本文对BMS进行了介绍，并分别利用随机过程中马尔可夫链的知识和时间序列中的INAR(1)模型对BMS进行了研究。
This paper will first introduce BMS, then study BMS by Markov chain in stochastic process and INAR (1) model in time series.
对间断雨量序列有雨、无雨状态的交替变化规律，本文沿用马尔可夫转移概率描述。
The Markov transition probability has been used to describe the interchange properties of the states of rain and non-rain in this paper.
而且，我们还提出一种所谓更新图，它和马尔可夫图的关系类似于更新序列和马尔可夫链的关系。
Moreover, we also find the relation between Markov digraphs and renewal digraphs, similar to that between Markov chains and renewal sequences.
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