On invertibility of the C‐matrix in quadratic inference functions. Issue 1 (10th November 2016)

• Record Type: Journal Article
• Authors: Lian, Heng
• Is Part Of: Stat. Volume 5:Issue 1(2016)
• Page Start: 279
• Page End: 285
• Publication Date: 2016-11-10
• Subjects: diverging dimensionality -- estimating equations -- longitudinal data -- quantile regression; Statistics -- Periodicals; 519.2
• DOI: 10.1002/sta4.127
• Languages: English
• ISSNs: 2049-1573

Abstract

Abstract : A quadratic inference function is often applied to correlated data, with the advantages that it does not involve direct estimation of the correlation parameter and it is more efficient than using generalized estimating equations when the correlation is misspecified. TheC ‐matrix is used in the definition of a quadratic inference function and is required to be invertible. In this paper, we investigate carefully the question about when theC ‐matrix is invertible, which turns out to be non‐trivial. Such a study is missing in the current literature and is especially interesting in a "diverging p " setting where the invertibility ofC ‐matrix is less clear. Copyright © 2016 John Wiley & Sons, Ltd.