In this paper we address the problem of estimating y 1 when Y i B ind NΓ°y i ; s 2 i Γ; i ΒΌ 1; 2; are observed and jy 1 Γ y 2 jpc for a known constant c: Clearly Y 2 contains information about y 1 : We show how the so-called weighted likelihood function may be used to generate a class of estimators t
A bound on the expected maximal deviation of averages from their means
β Scribed by Michael Hamers; Michael Kohler
- Publisher
- Elsevier Science
- Year
- 2003
- Tongue
- English
- Weight
- 136 KB
- Volume
- 62
- Category
- Article
- ISSN
- 0167-7152
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β¦ Synopsis
A bound on the expected maximal deviation of averages from their means over a ΓΏnite space of functions is derived. The usefulness of this new bound is demonstrated by an application in nonparametric regression.
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