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Some remarks on multivariate stable distributions

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  • Paulauskas, V. J.

Abstract

This paper deals with multivariate stable distributions. [6], 444-462]. We present counter-examples and correct proofs of some of the statements of Press. The properties of multivariate stable distributions, connected with the spectral measure [Gamma], present in the expression of the characteristic function, are studied.

Suggested Citation

  • Paulauskas, V. J., 1976. "Some remarks on multivariate stable distributions," Journal of Multivariate Analysis, Elsevier, vol. 6(3), pages 356-368, September.
  • Handle: RePEc:eee:jmvana:v:6:y:1976:i:3:p:356-368
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    Cited by:

    1. Tsionas, Mike, 2012. "Simple techniques for likelihood analysis of univariate and multivariate stable distributions: with extensions to multivariate stochastic volatility and dynamic factor models," MPRA Paper 40966, University Library of Munich, Germany, revised 20 Aug 2012.
    2. Tsionas, Mike G., 2016. "Bayesian analysis of multivariate stable distributions using one-dimensional projections," Journal of Multivariate Analysis, Elsevier, vol. 143(C), pages 185-193.
    3. Z. Fang & H. Joe, 1992. "Further developments on some dependence orderings for continuous bivariate distributions," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 44(3), pages 501-517, September.
    4. Damarackas, Julius & Paulauskas, Vygantas, 2017. "Spectral covariance and limit theorems for random fields with infinite variance," Journal of Multivariate Analysis, Elsevier, vol. 153(C), pages 156-175.
    5. Phillips, Peter C.B., 1995. "Robust Nonstationary Regression," Econometric Theory, Cambridge University Press, vol. 11(05), pages 912-951, October.

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