Open Access
February 2016 Polynomial Pickands functions
Simon Guillotte, François Perron
Bernoulli 22(1): 213-241 (February 2016). DOI: 10.3150/14-BEJ656

Abstract

Pickands dependence functions characterize bivariate extreme value copulas. In this paper, we study the class of polynomial Pickands functions. We provide a solution for the characterization of such polynomials of degree at most $m+2$, $m\geq0$, and show that these can be parameterized by a vector in $\mathbb{R}^{m+1}$ belonging to the intersection of two ellipsoids. We also study the class of Bernstein approximations of order $m+2$ of Pickands functions which are shown to be (polynomial) Pickands functions and parameterized by a vector in $\mathbb{R}^{m+1}$ belonging to a polytope. We give necessary and sufficient conditions for which a polynomial Pickands function is in fact a Bernstein approximation of some Pickands function. Approximation results of Pickands dependence functions by polynomials are given. Finally, inferential methodology is discussed and comparisons based on simulated data are provided.

Citation

Download Citation

Simon Guillotte. François Perron. "Polynomial Pickands functions." Bernoulli 22 (1) 213 - 241, February 2016. https://doi.org/10.3150/14-BEJ656

Information

Received: 1 May 2013; Revised: 1 June 2014; Published: February 2016
First available in Project Euclid: 30 September 2015

zbMATH: 06543268
MathSciNet: MR3449781
Digital Object Identifier: 10.3150/14-BEJ656

Keywords: Bernstein’s theorem , extreme value copulas , Lorentz degree , Pickands dependence function , polynomials , spectral measure

Rights: Copyright © 2016 Bernoulli Society for Mathematical Statistics and Probability

Vol.22 • No. 1 • February 2016
Back to Top