Optimal model averaging for multivariate regression models

In this paper, frequentist model averaging is considered in the context of a multivariate multiple regression model. We propose a weight choice criterion based on a plug-in counterpart of the quadratic risk of the model average estimator that involves an approximation of the distribution of a ratio...

Full description

Saved in:
Bibliographic Details
Published in:Journal of multivariate analysis 2022-05, Vol.189, p.104858, Article 104858
Main Authors: Liao, Jun, Wan, Alan T.K., He, Shuyuan, Zou, Guohua
Format: Article
Language:English
Subjects:
[formula omitted] distribution
Asymptotic optimality
Consistency
Model averaging
Weight choice
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this paper, frequentist model averaging is considered in the context of a multivariate multiple regression model. We propose a weight choice criterion based on a plug-in counterpart of the quadratic risk of the model average estimator that involves an approximation of the distribution of a ratio of quadratic forms by an F distribution. We establish an asymptotic theory for the resultant model average estimator for both the general and restricted weight sets, and derive the convergence rate of the model weights to the quadratic risk-based optimal weights. The merits of our approach are illustrated by a simulation study and an application based on from the Sixth National Population Census of China.
ISSN:0047-259X
1095-7243
DOI:10.1016/j.jmva.2021.104858