Abstract:

A simple but efficient method has been proposed to select variables in
heteroscedastic regression models. It is shown that the pseudo empirical
wavelet coefficients corresponding to the significant explanatory variables
in the regression models are clearly larger than those nonsignificant ones,
on the basis of which a procedure is developed to select variables in regression models. The coefficients of the models are also estimated. All estimators are proved to be consistent.

Key words: Heteroscedastic regression models, variable selection, wavelets