[R] How to transform OLS covariance matrix to White standard errors?
David Winsemius
dwinsemius at comcast.net
Sat May 26 16:49:49 CEST 2012
On May 26, 2012, at 3:09 AM, Dunken wrote:
> Hi!
>
> I am working with a regression of a log-log model that suffers from
> heteroskedasticity. I have calculated the "White standard errors". I
> would
> like to use these "White standard errors" in a RESET test instead of
> the
> originally OLS standard errors calculated by the regression. How can I
> transform the covariance matrix of a model?
>
>
> labmodel2 <- lm(formula = log(L) ~ log(W) + log(K) + log(Y),
> data=labordat)
> sumlabmodel2 <- summary(labmodel2)
> sumlabmodel2
>
> coeftest(labmodel2,vcov=vcovHC(labmodel2,type="HC0"
>
> That is, I want to replace vcov with vcovHC in labmodel2 to perform
> a RESET
> test with the robust White standard errors.
Have your read? :
"Econometric Computing with HC and HAC Covariance Matrix Estimators",
Achim Zeileis
http://www.jstatsoft.org/v11/i10/
>
> Can anyone help?
>
> Thank you!
>
>
>
> --
> View this message in context: http://r.789695.n4.nabble.com/How-to-transform-OLS-covariance-matrix-to-White-standard-errors-tp4631432.html
> Sent from the R help mailing list archive at Nabble.com.
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
More information about the R-help
mailing list