Coefficients of determination for least absolute deviation analysis

Joseph W. McKean and Gerald L. Sievers

Statistics & Probability Letters, 1987, vol. 5, issue 1, 49-54

Abstract: The least-absolute deviation or l1 analysis of a linear model is an important alternative to the classical least squares analysis from the point of view of efficiency for longer-tailed error distributions and robustness to the presence of outliers. In this paper two coefficients of determination are proposed for the least-absolute deviation analysis. It is shown that they have desirable properties as measures of multiple association. Both fixed and random predictor variable cases are considered. In the case of random predictor variables, the sample coefficients of determination are shown to be consistent estimators of appropriate population parameters.

Keywords: least; absolute; deviation; coefficient; of; determination; linear; model; stochastic; predictors; roburtness (search for similar items in EconPapers)
Date: 1987
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Citations: View citations in EconPapers (10)

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