Non-Uniform Random Number Generation: A Survey And Tutorial

The basic pseudo-random number generators on computers return deviates which are uniformly distributed in the interval between 0 and 1. For simulations and other applications other random variables are needed which follow given statistical distributions, for instance normal deviates. The survey will...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
1. Verfasser: Ahrens, J.H.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 50
container_issue
container_start_page 50
container_title
container_volume
creator Ahrens, J.H.
description The basic pseudo-random number generators on computers return deviates which are uniformly distributed in the interval between 0 and 1. For simulations and other applications other random variables are needed which follow given statistical distributions, for instance normal deviates. The survey will concentrate on the most important distributions arising in simulation applications. The considered non-uniform distributions fall into two categories: continuous and discrete. In either class very efficient methods for sampling from general distributions are presented. Specific cases considered include the exponential, normal, gamma, beta and Cauchy distributions in the continuous, and Poisson, binomial and hypergeometric generators in the discrete category. In selecting suitable specific algorithms for each distribution we rejected the 'easiest' methods which are not fast enough. On the other hand, some of the most efficient generators are rather difficult to implement. The selected algorithms are almost as fast as these, but not too complex. Their Fortran versions are portable except for the employed basic (0, 1)-uniform generators for which, however, the user may substitute his or her own favorite. A number of the proposed methods are the author's recent developments. Some well-known alternatives will also be mentioned.
doi_str_mv 10.1109/WSC.1989.718661
format Conference Proceeding
fullrecord <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_718661</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>718661</ieee_id><sourcerecordid>718661</sourcerecordid><originalsourceid>FETCH-LOGICAL-i601-4085de38865569187d6e49d44b94c22397eec697bac58e9292b59392f66c2dd93</originalsourceid><addsrcrecordid>eNotj1FLwzAURgMiqHPPgk_5A625aZLm6lMpOoUxwVV8HGlzC5E1lXQV9u8dzO_lcF4OfIzdgcgBBD58besc0GJegjUGLtiNQAArQFt7xZbT9C1O0ycT6po9bcaYfcbQj2ngHy76ceCbeWgp8RVFSu4QxvjIK76d0y8deRU9b-bDmILb37LL3u0nWv5zwZqX56Z-zdbvq7e6WmfBCMiUsNpTYa3R2iDY0htS6JVqUXVSFlgSdQbL1nXaEkqUrcYCZW9MJ73HYsHuz9lARLufFAaXjrvzu-IPgY9DLg</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Non-Uniform Random Number Generation: A Survey And Tutorial</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Ahrens, J.H.</creator><creatorcontrib>Ahrens, J.H.</creatorcontrib><description>The basic pseudo-random number generators on computers return deviates which are uniformly distributed in the interval between 0 and 1. For simulations and other applications other random variables are needed which follow given statistical distributions, for instance normal deviates. The survey will concentrate on the most important distributions arising in simulation applications. The considered non-uniform distributions fall into two categories: continuous and discrete. In either class very efficient methods for sampling from general distributions are presented. Specific cases considered include the exponential, normal, gamma, beta and Cauchy distributions in the continuous, and Poisson, binomial and hypergeometric generators in the discrete category. In selecting suitable specific algorithms for each distribution we rejected the 'easiest' methods which are not fast enough. On the other hand, some of the most efficient generators are rather difficult to implement. The selected algorithms are almost as fast as these, but not too complex. Their Fortran versions are portable except for the employed basic (0, 1)-uniform generators for which, however, the user may substitute his or her own favorite. A number of the proposed methods are the author's recent developments. Some well-known alternatives will also be mentioned.</description><identifier>ISBN: 0911801588</identifier><identifier>ISBN: 9780911801583</identifier><identifier>DOI: 10.1109/WSC.1989.718661</identifier><language>eng</language><publisher>IEEE</publisher><subject>Distributed computing ; Educational institutions ; Gaussian distribution ; Mathematics ; Random number generation ; Random variables ; Sampling methods ; Statistical distributions ; Tutorial</subject><ispartof>1989 Winter Simulation Conference Proceedings, 1989, p.50-50</ispartof><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/718661$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,4050,4051,27925,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/718661$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Ahrens, J.H.