Simulate from MVN with compound symmetry variance structure and mean zero. The result is returned as a list where the ith element is the column vector with n observations from the ith coordinate of the MVN.
Usage
covar_normal(
n,
normal.cor = NULL,
normal.var = 1,
names = c("z"),
type = "cs",
...
)Arguments
- n
Number of samples
- normal.cor
Correlation parameter (n x r) or (1 x r) matrix
- normal.var
marginal variance (can be specified as a p-dim. vector or a nxp matrix)
- names
Column name of the column vector (default "z")
- type
of correlation matrix structure (cs: compound-symmetry / exchangable, ar: autoregressive, un: unstructured, to: toeplitz). The dimension of
normal.cormust match, i.e., for a Toeplitz correlation matrix r = p-1, and for a cs and ar r=1.- ...
Additional arguments passed to lower level functions