A Robust Method for Multiple Linear Regression

Techniques of fitting are said to be resistant when the result is not greatly altered in the case a small fraction of the data is altered: techniques of fitting are said to be robust of efficiency when their statistical efficiency remains high for conditions more realistic than the utopian cases of Gaussian distributions with errors of equal variance. These properties are particularly important in the formative stages of model building when the form of the response is not known exactly. Techniques with these properties are proposed and discussed.