## Scatter Plot Smoothing

## Usage

    lowess(x, y, f=2/3, iter=3, delta=.01*diff(range(x)))

## Arguments

`x,y` | vectors giving the coordinates of the points in the scatter plot. Alternatively a single plotting structure can be specified.
`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.
`iter` | the number of robustifying iterations which should be performed. Using smaller values of `iter` will make `lowess` run faster.
`delta` | values of `x` which lie within `delta` of each other replaced by a single value in the output from `lowess`.

## Description

This function performs the computations for the LOWESS smoother (see the reference below). `lowess` returns a list containing components `x` and `y` which give the coordinates of the smooth. The smooth should be added to a plot of the original points with the function `lines`.

## References

Cleveland, W. S. (1979). Robust locally weighted regression and smoothing scatterplots. J. Amer. Statist. Assoc. 74, 829-836.

Cleveland, W. S. (1981). LOWESS: A program for smoothing scatterplots by robust locally weighted regression. The American Statistician, 35, 54.

## Examples

    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)

[Package Contents]