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On normal variance–mean mixtures

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  • Yu, Yaming

Abstract

We study shape properties of normal variance–mean mixtures, in both the univariate and multivariate cases, and determine conditions for unimodality and log-concavity of the density functions. We also interpret such results in practical terms and discuss discrete analogues.

Suggested Citation

  • Yu, Yaming, 2017. "On normal variance–mean mixtures," Statistics & Probability Letters, Elsevier, vol. 121(C), pages 45-50.
    • Handle: RePEc:eee:stapro:v:121:y:2017:i:c:p:45-50
    DOI: 10.1016/j.spl.2016.07.024
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    References listed on IDEAS

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    1. Ying Chen & Wolfgang Härdle & Seok-Oh Jeong, 2004. "Nonparametric Risk Management with Generalized Hyperbolic Distributions," SFB 649 Discussion Papers SFB649DP2005-001, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Bertin, Emile & Theodorescu, Radu, 1995. "Preserving unimodality by mixing," Statistics & Probability Letters, Elsevier, vol. 25(3), pages 281-288, November.
    3. Sato, Ken-iti, 2001. "Subordination and self-decomposability," Statistics & Probability Letters, Elsevier, vol. 54(3), pages 317-324, October.
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    Cited by:

    1. Stergios B. Fotopoulos & Venkata K. Jandhyala & Alex Paparas, 2021. "Some Properties of the Multivariate Generalized Hyperbolic Laws," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(1), pages 187-205, February.
    2. Mattei, Pierre-Alexandre, 2017. "Multiplying a Gaussian matrix by a Gaussian vector," Statistics & Probability Letters, Elsevier, vol. 128(C), pages 67-70.

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