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Moments of skew-normal random vectors and their quadratic forms

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  • Genton, Marc G.
  • He, Li
  • Liu, Xiangwei

Abstract

In this paper, we derive the moments of random vectors with multivariate skew-normal distribution and their quadratic forms. Applications to time series and spatial statistics are discussed. In particular, it is shown that the moments of the sample autocovariance function and of the sample variogram estimator do not depend on the skewness vector.

Suggested Citation

  • Genton, Marc G. & He, Li & Liu, Xiangwei, 2001. "Moments of skew-normal random vectors and their quadratic forms," Statistics & Probability Letters, Elsevier, vol. 51(4), pages 319-325, February.
    • Handle: RePEc:eee:stapro:v:51:y:2001:i:4:p:319-325
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    References listed on IDEAS

    as
    1. A. Azzalini & A. Capitanio, 1999. "Statistical applications of the multivariate skew normal distribution," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(3), pages 579-602.
    2. Genton, Marc G., 1999. "The correlation structure of the sample autocovariance function for a particular class of time series with elliptically contoured distribution," Statistics & Probability Letters, Elsevier, vol. 41(2), pages 131-137, January.
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