Partial sum process to check regression models with multiple correlated response With an application for testing a change-point in profile data

JOURNAL OF MULTIVARIATE ANALYSIS

卷:102

Article

Bischoff, W.¹  Gegg, A.¹ 

[1] Catholic Univ Eichstatt Ingolstadt, Fac Math & Geog, D-85071 Eichstatt, Germany

关键词: Multiple linear regression model;    Multiple residual partial sum limit process;    Multivariate Brownian motion;    Change-point problem;    Panel data;    Profile data;    Repeated measurements;   

DOI  :  10.1016/j.jmva.2010.08.014

来源: Elsevier

【 摘 要 】

We consider regression models with multiple correlated responses for each design point Under the null hypothesis a linear regression is assumed For the least-squares residuals of this linear regression we establish the limit of the partial sums This limit is a projection on a certain subspace of the reproducing Kernel Hilbert space of a multivariate Brownian motion Based on this limit we propose a significance test of Kolmogorov-Smirnov type to test the null hypothesis and show that this result can be used to study a change-point problem in the case of linear profile data (panel data) We compare our proposed method which does not rely on any distributional assumptions with the likelihood ratio test in a simulation study (C) 2010 Elsevier Inc All rights reserved

【 授权许可】

Free