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

W. Bischoff and A. Gegg

Journal of Multivariate Analysis, 2011, vol. 102, issue 2, 281-291

Abstract: 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.

Keywords: Multiple; linear; regression; model; Multiple; residual; partial; sum; limit; process; Multivariate; Brownian; motion; Change-point; problem; Panel; data; Profile; data; Repeated; measurements (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (2)

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