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Asymptotic Normality for Density Kernel Estimators in Discrete and Continuous Time

✍ Scribed by Denis Bosq; Florence Merlevède; Magda Peligrad


Publisher
Elsevier Science
Year
1999
Tongue
English
Weight
153 KB
Volume
68
Category
Article
ISSN
0047-259X

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✦ Synopsis


In this paper, we build a central limit theorem for triangular arrays of sequences which satisfy a mild mixing condition. This result allows us to study asymptotic normality of density kernel estimators for some classes of continuous and discrete time processes.


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