Re: [R] Incorporating the results of White's HCCM into a linear regression:

On 2009.12.03 23:52:15, Yoseph Zuback wrote: Hi Frank, I'm trying to repair heteroscedastic variables using the hccm. A statistician in my department gave an incomplete solution that included: OLS1$coefficients/(sqrt(hccm(OLS1))) Trying to solve my problem I get different results with

Re: [R] Incorporating the results of White's HCCM into a linear regression:

Hi Frank, I'm trying to repair heteroscedastic variables using the hccm. A statistician in my department gave an incomplete solution that included: OLS1$coefficients/(sqrt(hccm(OLS1))) Trying to solve my problem I get different results with the method you gave me and what I am trying with the

[R] Incorporating the results of White's HCCM into a linear regression:

Using hccm() I got a heteroscedasticity correction factor on the diagonal of the return matrix, but I don't know how to incorporate this into my linear model: METHOD 1: OLS1 - lm(formula=uer92~uer+low2+mlo+spec+degree+hit) Coefficients: Estimate Std. Error t value Pr(|t|)

Re: [R] Incorporating the results of White's HCCM into a linear regression:

Yoseph, What do you mean by 'incorporate into'? If you mean to update the fit object's variance-covariance matrix, one approach might be require(rms) ols1 - ols(uer92 ~ ..., x=TRUE, y=TRUE) ols1 - robcov(ols1) anova(ols1); summary(ols1); ... # uses 'robust' variancescovariances You can