Random variate generators are developed for the Poisson-Poisson (or generalized Poisson) distribution. The expected time per generated random variate is uniformly bounded over the parameter space. Random variate generation for related distributions is also discussed; these include the Abel and Ressel families, and a family introduced by Haight.

A two-parameter family of distributions on (0, 1) is explored which has many similarities to the beta distribution and a number of advantages in terms of tractability (it also, of course, has some disadvantages). The minimax distribution, so-called because of its genesis in terms of uniform order statistics, particularly has straightforward distribution and quantile functions which do not depen...

Input-output, growth-decay, production-consumption type situations abound in many practical problems. When the input and output variables are independently gamma distributed, various aspects of the residual effect are already tackled by the author. Matrix-variate analogues, their connections to quadratic and bilinear forms, matrix-variate Whittaker functions, and many properties of such matrix-...

We study biased control variates (BCVs), whose purpose is to improve the efficiency of stochastic simulation experiments. BCVs replace the control-simulation mean with an approximation; the resulting control-variate estimator is biased. This bias may not be a significant issue for finite sample sizes, however, because our estimator minimizes the more general mean-squared-error (mse), i.e., the ...