Simulation of Markovian models using bootstrap method

Authors:
Ricardo M. Czekster;Paulo Fernandes;Afonso Sales;Dione Taschetto;Thais Webber
Affiliations:
Faculdade de Informática - Pontifícia Universidade Católica do Rio Grande do Sul, Porto Alegre -- RS -- Brasil;Faculdade de Informática - Pontifícia Universidade Católica do Rio Grande do Sul, Porto Alegre -- RS -- Brasil;Faculdade de Informática - Pontifícia Universidade Católica do Rio Grande do Sul, Porto Alegre -- RS -- Brasil;Faculdade de Informática - Pontifícia Universidade Católica do Rio Grande do Sul, Porto Alegre -- RS -- Brasil;Faculdade de Informática - Pontifícia Universidade Católica do Rio Grande do Sul, Porto Alegre -- RS -- Brasil
Venue:
Proceedings of the 2010 Summer Computer Simulation Conference
Year:
2010

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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.