[R] ow to apply a panel function to each of several data series plotted on the same graph in lattice

From: David Wyllie <David.Wyllie_at_ndm.ox.ac.uk>
Date: Fri, 18 Jun 2010 08:45:26 +0100


Hi

is it possible to fit a trend line (or some other panel function) through each of multiple data series plotted on the same graph? Specifically, while one can do something like xyplot(a+b+c~x)
which plots three series, a,b & c, but can one automatically fit lines through each of them?

I suppose one could generate three more variables afit, bfit, and cfit with a model & predict and then plot them, but wondered if there was an easier way.

Thank you for any advice. Here is an example:

# use an example panel function using smooth.spline; however, the issue relates to all panel functions
# a panel function to fit smoothed lines through data
panel.smooth.spline <- function(x, y,

            w=NULL, df, spar = NULL, cv = FALSE, 
            lwd=plot.line$lwd, lty=plot.line$lty,col, col.line=plot.line$col, 
            type, horizontal=FALSE,... ) 
{
  # Deepayan Sarkar code from: http://www.mail-archive.com/r-help@r-project.org/msg39654.html     x <- as.numeric(x)

          y <- as.numeric(y)

          ok <- is.finite(x) & is.finite(y)

          if (sum(ok) < 1) 
              return() 
          if (!missing(col)) { 
              if (missing(col.line)) 
                  col.line <- col 
          } 
          plot.line <- trellis.par.get("plot.line") 
          if (horizontal) { 
              spline <- 
                  smooth.spline(y[ok], x[ok], 
                                w=w, df=df, spar = spar, cv = cv, ...) 
              panel.lines(x = spline$y, y = spline$x, col = col.line, 
                  lty = lty, lwd = lwd, ...) 
          } 
          else { 
              spline <- 
                  smooth.spline(x[ok], y[ok], 
                                w=w, df=df, spar = spar, cv = cv, ...) 
              panel.lines(x = spline$x, y = spline$y, col = col.line, 
                  lty = lty, lwd = lwd, ...) 
          } 
      }




# a composite function combining the xyplot and smooth.spline functions

panel.composite<-function(x,y,groups, subscripts, ...) {
panel.xyplot(x,y,...)
panel.smooth.spline(x,y,...)

}

# generate mock data; this comprises three data series, a,b,c with means of about 5,35, and 105.
test <- data.frame(

a = runif(100, min=0, max=10), 
b = 30+runif(100, min=0, max=10), 
c = 100+runif(100, min=0, max=10), 
x = 1:100)


# illustrate data

xyplot(a + b + c ~ x, data = test, type = "p", auto.key=TRUE)

# plot with fits .. but actually only one fit
xyplot(
a + b + c ~ x,

panel=panel.composite,
data = test, 
type = "p", 

auto.key=TRUE)

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