Multinomial distribution
polynomial distribution
The joint distribution of random variables that is defined for any set of non-negative integers satisfying the condition , , , by the formula
(*) |
where (, ) are the parameters of the distribution. A multinomial distribution is a multivariate discrete distribution, namely the distribution for the random vector with (this distribution is in essence -dimensional, since it is degenerate in the Euclidean space of dimensions). A multinomial distribution is a natural generalization of a binomial distribution and coincides with the latter for . The name of the distribution is given because the probability (*) is the general term in the expansion of the multinomial . The multinomial distribution appears in the following probability scheme. Each of the random variables is the number of occurrences of one of the mutually exclusive events , , in repeated independent trials. If in each trial the probability of event is , , then the probability (*) is equal to the probability that in trials the events will appear times, respectively. Each of the random variables has a binomial distribution with mathematical expectation and variance .
The random vector has mathematical expectation and covariance matrix , where
(the rank of the matrix is because ). The characteristic function of a multinomial distribution is
For , the distribution of the vector with normalized components
tends to a certain multivariate normal distribution, while the distribution of the sum
(which is used in mathematical statistics to construct the "chi-squared" test) tends to the "chi-squared" distribution with degrees of freedom.
References
[1] | H. Cramér, "Mathematical methods of statistics" , Princeton Univ. Press (1946) |
Comments
References
[a1] | N.L. Johnson, S. Kotz, "Discrete distributions" , Wiley (1969) |
Multinomial distribution. Encyclopedia of Mathematics. URL: http://encyclopediaofmath.org/index.php?title=Multinomial_distribution&oldid=11687