CRAN Package Check Results for Package msgl

Last updated on 2015-08-04 09:47:26.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 2.0.125.1 17.06 73.87 90.93 NOTE
r-devel-linux-x86_64-debian-gcc 2.0.125.1 17.74 67.69 85.43 NOTE
r-devel-linux-x86_64-fedora-clang 2.0.125.1 190.41 NOTE
r-devel-linux-x86_64-fedora-gcc 2.0.125.1 177.94 NOTE
r-devel-osx-x86_64-clang 2.0.125.1 146.89 OK
r-devel-windows-ix86+x86_64 2.0.125.1 65.00 256.00 321.00 NOTE
r-patched-linux-x86_64 2.0.125.1 17.83 70.83 88.66 OK
r-patched-solaris-sparc 2.0.125.1 1198.50 OK
r-patched-solaris-x86 2.0.125.1 257.80 ERROR
r-release-linux-x86_64 2.0.125.1 17.81 69.88 87.69 OK
r-release-osx-x86_64-mavericks 2.0.125.1 OK
r-release-windows-ix86+x86_64 2.0.125.1 70.00 267.00 337.00 OK
r-oldrel-windows-ix86+x86_64 2.0.125.1 61.00 230.00 291.00 OK

Check Details

Version: 2.0.125.1
Check: R code for possible problems
Result: NOTE
    coef.msgl: no visible global function definition for ‘coef’
    msgl: no visible global function definition for ‘is’
    msgl: no visible global function definition for ‘packageVersion’
    msgl.cv: no visible global function definition for ‘is’
    msgl.cv: no visible global function definition for ‘packageVersion’
    msgl.lambda.seq: no visible global function definition for ‘is’
    msgl.subsampling: no visible global function definition for ‘is’
    msgl.subsampling: no visible global function definition for
     ‘packageVersion’
    predict.msgl: no visible global function definition for ‘is’
    predict.msgl: no visible global function definition for ‘as’
    predict.msgl: no visible global function definition for
     ‘packageVersion’
    Undefined global functions or variables:
     as coef is packageVersion
    Consider adding
     importFrom("methods", "as", "is")
     importFrom("stats", "coef")
     importFrom("utils", "packageVersion")
    to your NAMESPACE.
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

Version: 2.0.125.1
Check: examples
Result: ERROR
    Running examples in ‘msgl-Ex.R’ failed
    The error most likely occurred in:
    
    > ### Name: print.msgl
    > ### Title: Print function for msgl
    > ### Aliases: print.msgl
    >
    > ### ** Examples
    >
    > data(SimData)
    > x <- sim.data$x
    > classes <- sim.data$classes
    >
    > ### Estimation
    > lambda <- msgl.lambda.seq(x, classes, alpha = .5, d = 50, lambda.min = 0.05)
    > fit <- msgl(x, classes, alpha = .5, lambda = lambda)
    
    Running msgl (sparse design matrix)
    
     Samples: Features: Classes: Groups: Parameters:
     100 401 10 401 4010
    
    0 %
    |----|----|----|----|----|----|----|----|----|----|
    **************************************************|
    |
    >
    > # Print some information about the estimated models
    > fit
    
    Call:
    msgl(x = x, classes = classes, alpha = 0.5, lambda = lambda)
    
    Models:
    
     Index: Lambda: Features: Parameters:
     10 0.082 4 23
     20 0.072 11 57
     30 0.064 15 82
     40 0.057 21 117
     50 0.050 24 141
    
    >
    > ### Cross validation
    > fit.cv <- msgl.cv(x, classes, alpha = .5, lambda = lambda)
    Running msgl 10 fold cross validation (dense design matrix)
    
     Samples: Features: Classes: Groups: Parameters:
     100 401 10 401 4010
    
    0 %
    |----|----|----|----|----|----|----|----|----|----|
    **************************************************|
    |
    >
    > # Print some information
    > fit.cv
    
    Call:
    msgl.cv(x = x, classes = classes, alpha = 0.5, lambda = lambda)
    
    Models:
    
     Index: Lambda: Features: Parameters: Error:
     10 0.082 4 23 0.78
     20 0.072 10 55 0.54
     30 0.064 16 87 0.40
     40 0.057 20 113 0.33
     50 0.050 25 144 0.29
    
    Best model:
    
     Index: Lambda: Features: Parameters: Error:
     50 0.05 25 144 0.29
    
    >
    > ### Subsampling
    > test <- list(1:20, 21:40)
    > train <- lapply(test, function(s) (1:length(classes))[-s])
    >
    > lambda <- msgl.lambda.seq(x, classes, alpha = .5, d = 50, lambda.min = 0.05)
    > fit.sub <- msgl.subsampling(x, classes, alpha = .5, lambda = lambda, training = train, test = test)
    Running msgl subsampling with 2 subsamples (dense design matrix)
    
     Samples: Features: Classes: Groups: Parameters:
     100 401 10 401 4010
    
    0 %
    |----|----|----|----|----|----|----|----|----|----|
    **************************************************|
    |
    >
    > # Print some information
    > fit.sub
    
    Call:
    msgl.subsampling(x = x, classes = classes, alpha = 0.5, lambda = lambda,
     training = train, test = test)
    
    Best models:
    
     Subsample: Model index: Lambda: Features: Parameters: Error:
     1 41 0.056 13 72 0.5
     2 46 0.053 13 67 0.4
    
    >
    >
    >
    > ### * <FOOTER>
    > ###
    > options(digits = 7L)
    > base::cat("Time elapsed: ", proc.time() - base::get("ptime", pos = 'CheckExEnv'),"\n")
    Time elapsed: 34.667 1.437 34.511 0 0
    > grDevices::dev.off()
    null device
     1
    > ###
    > ### Local variables: ***
    > ### mode: outline-minor ***
    > ### outline-regexp: "\\(> \\)?### [*]+" ***
    > ### End: ***
    > quit('no')
    
     *** caught segfault ***
    address 4, cause 'memory not mapped'
    
    Traceback:
     1: quit("no")
    aborting ...
Flavor: r-patched-solaris-x86