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Estimation of the Asymptotic Variance of Kernel Density Estimators for Continuous Time Processes

✍ Scribed by Armelle Guillou; Florence Merlevède

Publisher
Elsevier Science
Year
2001
Tongue
English
Weight
196 KB
Volume
79
Category
Article
ISSN
0047-259X

No coin nor oath required. For personal study only.

✦ Synopsis

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 -T f T , an unknown quantity dependent on f. We construct two estimators and study their asymptotic properties.

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