supsmu {modreg}

R Documentation

Friedman's SuperSmoother

Description

Smooth the (x, y) values by Friedman's “super smoother”.

Usage

supsmu(x, y, wt = rep(1, length(y)), span = "cv", periodic = FALSE,
       bass = 0)

Arguments

x	x values for smoothing
y	y values for smoothing
wt	case weights
span	the fraction of the observations in the span of the running lines smoother, or "cv" to choose this by leave-one-out cross-validation.
periodic	if TRUE, the x values are assumed to be in [0, 1] and of period 1.
bass	controls the smoothness of the fitted curve. Values of up to 10 indicate increasing smoothness.

Details

supsmu is a running lines smoother which chooses between three spans for the lines. The running lines smoothers are symmetric, with k/2 data points each side of the predicted point, and values of k as 0.5 * n, 0.2 * n and 0.05 * n, where n is the number of data points. If span is specified, a single smoother with span span * n is used.

The best of the three smoothers is chosen by cross-validation for each prediction. The best spans are then smoothed by a running lines smoother and the final prediction chosen by linear interpolation.

The FORTRAN code says: “For small samples (n < 40) or if there are substantial serial correlations between observations close in x - value, then a prespecified fixed span smoother (span > 0) should be used. Reasonable span values are 0.2 to 0.4.”

Value

A list with components

x	the input values in increasing order with duplicates removed.
y	the corresponding y values on the fitted curve.

References

Friedman, J. H. (1984) SMART User's Guide. Laboratory for Computational Statistics, Stanford University Technical Report No. 1.

Friedman, J. H. (1984) A variable span scatterplot smoother. Laboratory for Computational Statistics, Stanford University Technical Report No. 5.

See Also

ppr

Examples

data(cars)
attach(cars)
plot(speed, dist)
lines(supsmu(speed, dist))
lines(supsmu(speed, dist, bass=7), lty=2)
detach()