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An approximate method for generating symmetric random variables

Authors:

John S. Ramberg,

Bruce W. SchmeiserAuthors Info & Claims

Communications of the ACM, Volume 15, Issue 11

Pages 987 - 990

https://doi.org/10.1145/355606.361888

Published: 01 November 1972 Publication History

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Abstract

A method for generating values of continuous symmetric random variables that is relatively fast, requires essentially no computer memory, and is easy to use is developed. The method, which uses a uniform zero-one random number source, is based on the inverse function of the lambda distribution of Tukey. Since it approximates many of the continuous theoretical distributions and empirical distributions frequently used in simulations, the method should be useful to simulation practitioners.

References

[1]

Filliben, J.J. Simple and robust linear estimation of the location parameter of a symmetric distribution. Princeton U., Princeton, N.J., 1969.

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Hogg, R.V., and Craig, A.T. Introduction to Mathematical Statistics. Macmillan, New York, 1970.

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Johnson, N.L., and Leone, F.C. Statistics and Experimental Design. Wiley, New York, 1964.

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Naylor, T.H., Balintfy, J.L., Burdick, D.S., and Chu, K. Computer Simulation Techniques. Wiley, New York, 1966.

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Tukey, J.W. Technical Report 36, Stat. Techniques Res. Group, Princeton U., Princeton, N.J., 1960.

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Ratnasingama SBuzaianub ENing W(2022)Modified information criterion for testing changes in generalized lambda distribution model based on confidence distributionCommunications for Statistical Applications and Methods10.29220/CSAM.2022.29.3.30129:3(301-317)Online publication date: 31-May-2022
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An approximate method for generating symmetric random variables
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Published In

Communications of the ACM Volume 15, Issue 11

Nov. 1972

70 pages

ISSN:0001-0782

EISSN:1557-7317

DOI:10.1145/355606

Editor:
M. Stuart Lynn
Rice Univ., Houston, TX

Issue’s Table of Contents

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 November 1972

Published in CACM Volume 15, Issue 11

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https://doi.org/10.3390/econometrics12030020
Deepthy GSebastian NChandra N(2023)Applications of Burr III-Weibull quantile function in reliability analysisStatistical Theory and Related Fields10.1080/24754269.2023.22010967:4(296-308)Online publication date: 9-May-2023
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Ratnasingama SBuzaianub ENing W(2022)Modified information criterion for testing changes in generalized lambda distribution model based on confidence distributionCommunications for Statistical Applications and Methods10.29220/CSAM.2022.29.3.30129:3(301-317)Online publication date: 31-May-2022
https://doi.org/10.29220/CSAM.2022.29.3.301
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Approximating Inverse Cumulative Distribution Functions to Produce Approximate Random Variables

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