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Large deviations for additive functionals of Markov chains
About this Title
Alejandro D. de Acosta and Peter Ney
Publication: Memoirs of the American Mathematical Society
Publication Year:
2014; Volume 228, Number 1070
ISBNs: 978-0-8218-9089-9 (print); 978-1-4704-1482-5 (online)
DOI: https://doi.org/10.1090/memo/1070
Published electronically: July 15, 2013
Keywords: Large deviations,
Markov chains,
additive functionals,
transform kernels,
convergence parameter,
geometric ergodicity.
MSC: Primary 60J05, 60F10.
Table of Contents
Chapters
- 1. Introduction
- 2. The transform kernels $K_{g}$ and their convergence parameters
- 3. Comparison of $\Lambda (g)$ and $\phi _\mu (g)$
- 4. Proof of Theorem 1
- 5. A characteristic equation and the analyticity of $\Lambda _f$: the case when $P$ has an atom $C\in \mathcal {S}^+$ satisfying $\lambda ^*(C)>0$
- 6. Characteristic equations and the analyticity of $\Lambda _f$: the general case when $P$ is geometrically ergodic
- 7. Differentiation formulas for $u_g$ and $\Lambda _f$ in the general case and their consequences
- 8. Proof of Theorem 2
- 9. Proof of Theorem 3
- 10. Examples
- 11. Applications to an autoregressive process and to reflected random walk
- Appendix
- Background comments
Abstract
For a Markov chain $\{X_j\}$ with general state space $S$ and ${f:S\rightarrow \mathbf {R}^d}$, the large deviation principle for ${\{n^{-1}\sum _{j=1}^nf(X_j)\}}$ is proved under a condition on the chain which is weaker than uniform recurrence but stronger than geometric recurrence and an integrability condition on $f$, for a broad class of initial distributions. This result is extended to the case when $f$ takes values in a separable Banach space. Assuming only geometric ergodicity and under a non-degeneracy condition, a local large deviation result is proved for bounded $f$. A central analytical tool is the transform kernel, whose required properties, including new results, are established. The rate function in the large deviation results is expressed in terms of the convergence parameter of the transform kernel.- A. de Acosta, Upper bounds for large deviations of dependent random vectors, Z. Wahrsch. Verw. Gebiete 69 (1985), no. 4, 551–565. MR 791911, DOI 10.1007/BF00532666
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