CRAN Package Check Results for Package MESS

Last updated on 2019-03-18 17:48:20 CET.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.5.5 148.74 82.09 230.83 OK
r-devel-linux-x86_64-debian-gcc 0.5.5 118.23 65.57 183.80 OK
r-devel-linux-x86_64-fedora-clang 0.5.5 346.38 NOTE
r-devel-linux-x86_64-fedora-gcc 0.5.5 315.04 OK
r-devel-windows-ix86+x86_64 0.5.5 339.00 169.00 508.00 NOTE
r-patched-linux-x86_64 0.5.5 143.81 73.11 216.92 OK
r-patched-solaris-x86 0.5.5 309.80 OK
r-release-linux-x86_64 0.5.5 139.98 72.96 212.94 OK
r-release-windows-ix86+x86_64 0.5.5 367.00 119.00 486.00 NOTE
r-release-osx-x86_64 0.5.5 NOTE
r-oldrel-windows-ix86+x86_64 0.5.5 297.00 137.00 434.00 ERROR
r-oldrel-osx-x86_64 0.5.5 NOTE

Check Details

Version: 0.5.5
Check: installed package size
Result: NOTE
     installed size is 8.4Mb
     sub-directories of 1Mb or more:
     data 2.8Mb
     libs 5.3Mb
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-windows-ix86+x86_64, r-release-windows-ix86+x86_64, r-release-osx-x86_64, r-oldrel-windows-ix86+x86_64, r-oldrel-osx-x86_64

Version: 0.5.5
Check: running examples for arch ‘i386’
Result: ERROR
    Running examples in 'MESS-Ex.R' failed
    The error most likely occurred in:
    
    > ### Name: adaptive.weights
    > ### Title: Compute weights for use with adaptive lasso.
    > ### Aliases: adaptive.weights
    > ### Keywords: manip
    >
    > ### ** Examples
    >
    >
    > set.seed(1)
    > x <- matrix(rnorm(50000), nrow=50)
    > y <- rnorm(50, mean=x[,1])
    > weights <- adaptive.weights(x, y)
    Warning in adaptive.weights(x, y) :
     using univariate weight method since p>n
    >
    > if (requireNamespace("glmnet", quietly = TRUE)) {
    + res <- glmnet::glmnet(x, y, penalty.factor=weights$weights)
    + head(res)
    + }
    $a0
     s0 s1 s2 s3 s4 s5
    -0.04508605 -0.04957984 -0.05386937 -0.05796394 -0.06187241 -0.06560323
     s6 s7 s8 s9 s10 s11
    -0.06916447 -0.07256386 -0.07580873 -0.07890612 -0.08186273 -0.08468496
     s12 s13 s14 s15 s16 s17
    -0.08737891 -0.08995042 -0.09240505 -0.09474812 -0.09698468 -0.09911960
     s18 s19 s20 s21 s22 s23
    -0.10115747 -0.10310272 -0.10495956 -0.10673200 -0.10842388 -0.11003887
     s24 s25 s26 s27 s28 s29
    -0.11158045 -0.11305196 -0.11315442 -0.11217988 -0.11124962 -0.11274846
     s30 s31 s32 s33 s34 s35
    -0.11443148 -0.11603803 -0.11757155 -0.11903538 -0.12043268 -0.12176418
     s36 s37 s38 s39 s40 s41
    -0.12382080 -0.12695407 -0.12994621 -0.13174222 -0.13382846 -0.13657833
     s42 s43 s44 s45 s46 s47
    -0.13922019 -0.14174209 -0.14337473 -0.14460048 -0.14587624 -0.14683841
     s48 s49 s50 s51 s52 s53
    -0.14598006 -0.14551800 -0.14515131 -0.14654052 -0.14793854 -0.14703048
     s54 s55 s56 s57 s58 s59
    -0.14544355 -0.14428523 -0.14174165 -0.13935623 -0.13684380 -0.13404860
     s60 s61 s62 s63 s64 s65
    -0.13141279 -0.12866379 -0.12558463 -0.12271573 -0.11982685 -0.11860664
     s66 s67 s68 s69 s70 s71
    -0.11921148 -0.11991105 -0.12072935 -0.12138379 -0.12181416 -0.12216777
     s72 s73 s74 s75 s76 s77
    -0.12250578 -0.12310778 -0.12363399 -0.12307142 -0.12180241 -0.11898919
     s78 s79 s80 s81 s82 s83
    -0.11512734 -0.11186195 -0.11013196 -0.10871956 -0.10687742 -0.10507979
     s84 s85 s86 s87 s88 s89
    -0.10332845 -0.10263582 -0.10141322 -0.09891765 -0.09613616 -0.09343532
     s90 s91 s92 s93 s94 s95
    -0.09082651 -0.08857783 -0.08634300 -0.08379328 -0.08152156 -0.07919755
     s96 s97 s98 s99
    -0.07759747 -0.07633886 -0.07523094 -0.07422980
    