</creatorcontrib><title>Non-Uniform Random Number Generation: A Survey And Tutorial</title><title>1989 Winter Simulation Conference Proceedings</title><addtitle>WSC</addtitle><description>The basic pseudo-random number generators on computers return deviates which are uniformly distributed in the interval between 0 and 1. For simulations and other applications other random variables are needed which follow given statistical distributions, for instance normal deviates. The survey will concentrate on the most important distributions arising in simulation applications. The considered non-uniform distributions fall into two categories: continuous and discrete. In either class very efficient methods for sampling from general distributions are presented. Specific cases considered include the exponential, normal, gamma, beta and Cauchy distributions in the continuous, and Poisson, binomial and hypergeometric generators in the discrete category. In selecting suitable specific algorithms for each distribution we rejected the 'easiest' methods which are not fast enough. On the other hand, some of the most efficient generators are rather difficult to implement. The selected algorithms are almost as fast as these, but not too complex. Their Fortran versions are portable except for the employed basic (0, 1)-uniform generators for which, however, the user may substitute his or her own favorite. A number of the proposed methods are the author's recent developments. Some well-known alternatives will also be mentioned.</description><subject>Distributed computing</subject><subject>Educational institutions</subject><subject>Gaussian distribution</subject><subject>Mathematics</subject><subject>Random number generation</subject><subject>Random variables</subject><subject>Sampling methods</subject><subject>Statistical distributions</subject><subject>Tutorial</subject><isbn>0911801588</isbn><isbn>9780911801583</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>1989</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotj1FLwzAURgMiqHPPgk_5A625aZLm6lMpOoUxwVV8HGlzC5E1lXQV9u8dzO_lcF4OfIzdgcgBBD58besc0GJegjUGLtiNQAArQFt7xZbT9C1O0ycT6po9bcaYfcbQj2ngHy76ceCbeWgp8RVFSu4QxvjIK76d0y8deRU9b-bDmILb37LL3u0nWv5zwZqX56Z-zdbvq7e6WmfBCMiUsNpTYa3R2iDY0htS6JVqUXVSFlgSdQbL1nXaEkqUrcYCZW9MJ73HYsHuz9lARLufFAaXjrvzu-IPgY9DLg</recordid><startdate>1989</startdate><enddate>1989</enddate><creator>Ahrens, J.H.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>1989</creationdate><title>Non-Uniform Random Number Generation: A Survey And Tutorial</title><author>Ahrens, J.H.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i601-4085de38865569187d6e49d44b94c22397eec697bac58e9292b59392f66c2dd93</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>1989</creationdate><topic>Distributed computing</topic><topic>Educational institutions</topic><topic>Gaussian distribution</topic><topic>Mathematics</topic><topic>Random number generation</topic><topic>Random variables</topic><topic>Sampling methods</topic><topic>Statistical distributions</topic><topic>Tutorial</topic><toplevel>online_resources</toplevel><creatorcontrib>Ahrens, J.H.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Ahrens, J.H.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Non-Uniform Random Number Generation: A Survey And Tutorial</atitle><btitle>1989 Winter Simulation Conference Proceedings</btitle><stitle>WSC</stitle><date>1989</date><risdate>1989</risdate><spage>50</spage><epage>50</epage><pages>50-50</pages><isbn>0911801588</isbn><isbn>9780911801583</isbn><abstract>The basic pseudo-random number generators on computers return deviates which are uniformly distributed in the interval between 0 and 1. For simulations and other applications other random variables are needed which follow given statistical distributions, for instance normal deviates. The survey will concentrate on the most important distributions arising in simulation applications. The considered non-uniform distributions fall into two categories: continuous and discrete. In either class very efficient methods for sampling from general distributions are presented. Specific cases considered include the exponential, normal, gamma, beta and Cauchy distributions in the continuous, and Poisson, binomial and hypergeometric generators in the discrete category. In selecting suitable specific algorithms for each distribution we rejected the 'easiest' methods which are not fast enough. On the other hand, some of the most efficient generators are rather difficult to implement. The selected algorithms are almost as fast as these, but not too complex. Their Fortran versions are portable except for the employed basic (0, 1)-uniform generators for which, however, the user may substitute his or her own favorite. A number of the proposed methods are the author's recent developments. Some well-known alternatives will also be mentioned.</abstract><pub>IEEE</pub><doi>10.1109/WSC.1989.718661</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record>
fulltext fulltext_linktorsrc
identifier ISBN: 0911801588
ispartof 1989 Winter Simulation Conference Proceedings, 1989, p.50-50
issn
language eng
recordid cdi_ieee_primary_718661
source IEEE Electronic Library (IEL) Conference Proceedings
subjects Distributed computing
Educational institutions
Gaussian distribution
Mathematics
Random number generation
Random variables
Sampling methods
Statistical distributions
Tutorial
title Non-Uniform Random Number Generation: A Survey And Tutorial
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-24T14%3A10%3A07IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Non-Uniform%20Random%20Number%20Generation:%20A%20Survey%20And%20Tutorial&rft.btitle=1989%20Winter%20Simulation%20Conference%20Proceedings&rft.au=Ahrens,%20J.H.&rft.date=1989&rft.spage=50&rft.epage=50&rft.pages=50-50&rft.isbn=0911801588&rft.isbn_list=9780911801583&rft_id=info:doi/10.1109/WSC.1989.718661&rft_dat=%3Cieee_6IE%3E718661%3C/ieee_6IE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=718661&rfr_iscdi=true