Efficient generation of PH-distributed random variates

Gábor Horváth, Philipp Reinecke, Miklós Telek, Katinka Wolter

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Phase-type (PH) distributions are being used to model a wide range of phenomena in performance and dependability evaluation. The resulting models may be employed in analytical as well as in simulation-driven approaches. Simulations require the efficient generation of random variates from PH distributions. PH distributions have different representations and different associated computational costs for random-variate generation. In this paper we study the problem of efficient representation and efficient generation of PH distributed variates.

Original languageEnglish
Title of host publicationAnalytical and Stochastic Modeling Techniques and Applications - 19th International Conference, ASMTA 2012, Proceedings
Pages271-285
Number of pages15
DOIs
Publication statusPublished - Jun 18 2012
Event19th International Conference on Analytical and Stochastic Modelling and Applications, ASMTA 2012 - Grenoble, France
Duration: Jun 4 2012Jun 6 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7314 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other19th International Conference on Analytical and Stochastic Modelling and Applications, ASMTA 2012
CountryFrance
CityGrenoble
Period6/4/126/6/12

Keywords

  • PH distribution
  • pseudo random number generation

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Horváth, G., Reinecke, P., Telek, M., & Wolter, K. (2012). Efficient generation of PH-distributed random variates. In Analytical and Stochastic Modeling Techniques and Applications - 19th International Conference, ASMTA 2012, Proceedings (pp. 271-285). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7314 LNCS). https://doi.org/10.1007/978-3-642-30782-9_19