Several extensively tested multiple recursive random number generators

Chiang Kao, Hui Chin Tang

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)


The Multiple Recursive Generator (MRG) has been considered by many scholars as a very good Random Number (RN) generator. This paper applies a sequential search to identify the MRGs of orders one, two, and three which are able to produce RNs with good lattice structure in terms of the spectral value and Beyer quotient. To detect departures from local randomness and homogeneity, extensive statistical tests including runs, auto-correlation, chi-square, serial, and the sparse occupancy tests have been conducted. In approximately 19.3 billion candidates, only four MRGs, namely, (1280550, -45991), (0, 45991, 1758790), (885300443, 0, 1552858447), and (885300443, 1546795921, 598295599), have passed all the theoretical and empirical tests. Among which (0, 45991, 1758790) can be implemented efficiently by applying the approximate factoring method and is therefore most recommended.

Original languageEnglish
Pages (from-to)129-136
Number of pages8
JournalComputers and Mathematics with Applications
Issue number6
Publication statusPublished - 1998 Sept

All Science Journal Classification (ASJC) codes

  • Modelling and Simulation
  • Computational Theory and Mathematics
  • Computational Mathematics


Dive into the research topics of 'Several extensively tested multiple recursive random number generators'. Together they form a unique fingerprint.

Cite this