[R] Alternatives to linear regression with multiple variables

[Liaw, Andy]

You can try the locfit package, which I believe can handle up to 5
variables.  E.g.,

R> library(locfit)
Loading required package: akima
Loading required package: lattice
locfit 1.5-6     2010-01-20 
R> x <- matrix(runif(1000 * 3), 1000, 3)
R> y <- rnorm(1000)
R> mydata <- data.frame(x, y)
R> str(mydata)
'data.frame':   1000 obs. of  4 variables:
 $ X1: num  0.21 0.769 0.661 0.978 0.15 ...
 $ X2: num  0.426 0.132 0.214 0.774 0.472 ...
 $ X3: num  0.971 0.659 0.474 0.867 0.479 ...
 $ y : num  -0.496 -0.636 1.778 -0.876 0.657 ...
R> fit <- locfit(y ~ lf(X1, X2, X3), data=mydata)
R> plot(fit)

Andy


> -----Original Message-----
> From: r-help-bounces at r-project.org 
> [mailto:r-help-bounces at r-project.org] On Behalf Of Guy Green
> Sent: Monday, February 22, 2010 7:47 AM
> To: r-help at r-project.org
> Subject: [R] Alternatives to linear regression with multiple variables
> 
> 
> I wonder if someone can give some pointers on alternatives to linear
> regression (e.g. Loess) when dealing with multiple variables.
> 
> Taking any simple table with three variables, you can very 
> easily get the
> intercept and coefficients with:
> 	summary(lm(read_table))
> 
> For obvious reasons, the coefficients in a multiple 
> regression are quite
> different from what you get if you calculate regressions for 
> the single
> variables separately.  Alternative approaches such as Loess seem
> straightforward when you have only one variable, and have the 
> advantage that
> they can cope even if the relationship is not linear.
> 
> My question is: how can you extend a flexible approach like Loess to a
> multi-variable scenario?  I assume that any non-parametric calculation
> becomes very resource-intensive very quickly.  Can anyone suggest
> alternatives (preferably R-based) that cope with multiple 
> variables, even
> when the relationship (linear, etc) is not known in advance?
> 
> Thanks,
> 
> Guy
> -- 
> View this message in context: 
> http://n4.nabble.com/Alternatives-to-linear-regression-with-mu
> ltiple-variables-tp1564370p1564370.html
> Sent from the R help mailing list archive at Nabble.com.
> 
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