Last updated on 2026-08-03 07:51:09 CEST.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 2.4.7 | 21.72 | 193.30 | 215.02 | OK | |
| r-devel-linux-x86_64-debian-gcc | 2.4.7 | 14.57 | 133.46 | 148.03 | NOTE | |
| r-devel-linux-x86_64-fedora-clang | 2.4.7 | 37.00 | 295.06 | 332.06 | OK | |
| r-devel-linux-x86_64-fedora-gcc | 2.4.7 | 15.00 | 133.63 | 148.63 | OK | |
| r-devel-windows-x86_64 | 2.4.7 | 24.00 | 205.00 | 229.00 | OK | |
| r-patched-linux-x86_64 | 2.4.7 | 26.23 | 183.78 | 210.01 | OK | |
| r-release-linux-x86_64 | 2.4.7 | 19.40 | 185.95 | 205.35 | OK | |
| r-release-macos-arm64 | 2.4.7 | 5.00 | 47.00 | 52.00 | OK | |
| r-release-macos-x86_64 | 2.4.7 | 15.00 | 285.00 | 300.00 | OK | |
| r-release-windows-x86_64 | 2.4.7 | 24.00 | 284.00 | 308.00 | OK | |
| r-oldrel-macos-arm64 | 2.4.7 | 5.00 | 50.00 | 55.00 | ERROR | |
| r-oldrel-macos-x86_64 | 2.4.7 | 14.00 | 193.00 | 207.00 | OK | |
| r-oldrel-windows-x86_64 | 2.4.7 | 34.00 | 304.00 | 338.00 | OK |
Version: 2.4.7
Check: for new files in some other directories
Result: NOTE
Found the following files/directories:
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‘~/tmp/scratch/RtmpKszYqY’ ‘~/tmp/scratch/RtmpL8iQe1’
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‘~/tmp/scratch/RtmprH9dTA’ ‘~/tmp/scratch/RtmpswnCDp’
‘~/tmp/scratch/RtmptNFbhw’ ‘~/tmp/scratch/RtmptoMOPo’
‘~/tmp/scratch/RtmptvQIoH’ ‘~/tmp/scratch/Rtmpu84rMb’
‘~/tmp/scratch/Rtmpv43dmv’ ‘~/tmp/scratch/RtmpvmMNir’
‘~/tmp/scratch/RtmpvtRxGz’ ‘~/tmp/scratch/RtmpwRFpsz’
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‘~/tmp/scratch/xvfb-run.zjP5Lg’
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 2.4.7
Check: examples
Result: ERROR
Running examples in ‘fungible-Ex.R’ failed
The error most likely occurred in:
> ### Name: monte
> ### Title: Simulate Clustered Data with User-Defined Properties
> ### Aliases: monte
> ### Keywords: datagen
>
> ### ** Examples
>
>
> ## Example 1
> ## Simulating Fisher's Iris data
> # The original data were reported in:
> # Fisher, R. A. (1936) The use of multiple measurements in taxonomic
> # problems. Annals of Eugenics, 7, Part II, 179-188.
> #
> # This example includes 3 clusters. Each cluster represents
> # an Iris species: Setosa, Versicolor, and Virginica.
> # On each species, four variables were measured: Sepal Length,
> # Sepal Width, Petal Length, and Petal Width.
> #
> # The within species (cluster) correlations of the flower
> # indicators are as follows:
> #
> # Iris Type 1:
> # [,1] [,2] [,3] [,4]
> # [1,] 1.000 0.743 0.267 0.178
> # [2,] 0.743 1.000 0.278 0.233
> # [3,] 0.267 0.278 1.000 0.332
> # [4,] 0.178 0.233 0.332 1.000
> #
> # Iris Type 2
> # [,1] [,2] [,3] [,4]
> # [1,] 1.000 0.526 0.754 0.546
> # [2,] 0.526 1.000 0.561 0.664
> # [3,] 0.754 0.561 1.000 0.787
> # [4,] 0.546 0.664 0.787 1.000
> #
> # Iris Type 3
> # [,1] [,2] [,3] [,4]
> # [1,] 1.000 0.457 0.864 0.281
> # [2,] 0.457 1.000 0.401 0.538
> # [3,] 0.864 0.401 1.000 0.322
> # [4,] 0.281 0.538 0.322 1.000
> #
> # 'monte' expects a list of correlation matrices
> #
>
> #create a list of within species correlations
> data(iris)
> cormat <- cm <- lapply(split(iris[,1:4], iris[,5]), cor)
>
> # create a list of within species indicator
> # skewness and kurtosis
> sk.lst <- list(c(0.120, 0.041, 0.106, 1.254),
+ c(0.105, -0.363, -0.607, -0.031),
+ c(0.118, 0.366, 0.549, -0.129) )
>
>
> kt.lst <- list(c(-0.253, 0.955, 1.022, 1.719),
+ c(-0.533,-0.366, 0.048, -0.410),
+ c( 0.033, 0.706, -0.154, -0.602) )
>
>
> #Generate a new sample of iris data
> my.iris <- monte(seed=123, nvar = 4, nclus = 3, cor.list = cormat,
+ clus.size = c(50, 50, 50),
+ eta2=c(0.619, 0.401, 0.941, 0.929),
+ random.cor = FALSE,
+ skew.list = sk.lst,
+ kurt.list = kt.lst,
+ secor = .3, compactness=c(1, 1, 1),
+ sortMeans = TRUE)
[1] 1
[1] 2
[1] 3
Error in apply(apply(data.means, 2, unique), 2, sort) :
dim(X) must have a positive length
Calls: monte -> apply
Execution halted
Flavor: r-oldrel-macos-arm64