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 19
On efficient estimation of invariant density for ergodic diffusion processes
β Scribed by Ilia Negri
- Publisher
- Elsevier Science
- Year
- 2001
- Tongue
- English
- Weight
- 96 KB
- Volume
- 51
- Category
- Article
- ISSN
- 0167-7152
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β¦ Synopsis
The problem of nonparametric invariant density function estimation of an ergodic di usion process is considered. The local asymptotic minimax lower bound on the risk of all the estimators is established. The asymptotic risk considered measures the distance between the estimators and the density that has to be estimate in a functional space endowed with the supremum norm. The local time estimator is asymptotically e cient in the sense of this lower bound.
π SIMILAR VOLUMES
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