Rank estimating equations for partial spline models with monotonicity

機構典藏 > College of Sciences > Graduate Institute & Department of Mathematics > Journal Article > Item 987654321/41306

Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/41306

Title:	Rank estimating equations for partial spline models with monotonicity
Authors:	陳主智;Chen, Chu-chih;Hsieh, Fushing
Contributors:	淡江大學數學學系
Keywords:	Asymptotic relative efficiency;censored regression;rank analysis of covariance;rank transformation;semiparametric regression model
Date:	1999
Issue Date:	2010-01-28 07:15:14 (UTC+8)
Publisher:	Taipei: Institute of Statistical Science, Academia Sinica
Abstract:	For partial spline models with a monotone nonlinear component, a class of monotone estimating equations is proposed for estimating the slope parameters of the vector of covariables Z of the linear component, while adjusting for the corresponding ranks of the vector of covariables X of the nonlinear component. This approach avoids the technical complications due to the smoothing of estimators for the nonlinear component with monotonicity, as well as the curse of dimensionality. Also, computationally, our inferences do not involve the unknown error probability density function. As an R-estimator taking into account the rank correlation between Y and X, the asymptotic relative efficiency with respect to other estimators ignoring X is proportional to the Spearman correlation coefficient between them.
Relation:	Statistica Sinica 9(1), pp.199-210
Appears in Collections:	[Graduate Institute & Department of Mathematics] Journal Article

Files in This Item:

File	Description	Size	Format
Extended rank and matched-pair analysis of covariance.pdf		153Kb	Adobe PDF	145	View/Open
index.html		0Kb	HTML	171	View/Open