CRAN Package Check Results for Package smart

Last updated on 2019-03-24 22:49:57 CET.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 1.0.1 5.90 65.31 71.21 ERROR
r-devel-linux-x86_64-debian-gcc 1.0.1 6.52 52.17 58.69 ERROR
r-devel-linux-x86_64-fedora-clang 1.0.1 91.97 ERROR
r-devel-linux-x86_64-fedora-gcc 1.0.1 86.86 ERROR
r-devel-windows-ix86+x86_64 1.0.1 20.00 101.00 121.00 ERROR
r-patched-linux-x86_64 1.0.1 5.07 65.55 70.62 NOTE
r-patched-solaris-x86 1.0.1 148.90 NOTE
r-release-linux-x86_64 1.0.1 5.02 65.00 70.02 NOTE
r-release-windows-ix86+x86_64 1.0.1 9.00 80.00 89.00 NOTE
r-release-osx-x86_64 1.0.1 NOTE
r-oldrel-windows-ix86+x86_64 1.0.1 8.00 103.00 111.00 NOTE
r-oldrel-osx-x86_64 1.0.1 NOTE

Check Details

Version: 1.0.1
Check: R code for possible problems
Result: NOTE
    TCA: no visible global function definition for 'cov2cor'
    TCA: no visible global function definition for 'flush.console'
    TCE: no visible global function definition for 'cov2cor'
    TCE: no visible global function definition for 'flush.console'
    gnsc.heatmap: no visible binding for global variable 'dist'
    gnsc.heatmap: no visible binding for global variable 'hclust'
    gnsc.heatmap: no visible global function definition for 'par'
    gnsc.heatmap: no visible global function definition for 'median'
    gnsc.heatmap: no visible global function definition for
     'order.dendrogram'
    gnsc.heatmap: no visible global function definition for 'as.dendrogram'
    gnsc.heatmap: no visible global function definition for 'reorder'
    gnsc.heatmap: no visible binding for global variable 'sd'
    gnsc.heatmap: no visible global function definition for 'image'
    gnsc.heatmap: no visible global function definition for 'axis'
    gnsc.heatmap: no visible global function definition for 'mtext'
    gnsc.heatmap: no visible global function definition for 'title'
    gnsc.icov: no visible global function definition for 'cov'
    gnsc.icov: no visible global function definition for 'median'
    gnsc.train: no visible binding for global variable 'sd'
    plot.TCA: no visible global function definition for 'plot'
    plot.TCA: no visible global function definition for 'par'
    plot.TCE: no visible global function definition for 'par'
    plot.TCE: no visible global function definition for 'plot'
    plot.TCE: no visible global function definition for 'lines'
    plot.gnsc: no visible global function definition for 'par'
    plot.gnsc: no visible global function definition for 'plot'
    plot.gnsccv: no visible global function definition for 'par'
    plot.gnsccv: no visible global function definition for 'plot'
    smart.npn: no visible global function definition for 'qnorm'
    smart.npn: no visible global function definition for 'sd'
    smart.npn: no visible global function definition for 'cor'
    Undefined global functions or variables:
     as.dendrogram axis cor cov cov2cor dist flush.console hclust image
     lines median mtext order.dendrogram par plot qnorm reorder sd title
    Consider adding
     importFrom("graphics", "axis", "image", "lines", "mtext", "par",
     "plot", "title")
     importFrom("stats", "as.dendrogram", "cor", "cov", "cov2cor", "dist",
     "hclust", "median", "order.dendrogram", "qnorm", "reorder",
     "sd")
     importFrom("utils", "flush.console")
    to your NAMESPACE file.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-ix86+x86_64, r-patched-linux-x86_64, r-patched-solaris-x86, r-release-linux-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: 1.0.1
Check: examples
Result: ERROR
    Running examples in 'smart-Ex.R' failed
    The error most likely occurred in:
    
    > base::assign(".ptime", proc.time(), pos = "CheckExEnv")
    > ### Name: gnsc.cv
    > ### Title: A function to cross-validate the Group Nearest Shrunken Centroid
    > ### Classifier
    > ### Aliases: gnsc.cv
    >
    > ### ** Examples
    >
    > set.seed(120)
    > x <- matrix(rnorm(1000*20),ncol=20)
    > y <- sample(c(1:4),size=20,replace=TRUE)
    > z <- sample(c(1:10),size=1000,replace=TRUE)
    > fit=gnsc.train(x, col.struc=y, row.struc=z,lambda.max=5, nlambda=20)
    Conducting Group Nearest Shrunken Centroids...
