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ExtremalDep (version 0.0.4-2)

Extremal Dependence Models

Description

A set of procedures for parametric and non-parametric modelling of the dependence structure of multivariate extreme-values is provided. The statistical inference is performed with non-parametric estimators, likelihood-based estimators and Bayesian techniques. It adapts the methodologies of Beranger and Padoan (2015) , Marcon et al. (2016) , Marcon et al. (2017) , Marcon et al. (2017) and Beranger et al. (2021) . This package also allows for the modelling of spatial extremes using flexible max-stable processes. It provides simulation algorithms and fitting procedures relying on the Stephenson-Tawn likelihood as per Beranger at al. (2021) .

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Version

Install

install.packages('ExtremalDep')

Monthly Downloads

301

Version

0.0.4-2

License

GPL (>= 2)

Maintainer

Simone Padoan

Last Published

October 6th, 2024

Functions in ExtremalDep (0.0.4-2)

dGEV

The Generalized Extreme Value Distribution
ellipse

Level sets for bivariate normal, student-t and skew-normal distributions probability densities.
desn

Univariate extended skew-normal distribution
dmesn

Bivariate and trivariate extended skew-normal distribution
dim_ExtDep

Dimensions calculations for parametric extremal dependence models
dmest

Bivariate and trivariate extended skew-t distribution
dest

Univariate extended skew-t distribution
fExtDep.np

Non-parametric extremal dependence estimation
fExtDep

Extremal dependence estimation
logReturns

Monthly maxima of log-return exchange rates of the Pound Sterling (GBP) against the US dollar (USD) and the Japanese yen (JPY), between March 1991 and December 2014.
pExtDep

Parametric and non-parametric distribution function of Extremal Dependence
fExtDepSpat

Fitting of a max-stable process
plot_ExtDep

Graphical summaries of parametric representations of extremal dependence.
plot_ExtDep.np

Graphical summaries of non-parametric representations of extremal dependence.
heat

Summer temperature maxima in Melbourne, Australia between 1961 and 2010.
fGEV

Fitting of the Generalized Extreme Value Distribution
rExtDep

Parametric and semi-parametric random generator of extreme events
madogram

Madogram-based estimation of the Pickands Dependence Function
simplex

Definition of a multivariate simplex
pFailure

Probability of falling into a failure region
pollution

Air quality datasets containing daily maxima of air pollutants (PM10, NO, NO2, 03 and S02) recorded in Leeds (U.K.), during five winter seasons (November-Februrary) between 1994 and 1998.
index.ExtDep

Index of extremal dependence
summary_ExtDep

Summary of MCMC algorithm.
trans2UFrechet

Transformation to unit Frechet distribution
trans2GEV

Transformation to GEV distribution
returns

Compute return values
rExtDepSpat

Random generation of max-stable processes
PrecipFrance

Weekly maxima of hourly rainfall in France
angular

Estimation of the angular density, angular measure and random generation from the angular distribution.
ExtQ

Univariate Extreme Quantile
beed.confband

Nonparametric Bootstrap Confidence Intervals
WindSpeedGust

Hourly wind gust, wind speed and air pressure at Lingen (GER), Ossendorf (GER) and Parcay-Meslay (FRA).
Wind

Weekly maximum wind speed data collected over 4 stations across Oklahoma, USA, over the March-May preiod between 1996 and 2012.
dExtDep

Parametric and non-parametric density of Extremal Dependence
beed.boot

Bootstrap Resampling and Bernstein Estimation of Extremal Dependence
MilanPollution

Pollution data for summer and winter months in Milan, Italy.
beed

Bernstein Polynomials Based Estimation of Extremal Dependence
diagnostics

Diagnostics plots for MCMC algorithm.