Difference between revisions of "R reg diag"
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= Heteroskedasticity = | = Heteroskedasticity = | ||
| − | One of the Gauss-Markov assumption is that the variance of the regression error terms is constant. | + | One of the Gauss-Markov assumption is that the variance of the regression error terms is constant. If they are not, then the OLS parameter estimators will not be efficient and one needs to use heteroskedasticity robust standard errors to obtain valid inference on regression coefficients (see [[R_robust_se]]). |
= Autocorrelation = | = Autocorrelation = | ||
Revision as of 16:37, 13 April 2015
When estimating regression models you will usually want to undertake some diagnostic testing
Heteroskedasticity
One of the Gauss-Markov assumption is that the variance of the regression error terms is constant. If they are not, then the OLS parameter estimators will not be efficient and one needs to use heteroskedasticity robust standard errors to obtain valid inference on regression coefficients (see R_robust_se).
