Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1154607 | Statistics & Probability Letters | 2006 | 5 Pages |
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
Anton Schick, Wolfgang Wefelmeyer,