[R] Can I build an array of regrssion model?

[Liaw, Andy]

And if you *really* want piecewise linear function (and most likely you want
the pieces to be continuous, no?), there are better ways than yours.  For
"manual" fitting, use something like:

  library(splines)
  lm(y ~ bs(x, knots=..., deg=1))

For more automatic fitting, I believe bruto() or even mars() in the package
`mda' will do.

Andy

> -----Original Message-----
> From: Jason Turner [mailto:jasont at indigoindustrial.co.nz]
> Sent: Wednesday, December 18, 2002 5:08 PM
> To: Zhongming Yang
> Cc: r-help at stat.math.ethz.ch
> Subject: Re: [R] Can I build an array of regrssion model?
> 
> 
> On Wed, Dec 18, 2002 at 03:51:47PM -0500, Zhongming Yang wrote:
> > I am trying to use piecewise linear regression to approximate a
> > nonlinear function. 
> 
> Why not smooth regression, or non-linear regression?
> 
> > Actually, I don't know how many linear functions I
> > need, therefore, I want build an array of regression models 
> to automate
> > the approximation job. Could you please give me any clue?
> 
> Clue 1) See above.  You might be using the wrong tool.  A smooth
> regression might be better here.  help(loess), library(gss), and
> library(sm) are your friends.
> 
> Clue 2) If you really want piecewise linear, a list makes more
> sense than a vector.  R does handle vectors quite nicely, but I
> find its real strength is the way it handles complex lists with
> ease.
> 
> > Attached is ongoing code:
> > 
> > rawData = scan("c:/zyang/mass/data/A01/1.PRN",
> > what=list(numeric(),numeric()));
> > len = length(rawData[[1]]);
> > cuts = len*c(0.01, 0.03, 0.08, 0.18, 0.38, 0.69, 1);
> > cuts = as.integer(cuts); 
> 
> #change cuts to a matrix of values, col 1 is the lower
> #bound, col 2 is the upper bound for your segments.
> 
> cuts <- cbind(c(1,cuts[1:(length(cuts)-1)], cuts)
> 
> #make an empty list
> mod.list <- list()
> #fill that list with models
> for(ii in 1:dim(cuts)[1]) { 
> 	start <- cuts[ii,1]
> 	end <- cuts[ii,2]
> 	mod.list[[ii]] <- lm(rawData[[2]][start,end] ~ 
> rawData[[1]][start,end])
> }
> 
> #to extract coefficients
> lapply(mod.list,coef)
> 
> #to extract coefficients, and confidence intervals
> lapply(mod.list,function(x,...){ coef(summary(x))} )
> 
> #to reproduce your ablines
> lapply(mod.list,abline,col="red")
> 
> etc
> 
> Cheers
> 
> Jason
> -- 
> Indigo Industrial Controls Ltd.
> 64-21-343-545
> jasont at indigoindustrial.co.nz
> 
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