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Uniform fractional part: a simple fast method for generating continuous random variates

Uniform fractional part: a simple fast method for generating continuous random variates
Uniform fractional part: a simple fast method for generating continuous random variates
A known theorem in probability is adopted and through a probabilistic approach, it is generalized to develop a method for generating random deviates from the distribution of any continuous random variable. This method, which may be considered as an approximate version of the Inverse Transform algorithm, takes two random numbers to generate a random deviate, while maintaining all the other advantages of the Inverse Transform method, such as the possibility of generating ordered as well as correlated deviates and being applicable to all density functions, regardless of their parameter values
1026-3098
613-622
Mahlooji, H.
b194e796-03e8-4053-bdd1-048675df2f1d
Eshragh Jahromi, A.
f836cd6a-f6d8-46f2-a697-6a1dc171b6df
Abouee Mehrizi, H.
d9e7ce5d-559a-4d0a-81d8-6b2ec7036691
Izady, N.
bca6a7c0-064b-4502-a273-5645723a0b02
Mahlooji, H.
b194e796-03e8-4053-bdd1-048675df2f1d
Eshragh Jahromi, A.
f836cd6a-f6d8-46f2-a697-6a1dc171b6df
Abouee Mehrizi, H.
d9e7ce5d-559a-4d0a-81d8-6b2ec7036691
Izady, N.
bca6a7c0-064b-4502-a273-5645723a0b02

Mahlooji, H., Eshragh Jahromi, A., Abouee Mehrizi, H. and Izady, N. (2008) Uniform fractional part: a simple fast method for generating continuous random variates. Scientia Iranica, 15 (5), 613-622.

Record type: Article

Abstract

A known theorem in probability is adopted and through a probabilistic approach, it is generalized to develop a method for generating random deviates from the distribution of any continuous random variable. This method, which may be considered as an approximate version of the Inverse Transform algorithm, takes two random numbers to generate a random deviate, while maintaining all the other advantages of the Inverse Transform method, such as the possibility of generating ordered as well as correlated deviates and being applicable to all density functions, regardless of their parameter values

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Published date: October 2008
Organisations: Operational Research

Identifiers

Local EPrints ID: 176777
URI: http://eprints.soton.ac.uk/id/eprint/176777
ISSN: 1026-3098
PURE UUID: cba7e562-b8b9-40a7-86d0-789b8980ed1c

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Date deposited: 11 Mar 2011 09:33
Last modified: 09 Dec 2019 20:24

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