Testing for reversibility in markov chain data

PROBABILITY IN THE ENGINEERING AND INFORMATIONAL SCIENCES(2012)

引用 4|浏览2
暂无评分
摘要
This paper introduces two statistics that assess whether (or not) a sequence sampled from a stationary time-homogeneous Markov chain on a finite state space is reversible. The test statistics are based on observed deviations of transition sample counts between each pair of states in the chain. First, the joint asymptotic normality of these sample counts is established. This result is then used to construct two chi-squared-based tests for reversibility. Simulations assess the power and type one error of the proposed tests.
更多
查看译文
关键词
joint asymptotic normality,transition sample count,markov chain data,sample count,test statistic,chi-squared-based test,proposed test,stationary time-homogeneous markov chain,observed deviation,finite state space
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要