Hall and Hart (1990) proved that the mean integrated squared error (MISE) of a marginal kernel density estimator from an infinite moving average process X1, )(2 .... may be decomposed into the sum of MISE of the same kernel estimator for a random sample of the same size and a term proportional to th
On the asymptotic behaviour of the integrated square error of kernel density estimators with data-dependent bandwidth
โ Scribed by Carlos Tenreiro
- Publisher
- Elsevier Science
- Year
- 2001
- Tongue
- English
- Weight
- 131 KB
- Volume
- 53
- Category
- Article
- ISSN
- 0167-7152
No coin nor oath required. For personal study only.
โฆ Synopsis
In this paper, we consider the integrated square error Jn = { f n (x) -f(x)} 2 d x; where f is the common density function of the independent and identically distributed random vectors X1; : : : ; Xn and f n is the kernel estimator with a data-dependent bandwidth. Using the approach introduced by Hall (J. Multivariate Anal. 14 (1984) 1), and under some regularity conditions, we derive the L2 consistency in probability of f n and we establish an asymptotic expansion in probability and a central limit theorem for Jn.
๐ SIMILAR VOLUMES
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
We give a new proof of the mean integrated squared error expansion for non smooth densities of Van Eeden. The proof exploits the Fourier representation of the mean integrated squared error.