Moderate Deviations in L_1(\mathbbR^d) for a Test of Symmetry Based on Kernel Density Estimator

XU Mingzhou; DING Yunzheng; ZHOU Yongzheng

doi:10.3969/j.issn.1001-4268.2019.02.003

XU Mingzhou, DING Yunzheng, ZHOU Yongzheng. Moderate Deviations in L_1(\mathbb{R}^d) for a Test of Symmetry Based on Kernel Density Estimator[J]. Chinese Journal of Applied Probability and Statistics, 2019, 35(2): 141-152. DOI: 10.3969/j.issn.1001-4268.2019.02.003

Citation:

XU Mingzhou, DING Yunzheng, ZHOU Yongzheng. Moderate Deviations in L_1(\mathbb{R}^d) for a Test of Symmetry Based on Kernel Density Estimator[J]. Chinese Journal of Applied Probability and Statistics, 2019, 35(2): 141-152. DOI: 10.3969/j.issn.1001-4268.2019.02.003

Citation:

XU Mingzhou, DING Yunzheng, ZHOU Yongzheng. Moderate Deviations in L_1(\mathbb{R}^d) for a Test of Symmetry Based on Kernel Density Estimator[J]. Chinese Journal of Applied Probability and Statistics, 2019, 35(2): 141-152. DOI: 10.3969/j.issn.1001-4268.2019.02.003

Moderate Deviations in L_1(\mathbbR^d) for a Test of Symmetry Based on Kernel Density Estimator

Graphical Abstract

Abstract

Abstract

Let f_n be a non-parametric kernel density estimator based on a kernel function K and a sequence of independent and identically distributed random variables taking values in \mathbbR^d. In this paper we prove two moderate deviation theorems in L_1(\mathbbR^d) for \f_n(x)-f_n(-x),\,n\ge1\.

FullText(HTML)

References (0)

Moderate Deviations in L_1(\mathbbR^d) for a Test of Symmetry Based on Kernel Density Estimator

Abstract

Catalog

Export File

Citation

Format

Content