multivariate distribution


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multivariate distribution

[¦məl·tē′ver·ē·ət ′dis·trə′byü·shən]
(mathematics)
For two or more random variables, X 1, X 2, …, and Xn, the distribution which gives the probability that X 1 = x 1, X 2 = x 2, …, and Xn = xn for all values, x 1, x 2, …, and xn, of X 1, X 2, …, and Xn respectively.
References in periodicals archive ?
The above result implies the possibility of expressing a multivariate distribution through its marginal distributions.
Multivariate distributions are the best tools to model the portfolio and there is a need to extend the classical multivariate normal approach.
Copulas are invariant under strictly increasing transformations of the marginal variables and play an important role when constructing multivariate distributions with given marginals.
1985, Construction of Multivariate Distributions With Given
van der Merwe, "Families of multivariate distributions having properties usually associated with the Wishart distribution," South African Statistical Journal, vol.
For sampling from multivariate distributions, functions such as randnormal, randmvt and randmultinomial can be used to generate samples from multivariate normal, multivariate Student's t and multinomial distributions, respectively.
Joint probability, multivariate distributions, and criteria for independence and randomness are then covered.
On maximum entropy characterization of Pearson's type II and VII multivariate distributions.
We show that the positive multivariate distributions so obtained account for the joint behavior of financial data, but the choice among them requires a careful analysis of moments, specifically when conditional variance and kurtosis are considered.
Kotz, Kummer-Gamma and Kummer-Beta univariate and multivariate distributions.

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