Boos, Dennis D. Detecting skewed errors from regression residuals. (English) Zbl 0608.62043 Technometrics 29, 83-90 (1987). Symmetry of the error distribution is a common assumption in robust estimation of location and regression parameters. Tests for detecting asymmetry in the location problem are available, but their performance in regression situations is unknown. Here two such tests are investigated, and the evidence suggests two conclusions. First, the tests are valid when applied directly to either robust or least squares residuals as long as the number of parameters estimated is no more than a fourth of the sample size. Second, the effect of the design matrix on power for detecting a skewed error distribution is roughly characterized by a third-moment quantity based on least squares analysis. Cited in 3 Documents MSC: 62F35 Robustness and adaptive procedures (parametric inference) 62J05 Linear regression; mixed models Keywords:Monte Carlo results; linear model; Symmetry; error distribution; robust estimation; location; regression parameters; Tests for detecting asymmetry; least squares residuals; skewed error distribution PDF BibTeX XML Cite \textit{D. D. Boos}, Technometrics 29, 83--90 (1987; Zbl 0608.62043) Full Text: DOI