Ronald M. Schrader, Joseph W. Mc Kean
Abstract
The classes of R- and M-estimates contain practical robust alternatives to least squares estimation in linear models. These estimates form the basis for a robust analysis of variance. This inference procedure is described and its versatility demonstrated.
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The classes of R- and M-estimates contain practical robust alternatives to least squares estimation in linear models. These estimates form the basis for a robust analysis of variance. This inference procedure is described and its versatility demonstrated.
Key concepts: Variance (accounting), Mathematics, Basis (linear algebra), Least-squares function approximation, Inference, Statistics, Algorithm, Computer science