Best asymptotic normality of the kernel density entropy estimator for smooth densities
β Scribed by Eggermont, P.B.; LaRiccia, V.N.
- Book ID
- 111860982
- Publisher
- IEEE
- Year
- 1999
- Tongue
- English
- Weight
- 237 KB
- Volume
- 45
- Category
- Article
- ISSN
- 0018-9448
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
In this paper, we build a central limit theorem for triangular arrays of sequences which satisfy a mild mixing condition. This result allows us to study asymptotic normality of density kernel estimators for some classes of continuous and discrete time processes.
The estimation of integrated density derivatives is a crucial problem which arises in data-based methods for choosing the bandwidth of kernel and histogram estimators. In this paper, we establish the asymptotic normality of a multistage kernel estimator of such quantities, by showing that under some