Search results for "GENERALISED EXTREME VALUE DISTRIBUTION"

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Bayesian inference for the extremal dependence

2016

A simple approach for modeling multivariate extremes is to consider the vector of component-wise maxima and their max-stable distributions. The extremal dependence can be inferred by estimating the angular measure or, alternatively, the Pickands dependence function. We propose a nonparametric Bayesian model that allows, in the bivariate case, the simultaneous estimation of both functional representations through the use of polynomials in the Bernstein form. The constraints required to provide a valid extremal dependence are addressed in a straightforward manner, by placing a prior on the coefficients of the Bernstein polynomials which gives probability one to the set of valid functions. The…

FOS: Computer and information sciencesStatistics and ProbabilityInferenceBernstein polynomialsBivariate analysisBayesian inference01 natural sciencesMethodology (stat.ME)Bayesian nonparametrics010104 statistics & probabilitysymbols.namesakeGeneralised extreme value distribution0502 economics and business62G07Applied mathematics62G05Degree of a polynomial0101 mathematicsStatistics - Methodology050205 econometrics MathematicsAngular measureMax-stable distributionGENERALISED EXTREME VALUE DISTRIBUTION EXTREMAL DEPENDENCE ANGULAR MEASURE MAX-STABLE DISTRIBUTION BERNSTEIN POLYNOMIALS BAYESIAN NONPARAMETRICS TRANS-DIMENSIONAL MCMC EXCHANGE RATEExchange rates05 social sciencesNonparametric statisticsMarkov chain Monte CarloBernstein polynomialGENERALISED EXTREME VALUE DISTRIBUTION; EXTREMAL DEPENDENCE; ANGULAR MEASURE; MAX-STABLE DISTRIBUTION; BERNSTEIN POLYNOMIALS; BAYESIAN NONPARAMETRICS; TRANS-DIMENSIONAL MCMC; EXCHANGE RATETrans-dimensional MCMCEXCHANGE RATEsymbolsStatistics Probability and UncertaintySettore SECS-S/01 - StatisticaMaximaExtremal dependence62G32Electronic Journal of Statistics
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