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

José Antonio Carnicero

DES - Working Papers. Statistics and Econometrics. WS from Universidad Carlos III de Madrid. Departamento de Estadística

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

Keywords: Bernstein; polynomials; Circular; distributions; Circular-Circular; data; Circular-linear; data; Copulas; Non-parametric; estimation (search for similar items in EconPapers)
Date: 2011-04
New Economics Papers: this item is included in nep-ecm
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Persistent link: https://EconPapers.repec.org/RePEc:cte:wsrepe:ws110704

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