Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Rebecca Killick, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: George Marsaglia
Title: Xorshift RNGs
Abstract: Description of a class of simple, extremely fast random number generators (RNGs) with periods 2k - 1 for k = 32, 64, 96, 128, 160, 192. These RNGs seem to pass tests of randomness very well.

Page views:: 87757. Submitted: 2003-05-06. Published: 2003-07-04.
Paper: Xorshift RNGs     Download PDF (Downloads: 113145)
DOI: 10.18637/jss.v008.i14

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Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.