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