- statistics: r = mvtrnd (rho, df)
- statistics: r = mvtrnd (rho, df, n)
 Random vectors from the multivariate Student’s t distribution.
 
Arguments
 
- 
 rho is the matrix of correlation coefficients.  If there are any
 non-unit diagonal elements then rho will be normalized, so that the
 resulting covariance of the obtained samples r follows:
 cov (r) = df/(df-2) * rho ./ (sqrt (diag (rho) * diag (rho))).
 In order to obtain samples distributed according to a standard multivariate
 student’s t-distribution, rho must be equal to the identity matrix. To
 generate multivariate student’s t-distribution samples r with arbitrary
 covariance matrix rho, the following scaling might be used:r = mvtrnd (rho, df, n) * diag (sqrt (diag (rho))).
- 
 df is the degrees of freedom for the multivariate t-distribution.
 df must be a vector with the same number of elements as samples to be
 generated or be scalar.
 
- 
 n is the number of rows of the matrix to be generated. n must be
 a non-negative integer and corresponds to the number of samples to be
 generated.
 
Return values
 
- 
 r is a matrix of random samples from the multivariate t-distribution
 with n row samples.
 
Examples
 |  |    rho = [1, 0.5; 0.5, 1];
 df = 3;
 n = 10;
 r = mvtrnd (rho, df, n);
  
   rho = [1, 0.5; 0.5, 1];
 df = [2; 3];
 n = 2;
 r = mvtrnd (rho, df, 2);
    | 
 
References
 
- 
 Wendy L. Martinez and Angel R. Martinez. Computational Statistics
 Handbook with MATLAB. Appendix E, pages 547-557, Chapman & Hall/CRC, 2001.
 
- 
 Samuel Kotz and Saralees Nadarajah. Multivariate t Distributions and
 Their Applications. Cambridge University Press, Cambridge, 2004.
 
 See also: 
  mvtcdf, 
  mvtcdfqmc, 
  mvtpdf
Source Code: 
  mvtrnd