Abstract
The integrity of computer simulation models is only as good as the reliability of the random number generator that produces the stream of random numbers one after the other. The chapter describes the difficult task of developing an algorithm to generate random numbers that are statistically valid and have a large cycle length. The linear congruent method is currently the common way to generate the random numbers for a computer. The parameters of this method include the multiplier and the seed. Only a few multipliers are statistically recommended, and two popular ones in use for 32-bit word length computers are presented. Another parameter is the seed and this allows the analyst the choice of altering the sequence of random numbers with each run, and also when necessary, offers the choice of using the same sequence of random numbers from one run to another.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Fishman, G.S., Moore, L.R.: A statistical evaluation of multiplicative congruent random number generators with modulus 231-1. J. Am. Stat. Assoc. 77, 129–136 (1982)
Lehmer, D.H.: Mathematical methods in large scale computing units. Ann. Comput. Lab. 26, 142–146 (1951). Harvard University
Lewis, P.S.W., Goodman, A.S., Miller, J.M.: A pseudo random number generator for the system/360. IBM Syst. J. 8, 136–146 (1969)
Payne, W.H., Rabung, J.R., Bogyo, T.P.: Coding the lehmer pseudorandom number generator. Commun. Assoc. Comput. Mach. 12, 85–86 (1969)
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer Science+Business Media New York
About this chapter
Cite this chapter
Thomopoulos, N.T. (2013). Random Number Generators. In: Essentials of Monte Carlo Simulation. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6022-0_2
Download citation
DOI: https://doi.org/10.1007/978-1-4614-6022-0_2
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-6021-3
Online ISBN: 978-1-4614-6022-0
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)