In
statistics
Statistics (from German language, German: ''wikt:Statistik#German, Statistik'', "description of a State (polity), state, a country") is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of ...
, the matrix ''t''-distribution (or matrix variate ''t''-distribution) is the generalization of the
multivariate ''t''-distribution from vectors to
matrices
Matrix most commonly refers to:
* ''The Matrix'' (franchise), an American media franchise
** ''The Matrix'', a 1999 science-fiction action film
** "The Matrix", a fictional setting, a virtual reality environment, within ''The Matrix'' (franchis ...
. The matrix ''t''-distribution shares the same relationship with the multivariate ''t''-distribution that the
matrix normal distribution
In statistics, the matrix normal distribution or matrix Gaussian distribution is a probability distribution that is a generalization of the multivariate normal distribution to matrix-valued random variables.
Definition
The probability density ...
shares with the
multivariate normal distribution
In probability theory and statistics, the multivariate normal distribution, multivariate Gaussian distribution, or joint normal distribution is a generalization of the one-dimensional (univariate) normal distribution to higher dimensions. One d ...
. For example, the matrix ''t''-distribution is the
compound distribution In probability and statistics, a compound probability distribution (also known as a mixture distribution or contagious distribution) is the probability distribution that results from assuming that a random variable is distributed according to som ...
that results from sampling from a matrix normal distribution having sampled the covariance matrix of the matrix normal from an
inverse Wishart distribution
In statistics, the inverse Wishart distribution, also called the inverted Wishart distribution, is a probability distribution defined on real-valued positive-definite matrices. In Bayesian statistics it is used as the conjugate prior for the cov ...
.
In a
Bayesian analysis
Bayesian inference is a method of statistical inference in which Bayes' theorem is used to update the probability for a hypothesis as more evidence or information becomes available. Bayesian inference is an important technique in statistics, and ...
of a
multivariate linear regression
The general linear model or general multivariate regression model is a compact way of simultaneously writing several multiple linear regression models. In that sense it is not a separate statistical linear model. The various multiple linear regre ...
model based on the matrix normal distribution, the matrix ''t''-distribution is the
posterior predictive distribution
Posterior may refer to:
* Posterior (anatomy), the end of an organism opposite to its head
** Buttocks, as a euphemism
* Posterior horn (disambiguation)
* Posterior probability
The posterior probability is a type of conditional probability that r ...
.
Definition
For a matrix ''t''-distribution, the
probability density function
In probability theory, a probability density function (PDF), or density of a continuous random variable, is a function whose value at any given sample (or point) in the sample space (the set of possible values taken by the random variable) can ...
at the point
of an
space is
:
where the constant of integration ''K'' is given by
:
Here
is the
multivariate gamma function
In mathematics, the multivariate gamma function Γ''p'' is a generalization of the gamma function. It is useful in multivariate statistics, appearing in the probability density function of the Wishart and inverse Wishart distributions, and the mat ...
.
The
characteristic function In mathematics, the term "characteristic function" can refer to any of several distinct concepts:
* The indicator function of a subset, that is the function
::\mathbf_A\colon X \to \,
:which for a given subset ''A'' of ''X'', has value 1 at points ...
and various other properties can be derived from the generalized matrix ''t''-distribution (see below).
Generalized matrix ''t''-distribution
The generalized matrix ''t''-distribution is a generalization of the matrix ''t''-distribution with two parameters ''α'' and ''β'' in place of ''ν''.
[Iranmanesh, Anis, M. Arashi and S. M. M. Tabatabaey (2010)]
"On Conditional Applications of Matrix Variate Normal Distribution"
''Iranian Journal of Mathematical Sciences and Informatics'', 5:2, pp. 33–43.
This reduces to the standard matrix ''t''-distribution with
The generalized matrix ''t''-distribution is the
compound distribution In probability and statistics, a compound probability distribution (also known as a mixture distribution or contagious distribution) is the probability distribution that results from assuming that a random variable is distributed according to som ...
that results from an infinite
mixture
In chemistry, a mixture is a material made up of two or more different chemical substances which are not chemically bonded. A mixture is the physical combination of two or more substances in which the identities are retained and are mixed in the ...
of a matrix normal distribution with an
inverse multivariate gamma distribution
In statistics, the inverse matrix gamma distribution is a generalization of the inverse gamma distribution to positive-definite matrices. It is a more general version of the inverse Wishart distribution, and is used similarly, e.g. as the conjug ...
placed over either of its covariance matrices.
Properties
If
then
:
The property above comes from
Sylvester's determinant theorem:
:
::
If
and
and
are
nonsingular matrices
In linear algebra, an -by- square matrix is called invertible (also nonsingular or nondegenerate), if there exists an -by- square matrix such that
:\mathbf = \mathbf = \mathbf_n \
where denotes the -by- identity matrix and the multiplicati ...
then
:
The
characteristic function In mathematics, the term "characteristic function" can refer to any of several distinct concepts:
* The indicator function of a subset, that is the function
::\mathbf_A\colon X \to \,
:which for a given subset ''A'' of ''X'', has value 1 at points ...
is
:
where
:
and where
is the type-two
Bessel function
Bessel functions, first defined by the mathematician Daniel Bernoulli and then generalized by Friedrich Bessel, are canonical solutions of Bessel's differential equation
x^2 \frac + x \frac + \left(x^2 - \alpha^2 \right)y = 0
for an arbitrary ...
of Herz of a matrix argument.
See also
*
Multivariate ''t''-distribution
*
Matrix normal distribution
In statistics, the matrix normal distribution or matrix Gaussian distribution is a probability distribution that is a generalization of the multivariate normal distribution to matrix-valued random variables.
Definition
The probability density ...
Notes
External links
A C++ library for random matrix generator
{{ProbDistributions, multivariate
Random matrices
Multivariate continuous distributions