摘要
在多元马尔可夫理论模型下研究了状态空间的基本性质及其分解问题.基于高维马氏模型,结合传统马氏链状态空间的定义法,给出了多元马氏模型状态空间的闭集和不可约等基本概念,并研究了在多元马氏模型下闭集与几步转移概率、不可约与状态互通等之间的关系.同时,利用多元马氏模型的状态常返性,对其状态空间进行分解.
The basic properties and decomposition theorem of state space for Markov chain were analyzed un- der multivariate condition. Based on high - dimensional Markovian model, the basic conception of closed set and irreducibility for the model＇ s state space are defined by the method of definition of conventional Markovian chain, and studied the relationships between closed set and nth transition probability as well as irreducibility and state interoperability under the model. The state space was decomposed into subspace by the recurrence of multivariate Markovian model＇s state.
出处
《琼州学院学报》
2014年第2期15-18,共4页
Journal of Qiongzhou University
关键词
多元马氏模型
状态空间
分解定理
Multivariate Markovian model
State space
Decomposition theorem