    Conducting Group Nearest Shrunken Centroids... 25 %
    Conducting Group Nearest Shrunken Centroids... 50 %
    Conducting Group Nearest Shrunken Centroids... 75 %
    Conducting Group Nearest Shrunken Centroids... 100 %
    5 %10 %15 %20 %25 %30 %35 %40 %45 %50 %55 %60 %65 %70 %75 %80 %85 %90 %95 %100 %done
    > fit
    Group Nearest Shrunken Centroids Output
    Number of Threshold Values: 20
     threshold nonzero errors
     [1,] 5.0000000 0 0.65
     [2,] 4.4293340 0 0.65
     [3,] 3.9237999 0 0.65
     [4,] 3.4759640 0 0.65
     [5,] 3.0792411 0 0.65
     [6,] 2.7277974 0 0.65
     [7,] 2.4164651 0 0.65
     [8,] 2.1406662 0 0.65
     [9,] 1.8963451 0 0.65
    [10,] 1.6799091 0 0.65
    [11,] 1.4881757 0 0.65
    [12,] 1.3183254 0 0.65
    [13,] 1.1678607 0 0.65
    [14,] 1.0345690 0 0.65
    [15,] 0.9164904 0 0.65
    [16,] 0.8118884 0 0.65
    [17,] 0.7192249 0 0.65
    [18,] 0.6371375 0 0.65
    [19,] 0.5644189 0 0.65
    [20,] 0.5000000 0 0.65
    predicted sample classes:
     5 4.42933395205041 3.92379985175731 3.4759639808878 3.07924105533013
     [1,] 1 1 1 1 1
     [2,] 1 1 1 1 1
     [3,] 1 1 1 1 1
     [4,] 1 1 1 1 1
     [5,] 1 1 1 1 1
     [6,] 1 1 1 1 1
     [7,] 1 1 1 1 1
     [8,] 1 1 1 1 1
     [9,] 1 1 1 1 1
    [10,] 1 1 1 1 1
    [11,] 1 1 1 1 1
    [12,] 1 1 1 1 1
    [13,] 1 1 1 1 1
    [14,] 1 1 1 1 1
    [15,] 1 1 1 1 1
    [16,] 1 1 1 1 1
    [17,] 1 1 1 1 1
    [18,] 1 1 1 1 1
    [19,] 1 1 1 1 1
    [20,] 1 1 1 1 1
     2.72779739058426 2.41646511928588 2.1406661993597 1.89634509536612
     [1,] 1 1 1 1
     [2,] 1 1 1 1
     [3,] 1 1 1 1
     [4,] 1 1 1 1
     [5,] 1 1 1 1
     [6,] 1 1 1 1
     [7,] 1 1 1 1
     [8,] 1 1 1 1
     [9,] 1 1 1 1
    [10,] 1 1 1 1
    [11,] 1 1 1 1
    [12,] 1 1 1 1
    [13,] 1 1 1 1
    [14,] 1 1 1 1
    [15,] 1 1 1 1
    [16,] 1 1 1 1
    [17,] 1 1 1 1
    [18,] 1 1 1 1
    [19,] 1 1 1 1
    [20,] 1 1 1 1
     1.67990914314189 1.48817572081566 1.31832544936518 1.16786073454506
     [1,] 1 1 1 1
     [2,] 1 1 1 1
     [3,] 1 1 1 1
     [4,] 1 1 1 1
     [5,] 1 1 1 1
     [6,] 1 1 1 1
     [7,] 1 1 1 1
     [8,] 1 1 1 1
     [9,] 1 1 1 1
    [10,] 1 1 1 1
    [11,] 1 1 1 1
    [12,] 1 1 1 1
    [13,] 1 1 1 1
    [14,] 1 1 1 1
    [15,] 1 1 1 1
    [16,] 1 1 1 1
    [17,] 1 1 1 1
    [18,] 1 1 1 1
    [19,] 1 1 1 1
    [20,] 1 1 1 1
     1.03456904055739 0.916490355416218 0.811888369594361 0.719224944143832
     [1,] 1 1 1 1
     [2,] 1 1 1 1
     [3,] 1 1 1 1
     [4,] 1 1 1 1
     [5,] 1 1 1 1
