Testing for reversibility in markov chain data
PROBABILITY IN THE ENGINEERING AND INFORMATIONAL SCIENCES(2012)
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.
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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
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