Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1146893 | Journal of Multivariate Analysis | 2011 | 11 Pages |
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.
Related Topics
Physical Sciences and Engineering
Mathematics
Numerical Analysis
Authors
W. Bischoff, A. Gegg,