On the Twisted Markov Chain of Importance Sampling Simulation (Special Section on Information Theory and Its Applications)

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概要

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• The importance sampling simulation technique has been exploited to obtain an accurate estimate for a very small probability which is not tractable by the ordinary Monte Carlo simulation. In this paper, we will investigate the simulation for a sample average of an output sequence from a Markov chain. The optimal simulation distribution will be characterized by the Kullback-Leibler divergence of Markov chains and geometric properties of the importance sampling simulation will be presented. As a result, an effective computation method for the optimal simulation distribution will be obtained.

• 社団法人電子情報通信学会の論文
• 1996-09-25

著者

• Nakagawa Kenji

  The Department Of Electrical Engineering Nagaoka University Of Technology

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