     [6,] 1 1 1 1
     [7,] 1 1 1 1
     [8,] 1 1 1 1
     [9,] 1 1 1 1
    [10,] 1 1 1 1
    [11,] 1 1 1 1
    [12,] 1 1 1 1
    [13,] 1 1 1 1
    [14,] 1 1 1 1
    [15,] 1 1 1 1
    [16,] 1 1 1 1
    [17,] 1 1 1 1
    [18,] 1 1 1 1
    [19,] 1 1 1 1
    [20,] 1 1 1 1
     0.637137492851567 0.564418945842345 0.5
     [1,] 1 1 1
     [2,] 1 1 1
     [3,] 1 1 1
     [4,] 1 1 1
     [5,] 1 1 1
     [6,] 1 1 1
     [7,] 1 1 1
     [8,] 1 1 1
     [9,] 1 1 1
    [10,] 1 1 1
    [11,] 1 1 1
    [12,] 1 1 1
    [13,] 1 1 1
    [14,] 1 1 1
    [15,] 1 1 1
    [16,] 1 1 1
    [17,] 1 1 1
    [18,] 1 1 1
    [19,] 1 1 1
    [20,] 1 1 1
    > plot(fit)
    > fit.cv=gnsc.cv(fit,x,y,z)
    Conducting GNSC crossvalidation:
    Conducting GNSC crossvalidation: 5 %
    Error in t(G.x3) %*% inv.cov.mat[[k]] : non-conformable arguments
    Calls: gnsc.cv -> gnsc.predict -> diag
    Execution halted
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc

Version: 1.0.1
Check: examples
Result: ERROR
    Running examples in ‘smart-Ex.R’ failed
    The error most likely occurred in:
    
    > ### Name: gnsc.cv
    > ### Title: A function to cross-validate the Group Nearest Shrunken Centroid
    > ### Classifier
    > ### Aliases: gnsc.cv
    >
    > ### ** Examples
    >
    > set.seed(120)
    > x <- matrix(rnorm(1000*20),ncol=20)
    > y <- sample(c(1:4),size=20,replace=TRUE)
    > z <- sample(c(1:10),size=1000,replace=TRUE)
    > fit=gnsc.train(x, col.struc=y, row.struc=z,lambda.max=5, nlambda=20)
    Conducting Group Nearest Shrunken Centroids...
    Conducting Group Nearest Shrunken Centroids... 25 %
    Conducting Group Nearest Shrunken Centroids... 50 %
    Conducting Group Nearest Shrunken Centroids... 75 %
    Conducting Group Nearest Shrunken Centroids... 100 %
    5 %10 %15 %20 %25 %30 %35 %40 %45 %50 %55 %60 %65 %70 %75 %80 %85 %90 %95 %100 %done
    > fit
    Group Nearest Shrunken Centroids Output
    Number of Threshold Values: 20
     threshold nonzero errors
     [1,] 5.0000000 0 0.65
     [2,] 4.4293340 0 0.65
     [3,] 3.9237999 0 0.65
     [4,] 3.4759640 0 0.65
     [5,] 3.0792411 0 0.65
     [6,] 2.7277974 0 0.65
     [7,] 2.4164651 0 0.65
     [8,] 2.1406662 0 0.65
     [9,] 1.8963451 0 0.65
    [10,] 1.6799091 0 0.65
    [11,] 1.4881757 0 0.65
    [12,] 1.3183254 0 0.65
    [13,] 1.1678607 0 0.65
    [14,] 1.0345690 0 0.65
    [15,] 0.9164904 0 0.65
    [16,] 0.8118884 0 0.65
    [17,] 0.7192249 0 0.65
    [18,] 0.6371375 0 0.65
    [19,] 0.5644189 0 0.65
