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
[test by reto]
Authors: A. Talha Yalta, Sven Schreiber
Title: Random Number Generation in gretl
Abstract: The increasing popularity and complexity of random number intensive methods such as simulation and bootstrapping in econometrics requires researchers to have a good grasp of random number generation in general, and the specific generators that they employ in particular. Here, we discuss the random number generation options, their specifications, and their implementations in gretl. We also assess the performance and the reliability of gretl in this department by conducting extensive empirical testing using the TestU01 library. Our results show that the available alternatives are soundly implemented and should be sufficient for most econometric applications.

Page views:: 4854. Submitted: 2011-01-31. Published: 2012-08-14.
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DOI: 10.18637/jss.v050.c01

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.