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On the Conditional Distribution of the Multivariate Distribution

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  • Peng Ding

Abstract

As alternatives to the normal distributions, t distributions are widely applied in robust analysis for data with outliers or heavy tails. The properties of the multivariate t distribution are well documented in Kotz and Nadarajah's book, which, however, states a wrong conclusion about the conditional distribution of the multivariate t distribution. Previous literature has recognized that the conditional distribution of the multivariate t distribution also follows the multivariate t distribution. We provide an intuitive proof without directly manipulating the complicated density function of the multivariate t distribution.

Suggested Citation

  • Peng Ding, 2016. "On the Conditional Distribution of the Multivariate Distribution," The American Statistician, Taylor & Francis Journals, vol. 70(3), pages 293-295, July.
    • Handle: RePEc:taf:amstat:v:70:y:2016:i:3:p:293-295
    DOI: 10.1080/00031305.2016.1164756
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    References listed on IDEAS

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    1. Ding, Peng, 2014. "Bayesian robust inference of sample selection using selection-t models," Journal of Multivariate Analysis, Elsevier, vol. 124(C), pages 451-464.
    2. Cambanis, Stamatis & Huang, Steel & Simons, Gordon, 1981. "On the theory of elliptically contoured distributions," Journal of Multivariate Analysis, Elsevier, vol. 11(3), pages 368-385, September.
    3. Yulia V. Marchenko & Marc G. Genton, 2012. "A Heckman Selection- t Model," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(497), pages 304-317, March.
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