On Oct 7, 2014, at 9:15 PM, Duncan Mackay wrote:
I'm a tad puzzled by the comments about needing to build a panel function for
locfit. The various plot.locfit functions are actually lattice calls.
locfit:::panel.locfit # already exists, and even has versions for 1d, 2d and
3d purposes.
And there is a llines.locfit function that will add locfit smooths to existing
lattice plots.
It's a very simple function and could easily be modified to any regression
method that has a predict functions:
> locfit:::llines.locfit
function (x, m = 100, tr = x$trans, ...)
{
newx <- lfmarg(x, m = m)[[1]] # probably need to modify to your purposes
y <- predict(x, newx, tr = tr)
llines(newx, y, ...)
}
<environment: namespace:locfit>
--
David
>
> You will have to make your own panel function for locfit if you want to use
> it
> I have done it in the past - read the help for
> library(locfit)
> ?plot.locfit
> and the links
> ?lattice::prepanel
>
> Regards
>
> Duncan
>
> Duncan Mackay
> Department of Agronomy and Soil Science
> University of New England
> Armidale NSW 2351
> Email: home: [email protected]
>
>
> -----Original Message-----
> From: [email protected] [mailto:[email protected]] On
> Behalf Of Bond, Stephen
> Sent: Tuesday, 7 October 2014 23:02
> To: [email protected]
> Subject: [R] lattice add a fit
>
> What is the way to add an arbitrary fit from a model to a lattice
> conditioning plot ?
>
> For example
> xyplot(v1 ~v2 | v3,data=mydata,
> panel=function(...){
> panel.xyplot(...)
> panel.loess(...,col.line="red")
> }
> )
> Will add a loess smoother. Instead, I want to put a fit from lm (but not a
> simple straight line) and the fit has to be done for each panel separately,
> not one fit for the full data set, so sth like an lm equivalent of
> panel.locfit (there is no panel.lmfit)
> Thank you.
>
> Stephen B
>
>
> [[alternative HTML version deleted]]
>
David Winsemius
Alameda, CA, USA
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