Testing the hypothesis of a doubly exchangeable covariance matrix

Carlos A. Coelho () and Anuradha Roy
Additional contact information
Carlos A. Coelho: Universidade Nova de Lisboa
Anuradha Roy: The University of Texas at San Antonio

Metrika: International Journal for Theoretical and Applied Statistics, 2020, vol. 83, issue 1, No 3, 45-68

Abstract: Abstract In this paper the authors study the problem of testing the hypothesis of a doubly exchangeable covariance matrix for three-level multivariate observations, taken on m variables over u sites and over v time/space points. Through the decomposition of the main hypothesis into a set of three sub-hypotheses, the likelihood ratio test statistic is defined, its exact moments are determined, and its exact distribution is studied. Because this distribution is very much intricate, a very precise near-exact distribution is developed. Numerical studies conducted to evaluate the closeness between this near-exact distribution and the exact distribution show the very good performance of this approximation even for very small sample sizes. A simulation study is also conducted and two real-data examples are presented.

Keywords: Characteristic function; Composition of hypotheses; Distribution of likelihood ratio statistics; Mixtures; Near-exact distributions; Product distribution; 62H15; 62H10; 62E15; 62E20; 62E10; 60E10 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s00184-019-00724-7 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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: https://EconPapers.repec.org/RePEc:spr:metrik:v:83:y:2020:i:1:d:10.1007_s00184-019-00724-7

Ordering information: This journal article can be ordered from
http://www.springer.com/statistics/journal/184/PS2

DOI: 10.1007/s00184-019-00724-7

Access Statistics for this article

Metrika: International Journal for Theoretical and Applied Statistics is currently edited by U. Kamps and Norbert Henze

More articles in Metrika: International Journal for Theoretical and Applied Statistics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().