Non-parametric methods for circular-circular and circular-linear
AbstractWe 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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Bibliographic InfoPaper provided by Universidad Carlos III, Departamento de Estadística y Econometría in its series Statistics and Econometrics Working Papers with number ws110704.
Date of creation: Apr 2011
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Bernstein polynomials; Circular distributions; Circular-Circular data; Circular-linear data; Copulas; Non-parametric estimation;
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