Produces a sample of QQ-plots based on the fitted values, overlaid by a QQ-plot of the original data.

iNZightQQplot(x, n = 5, env = parent.frame())

Arguments

x

an lm or svyglm object (with family = "Gaussian".

n

the number of sampled QQ plots to produce beneath the QQ plot of x.

env

environment for finding data to bootstrap

Value

No return value, called to produce plot.

Details

Multiple bootstrap models are generated from the fitted values of the model, each with different random normal errors with standard error equal to the estimated residual standard error from the original model. These are plotted, and then overlaid by the QQ plot from the original data.

This plot can be used to assess the assumption of normality in the residuals for a linear regression model.

See also

Author

David Banks, Tom Elliott

Examples

fit <- lm(Volume ~ Height + Girth, data = trees)
iNZightQQplot(fit)