Convergence rates in weighted L1 spaces of kernel density estimators for linear processes

被引：0

作者：

Schick, Anton ^{[1
]}

Wefelmeyer, Wolfgang ^{[2
]}

机构：

[1] SUNY Binghamton, Dept Math Sci, Binghamton, NY 13902 USA

[2] Univ Cologne, Math Inst, D-50931 Cologne, Germany

来源：

ALEA-LATIN AMERICAN JOURNAL OF PROBABILITY AND MATHEMATICAL STATISTICS | 2008年 / 4卷

关键词：

L-1-Lipschitz; smoothness of convolutions; variance bound;

D O I：

暂无

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

Pointwise and uniform convergence rates for kernel estimators of the stationary density of a linear process have been obtained by several authors. Here we obtain rates in weighted L-1 spaces. In particular, if infinitely many coefficients of the process are non-zero and the innovation density has bounded variation, then nearly parametric rates are achievable by proper choice of kernel and bandwidth.

引用

页码：117 / 129

页数：13

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