Re: [R] Beginning lm

From: Marc Schwartz <>
Date: Sat, 26 Jul 2008 12:43:49 -0500

on 07/26/2008 10:37 AM wrote:
> I have ussed lm to generate a basic line correlation:
> fit = lm(hours.of.sleep ~ ToSleep)
> Note: From "Bayesian Computation with R", Jim Albert, p. 7
> I understand the simple y = mx + b line that this fits the data to.
> Now apparently I don't understand formulas. The documentation
> indicates that there is an implied "intercept" in the formula so now
> I want to try and fit the line to a second degree polynomial so I
> tried:
> ft = lm(hours.of.sleep ~ ToSleep ^ 2 + ToSleep)
> and I still seem to get results that indicate a slope intercept, y =
> mx + b, type of fit. Can anyone give me a short tutorial on the
> formula syntax? I would like to fit the data to 2nd and higher order
> polynomials, 1 / x, log(x), etc. I am sorry but I could not glean
> this information from the help page on lm.

The help system is not intended to be a tutorial, but a reference showing the syntax of function calls, what they do, what they return, some potential gotchas, references/citations and a _limited_ number of common examples of use.

The first place to start is to read "An Introduction to R", which is available with your R installation and online at:

The apropos section in that document is "Statistical models in R":

which provides more in-depth examples, including your situation.

There are also other books available for R listed here:

which will provide more generalized overviews of R, since subject focused books, such as Jim Albert's, will by necessity, have rather brief introductions to the language.

There are also some contributed documents here:

HTH, Marc Schwartz mailing list PLEASE do read the posting guide and provide commented, minimal, self-contained, reproducible code. Received on Sat 26 Jul 2008 - 17:48:33 GMT

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