cg (version 1.0-0)

varianceGraph: Variance Graphs

Description

Create an equal variance assessment graph of the residuals of a fitted object from the cg package

Usage

varianceGraph(fit, trend = NULL, cgtheme = TRUE, device = "single", ...)

Arguments

fit

A fit object, typically created by the fit generic function.

trend

Add a trend line to help assess the trend of the residuals. See specific method written for the fit argument.

cgtheme

When set to the default TRUE, ensures a trellis device is active with limited color scheme. Namely background, strip.shingle, and strip.background are each set to "white".

device

Can be one of three values: [object Object],[object Object],[object Object]

...

Additional arguments, depending on the specific method written for the object. See the method-specific documentation for additional details.

Value

• varianceGraph returns an invisible NULL. The main purpose is the side effect of graphing to the current device.

concept

• equal variance
• residual diagnostics

Details

The graphs plot the square root of the absolute value of the residuals against the fitted value. The notion of using the squared root of the absolute residuals is attributed to John Tukey.

See Also

varianceGraph.cgOneFactorFit

Examples

data(canine)
canine.data <- prepareCGOneFactorData(canine, format="groupcolumns",
                                      analysisname="Canine",
                                      endptname="Prostate Volume",
                                      endptunits=expression(plain(cm)^3),
                                      digits=1, logscale=TRUE, refgrp="CC")
canine.fit <- fit(canine.data)

varianceGraph(canine.fit)

varianceGraph(canine.fit, model="olsonly")