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Non-parametric methods for circular-circular and circular-linear

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  • Carnicero, José Antonio

Abstract

We present a non-parametric approach for the estimation of the bivariate distribution of two circular variables and the modelling of the joint distribution of a circular and a linear variable. We combine nonparametric estimates of the marginal densities of the circular and linear components with the use of class of nonparametric copulas, known as empirical Bernstein copulas, to model the dependence structure. We derive the necessary conditions to obtain continuous distributions defined on the cylinder for the circular-linear model and on the torus for the circular-circular model. We illustrate these two approaches with two sets of real environmental data

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  • Carnicero, José Antonio, 2011. "Non-parametric methods for circular-circular and circular-linear," DES - Working Papers. Statistics and Econometrics. WS ws110704, Universidad Carlos III de Madrid. Departamento de Estadística.
    • Handle: RePEc:cte:wsrepe:ws110704
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    References listed on IDEAS

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    1. J. J. Fernández-Durán, 2004. "Circular Distributions Based on Nonnegative Trigonometric Sums," Biometrics, The International Biometric Society, vol. 60(2), pages 499-503, June.
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    Keywords

    Bernstein polynomials;

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