Sometimes, a man’s gotta do what a man’s gotta do. Which, in my case, might be a little simulation of a random process involving an unordered categorical variable. In R, sampling from a multinomial distribution is trivial.

`rmultinom(1,1000,c(.1,.7,.2,.1))`

gives me a vector of random numbers from a multinomial distribution with outcomes 1, 2, 3, and 4, where the probability of observing a ‘1’ is 10 percent, the probability of observing a ‘2’ is 70 per cent, and so on. But I could not find an equivalent function in Stata. Generating artificial data in R is not very elegant, so I kept digging and found a solution in section M-5 of the Mata handbook. Hidden in the entry on `runiform` is a reference to `rdiscrete(r,c,p)`

, a Mata function which generates a `r*c` matrix of draws from a multinomial distribution defined by a vector `p` of probabilities.

That leaves but one question: Is wrapping a handful of lines around a Mata call to replace a non-existent Stata function more elegant than calling an external program?

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