supsmu {stats}R Documentation

Friedman's SuperSmoother


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


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


x x values for smoothing
y y values for smoothing
wt case weights, by default all equal
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.


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.”


A list with components

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


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



with(cars, {
    plot(speed, dist)
    lines(supsmu(speed, dist))
    lines(supsmu(speed, dist, bass = 7), lty = 2)

[Package stats version 2.2.1 Index]