In this paper, we are concerned with bivariate di erentiable models for joint extremes for dependent data sets. This question is often raised in hydrology and economics when the risk driven by two (or more) factors has to be quantiÿed. Here we give a full characterization of polynomial models by mea
Nonparametric Estimation of the Dependence Function in Bivariate Extreme Value Distributions
✍ Scribed by Javier Rojo Jiménez; Enrique Villa-Diharce; Miguel Flores
- Publisher
- Elsevier Science
- Year
- 2001
- Tongue
- English
- Weight
- 288 KB
- Volume
- 76
- Category
- Article
- ISSN
- 0047-259X
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✦ Synopsis
The paper considers the problem of estimating the dependence function of a bivariate extreme survival function with standard exponential marginals. Nonparametric estimators for the dependence function are proposed and their strong uniform convergence under suitable conditions is demonstrated. Comparisons of the proposed estimators with other estimators are made in terms of bias and mean squared error. Several real data sets from various applications are used to illustrate the procedures.
📜 SIMILAR VOLUMES
The traditional method for estimating the linear function of fiied parameters in mixed linear model is a two-stage p r d u r e . In the first stage of this procedure the variance components estimators are calculated and next in the second stage these estimators are taken as true values of variance c