FINCKE, U., AND POHST, M. 1985. Improved methods for calculating vectors of short length in a lattice, including a complexity analysis. Math. Comput. 44, 170, 463 471.

Google Scholar

[6]

FISHMAN, G. S. 1990. Multiplicative congruential random number generators with modulus 2 ~: An exhaustive analysis for/3 = 32 and a partial analysis for ~ = 48. Math. Comput. 54, 189 (Jan.), 331-344.

Google Scholar

[7]

FISHMAN, G. S., AND MOORE~ L. S., III 1986. An exhaustive analysis of multiplicative cougruential random number generators with modulus 231 - 1. SIAM J. Sci. Stat. Comput. 7, 1, 24-45.

Crossref

Google Scholar

[8]

GROTHE, H. 1988. Matrixgeneratoren zur erzeugung gleichverteilter pseudozufallsvektoren. Dissertation (thesis), Tech. Hochschule Darmstadt, Germany In German.

Google Scholar

[9]

GRUBE, A. 1973. Mehrfach rekursiv-erzeugte pseudo-zufallszahlen. Zeitschr~ft fur angewandte Moth. und Mechanik 53, T223-T225 In German.

Google Scholar

[10]

KNUTH, D.E. 1981. The Art of Computer Programming. Vol. 2, Semmumerwal Algorithms, 2nd ed. Addison-Wesley, Reading, Mass.

Crossref

Google Scholar

[11]

L'EEUYER, P 1990. Random numbers for simulation. Commun. ACM 33, 10, 85 97.

Crossref

Google Scholar

[12]

L'EcUYER, P. 1989. Efficient and portable combined random number generators Commun. ACM 31, 6, 742-749~ 744. See also pages 1019 1024.

Crossref

Google Scholar

[13]

L'EcuYER, P., AND BLOUIN, F. 1988. Linear congruential generators of order k > 1. In Proceed-ings of the 1988 Winter Stmulatwn Conference. IEEE Press, New York, 432 439.

Crossref

Google Scholar

[14]

L'EcUYER, P., AND COTE, S. 1991. A random number package with splitting facilities. ACM Trans. Math. So/h~. 17, 1, 98-111.

Crossref

Google Scholar

[15]

LIDL, R., AND NIEDERREITER, H. 1986. Introduction to Finite Fields and Their Applications. Cambridge Umversity Press, Cambridge, Mass.

Crossref

Google Scholar

[16]

MONTGOMERY, P.L. 1987. Speeding the Pollard and elliptic curve methods of factorization. Math Comput. 48, 177, 243-264.

Google Scholar

[17]

MORAIN, F. 1988. Implementation of the Atkin-Goldwasser-Kfiian primality testing algorithm. Rapport de recherche 911, INRIA, Rocquencourt, France.

Google Scholar

[18]

NIEDERREITER, H. 1992. Random Number Generation and Quasi-Monte Carlo Methods. In SIAM CBMS-NSF Regwnal Conference Ser~es in Applied Mathematics, vol. 63. SIAM, Philadelphia, Penn.

Crossref

Google Scholar

[19]

NIEDERREITER, H. 1991. Recent trends in random number and random vector generation. Ann. Oper. Res. 31,323-345.

Crossref

Google Scholar

[20]

NIEDERREITER, H. 1988. The serial test for digital k-step pseudorandom numbers. Math. J. Okayama Unw. 30, 93 119.

Google Scholar

[21]

NIEDERREiTER, $. 1986. A pseudorandom vector generator based on finite field arithmetic. Math. Japontca 31, 5, 759 774.

Google Scholar

[22]

NIEDERREITER, H. 1982 Statistical tests for Tausworthe pseudorandom numbers. In Probabd- ~ty and Statistical I, ference. Reidel, Dordrecht, Boston, 265-274.

Google Scholar

[23]

PARK, S. K., AND MILLER, K.W. 1988. Random number generators' Good ones are hard to find. Commun. ACM 31, 10, 1192-1201.

Crossref

Google Scholar

[24]

RIPLEY, B D. 1987. Stochastic Szmulation. Wiley, New York.

Crossref

Google Scholar

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Deng LWinter BHorng Shiau JHorng-Shing Lu HKumar NYang C(2024)Efficient spectral tests for multiple recursive generatorsCommunications in Statistics - Theory and Methods10.1080/03610926.2024.2329772(1-16)Online publication date: 31-Mar-2024
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A search for good multiple recursive random number generators

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cover image ACM Transactions on Modeling and Computer Simulation

ACM Transactions on Modeling and Computer Simulation Volume 3, Issue 2

April 1993

75 pages

ISSN:1049-3301

EISSN:1558-1195

DOI:10.1145/169702

Editor:
Richard E. Nance
Virginia Tech, Blacksburg

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Association for Computing Machinery

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Published: 01 April 1993

Published in TOMACS Volume 3, Issue 2

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https://doi.org/10.1080/03610926.2024.2329772
Brackett‐Rozinsky NLemire D(2024)Batched ranged random integer generationSoftware: Practice and Experience10.1002/spe.3369Online publication date: 25-Aug-2024
https://doi.org/10.1002/spe.3369
Deng LWinter BShiau JLu HKumar NYang C(2023)Parallelizable efficient large order multiple recursive generatorsParallel Computing10.1016/j.parco.2023.103036117(103036)Online publication date: Sep-2023
https://doi.org/10.1016/j.parco.2023.103036
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Combined Multiple Recursive Random Number Generators

Good Parameters and Implementations for Combined Multiple Recursive Random Number Generators

On the lattice structure of the add-with-carry and subtract-with-borrow random number generators

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