[R] Non-linear "linear" models?
HDoran at air.org
Mon Jul 25 15:21:10 CEST 2005
Even when the model includes polynomial terms as you have below, it is
still a linear model because it is linear in the parameters. It is your
coefficients that are not linear. There are other functions in R for
From: r-help-bounces at stat.math.ethz.ch
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Subject: [R] Non-linear "linear" models?
I'm new to R (though I have spent hours trying to learn how to use
it) and also not very knowledgeable
about statistics, so I hope you will excuse what may seem like a very
basic question. I'm trying to use R to do an ANOVA analysis for some
data with an unbalanced design, and while I was trying to figure that
out, I got confused about the purpose of the "lm". All definitions I can
find of "linear model" are of the
y = a + b * x + e
In other words, y is only linear in the dependent variable(s) x.
However, the lm model seems to support higher order polynomials, e.g.:
> lm(dist ~ speed + I(speed^2)+I(speed^3), cars)
Is there some sense in which that model is "linear", or is R's lm()
providing extra functionality?
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