\Header{lowess}{Scatter Plot Smoothing}
\keyword{smooth}{lowess}
\begin{Usage}
\begin{verbatim}
lowess(x, y, f=2/3, iter=3, delta=.01*diff(range(x)))
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\texttt{x,y}] vectors giving the coordinates of the points in the scatter plot.
Alternatively a single plotting structure can be specified.
\item[\texttt{f}] the smoother span.
This gives the proportion of points in the plot which
influence the smooth at each value.
Larger values give more smoothness.
\item[\texttt{iter}] the number of robustifying iterations which should be
performed.
Using smaller values of \texttt{iter} will make \texttt{lowess} run faster.
\item[\texttt{delta}] values of \texttt{x} which lie within \texttt{delta}
of each other replaced by a single value in the output from
\texttt{lowess}.
\end{ldescription}
\end{Arguments}
\begin{Description}
This function performs the computations for the
\emph{LOWESS} smoother (see the reference below).
\texttt{lowess} returns a list containing components
\texttt{x} and \texttt{y} which give the coordinates of the smooth.
The smooth should be added to a plot of the original
points with the function
\texttt{lines}.\end{Description}
\begin{References}
Cleveland, W. S. (1979).
Robust locally weighted regression and smoothing scatterplots.
\emph{J. Amer. Statist. Assoc.} \bold{74}, 829-836.

Cleveland, W. S. (1981).
LOWESS: A program for smoothing scatterplots by robust locally weighted
regression.
\emph{The American Statistician}, \bold{35}, 54.\end{References}
\begin{Examples}
\begin{ExampleCode}
data(cars)
plot(cars, main = "lowess(cars)")
lines(lowess(cars), col= 2)
lines(lowess(cars,f=.2), col= 3)
legend(5,120,c(paste("f = ", c("2/3", ".2"))), lty=1, col=2:3)
\end{ExampleCode}
\end{Examples}