    [20,] 0.5000000 0 0.65
    predicted sample classes:
     5 4.42933395205041 3.92379985175731 3.4759639808878 3.07924105533013
     [1,] 1 1 1 1 1
     [2,] 1 1 1 1 1
     [3,] 1 1 1 1 1
     [4,] 1 1 1 1 1
     [5,] 1 1 1 1 1
     [6,] 1 1 1 1 1
     [7,] 1 1 1 1 1
     [8,] 1 1 1 1 1
     [9,] 1 1 1 1 1
    [10,] 1 1 1 1 1
    [11,] 1 1 1 1 1
    [12,] 1 1 1 1 1
    [13,] 1 1 1 1 1
    [14,] 1 1 1 1 1
    [15,] 1 1 1 1 1
    [16,] 1 1 1 1 1
    [17,] 1 1 1 1 1
    [18,] 1 1 1 1 1
    [19,] 1 1 1 1 1
    [20,] 1 1 1 1 1
     2.72779739058426 2.41646511928588 2.1406661993597 1.89634509536612
     [1,] 1 1 1 1
     [2,] 1 1 1 1
     [3,] 1 1 1 1
     [4,] 1 1 1 1
     [5,] 1 1 1 1
     [6,] 1 1 1 1
     [7,] 1 1 1 1
     [8,] 1 1 1 1
     [9,] 1 1 1 1
    [10,] 1 1 1 1
    [11,] 1 1 1 1
    [12,] 1 1 1 1
    [13,] 1 1 1 1
    [14,] 1 1 1 1
    [15,] 1 1 1 1
    [16,] 1 1 1 1
    [17,] 1 1 1 1
    [18,] 1 1 1 1
    [19,] 1 1 1 1
    [20,] 1 1 1 1
     1.67990914314189 1.48817572081566 1.31832544936518 1.16786073454506
     [1,] 1 1 1 1
     [2,] 1 1 1 1
     [3,] 1 1 1 1
     [4,] 1 1 1 1
     [5,] 1 1 1 1
     [6,] 1 1 1 1
     [7,] 1 1 1 1
     [8,] 1 1 1 1
     [9,] 1 1 1 1
    [10,] 1 1 1 1
    [11,] 1 1 1 1
    [12,] 1 1 1 1
    [13,] 1 1 1 1
    [14,] 1 1 1 1
    [15,] 1 1 1 1
    [16,] 1 1 1 1
    [17,] 1 1 1 1
    [18,] 1 1 1 1
    [19,] 1 1 1 1
    [20,] 1 1 1 1
     1.03456904055739 0.916490355416218 0.811888369594361 0.719224944143832
     [1,] 1 1 1 1
     [2,] 1 1 1 1
     [3,] 1 1 1 1
     [4,] 1 1 1 1
     [5,] 1 1 1 1
     [6,] 1 1 1 1
     [7,] 1 1 1 1
     [8,] 1 1 1 1
     [9,] 1 1 1 1
    [10,] 1 1 1 1
    [11,] 1 1 1 1
    [12,] 1 1 1 1
    [13,] 1 1 1 1
    [14,] 1 1 1 1
    [15,] 1 1 1 1
    [16,] 1 1 1 1
    [17,] 1 1 1 1
    [18,] 1 1 1 1
    [19,] 1 1 1 1
    [20,] 1 1 1 1
     0.637137492851567 0.564418945842345 0.5
     [1,] 1 1 1
     [2,] 1 1 1
     [3,] 1 1 1
     [4,] 1 1 1
     [5,] 1 1 1
     [6,] 1 1 1
     [7,] 1 1 1
     [8,] 1 1 1
     [9,] 1 1 1
    [10,] 1 1 1
    [11,] 1 1 1
    [12,] 1 1 1
    [13,] 1 1 1
    [14,] 1 1 1
    [15,] 1 1 1
    [16,] 1 1 1
    [17,] 1 1 1
    [18,] 1 1 1
    [19,] 1 1 1
    [20,] 1 1 1
    > plot(fit)
    > fit.cv=gnsc.cv(fit,x,y,z)
    Conducting GNSC crossvalidation:
    Conducting GNSC crossvalidation: 5 %
    Error in t(G.x3) %*% inv.cov.mat[[k]] : non-conformable arguments
    Calls: gnsc.cv -> gnsc.predict -> diag
    Execution halted
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-ix86+x86_64