On the convergence rates of kernel estimator and hazard estimator for widely dependent samples

Yongming Li; Yong Zhou; Chao Liu

doi:10.1186/s13660-018-1659-1

On the convergence rates of kernel estimator and hazard estimator for widely dependent samples

Yongming Li^*
, Yong Zhou
, Chao Liu

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

7 Scopus citations

Abstract

In this paper, we establish a Bernstein-type inequality for widely orthant dependent random variables, and obtain the rates of strong convergence for kernel estimators of density and hazard functions, under some suitable conditions.

Original language	English
Article number	71
Journal	Journal of Inequalities and Applications
Volume	2018
DOIs	https://doi.org/10.1186/s13660-018-1659-1
State	Published - 2018
Externally published	Yes

Keywords

Hazard rate
Kernel density estimator
Strong convergence
Widely orthant dependent

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10.1186/s13660-018-1659-1

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title = "On the convergence rates of kernel estimator and hazard estimator for widely dependent samples",

abstract = "In this paper, we establish a Bernstein-type inequality for widely orthant dependent random variables, and obtain the rates of strong convergence for kernel estimators of density and hazard functions, under some suitable conditions.",

keywords = "Hazard rate, Kernel density estimator, Strong convergence, Widely orthant dependent",

author = "Yongming Li and Yong Zhou and Chao Liu",

note = "Publisher Copyright: {\textcopyright} 2018, The Author(s).",

year = "2018",

doi = "10.1186/s13660-018-1659-1",

language = "英语",

volume = "2018",

journal = "Journal of Inequalities and Applications",

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T1 - On the convergence rates of kernel estimator and hazard estimator for widely dependent samples

AU - Li, Yongming

AU - Zhou, Yong

AU - Liu, Chao

PY - 2018

Y1 - 2018

N2 - In this paper, we establish a Bernstein-type inequality for widely orthant dependent random variables, and obtain the rates of strong convergence for kernel estimators of density and hazard functions, under some suitable conditions.

AB - In this paper, we establish a Bernstein-type inequality for widely orthant dependent random variables, and obtain the rates of strong convergence for kernel estimators of density and hazard functions, under some suitable conditions.

KW - Hazard rate

KW - Kernel density estimator

KW - Strong convergence

KW - Widely orthant dependent

UR - https://www.scopus.com/pages/publications/85044978377

U2 - 10.1186/s13660-018-1659-1

DO - 10.1186/s13660-018-1659-1

M3 - 文章

AN - SCOPUS:85044978377

SN - 1025-5834

VL - 2018

JO - Journal of Inequalities and Applications

JF - Journal of Inequalities and Applications

M1 - 71

ER -

On the convergence rates of kernel estimator and hazard estimator for widely dependent samples

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Keywords

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