Generate correlated data multivariate categorical data via a copula.
gen.cop(
n,
tauvek = c(0.2, 0.35),
nr.cols = c(10, 10),
true.mu = runif(sum(nr.cols)),
err.coeff = 0.1,
random = FALSE,
reverse = TRUE,
reverse.thresh = 0.75
)Integer; the number of samples to draw.
A vector of association parameters for each of the Clayton copulae
(see copClayton), of the same length as nr.cols.
A vector giving the number of columns to draw from each of the copulae.
A vector giving the mean for each of the columns in the data.
The standard errors for underlying normal distribution.
Logical indicating whether or not the samples should be presented in random order.
Logical indicating whether some of the simulated variables should be reversed to have negative association or not.
The proportion of columns to reverse.