Diagonalization matrix and its application in distribution theory

Francisco J. Caro-Lopera, José A. Díaz-García

Resultado de la investigación: Contribución a una revistaArtículo

3 Citas (Scopus)

Resumen

© 2015 Taylor & Francis. Some matrix representations of diverse diagonal arrays are studied in this work; the results allow new definitions of classes of elliptical distributions indexed by kernels mixing Hadamard and usual products. A number of applications are derived in the setting of prior densities from the Bayesian multivariate regression model and families of non-elliptical distributions, such as the matrix multivariate generalized Birnbaum–Saunders density. The philosophy of the research about matrix representations of quadratic and inverse quadratic forms can be extended as a methodology for exploring possible new applications in non-standard distributions, matrix transformations and inference.
Idioma originalInglés estadounidense
Páginas (desde-hasta)870-880
Número de páginas11
PublicaciónStatistics
Volumen50
N.ºN/A
DOI
EstadoPublicada - 3 jul 2016

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