Bayesian nonparametric (BNP) models provide a flexible tool in modeling many processes. One area that has not yet utilized BNP estimation is semi‐Markov processes (SMPs). SMPs require a significant amount of computation; this, coupled with the computation requirements for BNP models, has hampered any applications of SMPs using BNP estimation. This paper presents a modeling and computational approach for BNP estimation in semi‐Markov models, which includes a simulation study and an application of asthma patients' first passage from one state of control to another.

中文翻译：

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半马尔可夫过程中第一通道分布的贝叶斯非参数估计

贝叶斯非参数（BNP）模型为建模许多过程提供了灵活的工具。半马尔可夫过程（SMP）是尚未利用BNP估计的一个领域。SMP需要大量计算；这加上BNP模型的计算要求，已经阻碍了使用BNP估计的SMP的任何应用。本文提出了一种半马尔可夫模型中BNP估计的建模和计算方法，其中包括模拟研究和哮喘患者从一种控制状态到另一种控制状态的首次应用。