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A numerical inversion of the bivariate characteristic function

Author

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  • Mijanović, Andjela
  • Popović, Božidar V.
  • Witkovský, Viktor

Abstract

We propose a numerical algorithm for the inversion of the bivariate characteristic function. This will allow the complex probability distribution specified by the characteristic function to be used in practise. Subsequently, it will be possible to create numerical algorithms for a copula function. We will also propose an algorithm for generating random numbers for the case where the bivariate distribution is specified by its characteristic function. This algorithm will be based on the conditional characteristic function. The concept and application of the algorithms will be illustrated using a version of the bivariate logistic distribution specified by its characteristic function.

Suggested Citation

  • Mijanović, Andjela & Popović, Božidar V. & Witkovský, Viktor, 2023. "A numerical inversion of the bivariate characteristic function," Applied Mathematics and Computation, Elsevier, vol. 443(C).
    • Handle: RePEc:eee:apmaco:v:443:y:2023:i:c:s009630032200875x
    DOI: 10.1016/j.amc.2022.127807
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    References listed on IDEAS

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    1. Shephard, N.G., 1991. "From Characteristic Function to Distribution Function: A Simple Framework for the Theory," Econometric Theory, Cambridge University Press, vol. 7(4), pages 519-529, December.
    2. N. Balakrishnan & A. Stepanov, 2014. "On the Use of Bivariate Mellin Transform in Bivariate Random Scaling and Some Applications," Methodology and Computing in Applied Probability, Springer, vol. 16(1), pages 235-244, March.
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