Economics at your fingertips  

Optimal Model Averaging Estimation for Generalized Linear Models and Generalized Linear Mixed-Effects Models

Xinyu Zhang, Dalei Yu, Guohua Zou and Hua Liang

Journal of the American Statistical Association, 2016, vol. 111, issue 516, 1775-1790

Abstract: Considering model averaging estimation in generalized linear models, we propose a weight choice criterion based on the Kullback–Leibler (KL) loss with a penalty term. This criterion is different from that for continuous observations in principle, but reduces to the Mallows criterion in the situation. We prove that the corresponding model averaging estimator is asymptotically optimal under certain assumptions. We further extend our concern to the generalized linear mixed-effects model framework and establish associated theory. Numerical experiments illustrate that the proposed method is promising.

Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations View citations in EconPapers (5) Track citations by RSS feed

Downloads: (external link) (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Ordering information: This journal article can be ordered from

Access Statistics for this article

Journal of the American Statistical Association is currently edited by Xuming He, Jun Liu, Joseph Ibrahim and Alyson Wilson

More articles in Journal of the American Statistical Association from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

Page updated 2018-07-07
Handle: RePEc:taf:jnlasa:v:111:y:2016:i:516:p:1775-1790