CRAN Package Check Results for Package vcdExtra

Last updated on 2015-05-24 14:47:14.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.6-8 3.82 78.20 82.01 OK
r-devel-linux-x86_64-debian-gcc 0.6-8 4.29 76.26 80.54 OK
r-devel-linux-x86_64-fedora-clang 0.6-8 168.26 OK
r-devel-linux-x86_64-fedora-gcc 0.6-8 160.53 OK
r-devel-osx-x86_64-clang 0.6-8 137.81 OK
r-devel-windows-ix86+x86_64 0.6-8 11.00 116.00 127.00 OK
r-patched-linux-x86_64 0.6-8 3.73 77.53 81.26 OK
r-patched-solaris-sparc 0.6-8 932.20 OK
r-patched-solaris-x86 0.6-8 203.70 OK
r-release-linux-x86_64 0.6-8 4.02 79.28 83.30 OK
r-release-osx-x86_64-mavericks 0.6-8 NOTE
r-release-osx-x86_64-snowleopard 0.6-8 ERROR
r-release-windows-ix86+x86_64 0.6-8 10.00 115.00 125.00 OK
r-oldrel-windows-ix86+x86_64 0.6-8 14.00 128.00 142.00 OK

Check Details

Version: 0.6-8
Check: package dependencies
Result: NOTE
    Package suggested but not available for checking: ‘AER’
Flavor: r-release-osx-x86_64-mavericks

Version: 0.6-8
Check: package dependencies
Result: NOTE
    Packages suggested but not available for checking:
     ‘lmtest’ ‘ggplot2’ ‘car’ ‘AER’
Flavor: r-release-osx-x86_64-snowleopard

Version: 0.6-8
Check: Rd cross-references
Result: NOTE
    Packages unavailable to check Rd xrefs: ‘alr3’, ‘Hmisc’
Flavor: r-release-osx-x86_64-snowleopard

Version: 0.6-8
Check: examples
Result: ERROR
    Running examples in ‘vcdExtra-Ex.R’ failed
    The error most likely occurred in:
    
    > ### Name: Accident
    > ### Title: Traffic Accident Victims in France in 1958
    > ### Aliases: Accident
    > ### Keywords: datasets
    >
    > ### ** Examples
    >
    > # examples
    > data(Accident)
    > head(Accident)
     age result mode gender Freq
    1 50+ Died Pedestrian Male 704
    2 50+ Died Pedestrian Female 378
    3 50+ Died Bicycle Male 396
    4 50+ Died Bicycle Female 56
    5 50+ Died Motorcycle Male 742
    6 50+ Died Motorcycle Female 78
    >
    > # for graphs, reorder mode
    > Accident$mode <- ordered(Accident$mode,
    + levels=levels(Accident$mode)[c(4,2,3,1)])
    >
    > # Bertin's table
    > accident_tab <- xtabs(Freq ~ gender+mode+age+result, data=Accident)
    > structable(mode+gender ~ age+result, data=accident_tab)
     mode Pedestrian Bicycle Motorcycle 4-Wheeled
     gender Female Male Female Male Female Male Female Male
    age result
    0-9 Died 89 150 5 26 6 6 65 70
     Injured 1967 3341 126 378 131 181 1362 1593
    10-19 Died 28 70 31 76 54 362 61 150
     Injured 1495 1827 7218 3407 3587 12311 2593 3543
    20-29 Died 24 78 10 55 82 660 107 353
     Injured 864 1521 609 1565 4010 18558 4361 9084
    30-49 Died 49 223 24 146 98 889 199 720
     Injured 1814 3178 1118 3024 3664 18909 7712 15086
    50+ Died 378 704 56 396 78 742 253 513
     Injured 5449 5206 1030 3863 1387 8597 5552 7423
    >
    > ## Loglinear models
    > ## ----------------
    >
    > # mutual independence
    > acc.mod0 <- glm(Freq ~ age+result+mode+gender, data=Accident, family=poisson)
    > Summarise(acc.mod0)
    Likelihood summary table:
     AIC BIC LR Chisq Df Pr(>Chisq)
    acc.mod0 60983 61007 60320 70 < 2.2e-16 ***
    ---
    Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
    > mosaic(acc.mod0, ~mode+age+gender+result)
    >
    > # result as a response
    > acc.mod1 <- glm(Freq ~ age*mode*gender + result, data=Accident, family=poisson)
    > Summarise(acc.mod1)
    Likelihood summary table:
     AIC BIC LR Chisq Df Pr(>Chisq)
    acc.mod1 2942.4 3040.1 2217.7 39 < 2.2e-16 ***
    ---
    Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
    > mosaic(acc.mod1, ~mode+age+gender+result,
    + labeling_args = list(abbreviate = c(gender=1, result=4)))
    >
    > # allow two-way association of result with each explanatory variable
    > acc.mod2 <- glm(Freq ~ age*mode*gender + result*(age+mode+gender), data=Accident, family=poisson)
    > Summarise(acc.mod2)
    Likelihood summary table:
     AIC BIC LR Chisq Df Pr(>Chisq)
    acc.mod2 968.13 1084.8 227.47 31 < 2.2e-16 ***
    ---
    Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
    > mosaic(acc.mod2, ~mode+age+gender+result,
    + labeling_args = list(abbreviate = c(gender=1, result=4)))
    >
    > acc.mods <- glmlist(acc.mod0, acc.mod1, acc.mod2)
    > Summarise(acc.mods)
    Likelihood summary table:
     AIC BIC LR Chisq Df Pr(>Chisq)
    acc.mod0 60983 61007 60320 70 < 2.2e-16 ***
    acc.mod1 2942 3040 2218 39 < 2.2e-16 ***
    acc.mod2 968 1085 227 31 < 2.2e-16 ***
    ---
    Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
    >
    > ## Binomial (logistic regression) models for result
    > ## ------------------------------------------------
    > library(car) # for Anova()
    Error in library(car) : there is no package called ‘car’
    Execution halted
Flavor: r-release-osx-x86_64-snowleopard

Version: 0.6-8
Check: running R code from vignettes
Result: WARN
    Errors in running code in vignettes:
    when running code in ‘vcd-tutorial.Rnw’
     ...
    > library(vcdExtra)
    Loading required package: vcd
    Loading required package: grid
    Loading required package: gnm
    
    > library(ggplot2)
    
     When sourcing ‘vcd-tutorial.R’:
    Error: there is no package called ‘ggplot2’
    Execution halted
Flavor: r-release-osx-x86_64-snowleopard

Version: 0.6-8
Check: re-building of vignette outputs
Result: NOTE
    Error in re-building vignettes:
     ...
    Loading required package: vcd
    Loading required package: grid
    Loading required package: gnm
    
    Error: processing vignette 'vcd-tutorial.Rnw' failed with diagnostics:
     chunk 1 (label = preliminaries)
    Error in library(ggplot2) : there is no package called ‘ggplot2’
    Execution halted
Flavor: r-release-osx-x86_64-snowleopard