supsmu
Friedman's SuperSmoother
Smooth the (x, y) values by Friedman's ‘super smoother’.
 Keywords
 smooth
Usage
supsmu(x, y, wt, span = "cv", periodic = FALSE, bass = 0)
Arguments
 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 leaveoneout crossvalidation.  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 crossvalidation 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 xvalue, then a prespecified fixed span smoother (span >
0
) should be used. Reasonable span values are 0.2 to 0.4.”
Cases with nonfinite values of x
, y
or wt
are
dropped, with a warning.
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.\ifelse{latex}{\out{~}}{ } 1.
Friedman, J. H. (1984) A variable span scatterplot smoother. Laboratory for Computational Statistics, Stanford University Technical Report No.\ifelse{latex}{\out{~}}{ } 5.
See Also
Examples
library(stats)
require(graphics)
with(cars, {
plot(speed, dist)
lines(supsmu(speed, dist))
lines(supsmu(speed, dist, bass = 7), lty = 2)
})