Add more information to header of rand_multivariate_student.m
parent
787f6d37c2
commit
b67e9626f7
|
@ -1,4 +1,5 @@
|
|||
function draw = rand_multivariate_student(Mean,Sigma_upper_chol,df)
|
||||
% function draw = rand_multivariate_student(Mean,Sigma_upper_chol,df)
|
||||
% Pseudo random draws from a multivariate student distribution,
|
||||
% with expectation Mean, variance Sigma*df/(df-2) and degrees of freedom df>0.
|
||||
%
|
||||
|
@ -13,10 +14,14 @@ function draw = rand_multivariate_student(Mean,Sigma_upper_chol,df)
|
|||
% draw [double] 1*n vector drawn from a multivariate normal distribution with expectation Mean and
|
||||
% covariance Sigma.
|
||||
%
|
||||
% REMARK This is certainly not the most efficient way...
|
||||
%
|
||||
% NOTE See Zellner (appendix B.2, 1971) for a definition.
|
||||
%
|
||||
% Computes the t-distributed random numbers from
|
||||
% X = \mu + Y\sqrt{\frac{\nu}{U}}
|
||||
% where
|
||||
% Y~N(0,Sigma) with Sigma=Sigma_upper_chol'*Sigma_upper_chol
|
||||
% U~\Chi^2_{\nu}
|
||||
% The latter is constructed as the sum of \nu standard normals.
|
||||
|
||||
% Copyright (C) 2003-2009 Dynare Team
|
||||
%
|
||||
|
|
Loading…
Reference in New Issue