Article ID Journal Published Year Pages File Type
1154607 Statistics & Probability Letters 2006 5 Pages PDF
Abstract

Convergence rates and central limit theorems for kernel estimators of the stationary density of a linear process have been obtained under the assumption that the innovation density is smooth (Lipschitz). We show that smoothness is not required. For example, it suffices that the innovation density has bounded variation.

Related Topics
Physical Sciences and Engineering Mathematics Statistics and Probability
Authors
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