For a linear model object, finds the sum of squares for lack of fit and the sum of squares for pure error. These are added to the standard anova table to give a test for lack of fit. If there is no pure error, then the regular anova table is returned.
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an object of type
For regression models with one predictor, say
y ~ x, this method fits
y ~ x + factor(x) and prints the anova table. With more than one predictor, it
computes a random linear combination L of the terms in the mean function
and then gives the anova table for
Returns an analsis of variance table.
Sanford Weisberg, [email protected]
Weisberg, S. (2005). Applied Linear Regression, third edition, New York: Wiley, Chapter 5.
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