The Block-Matrix Sphericity Test: Exact and Near-Exact Distributions for the Test Statistic

DOI10.1007/978-3-642-32419-2_18zbMath1407.62202OpenAlexW148273162MaRDI QIDQ4644984

Paula Marques, Carlos A. Coelho, Filipe J. Marques

Publication date: 9 January 2019

Published in: Recent Developments in Modeling and Applications in Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-642-32419-2_18

zbMATH Keywords

likelihood ratio testblock-matrix sphericity testBox type asymptotic approximation

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Hypothesis testing in multivariate analysis (62H15) Sufficient statistics and fields (62B05)

Related Items (1)

Block-diagonal test for high-dimensional covariance matrices

Cites Work

• Unnamed Item
• Unnamed Item
• A general near-exact distribution theory for the most common likelihood ratio test statistics used in multivariate analysis
• The advantage of decomposing elaborate hypotheses on covariance matrices into conditionally independent hypotheses in building near-exact distributions for the test statistics
• The generalized integer gamma distribution -- a basis for distributions in multivariate statistics
• The generalized near-integer Gamma distribution: a basis for `near-exact' approximations to the distribution of statistics which are the product of an odd number of independent Beta random variables
• Near-exact distributions for the likelihood ratio test statistic to test equality of several variance-covariance matrices in elliptically contoured distributions
• Testing of homogeneity of diagonal blocks with blockwise independence
• A GENERAL DISTRIBUTION THEORY FOR A CLASS OF LIKELIHOOD CRITERIA

This page was built for publication: The Block-Matrix Sphericity Test: Exact and Near-Exact Distributions for the Test Statistic