alr3 (version 2.0.5)

pureErrorAnova: Pure Error analysis of variance

Description

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.

Usage

### This is a generic function.  
pureErrorAnova(mod)
"pureErrorAnova"(mod)
### Methods for other than models for type lm have not been defined.

Arguments

mod

an object of type lm

Value

Returns an analsis of variance table.

Details

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 update(mod, ~.+factor(L)).

References

Weisberg, S. (2005). Applied Linear Regression, third edition, New York: Wiley, Chapter 5.

See Also

lm

Examples

x <- c(1,1,1,2,3,3,4,4,4,4)
y <- c(2.55,2.75,2.57,2.40,4.19,4.70,3.81,4.87,2.93,4.52)
m1 <- lm(y~x)
anova(m1)  # ignore pure error
pureErrorAnova(m1)  # include pure error

head(forbes)
m2 <- lm(Lpres~Temp, data=forbes)
pureErrorAnova(m2)  # function does nothing because there is no pure error