March 2019
Beginner to intermediate
448 pages
13h 14m
English
Content preview from R Statistics Cookbook
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How it works...
Conceptually, we want to minimize the sum of the residuals, but weighting them in such a way that large residuals receive a small weight (so their influence is mitigated). We can think that in OLS (ordinary least squares), every observation has a weight of 1. Huber and bi-square weighting penalize each residual by assigning a small weight. The rlm function works by minimizing the sum of weighted residuals. The problem is that the weights depend on the residuals, and the residuals depend on the weights. The technique that is used for this is called iteratively reweighted least squares. Large residuals receive a large weight, and small residuals get a small one.
The specific weight depends on which weighting scheme is used. ...
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