A note on strong convergence rates in nonparametric regression
β Scribed by Philip E Cheng
- Publisher
- Elsevier Science
- Year
- 1995
- Tongue
- English
- Weight
- 514 KB
- Volume
- 24
- Category
- Article
- ISSN
- 0167-7152
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
We develop a nonparametric test, based on kernel smoothers, in order to decide whether some covariates could be suppressed in a multidimensional nonparametric regression study. We give the asymptotic distribution of the statistic involved in our test, under a general dependence assumption on the sam
A level set of type {f6c} (where f is a density on R d and c is a positive value) can be estimated by its empirical version { f n 6c}, where f n denotes a nonparametric (kernel) density estimator. We analyze, from two di erent points of view, the asymptotic behavior of the probability content of { f
In this paper, we construct a consistent estimstor of nonparametric regression by spline functions, an~point out that a key theorem of Quidels's is wrong.