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A new parametric method of estimating the joint probability density

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  • Alghalith, Moawia

Abstract

We present simple parametric methods that overcome major limitations of the literature on joint/marginal density estimation. In doing so, we do not assume any form of marginal or joint distribution. Furthermore, using our method, a multivariate density can be easily estimated if we know only one of the marginal densities. We apply our methods to financial data.

Suggested Citation

  • Alghalith, Moawia, 2017. "A new parametric method of estimating the joint probability density," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 799-803.
    • Handle: RePEc:eee:phsmap:v:471:y:2017:i:c:p:799-803
    DOI: 10.1016/j.physa.2016.12.043
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    References listed on IDEAS

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    1. David E. Allen & Mohammad A. Ashraf & Michael McAleer & Robert J. Powell & Abhay K. Singh, 2013. "Financial dependence analysis: applications of vine copulas," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 67(4), pages 403-435, November.
    2. Alghalith, Moawia, 2016. "Novel and simple non-parametric methods of estimating the joint and marginal densities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 454(C), pages 94-98.
    3. Talamakrouni, Majda & Van Keilegom, Ingrid & El Ghouch, Anouar, 2016. "Parametrically guided nonparametric density and hazard estimation with censored data," Computational Statistics & Data Analysis, Elsevier, vol. 93(C), pages 308-323.
    4. Alghalith, Moawia, 2008. "Recent applications of theory of the firm under uncertainty," European Journal of Operational Research, Elsevier, vol. 186(2), pages 443-450, April.
    5. David Pitt & Montserrat Guillen & Catalina Bolancé, 2011. "Estimation of Parametric and Nonparametric Models for Univariate Claim Severity Distributions - an approach using R," Working Papers XREAP2011-06, Xarxa de Referència en Economia Aplicada (XREAP), revised Jun 2011.
    6. Gregor Weiß, 2011. "Copula parameter estimation by maximum-likelihood and minimum-distance estimators: a simulation study," Computational Statistics, Springer, vol. 26(1), pages 31-54, March.
    7. Chavas, Jean-Paul & Holt, Matthew T, 1996. "Economic Behavior under Uncertainty: A Joint Analysis of Risk Preferences and Technology," The Review of Economics and Statistics, MIT Press, vol. 78(2), pages 329-335, May.
    8. Durante, Fabrizio & Okhrin, Ostap, 2014. "Estimation procedures for exchangeable Marshall copulas with hydrological application," SFB 649 Discussion Papers 2014-014, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
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