

    *** backward deletion ***
    x3 x2 deleted df= 7.381948 score= 122.7997
    x2 deleted df= 5.991096 score= 119.3122
    x5 x3 deleted df= 3.960439 score= 117.3763
    x3 deleted df= 2.508282 score= 116.0509
    x5 deleted df= 1 score= 114.8352
    CV fold 1
    *** forward addition ***
    x3 added df= 2.999919 score= 114.5661
    x1 added df= 4.999843 score= 119.6972
    x2 added df= 6.999742 score= 125.4378
    x3 x2 added df= 10.77163 score= 128.961
    x5 added df= 12.77034 score= 136.1169

    *** backward deletion ***
    x5 deleted df= 10.77163 score= 128.961
    x1 deleted df= 8.771917 score= 122.7932
    x3 x2 deleted df= 4.999838 score= 120.9765
    x2 deleted df= 2.999919 score= 114.5661
    x3 deleted df= 1 score= 113.4788
    *** forward addition ***
    x3 added df= 2.99198 score= 114.5314
    x1 added df= 4.984385 score= 119.6297
    x2 added df= 6.974366 score= 125.3270
    x3 x2 added df= 10.5513 score= 128.1839
    x5 added df= 12.53452 score= 135.2716

    *** backward deletion ***
    x5 deleted df= 10.5513 score= 128.1839
    x1 deleted df= 8.565505 score= 122.0774
    x3 x2 deleted df= 4.983914 score= 120.9069
    x2 deleted df= 2.99198 score= 114.5314
    x3 deleted df= 1 score= 113.4788
    *** forward addition ***
    x3 added df= 2.468481 score= 112.7832
    x2 x3 added df= 5.309377 score= 115.6502
    x2 added df= 5.867383 score= 117.3046
    x1 added df= 7.237771 score= 120.6122
    x3 x1 added df= 9.056246 score= 124.7564

    *** backward deletion ***
    x3 x1 deleted df= 7.237771 score= 120.6122
    x1 deleted df= 5.867383 score= 117.3046
    x2 x3 deleted df= 3.939127 score= 117.1286
    x2 deleted df= 2.468481 score= 112.7832
    x3 deleted df= 1 score= 113.4788
    CV fold 2
    *** forward addition ***
    x5 added df= 2.999934 score= 116.7101
    x2 added df= 4.999852 score= 121.6404
    x1 added df= 6.999757 score= 125.5874
    x3 added df= 8.999653 score= 132.732
    x5 x1 added df= 12.99898 score= 140.2813

    *** backward deletion ***
    x5 x1 deleted df= 8.999653 score= 132.732
    x3 deleted df= 6.999757 score= 125.5874
    x1 deleted df= 4.999852 score= 121.6404
    x2 deleted df= 2.999934 score= 116.7101
    x5 deleted df= 1 score= 115.0855
    *** forward addition ***
    x5 added df= 2.993397 score= 116.6815
    x2 added df= 4.985293 score= 121.5768
    x1 added df= 6.97587 score= 125.4831
    x5 x1 added df= 10.91515 score= 132.5687
    x4 added df= 12.89474 score= 139.6267

    *** backward deletion ***
    x4 deleted df= 10.91515 score= 132.5687
    x5 x1 deleted df= 6.97587 score= 125.4831
    x1 deleted df= 4.985293 score= 121.5768
    x2 deleted df= 2.993397 score= 116.6815
    x5 deleted df= 1 score= 115.0855
    *** forward addition ***
    x5 added df= 2.517828 score= 115.0246
    x1 x5 added df= 5.53386 score= 117.8717
    x1 added df= 6.106895 score= 119.6273
    x2 added df= 7.474905 score= 121.7764
    x3 added df= 8.817587 score= 126.5162

