Skip to main content
Log in

Large deviations for empirical measures of Markov chains

  • Published:
Journal of Theoretical Probability Aims and scope Submit manuscript

Abstract

In this paper we obtain large-deviation upper and lower bounds for the empirical measure of a Markov chain with general state space, as well as for the associated multivariate empirical measure and empirical process. In each of these instances we improve in various ways the results in the literature.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Acosta, A. de (1985). Upper bounds for large deviations of dependent random vectors.Z. Wahrsch. verw. Gebiete 69, 551–565.

    Google Scholar 

  2. Acosta, A. de (1988). Large deviations for vector-valued functionals of a Markov chain: Lower bounds.Ann. Probab. 16, 925–960.

    Google Scholar 

  3. Bolthausen, E. (1987). Markov process large deviations in τ-topology.Stoch. Proc. Appl. 25, 95–108.

    Google Scholar 

  4. Bourbaki, N. (1965).Topologie Générale, Hermann, Paris, Chaps. 1 and 2.

    Google Scholar 

  5. Dawson, D., and Gärtner, J. (1987). Large deviations from the McKean-Vlasov limit for interacting diffusions.Stochastics 20, 247–308.

    Google Scholar 

  6. Donsker, M. D., and Varadhan, S. R. S. (1976). Asymptotic evaluation of certain Markov process expectations for large time. IIICommun.Pure Appl. Math. 29, 389–461.

    Google Scholar 

  7. Donsker, M. D., and Varadhan, S. R. S. (1983). Asymptotic evaluation of certain Markov process expectations for large time. IV.Commun. Pure Appl. Math. 36, 183–212.

    Google Scholar 

  8. Ekeland, I., and Temam, R. (1976).Convex Analysis and Variational Problems, North-Holland, Amsterdam.

    Google Scholar 

  9. Ellis, R. (1984). Large deviations for a general class of dependent random vectors.Ann. Prob. 12, 1–12.

    Google Scholar 

  10. Ellis, R. (1988). Large deviations for the empirical measure of a Markov chain with an application to the multivariate empirical measure.Ann. Probab. 16, 1496–1508.

    Google Scholar 

  11. Ellis, R., and Wyner, A. (1988). Uniform large deviation property of the empirical process of a Markov chain.Ann. Probab. 17, 1147–1151.

    Google Scholar 

  12. Ganssler, P. (1971). Compactness and sequential compactness in spaces of measures.Z. Wahrsch. verw. Gebiete 17, 124–146.

    Google Scholar 

  13. Gärtner, J. (1977). On large deviations from the invariant measure.Theor. Probab. Appl. 12, 24–39.

    Google Scholar 

  14. Horvath, J. (1966).Topological Vector Spaces and Distributions. Addison-Wesley, Reading, Massachusetts.

    Google Scholar 

  15. Jain, N. (1988). Large deviation lower bounds for additive functionals of Markov processes. (To appear inAnn. Probab.)

  16. Neveu, J. (1964).Bases Mathématiques du Calcul des Probabilités. Masson, Paris.

    Google Scholar 

  17. Ney, P., and Nummelin, E. (1987). Markov additive processes. II: Large deviations.Ann. Probab. 15, 593–609.

    Google Scholar 

  18. Nummelin, E. (1984).General Irreducible Markov Chains and Non-negative Operators. Cambridge University Press, Cambridge, England.

    Google Scholar 

  19. Stroock, D. W. (1984).An Introduction to the Theory of Large Deviations. Springer-Verlag, Berlin and New York.

    Google Scholar 

  20. Varadhan, S. R. S. (1985). Large deviations and applications.Expositiones Math.3, 251–272.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

de Acosta, A. Large deviations for empirical measures of Markov chains. J Theor Probab 3, 395–431 (1990). https://doi.org/10.1007/BF01061260

Download citation

  • Received:

  • Revised:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF01061260

Key Words

Navigation