Wishart distribution
The joint distribution of the elements from the sample covariance matrix of observations from a multivariate normal distribution. Let the results of observations have a -dimensional normal distribution
with vector mean
and covariance matrix
. Then the joint density of the elements of the matrix
is given by the formula
![]() |
( denotes the trace of a matrix
), if the matrix
is positive definite, and
in other cases. The Wishart distribution with
degrees of freedom and with matrix
is defined as the
-dimensional distribution
with density
. The sample covariance matrix
, which is an estimator for the matrix
, has a Wishart distribution.
The Wishart distribution is a basic distribution in multivariate statistical analysis; it is the -dimensional generalization (in the sense above) of the
-dimensional "chi-squared" distribution.
If the independent random vectors and
have Wishart distributions
and
, respectively, then the vector
has the Wishart distribution
.
The Wishart distribution was first used by J. Wishart [1].
References
[1] | J. Wishart, Biometrika A , 20 (1928) pp. 32–52 |
[2] | T.W. Anderson, "An introduction to multivariate statistical analysis" , Wiley (1958) |
Comments
References
[a1] | A.M. Khirsagar, "Multivariate analysis" , M. Dekker (1972) |
[a2] | R.J. Muirhead, "Aspects of multivariate statistical theory" , Wiley (1982) |
Wishart distribution. Encyclopedia of Mathematics. URL: http://encyclopediaofmath.org/index.php?title=Wishart_distribution&oldid=17673