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. 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@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.
