Exact Asymptotics for Nonparametric Density Estimation from Dependent Data.

We derive sharp asymptotic minimax bounds (that is, bounds which concern the exact asymptotic constant of the risk) for nonparametric density estimation based on weakly dependent observations. We study two particular problems for which there already exist such results in the case of independent and identically distributed observations, namely, minimax density estimation in Sobolev classes with L2-loss and in Holder classes with L-loss.

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Year of publication:	1999
Authors:	Butucea, C. ; Neumann, M.H.
Subject:	ESTIMATOR \| ECONOMETRICS

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Type of publication:	Book / Working Paper
Notes:	43 pages
Classification:	C13 - Estimation ; C00 - Mathematical and Quantitative Methods. General
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005641142