Asymptotic normality of the NPMLE of linear functionals for interval censored data, case 1

Jian Huang; J. A. Wellner

doi:10.1111/j.1467-9574.1995.tb01462.x

Asymptotic normality of the NPMLE of linear functionals for interval censored data, case 1

Jian Huang, J. A. Wellner

Research output: Journal article publication › Journal article › Academic research › peer-review

56 Citations (Scopus)

Abstract

We give a new proof of the asymptotic normality of a class of linear functionals of the nonparametric maximum likelihood estimator (NPMLE) of a distribution function with “case 1” interval censored data. In particular our proof simplifies the proof of asymptotic normality of the mean given in Groeneboom and Wellner (1992). The proof relies strongly on a rate of convergence result due to van de Geer (1993), and methods from empirical process theory.

Original language	English
Pages (from-to)	153-163
Number of pages	11
Journal	Statistica Neerlandica
Volume	49
Issue number	2
DOIs	https://doi.org/10.1111/j.1467-9574.1995.tb01462.x
Publication status	Published - 1 Jan 1995
Externally published	Yes

Keywords

asymptotic distribution
empirical processes
linear functionals
mean moments
nonparametric maximum likelihood

ASJC Scopus subject areas

Statistics and Probability
Statistics, Probability and Uncertainty

More information

10.1111/j.1467-9574.1995.tb01462.x

Cite this

@article{537656a084c241dfb7ce6a464461646d,

title = "Asymptotic normality of the NPMLE of linear functionals for interval censored data, case 1",

abstract = "We give a new proof of the asymptotic normality of a class of linear functionals of the nonparametric maximum likelihood estimator (NPMLE) of a distribution function with “case 1” interval censored data. In particular our proof simplifies the proof of asymptotic normality of the mean given in Groeneboom and Wellner (1992). The proof relies strongly on a rate of convergence result due to van de Geer (1993), and methods from empirical process theory.",

keywords = "asymptotic distribution, empirical processes, linear functionals, mean moments, nonparametric maximum likelihood",

author = "Jian Huang and Wellner, {J. A.}",

year = "1995",

month = jan,

day = "1",

doi = "10.1111/j.1467-9574.1995.tb01462.x",

language = "English",

volume = "49",

pages = "153--163",

journal = "Statistica Neerlandica",

issn = "0039-0402",

publisher = "Wiley-Blackwell Publishing Ltd",

number = "2",

}

TY - JOUR

T1 - Asymptotic normality of the NPMLE of linear functionals for interval censored data, case 1

AU - Huang, Jian

AU - Wellner, J. A.

PY - 1995/1/1

Y1 - 1995/1/1

N2 - We give a new proof of the asymptotic normality of a class of linear functionals of the nonparametric maximum likelihood estimator (NPMLE) of a distribution function with “case 1” interval censored data. In particular our proof simplifies the proof of asymptotic normality of the mean given in Groeneboom and Wellner (1992). The proof relies strongly on a rate of convergence result due to van de Geer (1993), and methods from empirical process theory.

AB - We give a new proof of the asymptotic normality of a class of linear functionals of the nonparametric maximum likelihood estimator (NPMLE) of a distribution function with “case 1” interval censored data. In particular our proof simplifies the proof of asymptotic normality of the mean given in Groeneboom and Wellner (1992). The proof relies strongly on a rate of convergence result due to van de Geer (1993), and methods from empirical process theory.

KW - asymptotic distribution

KW - empirical processes

KW - linear functionals

KW - mean moments

KW - nonparametric maximum likelihood

UR - http://www.scopus.com/inward/record.url?scp=84983947578&partnerID=8YFLogxK

U2 - 10.1111/j.1467-9574.1995.tb01462.x

DO - 10.1111/j.1467-9574.1995.tb01462.x

M3 - Journal article

SN - 0039-0402

VL - 49

SP - 153

EP - 163

JO - Statistica Neerlandica

JF - Statistica Neerlandica

IS - 2

ER -

Asymptotic normality of the NPMLE of linear functionals for interval censored data, case 1

Abstract

Keywords

ASJC Scopus subject areas

More information

Other files and links

Fingerprint

Cite this