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On unbiased density estimation for ergodic diffusion

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  • Kutoyants, Yu. A.

Abstract

Two classes of unbiased estimators of the density function of ergodic distribution for the diffusion process of observations are proposed. The estimators are square-root consistent and asymptotically normal. This curious situation is entirely different from the case of discrete-time models (Davis 1977) where the unbiased estimator rarely exists and usually the estimators are not square-root consistent.

Suggested Citation

  • Kutoyants, Yu. A., 1997. "On unbiased density estimation for ergodic diffusion," Statistics & Probability Letters, Elsevier, vol. 34(2), pages 133-140, June.
    • Handle: RePEc:eee:stapro:v:34:y:1997:i:2:p:133-140
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    References listed on IDEAS

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    1. Castellana, J. V. & Leadbetter, M. R., 1986. "On smoothed probability density estimation for stationary processes," Stochastic Processes and their Applications, Elsevier, vol. 21(2), pages 179-193, February.
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    Cited by:

    1. Yu. Kutoyants, 1998. "Efficient Density Estimation for Ergodic Diffusion Processes," Statistical Inference for Stochastic Processes, Springer, vol. 1(2), pages 131-155, May.

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