    *** backward deletion ***
    x3 deleted df= 7.474905 score= 121.7764
    x2 deleted df= 6.106895 score= 119.6273
    x1 x5 deleted df= 4.003534 score= 118.3406
    x1 deleted df= 2.517828 score= 115.0246
    x5 deleted df= 1 score= 115.0855
    CV fold 3
    *** forward addition ***
    x5 added df= 2.999932 score= 115.936
    x3 added df= 4.999849 score= 121.6132
    x1 added df= 6.999768 score= 127.9967
    x4 added df= 8.999673 score= 135.8446
    x2 added df= 10.99955 score= 143.7635

    *** backward deletion ***
    x2 deleted df= 8.999673 score= 135.8446
    x4 deleted df= 6.999768 score= 127.9967
    x1 deleted df= 4.999849 score= 121.6132
    x3 deleted df= 2.999932 score= 115.936
    x5 deleted df= 1 score= 113.4788
    *** forward addition ***
    x5 added df= 2.993262 score= 115.9069
    x3 added df= 4.985004 score= 121.5483
    x1 added df= 6.976938 score= 127.8968
    x4 added df= 8.967487 score= 135.7038
    x2 added df= 10.95554 score= 143.5709

    *** backward deletion ***
    x2 deleted df= 8.967487 score= 135.7038
    x4 deleted df= 6.976938 score= 127.8968
    x1 deleted df= 4.985004 score= 121.5483
    x3 deleted df= 2.993262 score= 115.9069
    x5 deleted df= 1 score= 113.4788
    *** forward addition ***
    x5 added df= 2.510368 score= 114.1831
    x3 added df= 3.964743 score= 117.6392
    x1 added df= 5.423605 score= 121.7789
    x2 x3 added df= 8.094332 score= 126.9488
    x2 added df= 8.679524 score= 129.3296

    *** backward deletion ***
    x1 deleted df= 7.330648 score= 125.0964
    x5 deleted df= 5.984391 score= 122.8226
    x2 x3 deleted df= 3.979336 score= 122.5053
    x2 deleted df= 2.492981 score= 116.1615
    x3 deleted df= 1 score= 113.4788
    CV fold 4
    *** forward addition ***
    x3 added df= 2.999922 score= 116.2175
    x5 added df= 4.999842 score= 121.2104
    x3 x5 added df= 8.714189 score= 126.9471
    x2 x3 added df= 14.47894 score= 133.8267
    x2 added df= 14.51287 score= 133.9750

    *** backward deletion ***
    x3 x5 deleted df= 10.72497 score= 129.1127
    x5 deleted df= 8.727697 score= 123.0723
    x2 x3 deleted df= 4.999849 score= 124.5668
    x2 deleted df= 2.999922 score= 116.2175
    x3 deleted df= 1 score= 112.8229
    *** forward addition ***
    x3 added df= 2.992204 score= 116.1838
    x5 added df= 4.984312 score= 121.1425
    x3 x5 added df= 8.504352 score= 126.1728
    x2 x3 added df= 13.98883 score= 132.0570
    x2 added df= 14.07581 score= 132.4227

    *** backward deletion ***
    x3 x5 deleted df= 10.50706 score= 128.3178
    x5 deleted df= 8.525915 score= 122.3505
    x2 x3 deleted df= 4.984944 score= 124.5016
    x2 deleted df= 2.992204 score= 116.1838
    x3 deleted df= 1 score= 112.8229
    *** forward addition ***
    x3 added df= 2.477002 score= 114.3654
    x2 x3 added df= 5.34318 score= 116.4163
    x2 added df= 5.935558 score= 118.9945
    x5 x3 added df= 8.568087 score= 121.9529
    x5 added df= 9.122191 score= 124.1695

    *** backward deletion ***
    x5 x3 deleted df= 7.316865 score= 122.2257
    x5 deleted df= 5.935558 score= 118.9945
    x2 x3 deleted df= 3.96333 score= 120.4982
    x2 deleted df= 2.477002 score= 114.3654
    x3 deleted df= 1 score= 112.8229
    CV fold 5
    > x,y,lambda=1)
    Error: unexpected ',' in "x,"
    Execution halted