HAZARD REGRESSION WITH PENALIZED SPLINE： THE SMOOTHING PARAMETER CHOICE AND ASYMPTOTICS

In this article, we use penalized spline to estimate the hazard function from a set of censored failure time data. A new approach to estimate the amount of smoothing is provided. Under regularity conditions we establish the consistency and the asymptotic normality of the penalized likelihood estimat...

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Bibliographic Details
Published inActa mathematica scientia Vol. 30; no. 5; pp. 1759 - 1768
Main Author 童行伟 胡涛 崔恒建
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.09.2010
School of Mathematical Sciences,Beijing Normal University
Laboratory of Mathematics and Complex Systems,Ministry of Education,Beijing 100875,China
Subjects
62G08
asymptotic normality
Asymptotic properties
Consistency
Estimates
Hazards
Mathematical analysis
Mathematical models
penalized spline
proportional hazards
Regression
Smoothing
smoothing parameter choice
Splines
估计量
参数选择
正则条件
风险函数
asymptotic normality
smoothing parameter choice
62G08
proportional hazards
penalized spline
Online AccessGet full text
ISSN0252-9602
1572-9087
DOI10.1016/S0252-9602(10)60169-5

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Summary:In this article, we use penalized spline to estimate the hazard function from a set of censored failure time data. A new approach to estimate the amount of smoothing is provided. Under regularity conditions we establish the consistency and the asymptotic normality of the penalized likelihood estimators. Numerical studies and an example are conducted to evaluate the performances of the new procedure.
Bibliography:asymptotic normality
O241.5
proportional hazards; penalized spline; smoothing parameter choice; asymptotic normality
O211.67
penalized spline
smoothing parameter choice
42-1227/O
proportional hazards
ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0252-9602
1572-9087
DOI:10.1016/S0252-9602(10)60169-5