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Bivariate Tail Estimation: Dependence in Asymptotic Independence
by
Draisma, Gerrit
, Dress, Holger
, de Haan, Laurens
, Ferreira, Ana
in
Approximation
/ asymptotic normality
/ bivariate extreme value distribution
/ coefficient of tail dependence
/ Consistent estimators
/ copula
/ Distribution functions
/ Estimation bias
/ Estimators
/ failure probability
/ Gaussian distributions
/ Hill estimator
/ Maximum likelihood estimation
/ Maximum likelihood estimators
/ moment estimator
/ Standard deviation
/ Statistical variance
2004
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Bivariate Tail Estimation: Dependence in Asymptotic Independence
by
Draisma, Gerrit
, Dress, Holger
, de Haan, Laurens
, Ferreira, Ana
in
Approximation
/ asymptotic normality
/ bivariate extreme value distribution
/ coefficient of tail dependence
/ Consistent estimators
/ copula
/ Distribution functions
/ Estimation bias
/ Estimators
/ failure probability
/ Gaussian distributions
/ Hill estimator
/ Maximum likelihood estimation
/ Maximum likelihood estimators
/ moment estimator
/ Standard deviation
/ Statistical variance
2004
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While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Bivariate Tail Estimation: Dependence in Asymptotic Independence
by
Draisma, Gerrit
, Dress, Holger
, de Haan, Laurens
, Ferreira, Ana
in
Approximation
/ asymptotic normality
/ bivariate extreme value distribution
/ coefficient of tail dependence
/ Consistent estimators
/ copula
/ Distribution functions
/ Estimation bias
/ Estimators
/ failure probability
/ Gaussian distributions
/ Hill estimator
/ Maximum likelihood estimation
/ Maximum likelihood estimators
/ moment estimator
/ Standard deviation
/ Statistical variance
2004
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Bivariate Tail Estimation: Dependence in Asymptotic Independence
Journal Article
Bivariate Tail Estimation: Dependence in Asymptotic Independence
2004
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Overview
In the classical setting of bivariate extreme value theory, the procedures for estimating the probability of an extreme event are not applicable if the componentwise maxima of the observations are asymptotically independent. To cope with this problem, Ledford and Tawn proposed a submodel in which the penultimate dependence is characterized by an additional parameter. We discuss the asymptotic properties of two estimators for this parameter in an extended model. Moreover, we develop an estimator for the probability of an extreme event that works in the case of asymptotic independence as well as in the case of asymptotic dependence, and prove its consistency.
Publisher
International Statistics Institute / Bernoulli Society,Bernoulli Society for Mathematical Statistics and Probability
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