Weighted least squares estimates. Heteroskedasticity and the problems it causes for inference. How weighted least squares gets around the problems of heteroskedasticity, if we know the variance function. Estimating the variance function from regression residuals. An iterative method for estimating the regression function and the variance function together. Locally constant and locally linear modeling. Lowess.
Reading: Notes, chapter 6; Faraway, section 11.3.
Posted by crshalizi at February 02, 2012 10:30 | permanent link