Poisson equation, moment inequalities and quick convergence for Markov random walks
We provide moment inequalities and sufficient conditions for the quick convergence for Markov random walks, without the assumption of uniform ergodicity for the underlying Markov chain. Our approach is based on martingales associated with the Poisson equation and Wald equations for the second moment with a variance formula. These results are applied to nonlinear renewal theory for Markov random walks. A random coefficient autoregression model is investigated as an example.
Year of publication: |
2000
|
---|---|
Authors: | Fuh, Cheng-Der ; Zhang, Cun-Hui |
Published in: |
Stochastic Processes and their Applications. - Elsevier, ISSN 0304-4149. - Vol. 87.2000, 1, p. 53-67
|
Publisher: |
Elsevier |
Keywords: | Inequality Markov random walk Tail probability Moment Poisson equation Quick convergence Wald equation Renewal theory |
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