sfsmisc (version 1.1-0)

p.res.2x: Stahel's Residual Plot against 2 X's

Description

Plot Residuals (e.g., of a multiple linear regression) against two (predictor) variables. This is now a (S3) generic function with a default and a formula method.

Usage

p.res.2x(x, …)
# S3 method for default
p.res.2x(x, y, z, restricted, size = 1, slwd = 1, scol = 2:3,
         xlab = NULL, ylab = NULL, main = NULL,
         xlim = range(x), ylim = range(y), …)
# S3 method for formula
p.res.2x(x = ~., data, main = deparse(substitute(data)),
         xlab = NULL, ylab = NULL, …)

Arguments

x, y

numeric vectors of the same length specifying 2 covariates. For the formula method, x is a formula.

z

numeric vector of same length as x and y, typically residuals.

restricted

positive value which truncates the size. The corresponding symbols are marked by stars.

size

the symbols are scaled so that size is the size of the largest symbol in cm.

slwd, scol

line width and color(s) for the residual segments. If scol has length 2 as per default, the two colors are used for positive and negative z values, respectively.

xlab, ylab, main

axis labels, and title see title, each with a sensible default. To suppress, use, e.g., main = "".

xlim, ylim

the basic x- and y- axis extents, see plot.default. Note that these will be slightly extended such that segments are not cut off.

…

further arguments passed to plot, or p.res.2x.default(), respectively.

data

(for the formula method:) a data frame or a fitted "lm" object.

Details

The formula interface will call p.res.2fact() when both x and y are factors.

........... ..........

References

Stahel, W. (1996) ........

See Also

p.res.2fact, plot.lm, TA.plot.

Examples

xx <- rep(1:10,7)
yy <- rep(1:7, rep(10,7))
zz <- rnorm(70)
p.res.2x(xx,yy,zz, restr = 2, main = "i.i.d.  N(0,1) random residuals")

example(lm.influence, echo = FALSE)

op <- mult.fig(2, marP=c(-1,-1,-1,0), main="p.res.2x(*,*, residuals(lm.SR))")$old.par
with(LifeCycleSavings,
     { p.res.2x(pop15, ddpi, residuals(lm.SR), scol=c("red", "blue"))
       p.res.2x(pop75, dpi,  residuals(lm.SR), scol=2:1)
     })

## with formula interface:
p.res.2x(~ pop15 + ddpi, lm.SR, scol=c("red", "blue"))
p.res.2x(~ pop75 +  dpi, lm.SR, scol=2:1)

par(op) # revert par() settings above