Add to ORKGThis chapter covers the basic design principles and methods for uniform random number generators used in simulation. We also briefly mention the connections between these methods and those used to construct highly-uniform point sets for quasi-Monte Carlo integration. The emphasis is on the methods based on linear recurrences modulo a large integer, or modulo 2. This reflects the fact that their mathematical structure is much better understood than other types of generators, and that most generators used in simulation have that form. We discuss the main requirements for a good generator, theoretical figures of merit for certain classes of linear-type generators, implementation issues, nonlinear generators, and statistical testing
We will look at random number generation from the point-of-view of Monte Carlo computations. Thus...
AbstractNonstatistical notions of uniformity suitable for small samples are proposed and studied. Ne...
Monte Carlo techniques are often the only practical way to evaluate difficult integrals or to sample...
We briefly overview the design principles, implementation techniques, and empirical testing of unifo...
Use of empirical studies based on computer-generated random numbers has become a common practice in ...
Use of empirical studies based on computer-generated random numbers has become a common practice in ...
We consider the requirements for uniform pseudo-random number generators on modern vector and parall...
We consider the requirements for uniform pseudo-random number generators on modern vector and parall...
Includes bibliographical references (pages 91-93)This paper is an examination of the generation of r...
Fast and reliable pseudo-random number generators are required for simulation and other applications...
We will look at random number generation from the point-of-view of Monte Carlo computations. Thus...
We will look at random number generation from the point-of-view of Monte Carlo computations. Thus...
The simulation process depends on generating a series of random numbers subject to the uniform proba...
In an earlier report [1] we described methods to obtain pseudorandom numbers from various statistica...
We will look at random number generation from the point-of-view of Monte Carlo computations. Thus...
We will look at random number generation from the point-of-view of Monte Carlo computations. Thus...
AbstractNonstatistical notions of uniformity suitable for small samples are proposed and studied. Ne...
Monte Carlo techniques are often the only practical way to evaluate difficult integrals or to sample...
We briefly overview the design principles, implementation techniques, and empirical testing of unifo...
Use of empirical studies based on computer-generated random numbers has become a common practice in ...
Use of empirical studies based on computer-generated random numbers has become a common practice in ...
We consider the requirements for uniform pseudo-random number generators on modern vector and parall...
We consider the requirements for uniform pseudo-random number generators on modern vector and parall...
Includes bibliographical references (pages 91-93)This paper is an examination of the generation of r...
Fast and reliable pseudo-random number generators are required for simulation and other applications...
We will look at random number generation from the point-of-view of Monte Carlo computations. Thus...
We will look at random number generation from the point-of-view of Monte Carlo computations. Thus...
The simulation process depends on generating a series of random numbers subject to the uniform proba...
In an earlier report [1] we described methods to obtain pseudorandom numbers from various statistica...
We will look at random number generation from the point-of-view of Monte Carlo computations. Thus...
We will look at random number generation from the point-of-view of Monte Carlo computations. Thus...
AbstractNonstatistical notions of uniformity suitable for small samples are proposed and studied. Ne...
Monte Carlo techniques are often the only practical way to evaluate difficult integrals or to sample...