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Transactions of the American Mathematical Society
Transactions of the American Mathematical Society
ISSN 1088-6850(online) ISSN 0002-9947(print)

Matrix variate $ \theta$-generalized normal distribution


Authors: A. K. Gupta and T. Varga
Journal: Trans. Amer. Math. Soc. 347 (1995), 1429-1437
MSC: Primary 62H10; Secondary 60E05, 62E15
MathSciNet review: 1277112
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Abstract | References | Similar Articles | Additional Information

Abstract: In this paper, the matrix variate $ \theta $-generalized normal distribution is introduced. Then its properties are studied. In particular, it is proved that this distribution has maximal entropy in a certain class of distributions.


References [Enhancements On Off] (What's this?)

  • [T] R. Goodman and S. Kotz, Multivariate $ \theta $-generalized normal distributions, J. Multivariate Anal. 3 (1973), 204-219.
  • [A] K. Gupta and T. Varga, Characterization of matrix variate normal distributions, J. Multivariate Anal. 41 (1992), 80-88.
  • 1. -, Elliptically contoured models in statistics, Kluwer Academic, Dordrecht, 1993.
  • [R] J. Muirhead, Aspects of multivariate statistical theory, Wiley, New York, 1982.

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Additional Information

DOI: http://dx.doi.org/10.1090/S0002-9947-1995-1277112-9
PII: S 0002-9947(1995)1277112-9
Keywords: Normal distribution, matrix random variables, moments, characterization
Article copyright: © Copyright 1995 American Mathematical Society