On unbiased density estimation for ergodic diffusion

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.

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Year of publication:	1997
Authors:	Kutoyants, Yu. A.
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 34.1997, 2, p. 133-140
Publisher:	Elsevier
Keywords:	Diffusion process Nonparametric estimation Density function estimation Unbiased estimator Asymptotic normality

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005074634