Abstract

In this work, we interest to the estimation of the steady-state probabilities of the two processes (the hidden Markov chain and the emission process) composing a standard Hidden Markov Model. Since the estimation of steady-state Markov chain is well known, more attention will be given to the estimation of the steady-state of the emission process. Among different methods, we will focus more on the technique based on the regenerative notion, often used in steady-state Markov chain simulation. Numerical Monte Carlo simulations are carried to show the usefulness of our proposal and to appreciate the quality of different proposed estimators.

中文翻译：

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隐马尔可夫模型稳态估计

摘要

在这项工作中，我们对估计构成标准隐马尔可夫模型的两个过程（隐马尔可夫链和发射过程）的稳态概率感兴趣。由于稳态马尔可夫链的估计是众所周知的，所以将更多地关注排放过程的稳态估计。在不同的方法中，我们将更多地关注基于再生概念的技术，通常用于稳态马尔可夫链模拟。进行数值蒙特卡罗模拟以显示我们提议的有用性并了解不同提议的估计器的质量。