Methods Of Kernel Estimates Represent One Of The Most Effective Nonparametric Smoothing Techniques. These Methods Are Simple To Understand And They Possess Very Good Statistical Properties. This Book Provides A Concise And Comprehensive Overview Of Statistical Theory And In Addition, Emphasis Is Giv
Kernel estimation of a distribution function
β Scribed by Peter D., Hill
- Book ID
- 120407138
- Publisher
- Taylor and Francis Group
- Year
- 1985
- Tongue
- English
- Weight
- 444 KB
- Volume
- 14
- Category
- Article
- ISSN
- 0361-0926
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
The optimal bandwidth of the d-dimensional kernel estimator of a density is well known to have order n l.,(4+d). In this note, the multivariate distribution function F(x) is estimated by integrating a kernel estimator of its density. The asymptotic optimal bandwidth of the d-dimensional kernel dist
The asymptotic results for a kernel estimator of a distribution function F [Azzalini (1981)] are extended. Under certain smoothness conditions on the quantile function, it is established that. a class of kernel estimators of F can achieve a smaller mean squared error than the empirical distribution