Quantile estimation for left truncated and right censored data

Xian Zhou; Liuquan Sun; Haobo Ren

Quantile estimation for left truncated and right censored data

Xian Zhou^*, Liuquan Sun, Haobo Ren

^*Corresponding author for this work

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

19 Citations (Scopus)

Abstract

In this paper we study the estimation of a quantile function based on left truncated and right censored data by the kernel smoothing method. Asymptotic normality and a Berry-Esseen type bound for the kernel quantile estimator are derived. Monte Carlo studies are conducted to compare the proposed estimator with the PL-quantile estimator.

Original language	English
Pages (from-to)	1217-1229
Number of pages	13
Journal	Statistica Sinica
Volume	10
Issue number	4
Publication status	Published - Oct 2000
Externally published	Yes

Keywords

Asymptotic normality
Berry-Esseen type bound
Kernel estimation
Quantile function
Truncated and censored data

Cite this

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title = "Quantile estimation for left truncated and right censored data",

abstract = "In this paper we study the estimation of a quantile function based on left truncated and right censored data by the kernel smoothing method. Asymptotic normality and a Berry-Esseen type bound for the kernel quantile estimator are derived. Monte Carlo studies are conducted to compare the proposed estimator with the PL-quantile estimator.",

keywords = "Asymptotic normality, Berry-Esseen type bound, Kernel estimation, Quantile function, Truncated and censored data",

author = "Xian Zhou and Liuquan Sun and Haobo Ren",

year = "2000",

month = oct,

language = "English",

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pages = "1217--1229",

journal = "Statistica Sinica",

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TY - JOUR

T1 - Quantile estimation for left truncated and right censored data

AU - Zhou, Xian

AU - Sun, Liuquan

AU - Ren, Haobo

PY - 2000/10

Y1 - 2000/10

N2 - In this paper we study the estimation of a quantile function based on left truncated and right censored data by the kernel smoothing method. Asymptotic normality and a Berry-Esseen type bound for the kernel quantile estimator are derived. Monte Carlo studies are conducted to compare the proposed estimator with the PL-quantile estimator.

AB - In this paper we study the estimation of a quantile function based on left truncated and right censored data by the kernel smoothing method. Asymptotic normality and a Berry-Esseen type bound for the kernel quantile estimator are derived. Monte Carlo studies are conducted to compare the proposed estimator with the PL-quantile estimator.

KW - Asymptotic normality

KW - Berry-Esseen type bound

KW - Kernel estimation

KW - Quantile function

KW - Truncated and censored data

UR - https://www.scopus.com/pages/publications/0347607205

M3 - Article

AN - SCOPUS:0347607205

SN - 1017-0405

VL - 10

SP - 1217

EP - 1229

JO - Statistica Sinica

JF - Statistica Sinica

IS - 4

ER -

Quantile estimation for left truncated and right censored data

Abstract

Keywords

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