The spatial extreme value data observed at many sites is usually modelled by a multivariate extreme value distribution to take into account the inter-site dependence. However, the analysis involving many sites could create computational and mathematical issues because of the high dimensionality. This study will illustrate an alternative method to come up with estimates for dependent extreme data. The main interest will be in the trend parameter estimate and its standard error. We will show a simulation study to illustrate the advantages of the alternative method to the multivariate extreme value distribution
Currently available models for spatial extremes suffer either from inflexibility in the dependence s...
Several parametric families of multivariate extreme value distributions (Hüsler and Reiss 1989, Tawn...
Multivariate extreme value theory and methods concern the characterization, estimation and extrapola...
Projection of future extreme events is a major issue in a large number of areas including the enviro...
We present properties of a dependence measure that arises in the study of extreme values in multivar...
We present properties of a dependence measure that arises in the study of extreme values in multivar...
We present properties of a dependence measure that arises in the study of extreme values in multivar...
We present properties of a dependence measure that arises in the study of extreme values in multivar...
Extreme values of real phenomena are events that occur with low frequency, but can have a large impa...
Multivariate extreme value distributions arise as the limiting joint distribution of normalized comp...
The statistical theory of extremes is extended to independent multivariate observations that are non...
Extreme value modeling has been attracting the attention of researchers in diverse areas such as th...
Summary. Multivariate extreme value theory and methods concern the characterization, estimation and ...
Extreme-value theory is the branch of statistics concerned with modelling the joint tail of a multiv...
Currently available models for spatial extremes suffer either from inflexibility in the dependence s...
Currently available models for spatial extremes suffer either from inflexibility in the dependence s...
Several parametric families of multivariate extreme value distributions (Hüsler and Reiss 1989, Tawn...
Multivariate extreme value theory and methods concern the characterization, estimation and extrapola...
Projection of future extreme events is a major issue in a large number of areas including the enviro...
We present properties of a dependence measure that arises in the study of extreme values in multivar...
We present properties of a dependence measure that arises in the study of extreme values in multivar...
We present properties of a dependence measure that arises in the study of extreme values in multivar...
We present properties of a dependence measure that arises in the study of extreme values in multivar...
Extreme values of real phenomena are events that occur with low frequency, but can have a large impa...
Multivariate extreme value distributions arise as the limiting joint distribution of normalized comp...
The statistical theory of extremes is extended to independent multivariate observations that are non...
Extreme value modeling has been attracting the attention of researchers in diverse areas such as th...
Summary. Multivariate extreme value theory and methods concern the characterization, estimation and ...
Extreme-value theory is the branch of statistics concerned with modelling the joint tail of a multiv...
Currently available models for spatial extremes suffer either from inflexibility in the dependence s...
Currently available models for spatial extremes suffer either from inflexibility in the dependence s...
Several parametric families of multivariate extreme value distributions (Hüsler and Reiss 1989, Tawn...
Multivariate extreme value theory and methods concern the characterization, estimation and extrapola...