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arXiv 1107.4353math.PR
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无限级链在$\bar{d}$ -度量下的马氏逼近

Markov Approximations of chains of infinite order in the $\bar{d}$-metric

Sandro Gallo, Matthieu Lerasle, Daniel Yasumasa Takahashi

摘要:

我们得到明确的上界之间的$\bar{d}$ -距离的无限级链和它的规范$k$ -步骤马尔可夫近似。我们的证明是完全建设性的,并涉及一个“耦合从过去”的论点。新方法覆盖了不一定连续的概率核和具有空转移概率的链。这些结果特别暗示了这些过程的伯努利性质。

英文摘要:

We derive explicit upper bounds for the $\bar{d}$-distance between a chain of infinite order and its canonical $k$-steps Markov approximation. Our proof is entirely constructive and involves a "coupling from the past" argument. The new method covers non necessarily continuous probability kernels, and chains with null transition probabilities. These results imply in particular the Bernoulli property for these processes.

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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