rmvss | R Documentation |
Computes random vectors of the multivariate subgaussian stable distribution for arbitrary alpha, shape matrices, and location vectors. See Nolan (2013).
rmvss( n, alpha = 1, Q = NULL, delta = rep(0, d), which.stable = c("libstableR", "stabledist")[1] )
n |
number of observations |
alpha |
default to 1 (Cauchy). Must be 0< |
Q |
Shape matrix. See Nolan (2013). |
delta |
location vector. |
which.stable |
defaults to |
Returns the n
by d
matrix containing multivariate subgaussian stable
random variates where d=nrow(Q)
.
Nolan JP (2013), Multivariate elliptically contoured stable distributions: theory and estimation. Comput Stat (2013) 28:2067–2089 DOI 10.1007/s00180-013-0396-7
## generate 10 random variates of a bivariate mvss rmvss(n=10, alpha=1.71, Q=matrix(c(10,7.5,7.5,10),2)) ## generate 10 random variates of a trivariate mvss Q <- matrix(c(10,7.5,7.5,7.5,10,7.5,7.5,7.5,10),3) rmvss(n=10, alpha=1.71, Q=Q)
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