This review paper deals with nonlinear methods for the generation of uniform
pseudorandom numbers in the unit interval. The emphasis is on results of the theoretical …

Abstract Parallel Monte Carlo simulation requires reliable RNGs. For sequential machines,
good generators exist. It is not at all trivial to find high-quality RNGs for parallel machines. In …

A random number generator produces a periodic sequence of numbers on a computer. The
starting point can be random, but after it is chosen, everything else is deterministic. The goal …

Stochastic simulation requires a reliable source of randomness. Inversive methods are an
interesting and very promising new approach to produce uniform pseudorandom numbers …

The Monte Carlo and the quasi-Monte Carlo method are two of the most important
techniques to solve multidimensional problems. In both cases, we employ deterministic …

We present results from a series of empirical tests of pseudorandom number generators.
The tests cover a broad range of designs due to bit-oriented, efficient test statistics and a …

We briefly overview the design principles, implementation techniques, and empirical testing
of uniform random number generators for simulation. We first discuss some philosophical …

This is a collection of selected linear pseudorandom number that were implemented in
commercial software, used in applications, and some of which have extensively been tested …

Maurer (1992, A universal statistical test for random bit generators) discussed a statistic
whose value is closely related to the per-bit-entropy of an ergodic stationary source. Here …

Uniformity tests based on a discrete form of entropy are introduced and studied in the
context of empirical testing of uniform random number generators. Numerical results are …