A new approach for computing conditional probabilities of general stochastic processes

Fabian Wickborn, Claudia Isensee, Thomas Simon, Sanja Lazarova-Molnar, Graham Horton

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

4 Citations (Scopus)


In this paper Hidden Markov Model algorithms are considered as a method for computing conditional properties of continuous-time stochastic simulation models. The goal is to develop an algorithm that adapts known Hidden Markov Model algorithms for use with proxel-based simulation. It is shown how the Forward- and Viterbi-algorithms can be directly integrated in the proxel-method. The possibility of integrating the more complex Baum-Welch-algorithm is theoretically addressed. Experiments are conducted to determine the practicability of the new approach and to illustrate the type of analysis that is possible.

Original languageEnglish
Title of host publicationProceedings - 39th Annual Simulation Symposium
Number of pages8
Publication statusPublished - 2006
Event39th Annual Simulation Symposium, 2006 - San Diego, CA, United States
Duration: Apr 2 2006Apr 6 2006

Publication series

NameProceedings - Simulation Symposium
ISSN (Print)1080-241X


Other39th Annual Simulation Symposium, 2006
Country/TerritoryUnited States
CitySan Diego, CA

ASJC Scopus subject areas

  • General Engineering


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