Statistical significance of the LMS regression

Alexandros Leontitsis and Jenny Pange

Mathematics and Computers in Simulation (MATCOM), 2004, vol. 64, issue 5, 543-547

Abstract: We propose the use of simulation in order to obtain a statistical significance measure of the least median of squares (LMS) regression coefficients. We shuffle the values of the dependent variable many times (e.g. 100), so as to preserve their distribution, and we calculate the LMS regression coefficients for every shuffled data. In this way we form a confidence interval for the slope centered on 0, because the slopes of the shuffled data are considered statistically equal to 0. The coefficients of the original data are considered significant if they are not belong on the above mentioned interval.

Keywords: Statistical significance; Least median of squares regression; Simulation (search for similar items in EconPapers)
Date: 2004
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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:64:y:2004:i:5:p:543-547

DOI: 10.1016/j.matcom.2003.10.004

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