loess
.
plot.loess(object, given=6, evaluation=50, confidence=0, coverage=0.99, ranges, which.plots) preplot.loess(object, given=6, evaluation=50, confidence=0, coverage=0.99, ranges, which.plots)
k
numeric predictors,
ranges
should either be a list of minimum and
maximum pairs of length
k
, or a
2
by
k
matrix. Matching is done the
same way as for
xlab
. If missing, the range for a numeric predictor
is the range of the predictor observations used in the fit.
title
may also be given to
plot.loess
.
preplot.loess
returns an object of class
"preplot.loess"
with the evaluations necessary
to draw coplots using
plot.preplot.loess
, which is a method for
plot
.
plot.loess
returns
NULL
.
plot.loess
creates a plot on the current graphics device.
This function is a method for the generic function
for class loess.
It can be invoked by calling
for an object x of the appropriate class, or directly by calling
regardless of the class of the object.
Sometimes, the computation necessary to carry out
plot.loess
is substantial
enough that we want to save the evaluated surface that is graphed so we can
graph the surface many times, perhaps with changes to graphical parameters, but
carry out only one evaluation. This can be done by assigning the result
of
preplot
to a dataset and using the dataset as the first argument in
calls to
plot
.
plot.loess
ignores
ask=T
. You must set
ask=T
with
par
before
calling
plot.loess
.
ethanol.model <- loess(NOx ~ C * E, data = ethanol, span = 1/2, drop.square = "C", parametric = "C") ethanol.preplot <- preplot(ethanol.model, given = 16, confidence = 7, coverage = .95) plot(ethanol.preplot) # now try again with a smaller character size plot(ethanol.preplot, cex = .5) # now make hard copy postscript() plot(ethanol.preplot, cex = .5)