Hiroshima Mathematical Journal

A $C_p$ type criterion for model selection in the GEE method when both scale and correlation parameters are unknown

Tomoharu Sato and Yu Inatsu

Full-text: Open access

Abstract

In this paper, we consider a model selection criterion using the GEE method including unknown scale and correlation parameters. We propose a model selection criterion for selecting variables and a working correlation structure. Under some regularity conditions, we showed that our criterion is the same as the criterion proposed by Inatsu and Imori [8]. A numerical study reveals that we can reduce the prediction error by selecting both variables and a working correlation structure.

Article information

Source
Hiroshima Math. J., Volume 50, Number 1 (2020), 85-115.

Dates
Received: 6 March 2019
Revised: 17 October 2019
First available in Project Euclid: 10 March 2020

Permanent link to this document
https://projecteuclid.org/euclid.hmj/1583805651

Digital Object Identifier
doi:10.32917/hmj/1583805651

Mathematical Reviews number (MathSciNet)
MR4074381

Zentralblatt MATH identifier
07197872

Subjects
Primary: 62H12: Estimation
Secondary: 62F07: Ranking and selection

Keywords
generalized estimating equation longitudinal data prediction mean squared error model selection prediction error

Citation

Sato, Tomoharu; Inatsu, Yu. A $C_p$ type criterion for model selection in the GEE method when both scale and correlation parameters are unknown. Hiroshima Math. J. 50 (2020), no. 1, 85--115. doi:10.32917/hmj/1583805651. https://projecteuclid.org/euclid.hmj/1583805651


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