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Method and system for identifying regeneration points in a Markov chain Monte Carlo simulation
Method and system for identifying regeneration points in a Markov chain Monte Carlo simulation
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机译：马尔可夫链蒙特卡洛模拟中识别再生点的方法和系统
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摘要
The method of the present invention is to modify an initial target distribution it π by combining it with a point mass concentrated on an “artificial atom” α which is outside the state-space X. A Markov chain may then be constructed using any known technique (for example, using the Metropolis-Hastings Algorithm) with the new target distribution. For this chain, the state α is Harris-recurrent (i.e. with probability one, it occurs infinitely many times). By the Markov property, the times at which the new chain hits α are regeneration times. To recover an ergodic chain with limiting distribution π, it is sufficient simply to delete every occurrence of the state α from the new chain. The points immediately after the (deleted) occurrences of the state α are then regeneration times in a Markov chain with limiting distribution π.
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