R-help Digest wrote:
> ------------------------------
>
> Date: Thu, 07 Dec 2000 18:28:09 +0100
> From: Uwe Ligges <ligges at statistik.uni-dortmund.de>
> Subject: Re: [R] Heteroskedasticity in R
>
> Vincent Leycuras wrote:
> >
> > Hi all,
> >
> > I just discovered R a couple of days ago and I must say it rocks.
I've been
> > looking for heteroskedasticity tests and couldn't find any,
however.
> > Particularly, I've been told in one of my courses on econometrics
of White's
> > method (>< white.test()).
> >
> > The test's statistic is beta / sqrt(W), where W is Var(beta)
"? la White",
> > that is the beta(i) matrix is replaced by the residuals matrix.
I think what you mention here is not a test for heteroskedasticity but a
robustified (against misspecification, e.g., heteroskedasticity) t-test.
>
> >
> > Anyway, whatever anybody may haev, I'm interested, else I'll
write it this
> > week-end.
>
> Have a look at the package 'tseries', available at CRAN.
>
> Uwe Ligges
>
The White test which Vincent mentions is different from the White Test
implemented in tseries, which tests for neglected nonlinearity in the
conditional mean, essentially for a regression equation or linear time series
model.
One very simple way to test conditional heteroskedasticity (time series setup)
is to use the Box.test (package ts) on the squared values of a time series as
Box.test(x^2, lag = 1, type="Ljung")
Adrian
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