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\name{ncvTest}
\alias{ncvTest}
\alias{ncvTest.lm}
\alias{ncvTest.glm}
\title{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, ...)
\method{ncvTest}{lm}(model, var.formula, ...)
\method{ncvTest}{glm}(model, ...) # to report an error
}
\arguments{
\item{model}{a weighted or unweighted linear model, produced by \code{lm}.}
\item{var.formula}{a one-sided formula for the error variance; if omitted,
the error variance depends on the fitted values.}
\item{\dots}{arguments passed down to methods functions; not currently used.}
}
\details{
This test is often called the Breusch-Pagan test; it was independently
suggested with some extension by Cook and Weisberg (1983).
\code{ncvTest.glm} is a dummy function to generate an error when a \code{glm}
model is used.
}
\value{
The function returns a \code{chisqTest} object, which is usually just printed.
}
\references{
Breusch, T. S. and Pagan, A. R. (1979)
A simple test for heteroscedasticity and random coefficient variation.
\emph{Econometrica} \bold{47}, 1287--1294.
Cook, R. D. and Weisberg, S. (1983)
Diagnostics for heteroscedasticity in regression.
\emph{Biometrika} \bold{70}, 1--10.
Fox, J. (2016)
\emph{Applied Regression Analysis and Generalized Linear Models},
Third Edition. Sage.
Fox, J. and Weisberg, S. (2019)
\emph{An R Companion to Applied Regression}, Third Edition, Sage.
Weisberg, S. (2014) \emph{Applied Linear Regression}, Fourth Edition, Wiley.
}
\author{John Fox \email{jfox@mcmaster.ca}, Sandy Weisberg \email{sandy@umn.edu}}
\seealso{\code{\link{hccm}}, \code{\link{spreadLevelPlot}} }
\examples{
ncvTest(lm(interlocks ~ assets + sector + nation, data=Ornstein))
ncvTest(lm(interlocks ~ assets + sector + nation, data=Ornstein),
~ assets + sector + nation, data=Ornstein)
}
\keyword{htest}
\keyword{regression}
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