Mean Value Test for Three-Level Multivariate Observations with Doubly Exchangeable Covariance Structure
Ivan Žežula (),
Daniel Klein () and
Anuradha Roy ()
Additional contact information
Ivan Žežula: P. J. Šafárik University, Institute of Mathematics, Faculty of Science
Daniel Klein: P. J. Šafárik University, Institute of Mathematics, Faculty of Science
Anuradha Roy: The University of Texas at San Antonio, Department of Management Science and Statistics
Chapter Chapter 19 in Recent Developments in Multivariate and Random Matrix Analysis, 2020, pp 335-349 from Springer
Abstract:
Abstract We consider matrix-valued multivariate observation model with three-level doubly-exchangeable covariance structure. We derive estimators of unknown parameters and their distributions under multivariate normality assumption. Test statistic for testing a mean value is proposed, and its exact distribution is derived. Several methods of computing p-values and critical values of the distribution are compared in real data example.
Date: 2020
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
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:sprchp:978-3-030-56773-6_19
Ordering information: This item can be ordered from
http://www.springer.com/9783030567736
DOI: 10.1007/978-3-030-56773-6_19
Access Statistics for this chapter
More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().