Sentence examples for multivariate hypergeometric distribution from inspiring English sources

A number of well-known multivariate distributions, such as a multinomial distribution, multivariate hypergeometric distribution, negatively correlated normal distribution and joint distribution of ranks, possess the NA property.

A number of well-known multivariate distributions possess the NA property, such as the multinomial distribution, multivariate hypergeometric distribution, negatively correlated normal distribution, and joint distribution of ranks.

Joag-Dev and Proschan [1] introduced the definition of negative association and showed that many of the well-known multivariate distributions possess the negatively associated property, for example, multivariate hypergeometric distribution, negatively correlated normal distribution, random sampling without replacement, etc.

Both scenarios converge if the number of sampled individuals is large, and, for similar expected frequencies, multivariate hypergeometric distribution presents smaller variances.

We used the proposed model based on the multivariate hypergeometric distribution.

The probability of the observed class distribution in the splitted clusters is given by a generalized form of the polyhypergeometric distribution or multivariate hypergeometric distribution [ 17].

Joag-Dev and Proschan [2] pointed out that a number of well-known multivariate distributions possesses the negative association property, such as multinomial, convolution of unlike multinomial, multivariate hypergeometric, Dirichlet, permutation distribution, negatively correlated normal distribution, random sampling without replacement, and joint distribution of ranks.

As pointed out and proved by Joag-Dev and Proschan [2], a number of well-known multivariate distributions possess the negative association property, such as multinomial, convolution of unlike multinomial, multivariate hypergeometric, Dirichlet, permutation distribution, negatively correlated normal distribution, random sampling without replacement, and joint distribution of ranks.

Exact statistical inference involves dealing with the hypergeometric distribution.

Binomial, hypergeometric, negative binomial, geometric, multinomial, extended hypergeometric distribution, and the F-variance ratio approach are considered.

We obtain the average SEP in terms of the Lauricella multivariate hypergeometric function.