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Article: Sampling exponentially tilted stable distributions

TitleSampling exponentially tilted stable distributions
Authors
KeywordsExponentially tilted stable distributions
Laplace-Stieltjes transforms
Sampling algorithms
Stable distributions
Issue Date2011
Citation
ACM Transactions on Modeling and Computer Simulation, 2011, v. 22, n. 1, article no. 3 How to Cite?
AbstractSeveral algorithms for sampling exponentially tilted positive stable distributions have recently been suggested. Three of them are known as exact methods, that is, neither do they rely on approximations nor on numerically critical procedures. One of these algorithms is outperformed by another one uniformly over all parameters. The remaining two algorithms are based on different ideas and both have their advantages. After a brief overview of sampling algorithms for exponentially tilted positive stable distributions, the two algorithms are compared. A rule is derived when to apply which for sampling these distributions. © 2011 ACM.
Persistent Identifierhttp://hdl.handle.net/10722/325228
ISSN
2023 Impact Factor: 0.7
2023 SCImago Journal Rankings: 0.338
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorHofert, Marius-
dc.date.accessioned2023-02-27T07:30:48Z-
dc.date.available2023-02-27T07:30:48Z-
dc.date.issued2011-
dc.identifier.citationACM Transactions on Modeling and Computer Simulation, 2011, v. 22, n. 1, article no. 3-
dc.identifier.issn1049-3301-
dc.identifier.urihttp://hdl.handle.net/10722/325228-
dc.description.abstractSeveral algorithms for sampling exponentially tilted positive stable distributions have recently been suggested. Three of them are known as exact methods, that is, neither do they rely on approximations nor on numerically critical procedures. One of these algorithms is outperformed by another one uniformly over all parameters. The remaining two algorithms are based on different ideas and both have their advantages. After a brief overview of sampling algorithms for exponentially tilted positive stable distributions, the two algorithms are compared. A rule is derived when to apply which for sampling these distributions. © 2011 ACM.-
dc.languageeng-
dc.relation.ispartofACM Transactions on Modeling and Computer Simulation-
dc.subjectExponentially tilted stable distributions-
dc.subjectLaplace-Stieltjes transforms-
dc.subjectSampling algorithms-
dc.subjectStable distributions-
dc.titleSampling exponentially tilted stable distributions-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1145/2043635.2043638-
dc.identifier.scopuseid_2-s2.0-84857166975-
dc.identifier.volume22-
dc.identifier.issue1-
dc.identifier.spagearticle no. 3-
dc.identifier.epagearticle no. 3-
dc.identifier.eissn1558-1195-
dc.identifier.isiWOS:000298640600003-

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