Nonparametric estimation of a quantile density function by wavelet methods

Christophe Chesneau; Isha Dewan; Hassan Doosti

doi:10.1016/j.csda.2015.08.006

Nonparametric estimation of a quantile density function by wavelet methods

Christophe Chesneau^*, Isha Dewan, Hassan Doosti

^*Corresponding author for this work

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

18 Citations (Scopus)

Abstract

In this paper nonparametric wavelet estimators of the quantile density function are proposed. Consistency of the wavelet estimators is established under the L_p risk. A simulation study illustrates the good performance of our estimators.

Original language	English
Pages (from-to)	161-174
Number of pages	14
Journal	Computational Statistics and Data Analysis
Volume	94
DOIs	https://doi.org/10.1016/j.csda.2015.08.006
Publication status	Published - 2 Feb 2016
Externally published	Yes

Keywords

quantile density estimation
rates of convergence
wavelet methods

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10.1016/j.csda.2015.08.006

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title = "Nonparametric estimation of a quantile density function by wavelet methods",

abstract = "In this paper nonparametric wavelet estimators of the quantile density function are proposed. Consistency of the wavelet estimators is established under the Lp risk. A simulation study illustrates the good performance of our estimators.",

keywords = "quantile density estimation, rates of convergence, wavelet methods",

author = "Christophe Chesneau and Isha Dewan and Hassan Doosti",

year = "2016",

month = feb,

day = "2",

doi = "10.1016/j.csda.2015.08.006",

language = "English",

volume = "94",

pages = "161--174",

journal = "Computational Statistics and Data Analysis",

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TY - JOUR

T1 - Nonparametric estimation of a quantile density function by wavelet methods

AU - Chesneau, Christophe

AU - Dewan, Isha

AU - Doosti, Hassan

PY - 2016/2/2

Y1 - 2016/2/2

N2 - In this paper nonparametric wavelet estimators of the quantile density function are proposed. Consistency of the wavelet estimators is established under the Lp risk. A simulation study illustrates the good performance of our estimators.

AB - In this paper nonparametric wavelet estimators of the quantile density function are proposed. Consistency of the wavelet estimators is established under the Lp risk. A simulation study illustrates the good performance of our estimators.

KW - quantile density estimation

KW - rates of convergence

KW - wavelet methods

UR - https://www.scopus.com/pages/publications/84940508986

U2 - 10.1016/j.csda.2015.08.006

DO - 10.1016/j.csda.2015.08.006

M3 - Article

AN - SCOPUS:84940508986

SN - 0167-9473

VL - 94

SP - 161

EP - 174

JO - Computational Statistics and Data Analysis

JF - Computational Statistics and Data Analysis

ER -

Nonparametric estimation of a quantile density function by wavelet methods

Abstract

Keywords

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