Lattice plot diagnostics for lm objects

Lattice plot diagnostics for lm objects, mostly mimicking the behavior of stats::plot.lm() but based on lattice::xyplot() instead.

Usage

# S3 method for class 'lm'
xyplot(
  x,
  data = NULL,
  which = c(1:3, 5),
  main = FALSE,
  id.n = 3,
  labels.id = names(residuals(x)),
  cex.id = 0.75,
  cook.levels = c(0.5, 1),
  label.pos = c(4, 2),
  layout = NULL,
  ...
)

Arguments

x: lm object, typically result of lm or glm.
data: Only provided for method consistency and is ignored.
which: if a subset of the plots is required, specify a subset of the numbers 1:6
main: if TRUE plots default titles. Can also be a list or character vector of length 6.
id.n: number of points to be labelled in each plot, starting with the most extreme.
labels.id: vector of labels, from which the labels for extreme points will be chosen. NULL uses observation numbers.
cex.id: magnification of point labels.
cook.levels: levels of Cook's distance at which to draw contours.
label.pos: positioning of labels, for the left half and right half of the graph respectively, for plots 1-3, 5, 6.
layout: a numeric vector with [columns, rows] to use in the call to gridExtra::grid.arrange(), or a layout matrix which will then be passed as the layout_matrix in grid.arrange().
...: arguments to be passed to lattice::xyplot().

Value

A list of trellis objects or a single trellis object.

Author

Original by John Maindonald and Martin Maechler. Adaptation to lattice by Johan Larsson.

Examples

fit <- lm(Sepal.Length ~ Sepal.Width, data = iris)
xyplot(fit)

xyplot(fit, which = 5)