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--ZusammenfassungComputer Methods for Sampling from Gamma, Beta, Poisson and Binomial Distributions. Accurate computer methods are evaluated which transform uniformly distributed random numbers into quantities that follow gamma, beta, Poisson, binomial and negative-binomial distributions. All algorithms are designed for variable parameters. The known convenient methods are slow when the parameters are large. Therefore new procedures are introduced which can cope efficiently with parameters of all sizes. Some algorithms require sampling from the normal distribution as an intermediate step. In the reported computer experiments the normal deviates were obtained from a recent method which is also described.

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Summary. Exact expressions for serial correlations of sequences of pseudo-random numbers are derived. The reduction to generalized Dedekind sums is of optimum simplicity and covers all cases of the linear congruential method. The subsequent evaluation of the generalized Dedekind sums is based on a modified Euclidean algorithm whose quotients are recognized as the main contributors to the size of the serial correlations. This leads to the establishment of bounds as well as of fast computer programs. Moreover, some light is thrown upon the general question of quality in random number generation.

A suitable square root transformation of a gamma random variable with mean a ≥ 1 yields a probability density close to the standard normal density. A modification of the rejection technique then begins by sampling from the normal distribution, being able to accept and transform the initial normal observation quickly at least 85 percent of the time (95 percent if a ≥ 4). When used with efficient subroutines for sampling from the normal and exponential distributions, the resulting accurate method is significantly faster than competing algorithms.

Fast algorithms for selecting a random set of exactly k records from a file of n records are constructed. Selection is sequential: the sample records are chosen in the same order in which they occur in the file. All procedures run in O(k) time. The “geometric” method has two versions: with or without O(k) auxiliary space. A further procedure uses hashing techniques and requires O(k) space.