Asymptotic Normality for Density Kernel Estimators in Discrete and Continuous Time
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.
Volume (Year): 68 (1999)
Issue (Month): 1 (January)
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