Iterative component‐wise bounds for the steady‐state distribution of a Markov chain
Iterative component‐wise bounds for the steady‐state distribution of a Markov chain
复制标题
马尔可夫链稳态分布的迭代分量边界
DOI：
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发表时间：
2011
影响因子：
4.3
通讯作者：
J. Fourneau
中科院分区：
文献类型：
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作者：
A. Bušić;J. Fourneau
我们证明了一种新的迭代算法来提供不可约非周期马尔可夫链稳态分布的分量界。这些界限是基于（max,+）和（min,+）序列的简单属性。边界在每次迭代中都得到改进。因此，我们在边界的紧密性（一些算法收敛于真解）和计算时间之间有一个明确的权衡。版权所有©2011 John Wiley & Sons， Ltd
We prove new iterative algorithms to provide component‐wise bounds of the steady‐state distribution of an irreducible and aperiodic Markov chain. These bounds are based on simple properties of (max,+) and (min,+) sequences. The bounds are improved at each iteration. Thus, we have a clear trade‐off between tightness of the bounds (some algorithms converge to the true solution) and computation times. Copyright © 2011 John Wiley & Sons, Ltd.