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 expansion of the mean integrated squared error of a kernel density estimator
β Scribed by Bert van Es
- Publisher
- Elsevier Science
- Year
- 2001
- Tongue
- English
- Weight
- 104 KB
- Volume
- 52
- Category
- Article
- ISSN
- 0167-7152
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β¦ Synopsis
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.
π SIMILAR VOLUMES
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 Ha
In this paper we consider the weighted average square error A,(rc)= (l/n)~=1 {f"(3))f(Xj)}2~(Xj), where f is the common density function of the independent and identically distributed random vectors X~ ..... X,, f, is the kernel estimator based on these vectors and ~z is a weight function. Using U-s