Skip to main content
Log in

On the Uniform Convergence of the Empirical Density of an Ergodic Diffusion

  • Published:
Statistical Inference for Stochastic Processes Aims and scope Submit manuscript

Abstract

We investigate the uniform convergence of the density of the empirical measure of an ergodic diffusion. It is known that under certain conditions on the drift and diffusion coefficients of the diffusion, the empirical density f t converges in probability to the invariant density f, uniformly on the entire real line. We show that under the same conditions, uniform convergence of f t to f on compact intervals takes place almost surely. Moreover, we prove that under much milder conditions (the usual linear growth condition on the drift and diffusion coefficients and a finite second moment of the invariant measure suffice), we have the uniform convergence of f t to f on compacta in probability.

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. Billingsley, P.: Convergence of Probability Measures, Wiley, 1968.

  2. Bosq, D. and Davydov, Yu.: Local time and density estimation in continuous time, Math. Meth. Stat. 8(1) (1999), 22–45.

    MATH  MathSciNet  Google Scholar 

  3. Dudley, R. M.: A course on empirical processes ( École d' Éte de Probabilités de Saint-Flour XII-1982), Lecture Notes in Math. 1097, Springer, 1984, pp. 2–141.

    MathSciNet  Google Scholar 

  4. Gihman, I. I. and Skorohod, A. V.: Stochastic Differential Equations, Springer, 1972.

  5. Ibragimov, I. A. and Has'misnkii, R. Z.: Statistical Estimation, Asymptotic Theory, Springer, 1981.

  6. Karatzas, I. and Shreve, S.E.: Brownian Motion and Stochastic Calculus, 2nd edition, Springer, 1991.

  7. Kutoyants, Yu. A.: Efficiency of the empirical distribution for ergodic diffusion, Bernoulli 3(4) (1997), 445–456.

    Article  MATH  MathSciNet  Google Scholar 

  8. Kutoyants, Yu. A.: Efficient density estimation for ergodic diffusion processes, Stat. Inf. Stoch. Proc. 1(2) (1998), 131–155.

    Article  MATH  Google Scholar 

  9. Negri, I.: Stationary Distribution Function estimation for ergodic disffusion process, Stat. Inf. Stoch. Proc. 1(1) (1998a), 61–84.

    Article  MATH  MathSciNet  Google Scholar 

  10. Negri, I.: PhD Thesis, Université du Maine, 1998b.

  11. van der Vaart, A. W. and Wellner, J. A.: Weak Convergence and Empirical Processes with Applications to Statistics, Springer, 1996.

  12. van Zanten, J. H.: A multivariate central limit theorem for continuous local martingales, Statist. Probab. Lett. 50(3) (2000), 229–235.

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

van Zanten, J.H. On the Uniform Convergence of the Empirical Density of an Ergodic Diffusion. Statistical Inference for Stochastic Processes 3, 251–262 (2000). https://doi.org/10.1023/A:1009949802518

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1009949802518

Navigation