CRAN Package Check Results for Package revengc

Last updated on 2018-11-18 11:51:03 CET.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 1.0.3 5.27 60.04 65.31 OK
r-devel-linux-x86_64-debian-gcc 1.0.3 4.75 45.81 50.56 OK
r-devel-linux-x86_64-fedora-clang 1.0.3 77.74 OK
r-devel-linux-x86_64-fedora-gcc 1.0.3 74.60 OK
r-devel-windows-ix86+x86_64 1.0.3 16.00 82.00 98.00 OK
r-patched-linux-x86_64 1.0.3 4.90 56.92 61.82 OK
r-patched-solaris-x86 1.0.3 103.80 OK
r-release-linux-x86_64 1.0.3 4.76 55.92 60.68 OK
r-release-windows-ix86+x86_64 1.0.3 11.00 83.00 94.00 OK
r-release-osx-x86_64 1.0.3 WARN
r-oldrel-windows-ix86+x86_64 1.0.3 6.00 100.00 106.00 ERROR
r-oldrel-osx-x86_64 1.0.3 ERROR

Check Details

Version: 1.0.3
Check: whether package can be installed
Result: WARN
    Found the following significant warnings:
     Warning: package ‘dplyr’ was built under R version 3.5.1
Flavor: r-release-osx-x86_64

Version: 1.0.3
Check: R code for possible problems
Result: NOTE
    rec: no visible global function definition for 'isFALSE'
    reweight.contingencytable: no visible global function definition for
     'isFALSE'
    Undefined global functions or variables:
     isFALSE
Flavors: r-oldrel-windows-ix86+x86_64, r-oldrel-osx-x86_64

Version: 1.0.3
Check: examples
Result: ERROR
    Running examples in 'revengc-Ex.R' failed
    The error most likely occurred in:
    
    > ### Name: rec
    > ### Title: Reverse engineering censored and decoupled data
    > ### Aliases: rec
    > ### Keywords: Poisson negative binomial univariate table frequency table
    > ### count data censored dispersion truncated contingency
    >
    > ### ** Examples
    >
    > # provide two averages
    > # seed.matrix defaults to a matrix of ones
    > # seed.estimation.method defaults to ipfp
    > twoaverages.results<-rec(
    + X= 4.4,
    + Y = 571.3,
    + Xlowerbound = 1,
    + Xupperbound = 20,
    + Ylowerbound = 520,
    + Yupperbound = 620)
    [1] "Truncated Poisson distributions were calculated for both the X and Y variable (i.e. Var(X) = E(X) and Var(Y) = E(Y) has to be assumed when only averages are provided)"
    [1] "The default seed matrix implies independence between variables 1/(length(Xlowerbound:Xupperbound)*length(Ylowerbound:Yupperbound)) (i.e. independence between variables has to be assumed when there is no external information about the joint distribution)"
    Error in isFALSE(all.equal(sum(seedfinal), 1)) :
     could not find function "isFALSE"
    Calls: rec
    Execution halted
Flavors: r-oldrel-windows-ix86+x86_64, r-oldrel-osx-x86_64