GpdModelling
(Package: fExtremes) :
GPD Distributions for Extreme Value Theory
A collection and description to functions to compute the generalized Pareto distribution and to estimate its parameters. The functions compute density, distribution function, quantile function and generate random deviates for the GPD. Two approaches for parameter estimation are provided: Maximum likelihood estimation and the probability weighted moment method.
● Data Source:
CranContrib
● Keywords: distribution
● Alias: GpdModelling
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A collection and description functions to estimate the parameters of the GEV distribution. To model the GEV three types of approaches for parameter estimation are provided: Maximum likelihood estimation, probability weighted moment method, and estimation by the MDA approach. MDA includes functions for the Pickands, Einmal-Decker-deHaan, and Hill estimators together with several plot variants.
● Data Source:
CranContrib
● Keywords: models
● Alias: GevMdaEstimation
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A collection and description of functions to compute Value-at-Risk and conditional Value-at-Risk
● Data Source:
CranContrib
● Keywords: models
● Alias: ValueAtRisk
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A collection and description of functions for data preprocessing of extreme values. This includes tools to separate data beyond a threshold value, to compute blockwise data like block maxima, and to decluster point process data.
● Data Source:
CranContrib
● Keywords: programming
● Alias: DataPreprocessing
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A collection and description of functions to compute the generalized Pareto distribution. The functions compute density, distribution function, quantile function and generate random deviates for the GPD. In addition functions to compute the true moments and to display the distribution and random variates changing parameters interactively are available.
● Data Source:
CranContrib
● Keywords: distribution
● Alias: GpdDistribution
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A collection and description of functions to simulate time series with a known extremal index, and to estimate the extremal index by four different kind of methods, the blocks method, the reciprocal mean cluster size method, the runs method, and the method of Ferro and Segers.
● Data Source:
CranContrib
● Keywords: hplot
● Alias: ExtremeIndex
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Data sets used in the examples of the timeSeries packages.
● Data Source:
CranContrib
● Keywords:
● Alias: TimeSeriesData
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GevDistribution
(Package: fExtremes) :
Generalized Extreme Value Distribution
Density, distribution function, quantile function, random number generation, and true moments for the GEV including the Frechet, Gumbel, and Weibull distributions.
● Data Source:
CranContrib
● Keywords: models
● Alias: GevDistribution
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gpdRisk
(Package: fExtremes) :
GPD Distributions for Extreme Value Theory
A collection and description to functions to compute tail risk under the GPD approach.
● Data Source:
CranContrib
● Keywords: distribution
● Alias: gpdRisk
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GevRisk
(Package: fExtremes) :
Generalized Extreme Value Modelling
A collection and description functions to estimate the parameters of the GEV distribution. To model the GEV three types of approaches for parameter estimation are provided: Maximum likelihood estimation, probability weighted moment method, and estimation by the MDA approach. MDA includes functions for the Pickands, Einmal-Decker-deHaan, and Hill estimators together with several plot variants.
● Data Source:
CranContrib
● Keywords: models
● Alias: GevRisk
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