Keywords:
Forschungsbericht
Description / Table of Contents:
The paper presents a unified approach to local likelihood estimation for a broad class of nonparametric models, including e.g. the regression, density, Poisson and binary response model. Given a sequence of local likelihood estimates which we call ''weak'' estimates, the proposed method yields a new aggregated estimate whose pointwise risk does not exceed the smallest risk among all "weak" estimates multiplied by some logarithmic factor. We establish a number of important theoretical results concerning optimality of the aggregated estimate and show a good performance of the procedure in simulated examples.
Type of Medium:
Online Resource
Pages:
1 Online-Ressource (34 Seiten, 658,45 KB)
,
Diagramme
Series Statement:
Preprint / Weierstraß-Institut für Angewandte Analysis und Stochastik no. 1000
URL:
http://webdoc.sub.gwdg.de/ebook/serien/e/wias/2004/2004/wias_preprints_1000.pdf
URL:
https://edocs.tib.eu/files/e01fn21/50423000X.pdf
Language:
English
Note:
Literaturverzeichnis: Seite 30-32
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