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Journal of Probability and Statistics
Volume 2016, Article ID 2374907, 12 pages
http://dx.doi.org/10.1155/2016/2374907
Research Article

Properties of Matrix Variate Confluent Hypergeometric Function Distribution

1Department of Mathematics and Statistics, Bowling Green State University, Bowling Green, OH 43403-0221, USA
2Instituto de Matemáticas, Universidad de Antioquia, Calle 67, No. 53–108, Medellín, Colombia

Received 3 September 2015; Accepted 15 December 2015

Academic Editor: Z. D. Bai

Copyright © 2016 Arjun K. Gupta et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. A. K. Gupta and D. K. Nagar, Matrix Variate Distributions, Chapman & Hall/CRC Press, Boca Raton, Fla, USA, 2000.
  2. G. J. van der Merwe and J. J. J. Roux, “On a generalized matrix-variate hypergeometric distribution,” South African Statistical Journal, vol. 8, pp. 49–58, 1974. View at Google Scholar · View at MathSciNet
  3. J. M. Orozco-Castañeda, D. K. Nagar, and A. K. Gupta, “Generalized bivariate beta distributions involving Appell's hypergeometric function of the second kind,” Computers and Mathematics with Applications, vol. 64, no. 8, pp. 2507–2519, 2012. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  4. Y. L. Luke, The Special Functions and Their Approximations, vol. 1, Academic Press, New York, NY, USA, 1969.
  5. A. G. Constantine, “Some non-central distribution problems in multivariate analysis,” Annals of Mathematical Statistics, vol. 34, pp. 1270–1285, 1963. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  6. A. T. James, “Distributions of matrix variates and latent roots derived from normal samples,” Annals of Mathematical Statistics, vol. 35, pp. 475–501, 1964. View at Publisher · View at Google Scholar · View at MathSciNet
  7. R. J. Muirhead, Aspects of Multivariate Statistical Theory, Wiley Series in Probability and Mathematical Statistics, John Wiley & Sons, New York, NY, USA, 1982.
  8. H. Hashiguchi, Y. Numata, N. Takayama, and A. Takemura, “The holonomic gradient method for the distribution function of the largest root of a Wishart matrix,” Journal of Multivariate Analysis, vol. 117, pp. 296–312, 2013. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet · View at Scopus
  9. P. Koev and A. Edelman, “The efficient evaluation of the hypergeometric function of a matrix argument,” Mathematics of Computation, vol. 75, no. 254, pp. 833–846, 2006. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet · View at Scopus
  10. A. Iranmanesh, M. Arashi, D. K. Nagar, and S. M. Tabatabaey, “On inverted matrix variate gamma distribution,” Communications in Statistics—Theory and Methods, vol. 42, no. 1, pp. 28–41, 2013. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  11. J. J. Roux and G. J. van der Merwe, “Families of multivariate distributions having properties usually associated with the Wishart distribution,” South African Statistical Journal, vol. 8, pp. 111–117, 1974. View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  12. C. G. Khatrzi, “On certain distribution problems based on positive definite quadratic functions in normal vectors,” Annals of Mathematical Statistics, vol. 37, pp. 468–479, 1966. View at Publisher · View at Google Scholar · View at MathSciNet
  13. C. A. Coelho, R. P. Alberto, and L. M. Grilo, “When do the moments uniquely identify a distribution,” CMA 13-2005, Centro de Matemática e Aplicações, Departamento de Matemática, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, 2005. View at Google Scholar
  14. J. J. J. Roux, “On generalized multivariate distributions. South African Statist,” South African Statistical Journal, vol. 5, pp. 91–100, 1971. View at Google Scholar · View at MathSciNet