Bahadur Representation of Linear Kernel Quantile Estimator for Stationary Processes

被引：1

作者：

Huang Chu ^{[1
]}

Zhang Li-Xin ^{[1
]}

机构：

[1] Zhejiang Univ, Dept Math, Hangzhou 310003, Zhejiang, Peoples R China

来源：

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2014年 / 43卷 / 22期

基金：

中国国家自然科学基金;

关键词：

S-mixing; Kernel quantile estimator; Bahadur representation; SAMPLE QUANTILES; SEQUENCES;

D O I：

10.1080/03610926.2012.736582

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：

In this article, we discuss the method of linear kernel quantile estimator proposed by Parzen (1979). We establish a Bahadur representation in sense of almost surely convergence with the rate log-an under the case of S-mixing random variable sequence which was proposed by Berkes (2009). We also obtain the strong consistence of this estimator and its convergence rate.

引用

页码：4669 / 4678

页数：10

共 50 条

[21] A MODIFIED KERNEL QUANTILE ESTIMATOR UNDER CENSORING
LIO, YL
PADGETT, WJ
CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE, 1988, 16 (02): : 175 - 183
[22] The L1-norm kernel estimator of conditional median for stationary processes
Lin, Zhengyan
Li, Degui
RANDOM WALK, SEQUENTIAL ANALYSIS AND RELATED TOPICS: A FESTSCHRIFT IN HONOR OF YUAN-SHIH CHOW, 2006, : 281 - +
[23] Reduction principles for quantile and Bahadur-Kiefer processes of long-range dependent linear sequences
Csorgo, Miklos
Kulik, Rafal
PROBABILITY THEORY AND RELATED FIELDS, 2008, 142 (3-4) : 339 - 366
[24] Bahadur-Kiefer representations for time dependent quantile processes
Kevei, Peter
Mason, David M.
PERIODICA MATHEMATICA HUNGARICA, 2018, 76 (01) : 95 - 113
[25] A Bahadur representation of the linear support vector machine
Koo, Ja-Yong
Lee, Yoonkyung
Kim, Yuwon
Park, Changyi
Journal of Machine Learning Research, 2008, 9 : 1343 - 1368
[26] A Bahadur representation of the linear support vector machine
Koo, Ja-Yong
Lee, Yoonkyung
Kim, Yuwon
Park, Changyi
JOURNAL OF MACHINE LEARNING RESEARCH, 2008, 9 : 1343 - 1368
[27] Kernel conditional quantile estimation for stationary processes with application to conditional value-at-risk
Wu, Wei Biao
Yu, Keming
Mitra, Gautam
JOURNAL OF FINANCIAL ECONOMETRICS, 2008, 6 (02) : 253 - 270
[28] THE BAHADUR EFFICIENCY FOR ENERGY DETECTION OF STATIONARY GAUSSIAN PROCESSES
Lee, Yuni
Sung, Youngchul
2012 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2012, : 3945 - 3948
[29] Value at risk estimation by quantile regression and kernel estimator
Huang A.Y.
Review of Quantitative Finance and Accounting, 2013, 41 (2) : 225 - 251
[30] L2 consistency of the kernel quantile estimator
Youndje, E.
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 2023, 52 (17) : 6111 - 6125

← 1 2 3 4 5 →