Semiparametric maximum likelihood estimation for a two-sample density ratio model with right-censored data

doi:10.1002/cjs.11272

CSpace > 应用数学研究所

	Semiparametric maximum likelihood estimation for a two-sample density ratio model with right-censored data
	Wei, Wenhua 1,2; Zhou, Yong1,3
	2016-03-01
发表期刊	CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE
ISSN	0319-5724
卷号	44 期号:1 页码:58-81
摘要	In this paper we investigate a broader semiparametric two-sample density ratio model based on two groups of right-censored data. A semiparametric maximum likelihood estimator for the unknown finite and infinite dimensional parameters of the model is proposed and obtained by an EM algorithm. By using empirical process theory, we establish the uniform consistency and asymptotic normality of the proposed estimator. We moreover employ a Kolmogorov-Smirnov type test statistic to evaluate the model validity and a likelihood ratio test statistic to examine the treatment effects between the two groups. Simulation studies are conducted to assess the finite sample performance of the proposed estimator and to compare it with its alternatives. Finally a real data example is analyzed to illustrate its application. The Canadian Journal of Statistics 44: 58-81; 2016 (c) 2015 Statistical Society of Canada Resume Les auteurs explorent un modele semi-parametrique plus general pour le ratio des densites de deux echantillons base sur deux groupes de donnees censurees a droite. Ils proposent un estimateur semi-parametrique au maximum de vraisemblance pour les parametres de dimensions finies et infinies du modele et utilisent l'algorithme EM pour le calculer. l'aide de la theorie des processus empiriques, les auteurs etablissent la convergence uniforme et la normalite asymptotique de l'estimateur propose. De plus, ils emploient une statistique de type Kolmogorov-Smirnov pour evaluer la validite du modele et un test au rapport de vraisemblance pour examiner l'effet du traitement entre les deux groupes. Les auteurs procedent a des simulations afin d'evaluer la performance de l'estimateur propose sur des echantillons de taille finie, et de le comparer aux autres approches connues. Finalement, ils illustrent la mise en OEuvre de leur methode a l'aide de donnees reelles. La revue canadienne de statistique 44: 58-81; 2016 (c) 2015 Societe statistique du Canada
关键词	Density ratio model EM algorithm Empirical process right-censored data semiparametric maximum likelihood estimation
DOI	10.1002/cjs.11272
语种	英语
资助项目	National Natural Science Foundation of China ; State Key Program of National Natural Science Foundation of China ; Key Laboratory of RCSDS, AMSS, CAS ; Shanghai First-class Discipline A and IRTSHUFE, PCSIRT
WOS研究方向	Mathematics
WOS类目	Statistics & Probability
WOS记录号	WOS:000371485700004
出版者	WILEY-BLACKWELL
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/22261
专题	应用数学研究所
通讯作者	Wei, Wenhua
作者单位	1.Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China 2.City Univ Hong Kong, Dept Management Sci, Kowloon, Hong Kong, Peoples R China 3.Shanghai Univ Finance & Econ, Sch Stat & Management, Shanghai, Peoples R China
推荐引用方式 GB/T 7714	Wei, Wenhua,Zhou, Yong. Semiparametric maximum likelihood estimation for a two-sample density ratio model with right-censored data[J]. CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE,2016,44(1):58-81.
APA	Wei, Wenhua,&Zhou, Yong.(2016).Semiparametric maximum likelihood estimation for a two-sample density ratio model with right-censored data.CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE,44(1),58-81.
MLA	Wei, Wenhua,et al."Semiparametric maximum likelihood estimation for a two-sample density ratio model with right-censored data".CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE 44.1(2016):58-81.