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