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Multivariate inverse Gaussian and skew-normal densities

Author

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  • Joe, Harry
  • Seshadri, Vanamamalai
  • Arnold, Barry C.

Abstract

Based on inverse Gaussian random variables being transformations of skew-normal random variables, multivariate inverse Gaussian densities are obtained from appropriate multivariate skew-normal distributions. The new skew-normal distributions have some closure properties not satisfied by other multivariate skew-normal distributions.

Suggested Citation

  • Joe, Harry & Seshadri, Vanamamalai & Arnold, Barry C., 2012. "Multivariate inverse Gaussian and skew-normal densities," Statistics & Probability Letters, Elsevier, vol. 82(12), pages 2244-2251.
    • Handle: RePEc:eee:stapro:v:82:y:2012:i:12:p:2244-2251
    DOI: 10.1016/j.spl.2012.08.004
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    References listed on IDEAS

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    1. Barry Arnold & Robert Beaver & A. Azzalini & N. Balakrishnan & A. Bhaumik & D. Dey & C. Cuadras & J. Sarabia & Barry Arnold & Robert Beaver, 2002. "Skewed multivariate models related to hidden truncation and/or selective reporting," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 11(1), pages 7-54, June.
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    Cited by:

    1. Joe, Harry & Li, Haijun, 2019. "Tail densities of skew-elliptical distributions," Journal of Multivariate Analysis, Elsevier, vol. 171(C), pages 421-435.
    2. Demirhan, Haydar & Kalaylioglu, Zeynep, 2015. "On the generalized multivariate Gumbel distribution," Statistics & Probability Letters, Elsevier, vol. 103(C), pages 93-99.

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