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Section: Random Number Generation
This function generates samples from a multinomial distribution given the probability of each outcome. The general syntax for its use is
y = randmulti(N,pvec)
 where N is the number of experiments to perform, and pvec is the vector of probabilities describing the distribution of outcomes. 
A multinomial distribution describes the number of times each of m possible outcomes occurs out of N trials, where each outcome has a probability p_i. More generally, suppose that the probability of a Bernoulli random variable X_i is p_i, and that 
![\[ \sum_{i=1}^{m} p_i = 1. \]](form_145.png) 
 Then the probability that X_i occurs x_i times is 
![\[ P_N(x_1,x_2,\ldots,x_n) = \frac{N!}{x_1!\cdots x_n!} p_1^{x_1}\cdots p_n^{x_n}. \]](form_146.png) 
Suppose an experiment has three possible outcomes, say heads, tails and edge, with probabilities 0.4999, 0.4999 and 0.0002, respectively. Then if we perform ten thousand coin flips we get
--> randmulti(10000,[0.4999,0.4999,0.0002]) ans = 5051 0 4948