% File src/library/stats/man/supsmu.Rd % Part of the R package, https://www.R-project.org % Copyright 1995-2016 R Core Team % Distributed under GPL 2 or later \name{supsmu} \alias{supsmu} \title{Friedman's \I{SuperSmoother}} \description{ Smooth the (x, y) values by Friedman's \sQuote{super smoother}. } \usage{ supsmu(x, y, wt =, span = "cv", periodic = FALSE, bass = 0, trace = FALSE) } \arguments{ \item{x}{x values for smoothing} \item{y}{y values for smoothing} \item{wt}{case weights, by default all equal} \item{span}{the fraction of the observations in the span of the running lines smoother, or \code{"cv"} to choose this by leave-one-out cross-validation.} \item{periodic}{if \code{TRUE}, the x values are assumed to be in \code{[0, 1]} and of period 1.} \item{bass}{controls the smoothness of the fitted curve. Values of up to 10 indicate increasing smoothness.} \item{trace}{logical, if true, prints one line of info \dQuote{per spar}, notably useful for \code{"cv"}.} } \details{ \code{supsmu} is a running lines smoother which chooses between three spans for the lines. The running lines smoothers are symmetric, with \code{k/2} data points each side of the predicted point, and values of \code{k} as \code{0.5 * n}, \code{0.2 * n} and \code{0.05 * n}, where \code{n} is the number of data points. If \code{span} is specified, a single smoother with span \code{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: \dQuote{For small samples (\code{n < 40}) or if there are substantial serial correlations between observations close in x-value, then a pre-specified fixed span smoother (\code{span > 0}) should be used. Reasonable span values are 0.2 to 0.4.} Cases with non-finite values of \code{x}, \code{y} or \code{wt} are dropped, with a warning. } \value{ A list with components \item{x}{the input values in increasing order with duplicates removed.} \item{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.\sspace{}1. Friedman, J. H. (1984) A variable span scatterplot smoother. Laboratory for Computational Statistics, Stanford University Technical Report No.\sspace{}5. } \seealso{\code{\link{ppr}}} \examples{ require(graphics) with(cars, { plot(speed, dist) lines(supsmu(speed, dist)) lines(supsmu(speed, dist, bass = 7), lty = 2) }) } \keyword{smooth}