Visualization of evidence in regression with the QR decomposition

W. Braun ()

Computational Statistics, 2015, vol. 30, issue 4, 907-927

Abstract: Graphical ANOVA is a simple and effective tool for visualizing evidence of differences between treatment means for data coming from factorial experiments. The purpose of the present article is to propose an analogous method for the visualization of the significance of regression, using the QR decomposition. Two graphical tests are proposed and compared with the classical $$F$$ F test, by simulation. It is found that when the number of candidate predictors is small relative to the sample size, the classical test has slightly higher power than the graphical tests. When the number of predictors is large, the graphical tests remain powerful. while the classical $$F$$ F test exhibits poor power properties. Copyright Springer-Verlag Berlin Heidelberg 2015

Keywords: Least-squares; Data visualization; Evidence; Graphical $$F$$ F test (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1007/s00180-015-0558-x

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