On the Robust Rank Analysis of Linear Models with Nonsymetric Error Distributions.
WESTERN MICHIGAN UNIV KALAMAZOO DEPT OF MATHEMATICS
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The robust analysis of linear models based on R-estimates involves an estimate of a scale parameter which is used in the analysis as a standardizing constant. The consistency of previous estimates of this scale parameter required that the underlying errors be symmetrically distributed. This assumption is not always warranted, for instance in survival models. A new estimate is proposed for the scale parameter and it is shown to be consistent for nonsymmetric and symmetric error distributions. With this new scale estimate, a complete robust analysis of a linear model can be accomplished without assuming symmetry. The small sample properties of the anlaysis are examined in a Monte Carlo study of several different situations.
- Statistics and Probability