[R] Question re: interpolation

[David Winsemius]

On May 2, 2010, at 5:27 PM, Jessica Schedlbauer wrote:

> Hello,
>
> I have a matrix in which two variables, x and y, are used together  
> to determine z.  The variables x and y are sorted into classes.   
> Specifically, values for variable x range from 0 to 2.7 and are  
> sorted into class increments of 0.15 and variable y ranges from  
> 0-2100 with class increments of 100.  For each x-y class  
> combination, I have calculated a mean value of z from existing  
> data.  However there are gaps in the existing data (i.e., x-y  
> combinations for which there are no z data).  I would like to  
> interpolate values to fill in these missing datapoints, but have so  
> far been unable to find a straightforward way of doing so in R.   
> There are many gaps in the data and I need to repeat this process  
> for several individual datasets.  That said, I am looking for a way  
> to avoid interpolating each missing point separately.

Why not do a loess fit _before_ you do any binning and then  
predict.loess at the intervals where you want estimates?

x=rnorm(200, 1.5)
  y= (10*x)^2 +rnorm(200, 0, 100)
  plot(x,y, cex=0.5, xlim=c(-2, 5))
  points(seq(-2,5, by=0.15), predict(loess(y~x),
                      newdata=data.frame(x=seq(-2,5, by=0.15))),  
col="red", cex=2)
>
> Any suggestions would be greatly appreciated.
>
> Regards,
> Jessica Schedlbauer
>
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David Winsemius, MD
West Hartford, CT