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Multivariate generalized Laplace distribution and related random fields

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  • Kozubowski, Tomasz J.
  • Podgórski, Krzysztof
  • Rychlik, Igor

Abstract

Multivariate Laplace distribution is an important stochastic model that accounts for asymmetry and heavier than Gaussian tails, while still ensuring the existence of the second moments. A Lévy process based on this multivariate infinitely divisible distribution is known as Laplace motion, and its marginal distributions are multivariate generalized Laplace laws. We review their basic properties and discuss a construction of a class of moving average vector processes driven by multivariate Laplace motion. These stochastic models extend to vector fields, which are multivariate both in the argument and the value. They provide an attractive alternative to those based on Gaussianity, in presence of asymmetry and heavy tails in empirical data. An example from engineering shows modeling potential of this construction.

Suggested Citation

  • Kozubowski, Tomasz J. & Podgórski, Krzysztof & Rychlik, Igor, 2013. "Multivariate generalized Laplace distribution and related random fields," Journal of Multivariate Analysis, Elsevier, vol. 113(C), pages 59-72.
    • Handle: RePEc:eee:jmvana:v:113:y:2013:i:c:p:59-72
    DOI: 10.1016/j.jmva.2012.02.010
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    References listed on IDEAS

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    1. Sun, Lu, 2001. "Computer simulation and field measurement of dynamic pavement loading," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 56(3), pages 297-313.
    2. Olcay Arslan, 2010. "An alternative multivariate skew Laplace distribution: properties and estimation," Statistical Papers, Springer, vol. 51(4), pages 865-887, December.
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    Cited by:

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    3. Simos G. Meintanis, 2020. "Comments on: Tests for multivariate normality—a critical review with emphasis on weighted $$L^2$$ L 2 -statistics," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(4), pages 898-902, December.
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    7. Jevtić, Petar & Marena, Marina & Semeraro, Patrizia, 2017. "A note on Marked Point Processes and multivariate subordination," Statistics & Probability Letters, Elsevier, vol. 122(C), pages 162-167.
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    10. Chen, Feifei & Meintanis, Simos G. & Zhu, Lixing, 2019. "On some characterizations and multidimensional criteria for testing homogeneity, symmetry and independence," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 125-144.
    11. Chen, Feifei & Jiménez–Gamero, M. Dolores & Meintanis, Simos & Zhu, Lixing, 2022. "A general Monte Carlo method for multivariate goodness–of–fit testing applied to elliptical families," Computational Statistics & Data Analysis, Elsevier, vol. 175(C).
    12. Maria Grazia Zoia & Gianmarco Vacca & Laura Barbieri, 2020. "Modeling Multivariate Financial Series and Computing Risk Measures via Gram–Charlier-Like Expansions," Risks, MDPI, vol. 8(4), pages 1-21, November.
    13. Marc Hallin & Simos Meintanis & Klaus Nordhausen, 2024. "Consistent Distribution–Free Affine–Invariant Tests for the Validity of Independent Component Models," Working Papers ECARES 2024-04, ULB -- Universite Libre de Bruxelles.
    14. Steven Andrew Culpepper & Trevor Park, 2017. "Bayesian Estimation of Multivariate Latent Regression Models: Gauss Versus Laplace," Journal of Educational and Behavioral Statistics, , vol. 42(5), pages 591-616, October.
    15. Mariano González-Sánchez & Eva M. Ibáñez Jiménez & Ana I. Segovia San Juan, 2021. "Market and Liquidity Risks Using Transaction-by-Transaction Information," Mathematics, MDPI, vol. 9(14), pages 1-14, July.
    16. Yury Khokhlov & Victor Korolev & Alexander Zeifman, 2020. "Multivariate Scale-Mixed Stable Distributions and Related Limit Theorems," Mathematics, MDPI, vol. 8(5), pages 1-29, May.
    17. Maume-Deschamps, V. & Rullière, D. & Usseglio-Carleve, A., 2017. "Quantile predictions for elliptical random fields," Journal of Multivariate Analysis, Elsevier, vol. 159(C), pages 1-17.
    18. V. Maume-Deschamps & D. Rullière & A. Usseglio-Carleve, 2018. "Spatial Expectile Predictions for Elliptical Random Fields," Methodology and Computing in Applied Probability, Springer, vol. 20(2), pages 643-671, June.
    19. Mahmoudian, Behzad, 2018. "On the existence of some skew-Gaussian random field models," Statistics & Probability Letters, Elsevier, vol. 137(C), pages 331-335.

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