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The eigenvalues of the empirical transition matrix of a Markov chain
Published online by Cambridge University Press: 14 July 2016
Abstract
This paper investigates the probabilistic behaviour of the eigenvalue of the empirical transition matrix of a Markov chain which is of largest modulus other than 1, loosely called the second-largest eigenvalue. A central limit theorem is obtained for nonmultiple eigenvalues of the empirical transition matrix. When the Markov chain is actually a sequence of independent observations the distribution of the second-largest eigenvalue is determined and a test for independence is developed. The independence case is considered in more detail when the Markov chain has only two states, and some applications are given.
Keywords
MSC classification
- Type
- Part 6. Stochastic processes
- Information
- Journal of Applied Probability , Volume 41 , Issue A: Stochastic Methods and their Applications , 2004 , pp. 347 - 360
- Copyright
- Copyright © Applied Probability Trust 2004
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