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Generate random d-vectors from the multivariate Canonical Fundamental Skew-Normal (CFUSN) distribution
rCFUSN(n, Delta)
A random matrix \(n \times d\)
The number of variates to be generated
Correlation matrix, the skewness matrix Delta
Gy.Terdik, Multivariate statistical methods - Going beyond the linear, Springer 2021 (5.5) p.247
S. R. Jammalamadaka, E. Taufer, Gy. Terdik. On multivariate skewness and kurtosis. Sankhya A, 83(2), 607-644.
Other Random generation: rCFUSSD(), rSkewNorm(), rUniS()
rCFUSSD()
rSkewNorm()
rUniS()
d <- 2; p <- 3 Lamd <- matrix(sample(1:50-25, d*p), nrow=d) ieg<- eigen(diag(p)+t(Lamd)%*%Lamd) V <- ieg$vectors Delta <-Lamd %*% V %*% diag(1/sqrt(ieg$values)) %*% t(V) x<-rCFUSN(20,Delta)
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