A Non-Parametric Test for a Change-Point in Linear Profile Data

Journal Title: Journal of Applied Quantitative Methods - Year 2010, Vol 5, Issue 3

Abstract

We propose a change-point approach for testing the constancy of regression parameters in a linear profile data set (panel data in econometrics). Each sample collected over time in the historical data set consists of several multivariate observations for which a linear regression model is appropriate. The question now is whether all of the profiles follow a linear regression model with the same parameter vector or whether a change occurred in one or more model parameters after a special sample. We use the partial sum operator in several dimensions to test the null hypothesis "H0: no change-point occurred" and propose a non-parametric size α-test. In Bischoff and Gegg (2010) we compared our proposed method with the likelihood-ratio-test by Mahmoud et al. (2007) in a simulation study. By these simulations we could show that our procedure can, in contrast to the likelihood-ratio-test, even be applied to the non-normal case. In this paper, however, we show how to compute our proposed test statistic step-by-step by considering an artificial data set.

Authors and Affiliations

Wolfgang BISCHOFF, Andreas GEGG

Keywords

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  • EP ID EP102912
  • DOI -
  • Views 107
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How To Cite

Wolfgang BISCHOFF, Andreas GEGG (2010). A Non-Parametric Test for a Change-Point in Linear Profile Data. Journal of Applied Quantitative Methods, 5(3), 516-524. https://europub.co.uk/articles/-A-102912