car (version 2.0-8)

ncvTest: Score Test for Non-Constant Error Variance

Description

Computes a score test of the hypothesis of constant error variance against the alternative that the error variance changes with the level of the response (fitted values), or with a linear combination of predictors.

Usage

ncvTest(model, ...)

## S3 method for class 'lm':
ncvTest(model, var.formula, data=NULL, subset, na.action, ...)

## S3 method for class 'glm':
ncvTest(model, ...) # to report an error

Arguments

model

a weighted or unweighted linear model, produced by lm.

var.formula

a one-sided formula for the error variance; if omitted, the error variance depends on the fitted values.

data

an optional data frame containing the variables in the model. By default the variables are taken from the environment from which ncvTest is called. The data argument may therefore need to be specified even when t

subset

an optional vector specifying a subset of observations to be used.

na.action

a function that indicates what should happen when the data contain NAs. The default is set by the na.action setting of options.

...

arguments passed down to methods functions.

Value

• The function returns a chisqTest object, which is usually just printed.

Details

This test is often called the Breusch-Pagan test; it was independently suggested by Cook and Weisberg (1983). ncvTest.glm is a dummy function to generate an error when a glm model is used.

References

Breusch, T. S. and Pagan, A. R. (1979) A simple test for heteroscedasticity and random coefficient variation. Econometrica 47, 1287--1294. Cook, R. D. and Weisberg, S. (1983) Diagnostics for heteroscedasticity in regression. Biometrika 70, 1--10. Fox, J. (2008) Applied Regression Analysis and Generalized Linear Models, Second Edition. Sage. Fox, J. and Weisberg, S. (2011) An R Companion to Applied Regression, Second Edition, Sage. Weisberg, S. (2005) Applied Linear Regression, Third Edition, Wiley.

See Also

hccm, spreadLevelPlot

Examples

ncvTest(lm(interlocks ~ assets + sector + nation, data=Ornstein))

ncvTest(lm(interlocks ~ assets + sector + nation, data=Ornstein), 
    ~ assets + sector + nation, data=Ornstein)