On the least-squares model averaging interval estimator Sebastian Ankargren Shaobo Jin 10.6084/m9.figshare.4730329 https://tandf.figshare.com/articles/journal_contribution/On_the_least_squares_model_averaging_interval_estimator_sup_sup_/4730329 <p>In many applications of linear regression models, randomness due to model selection is commonly ignored in post-model selection inference. In order to account for the model selection uncertainty, least-squares frequentist model averaging has been proposed recently. We show that the confidence interval from model averaging is asymptotically equivalent to the confidence interval from the full model. The finite-sample confidence intervals based on approximations to the asymptotic distributions are also equivalent if the parameter of interest is a linear function of the regression coefficients. Furthermore, we demonstrate that this equivalence also holds for prediction intervals constructed in the same fashion.</p> 2017-09-06 14:21:02 Asymptotic equivalence Frequentist model averaging Linear model Local asymptotics Post-selection inference. 62E20 62J05 62J99 62F12 C12 C52 C20