Exact asymptotic L1-error of a kernel density estimator under censored data
✍ Scribed by Mohamed Lemdani; Elias Ould-Saı̈d
- Publisher
- Elsevier Science
- Year
- 2002
- Tongue
- English
- Weight
- 139 KB
- Volume
- 60
- Category
- Article
- ISSN
- 0167-7152
No coin nor oath required. For personal study only.
✦ Synopsis
In this paper, we give the exact asymptotic L 1 -error for the kernel estimator of the density function from censored data. We also give asymptotically optimal bandwidths. Strong approximation of the product-limit estimator by a Gaussian process is used to obtain the result.
📜 SIMILAR VOLUMES
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
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