Stata/Random Number Generation

Generate a univariate uniform distribution The function -runiform()- returns uniformly distributed pseudorandom numbers on the interval [0,1) . set obs 10 obs was 0, now 10 . gen x = runiform() You have built-in random number generation methods for the main distributions. The keyword is rnd. The list of all available distributions is given in the following help file: -h rnd- The Inverse CDF method The basic function for generating random numbers is uniform(). Therefore you generally have to use the inverse CDF method to sample from other distributions. We can draw from a uniform distribution : . clear . set obs 500 obs was 0, now 500 . gen unif=runiform() . hist unif (bin=22, start=.0043096, width=.04522361) We can draw from a normal distribution : . gen norm=invnorm(runiform()) . hist norm (bin=22, start=-2.8517358, width=.23821211) We can draw from a distribution . gen chi2=invchi2(1,uniform()) . hist chi2 (bin=22, start=.00002381, width=.50381869) . gen chi210=invchi2(10,uniform()) . hist chi210 (bin=22, start=1.8273849, width=1.3336678) We can draw from a Fisher Snedecor distribution . gen fisher=invF(10,10,uniform()) . hist fisher (bin=22, start=.14025442, width=.39209784) We can draw from a Student distribution. Remember that invttail() is not the inverse of the CDF (cumulative distribution function) but the inverse of the survival function (1 - the CDF). . gen student=1-invttail(10,uniform()) . hist student (bin=22, start=-3.9568543, width=.4741968) Multivariate Normal Distributions drawnorm draws directly from a multivariate normal distribution. Probability Function Data Management