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mobirep (version 0.2.3)

Models Bivariate Dependence and Produces Bivariate Return Periods

Description

Models the dependence between two variables in the extremes, identifies most relevant models among six models: the conditional extremes model, the Jt-KDE model and four copulae (Gumbel, Galambos, Normal, FGM). Bivariate return periods for the six models and bivariate level curves can be created. Methods used in the package are described in the following reference: Tilloy, Malamud, Winter and Joly-Laugel (2020) Supporting references for the conditional extremes model, Jt-KDE model and for copula modelling are the following: Heffernan and Tawn (2004) Cooley, Thibaud, Castillo and Wehner (2019) Nelsen (2006) .

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Version

Install

install.packages('mobirep')

Monthly Downloads

20

Version

0.2.3

License

GPL (>= 3)

Maintainer

Alois Tilloy

Last Published

April 22nd, 2021

Functions in mobirep (0.2.3)

fire01meantemp

Fire and extreme temperature in portugal
curve.funct

Creates extreme level curves for copulae
Bv.LT.Dep

Fits bivariate joint tail model
JT.KDE.ap

Fits the bivariate joint tail model with Kernel density estimator
evenPts.p

Spaces out curve points via linear interpolation
densi.curv.em

Computes the density of level curves for non-parametric models
Cond.mod.ap

Fits the bivariate conditional extremes model
densi.curv.cop

Computes the density of level curves for copulae models
AnalogSel

Identifies synthetic datasets analig to input data
digit.curves.p

Creates homogeneous level curve for every model
Margins.mod

Compute uniform margins with Generalized Pareto Distribution above threshold