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Multivariate t random numbers


R = mvtrnd(C,df,cases)
R = mvtrnd(C,df)


R = mvtrnd(C,df,cases) returns a matrix of random numbers chosen from the multivariate t distribution, where C is a correlation matrix. df is the degrees of freedom and is either a scalar or is a vector with cases elements. If p is the number of columns in C, then the output R has cases rows and p columns.

Let t represent a row of R. Then the distribution of t is that of a vector having a multivariate normal distribution with mean 0, variance 1, and covariance matrix C, divided by an independent chi-square random value having df degrees of freedom. The rows of R are independent.

C must be a square, symmetric and positive definite matrix. If its diagonal elements are not all 1 (that is, if C is a covariance matrix rather than a correlation matrix), mvtrnd rescales C to transform it to a correlation matrix before generating the random numbers.

R = mvtrnd(C,df) returns a single random number from the multivariate t distribution.


collapse all

Generate random numbers from a multivariate t distribution with correlation parameters SIGMA = [1 0.8;0.8 1] and 3 degrees of freedom.

rng default;  % For reproducibility
SIGMA = [1 0.8;0.8 1];
R = mvtrnd(SIGMA,3,100);

Plot the random numbers.


See Also


Introduced before R2006a

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