Matrix-variate distribution theory under elliptical models-4: Joint distribution of latent roots of covariance matrix and the largest and smallest latent roots

Francisco J. Caro-Lopera, Graciela González Farías, Narayanaswamy Balakrishnan

Resultado de la investigación: Contribución a una revista › Artículo

Resumen

© 2015 Elsevier Inc.. In this work, we derive the joint distribution of the latent roots of a sample covariance matrix under elliptical models. We then obtain the distributions of the largest and smallest latent roots. In the process of these derivations, we also correct some results present in the literature.
Idioma originalInglés estadounidense
Páginas (desde-hasta)224-235
Número de páginas12
PublicaciónJournal of Multivariate Analysis
DOI
EstadoPublicada - 1 mar 2016

Huella dactilar

Latent Root
Distribution Theory
Covariance matrix
Joint Distribution
Sample Covariance Matrix
Model
Joint distribution

Citar esto

Caro-Lopera, Francisco J. ; González Farías, Graciela ; Balakrishnan, Narayanaswamy. / Matrix-variate distribution theory under elliptical models-4: Joint distribution of latent roots of covariance matrix and the largest and smallest latent roots. En: Journal of Multivariate Analysis. 2016 ; pp. 224-235.
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abstract = "{\circledC} 2015 Elsevier Inc.. In this work, we derive the joint distribution of the latent roots of a sample covariance matrix under elliptical models. We then obtain the distributions of the largest and smallest latent roots. In the process of these derivations, we also correct some results present in the literature.",
author = "Caro-Lopera, {Francisco J.} and {Gonz{\'a}lez Far{\'i}as}, Graciela and Narayanaswamy Balakrishnan",
year = "2016",
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Caro-Lopera, FJ, González Farías, G & Balakrishnan, N 2016, 'Matrix-variate distribution theory under elliptical models-4: Joint distribution of latent roots of covariance matrix and the largest and smallest latent roots', Journal of Multivariate Analysis, pp. 224-235. https://doi.org/10.1016/j.jmva.2015.12.012

Matrix-variate distribution theory under elliptical models-4: Joint distribution of latent roots of covariance matrix and the largest and smallest latent roots. / Caro-Lopera, Francisco J.; González Farías, Graciela; Balakrishnan, Narayanaswamy.

En: Journal of Multivariate Analysis, 01.03.2016, p. 224-235.

Resultado de la investigación: Contribución a una revista › Artículo

TY - JOUR

T1 - Matrix-variate distribution theory under elliptical models-4: Joint distribution of latent roots of covariance matrix and the largest and smallest latent roots

AU - Caro-Lopera, Francisco J.

AU - González Farías, Graciela

AU - Balakrishnan, Narayanaswamy

PY - 2016/3/1

Y1 - 2016/3/1

N2 - © 2015 Elsevier Inc.. In this work, we derive the joint distribution of the latent roots of a sample covariance matrix under elliptical models. We then obtain the distributions of the largest and smallest latent roots. In the process of these derivations, we also correct some results present in the literature.

AB - © 2015 Elsevier Inc.. In this work, we derive the joint distribution of the latent roots of a sample covariance matrix under elliptical models. We then obtain the distributions of the largest and smallest latent roots. In the process of these derivations, we also correct some results present in the literature.

U2 - 10.1016/j.jmva.2015.12.012

DO - 10.1016/j.jmva.2015.12.012

M3 - Article

SP - 224

EP - 235

JO - Journal of Multivariate Analysis

JF - Journal of Multivariate Analysis

SN - 0047-259X

ER -

Caro-Lopera FJ, González Farías G, Balakrishnan N. Matrix-variate distribution theory under elliptical models-4: Joint distribution of latent roots of covariance matrix and the largest and smallest latent roots. Journal of Multivariate Analysis. 2016 mar 1;224-235. https://doi.org/10.1016/j.jmva.2015.12.012

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