rT {bbricks} | R Documentation |
Generate random samples from a (multivariate) t distribution. For a random vector x, the density function is defined as:
Gamma((df + p)/2) / (Gamma(df/2)df^{p/2} pi ^{p/2} |Sigma|^{1/2}) [1+1/df (x-df)^T Sigma^{-1} (x-df)]^{-(df +p)/2}
Where p is the dimension of x.
rT(n, mu, Sigma = NULL, A = NULL, df = 1)
n |
integer, number of samples. |
mu |
numeric, mean vector. |
Sigma |
matrix, Sigma is proportional to the covariance matrix of x, one of Sigma and A should be non-NULL. |
A |
matrix, the Cholesky decomposition of Sigma, an upper triangular matrix, one of Sigma and A should be non-NULL. |
df |
numeric, degrees of freedom. |
A matrix of n rows and length(mu) columns, each row is a sample.
x <- rT(1000,mu = c(1,1),Sigma = matrix(c(1,0.5,0.5,3),2,2)) plot(x)