A new inversive congruential pseudorandom number generator with power of two modulus
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Combining random number generators
WSC '91 Proceedings of the 23rd conference on Winter simulation
Generalized Lehmer-Tausworthe random number generators
ACM-SE 30 Proceedings of the 30th annual Southeast regional conference
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In typical stochastic simulations, randomness is produced by generating a sequence of independent uniform variates (usually real-valued between 0 and 1, or integer-valued in some interval) and transforming them in the appropriate way. In this tutorial, we examine practical ways of generating such variates on a computer. We compare them in terms of ease of implementation, efficiency, flexibility, theoretical support, and statistical robustness. We look in particular at the following classes of generators: linear congruential (in scalar and matrix form), lagged-Fibonacci (including generalized feedback shift register) and combined. We also mention others and give a bibliographic survey of the most recent papers on the subject.