Journal
JOURNAL OF MULTIVARIATE ANALYSIS
Volume 79, Issue 1, Pages 114-137Publisher
ACADEMIC PRESS INC
DOI: 10.1006/jmva.2000.1958
Keywords
kernel estimator; continuous processes; strong mixing sequences; confidence sets
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In order to construct confidence sets for a marginal density f of a strictly stationary continuous time process observed over the time interval [0, T], it is necessary to have at one's disposal a Central Limit Theorem for the kernel density estimator f(T) . In this paper we address the question of nonparametric estimation of the asymptotic variance of rootT f(T) an unknown quantity dependent on f. We construct two estimators and study their asymptotic properties, (C) 2001 Academic Press.
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