    $beta
    1000 x 100 sparse Matrix of class "dgCMatrix"
    Error in isFALSE(suppRows) : could not find function "isFALSE"
    Calls: print -> print -> .local
    Execution halted
Flavor: r-oldrel-windows-ix86+x86_64

Version: 0.5.5
Check: running examples for arch ‘x64’
Result: ERROR
    Running examples in 'MESS-Ex.R' failed
    The error most likely occurred in:
    
    > ### Name: adaptive.weights
    > ### Title: Compute weights for use with adaptive lasso.
    > ### Aliases: adaptive.weights
    > ### Keywords: manip
    >
    > ### ** Examples
    >
    >
    > set.seed(1)
    > x <- matrix(rnorm(50000), nrow=50)
    > y <- rnorm(50, mean=x[,1])
    > weights <- adaptive.weights(x, y)
    Warning in adaptive.weights(x, y) :
     using univariate weight method since p>n
    >
    > if (requireNamespace("glmnet", quietly = TRUE)) {
    + res <- glmnet::glmnet(x, y, penalty.factor=weights$weights)
    + head(res)
    + }
    $a0
     s0 s1 s2 s3 s4 s5
    -0.04508605 -0.04957984 -0.05386937 -0.05796394 -0.06187241 -0.06560323
     s6 s7 s8 s9 s10 s11
    -0.06916447 -0.07256386 -0.07580873 -0.07890612 -0.08186273 -0.08468496
     s12 s13 s14 s15 s16 s17
    -0.08737891 -0.08995042 -0.09240505 -0.09474812 -0.09698468 -0.09911960
     s18 s19 s20 s21 s22 s23
    -0.10115747 -0.10310272 -0.10495956 -0.10673200 -0.10842388 -0.11003887
     s24 s25 s26 s27 s28 s29
    -0.11158045 -0.11305196 -0.11315442 -0.11217988 -0.11124962 -0.11274846
     s30 s31 s32 s33 s34 s35
    -0.11443148 -0.11603803 -0.11757155 -0.11903538 -0.12043268 -0.12176418
     s36 s37 s38 s39 s40 s41
    -0.12382080 -0.12695407 -0.12994621 -0.13174222 -0.13382846 -0.13657833
     s42 s43 s44 s45 s46 s47
    -0.13922019 -0.14174209 -0.14337473 -0.14460048 -0.14587624 -0.14683841
     s48 s49 s50 s51 s52 s53
    -0.14598006 -0.14551800 -0.14515131 -0.14654052 -0.14793854 -0.14703048
     s54 s55 s56 s57 s58 s59
    -0.14544355 -0.14428523 -0.14174165 -0.13935623 -0.13684380 -0.13404860
     s60 s61 s62 s63 s64 s65
    -0.13141279 -0.12866379 -0.12558463 -0.12271573 -0.11982685 -0.11860664
     s66 s67 s68 s69 s70 s71
    -0.11921148 -0.11991105 -0.12072935 -0.12138379 -0.12181416 -0.12216777
     s72 s73 s74 s75 s76 s77
    -0.12250578 -0.12310778 -0.12363399 -0.12307142 -0.12180241 -0.11898920
     s78 s79 s80 s81 s82 s83
    -0.11512734 -0.11186196 -0.11013196 -0.10871956 -0.10687742 -0.10507979
     s84 s85 s86 s87 s88 s89
    -0.10332845 -0.10263582 -0.10141322 -0.09891765 -0.09613616 -0.09343532
     s90 s91 s92 s93 s94 s95
    -0.09082651 -0.08857783 -0.08634300 -0.08379328 -0.08152156 -0.07919755
     s96 s97 s98 s99
    -0.07759747 -0.07633886 -0.07523094 -0.07422980
    
    $beta
    1000 x 100 sparse Matrix of class "dgCMatrix"
    Error in isFALSE(suppRows) : could not find function "isFALSE"
    Calls: print -> print -> .local
    Execution halted
Flavor: r-oldrel-windows-ix86+x86_64