Smoothers

1 Supersmoother

While most smoothers require specification of a bandwidth, fraction of data, or level of smoothing, supersmoother is different in that it figures these things out for itself. Thus, it's an excellent choice for situations where smoothing needs to be done without any user intervention. Supersmoother works by performing lots of simple local regression smooths, and, at each x-value it uses those smooths to decide the best y-value to use. In R, supersmoother is made available through the supsmu function.

To illustrate, consider the car data which we used earlier when we were studying cluster analysis. The following lines produce a plot of weight versus MPG, and superimposes a supersmoother line.

> plot(cars$Weight,cars$MPG)
> lines(supsmu(cars$Weight,cars$MPG))

The plot appears below:

As another example, we can revisit the wheat data that we used earlier with spline smoothing:

> plot(wheat$year,wheat$production)
> lines(supsmu(wheat$year,wheat$production))

Here's the plot:

2 Smoothers with Lattice Plots

When working with lattice graphics, we've already seen the use of panel.lmline, which displays the best regression line in each panel of a lattice plot. A similar function, panel.loess, is available to superimpose a locally weighted regression smoother in each panel of a plot. As a simple illustration, consider the built-in Orange data set, which has information about the age and circumference of several orange trees. First, let's look at a plot with the best regression line smoother superimposed on the plot of age versus circumference for each Tree:

> library(lattice)
> xyplot(circumference~age|Tree,data=Orange,
+        panel=function(x,y,...){panel.xyplot(x,y,...);panel.lmline(x,y,...)})

Here's the plot:

To create the same plot, but using the panel.loess function, we can use the following:

> xyplot(circumference~age|Tree,data=Orange, 
+        panel=function(x,y,...){panel.xyplot(x,y,...);panel.loess(x,y,...)})

Here's how the plot looks:

If a panel. function doesn't exist for a smoother you'd like to use, you can use the panel.lines function to plot it directly:

> xyplot(circumference~age|Tree,data=Orange,
+        panel=function(x,y,...){panel.xyplot(x,y,...);z=supsmu(x,y);panel.lines(z$x,z$y,...)})

In this case supersmoother came closer to a straight line than lowess.

File translated from T_EX by T_TH, version 3.67.
On 21 Apr 2010, 11:00.