[R] Re: R-help Digest V2 #283

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Subject: [R] Re: R-help Digest V2 #283
From: Adrian Trapletti (adrian@olsen.ch)
Date: Fri 08 Dec 2000 - 19:03:30 EST 

Message-ID: <3A30A3E2.957BD504@olsen.ch>

R-help Digest wrote:

> ------------------------------
>
> Date: Thu, 07 Dec 2000 18:28:09 +0100
> From: Uwe Ligges <ligges@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) "à 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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