Simulation of Markovian models using Bootstrap method

Ricardo M. Czekster*, Paulo Fernandes, Afonso Sales, Dione Taschetto, Thais Webber

*Corresponding author for this work

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

6 Citations (Scopus)

Abstract

Simulation is an interesting alternative to solve Markovian models. However, when compared to analytical and numerical solutions it suffers from a lack of precision in the results due to the very nature of simulation, which is the choice of samples through pseudorandom generation. This paper proposes a different way to simulate Markovian models by using a Bootstrap-based statistical method to minimize the effect of sample choices. The effectiveness of the proposed method, called Bootstrap simulation, is compared to the numerical solution results for a set of examples described using Stochastic Automata Networks modeling formalism.

Original languageEnglish
Title of host publicationSummer Computer Simulation Conference, SCSC 2010 - Proceedings of the 2010 Summer Simulation Multiconference, SummerSim 2010
Pages564-569
Number of pages6
Edition1 BOOK
Publication statusPublished - 2010
EventSummer Computer Simulation Conference, SCSC 2010, Part of the 2010 Summer Simulation Multiconference, SummerSim 2010 - Ottawa, ON, Canada
Duration: 12 Jul 201014 Jul 2010

Publication series

NameSummer Computer Simulation Conference, SCSC 2010 - Proceedings of the 2010 Summer Simulation Multiconference, SummerSim 2010
Number1 BOOK

Conference

ConferenceSummer Computer Simulation Conference, SCSC 2010, Part of the 2010 Summer Simulation Multiconference, SummerSim 2010
Country/TerritoryCanada
CityOttawa, ON
Period12/07/1014/07/10

Keywords

  • Bootstrap method
  • Discrete event simulation
  • Markovian models

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