Testing independence via spectral moments

Abstract

Assume that a matrix X: p × n is matrix normally distributed and that the Kolmogorov condition, i.e., [Formula Present], holds. We propose a test for identity of the covariance matrix using a goodness-of-fit approach. Calculations are based on a recursive formula derived by Pielaszkiewicz et al. [19]. The test performs well regarding the power compared to presented alternatives, for both c < 1 or c ≥ 1.

Keywords

Covariance matrix; Goodness of fit test; Spectral moments; Test of independence; Wishart matrix

Published in

Springer Proceedings in Mathematics & Statistics
2017, number: 192, pages: 263-274
Title: Applied and Computational Matrix Analysis : MAT-TRIAD, Coimbra, Portugal, September 2015 Selected, Revised Contributions
Publisher: Springer

Conference

International Conference on Matrix Analysis and its Applications, MAT-TRIAD 2015

SLU Authors

• von Rosen, Dietrich

  • Department of Energy and Technology, Swedish University of Agricultural Sciences
    
  • Linköping University

UKÄ Subject classification

Probability Theory and Statistics

Publication identifier

• DOI: https://doi.org/10.1007/978-3-319-49984-0_18
• ISBN: 978-3-319-49982-6
• eISBN: 978-3-319-49984-0

Permanent link to this page (URI)

https://res.slu.se/id/publ/130300