• using R version 4.5.2 (2025-10-31)
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• this is package ‘fungible’ version ‘2.4.4.1’
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• checking examples ... [5s/5s] 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
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• DONE Status: 1 ERROR
• using check arguments '--no-clean-on-error '