leverage: Visualize Leverages

In glmxdiag: A Collection of Graphic Tools for GLM Diagnostics and some Extensions

Description

Graphical visualization of leverages for each observation within input model. Corresponds to the main diagonal of the hat matrix, i.e H[i,i].

Usage

leverage(object, label.id, n.label.id, xlab, ylab, pos,
         hline, lcol, lwd, lty, ...)

Arguments

object	object of class 'influence', see Details.
label.id	labels of observations, should be a vector with n elements.
n.label.id	number of observations with highest leverage to label in the plot.
xlab	title for the x axis.
ylab	title for the y axis.
pos	position of observations labels. Values 1, 2, 3, 4 respectively indicate below, left, above, right.
hline	numeric, where to position the horizontal line; useful to individuate points that exceed a specific treshold. Defaults to 2*p/n.
lcol	color of line.
lwd	width of line.
lty	type of line.
...	further arguments passed to plot

Details

This function only works with objects given as output from influenceDiag.

A rule of thumbs says that an observations has high leverage if H[i,i] > 2*p/n where p is the number of coefficients and n the sample size.

Value

Doesn't return a value, called for side effects.

Author(s)

Giuseppe Reale

Examples

data("mtcars")
mod <- glm(mpg ~ cyl + hp + carb, family = Gamma, data = mtcars)
inf <- influenceDiag(mod)
leverage(inf, label.id = rownames(mtcars))

glmxdiag documentation built on Jan. 10, 2022, 9:07 a.m.