Asymptotic normality in a semiparametric partially linear model with right-censored data

Hua Liang; Yong Zhou

doi:10.1080/03610929808832262

Asymptotic normality in a semiparametric partially linear model with right-censored data

Hua Liang^*
, Yong Zhou

^*Corresponding author for this work

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

8 Scopus citations

Abstract

The effect of incomplete observation characteristics in a semiparametric partially linear model is examined. To construct estimate of interest-inparameter, synthetic data and generalized proflle likelihood, are employed. It is shown that the resulting estimator is asymptotic normal under mild assumptions. Simulations are also presented to explain the behavior of the estimate in the case of small-samples.

Original language	English
Pages (from-to)	2895-2907
Number of pages	13
Journal	Communications in Statistics - Theory and Methods
Volume	27
Issue number	12
DOIs	https://doi.org/10.1080/03610929808832262
State	Published - 1998
Externally published	Yes

Keywords

Kaplan-Meier estimator
Split-sample

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10.1080/03610929808832262

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title = "Asymptotic normality in a semiparametric partially linear model with right-censored data",

abstract = "The effect of incomplete observation characteristics in a semiparametric partially linear model is examined. To construct estimate of interest-inparameter, synthetic data and generalized proflle likelihood, are employed. It is shown that the resulting estimator is asymptotic normal under mild assumptions. Simulations are also presented to explain the behavior of the estimate in the case of small-samples.",

keywords = "Kaplan-Meier estimator, Split-sample",

author = "Hua Liang and Yong Zhou",

year = "1998",

doi = "10.1080/03610929808832262",

language = "英语",

volume = "27",

pages = "2895--2907",

journal = "Communications in Statistics - Theory and Methods",

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T1 - Asymptotic normality in a semiparametric partially linear model with right-censored data

AU - Liang, Hua

AU - Zhou, Yong

PY - 1998

Y1 - 1998

N2 - The effect of incomplete observation characteristics in a semiparametric partially linear model is examined. To construct estimate of interest-inparameter, synthetic data and generalized proflle likelihood, are employed. It is shown that the resulting estimator is asymptotic normal under mild assumptions. Simulations are also presented to explain the behavior of the estimate in the case of small-samples.

AB - The effect of incomplete observation characteristics in a semiparametric partially linear model is examined. To construct estimate of interest-inparameter, synthetic data and generalized proflle likelihood, are employed. It is shown that the resulting estimator is asymptotic normal under mild assumptions. Simulations are also presented to explain the behavior of the estimate in the case of small-samples.

KW - Kaplan-Meier estimator

KW - Split-sample

UR - https://www.scopus.com/pages/publications/18744410518

U2 - 10.1080/03610929808832262

DO - 10.1080/03610929808832262

M3 - 文章

AN - SCOPUS:18744410518

SN - 0361-0926

VL - 27

SP - 2895

EP - 2907

JO - Communications in Statistics - Theory and Methods

JF - Communications in Statistics - Theory and Methods

IS - 12

ER -

Asymptotic normality in a semiparametric partially linear model with right-censored data

Abstract

Keywords

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