Spatial blind source separation-Reference-Cited by-同舟云学术

Spatial blind source separation

Published:2020-02-17 Issue:3 Volume:107 Page:627-646
ISSN:0006-3444
Container-title:Biometrika
language:en
Short-container-title:

Author:

Bachoc François¹,Genton Marc G²,Nordhausen Klaus³,Ruiz-Gazen Anne⁴,Virta Joni⁵

Affiliation:

1. Institut de Mathématiques de Toulouse, Université Paul Sabatier, 118 route de Narbonne, 31062 Toulouse, France

2. Statistics Program, King Abdullah University of Science and Technology, Thuwal 23955-6900, Saudi Arabia

3. Computational Statistics, Vienna University of Technology, Wiedner Hauptstr. 7, A-1040 Vienna, Austria

4. Toulouse School of Economics, University of Toulouse Capitole, 1, Esplanade de l’Université, 31080 Toulouse Cedex 06, France

5. Department of Mathematics and Statistics, University of Turku, 20014 Turun yliopisto, Finland

Abstract

Summary Recently a blind source separation model was suggested for spatial data, along with an estimator based on the simultaneous diagonalization of two scatter matrices. The asymptotic properties of this estimator are derived here, and a new estimator based on the joint diagonalization of more than two scatter matrices is proposed. The asymptotic properties and merits of the novel estimator are verified in simulation studies. A real-data example illustrates application of the method.

Funder

French National Research

Academy of Finland

Aalto University

Publisher

Oxford University Press (OUP)

Subject

Applied Mathematics,Statistics, Probability and Uncertainty,General Agricultural and Biological Sciences,Agricultural and Biological Sciences (miscellaneous),General Mathematics,Statistics and Probability

Link

http://academic.oup.com/biomet/article-pdf/107/3/627/33658463/asz079.pdf

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3. Using simultaneous diagonalization to identify a space–time linear coregionalization model;De Iaco,;Math. Geosci.,2013

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