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arXiv 1004.0113math.PR
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长记忆过程完美模拟的一般框架

A general framework for perfect simulation of long memory processes

Emilio De Santis, Mauro Piccioni

摘要:

本文提出了一种完美模拟状态空间至多可数的平稳过程的一般方法。这个过程是通过一个内核来指定的,它规定了每个状态的概率与整个过去的历史是有条件的。我们遵循彗星,费尔南德斯和法拉利,其中充分条件的建设,一定完美的模拟算法的开创性文件。我们通过定义这些过程的向后合并时间来推广这种方法,这使我们能够在较弱的条件下构建完美的模拟算法。

英文摘要:

In this paper a general approach for the perfect simulation of a stationary process with at most countable state space is outlined. The process is specified through a kernel, prescribing the probability of each state conditional to the whole past history. We follow the seminal paper of Comets, Fernandez and Ferrari, where sufficient conditions for the construction of a certain perfect simulation algorithm have been given. We generalize this approach by defining backward coalescence times for these kind of processes; this allows us to construct perfect simulation algorithms under weaker conditions.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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