Editing Multinomial distribution (section)

==Related distributions==
In some fields such as [[natural language processing]], categorical and multinomial distributions are synonymous and it is common to speak of a multinomial distribution when a [[categorical distribution]] is actually meant. This stems from the fact that it is sometimes convenient to express the outcome of a categorical distribution as a "1-of-k" vector (a vector with one element containing a 1 and all other elements containing a 0) rather than as an integer in the range <math>1 \dots k</math>; in this form, a categorical distribution is equivalent to a multinomial distribution over a single trial.

* When ''k'' = 2, the multinomial distribution is the [[binomial distribution]].
* [[Categorical distribution]], the distribution of each trial; for ''k'' = 2, this is the [[Bernoulli distribution]].
* The [[Dirichlet distribution]] is the [[conjugate prior]] of the multinomial in [[Bayesian statistics]].
* [[Dirichlet-multinomial distribution]].
* [[Beta-binomial distribution]].
* [[Negative multinomial distribution]]
* [[Hardy–Weinberg principle]] ( a trinomial distribution with probabilities <math>(\theta^2, 2 \theta (1-\theta), (1-\theta)^2) </math>)