gplots: lowess – R documentation

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lowess

Scatter Plot Smoothing

Description

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

Alternatively, plot can be called directly on the object returned from lowess and the 'lowess' method for plot will generate a scatterplot of the original data with a lowess line superimposed.

Finally, the plotLowess function both calculates the lowess smooth and plots the original data with a lowess smooth.

Usage

lowess(x, ...)

## Default S3 method:
lowess(x, y=NULL, f=2/3, iter=3L, delta=0.01 *
       diff(range(x)), ...)

## S3 method for class 'formula'
lowess(formula,data=parent.frame(), ..., subset, f=2/3,
       iter=3L, delta=.01*diff(range(mf[-response])))

## S3 method for class 'lowess'
plot(x, y, ..., col.lowess="red", lty.lowess=2)

plotLowess(formula, data=parent.frame(), ..., subset=parent.frame(),
           col.lowess="red", lty.lowess=2  )

Arguments

`formula`	formula providing a single dependent variable (y) and an single independent variable (x) to use as coordinates in the scatter plot.
`data`	a data.frame (or list) from which the variables in ‘formula’ should be taken.
`subset`	an optional vector specifying a subset of observations to be used in the fitting process.
`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`.
`...`	parameters for methods.
`col.lowess, lty.lowess`	color and line type for plotted line

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)

#
# x,y method
#
plot(cars$speed, cars$dist, main="lowess(cars)")
lines(lowess(cars$speed, cars$dist), col=2)
lines(lowess(cars$speed, cars$dist, f=.2), col=3)
legend(5, 120, c(paste("f=", c("2/3", ".2"))), lty=1, col=2:3)

#
# formula method: plot, then calculate the lowess smoother,
#                 then add smooth to the plot
#
plot(dist ~ speed, data=cars, main="lowess(cars)")
lines(lowess(dist ~ speed, data=cars), col=2, lty=2)
lines(lowess(dist ~ speed, data=cars, f=.2), col=3) # smaller bandwith
legend(5, 120, c(paste("f=", c("2/3", ".2"))), lty=1, col=2:3)

#
# formula method: calculate lowess() smoother, then call plot()
#                  on the lowess object
#
lw <- lowess(dist ~ speed, data=cars)
plot(lw, main="lowess(cars)"  )

#
# formula method: calculate and plot in a single command
#
plotLowess(dist ~ speed, data=cars, main="lowess(cars)")

gplots

Various R Programming Tools for Plotting Data

v3.1.1

GPL-2

Authors

Gregory R. Warnes [aut], Ben Bolker [aut], Lodewijk Bonebakker [aut], Robert Gentleman [aut], Wolfgang Huber [aut], Andy Liaw [aut], Thomas Lumley [aut], Martin Maechler [aut], Arni Magnusson [aut], Steffen Moeller [aut], Marc Schwartz [aut], Bill Venables [aut], Tal Galili [ctb, cre]

Initial release

2020-11-28