rndMVt#
Purpose#
Computes multivariate Student-t distributed random numbers given a covariance matrix.
Format#
- r = rndMVt(num, cov, df)#
- { r, newstate } = rndMVt(num, cov, df, state)
- Parameters:
num (scalar) – number of random vectors to create.
cov (NxN matrix) – covariance matrix
df (scalar) – degrees of freedom.
state (scalar or opaque vector) –
Optional argument.
scalar case
state = starting seed value only. If -1, GAUSS computes the starting seed based on the system clock.
opaque vector case
state = the state vector returned from a previous call to one of the
rnd
random number functions.
- Returns:
r (num x N matrix) – multivariate student-t distributed random numbers.
newstate (Opaque vector) – the updated state.
Examples#
// Degrees of freedom
df = 8;
// Covariance matrix
sigma = { 1 0.3,
0.3 1 };
x = rndMVt(100, sigma, df);
Remarks#
The properties of the pseudo-random numbers in x are:
\[ \begin{align}\begin{aligned}\begin{split}E(x) = 0\\\end{split}\\Var(x) = \bigg(\frac{df}{df - 2}\bigg) * \sigma\end{aligned}\end{align} \]
See also
Functions rndMVn()
, rndCreateState()