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POT: Generalized Pareto Distribution and Peaks Over Threshold

POT provides some functions useful to perform a Peak Over Threshold analysis in univariate and bivariate cases, see Beirlant et al. (2004)

The package

The stable version of POT can be installed from CRAN using:

install.packages("POT")

Finally load the package in your current R session with the following R command:

library(POT)

Documentation

The overall documentation is available at

help(POT)

See also the vignette.

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Version

Install

install.packages('POT')

Monthly Downloads

1,131

Version

1.1-11

License

GPL (>= 2)

Maintainer

Christophe Dutang

Last Published

October 17th, 2024

Functions in POT (1.1-11)

Density Plot: Univariate Case

Fitting Bivariate Peaks Over a Threshold Using Bivariate Extreme Value Distributions

Fit the GP Distribution

Fitting a GPD to Peaks Over a Threshold

Simulate Markov Chains With Extreme Value Dependence Structures

Fisher Confidence Interval

Fisher Based Confidence Interval for the GP Distribution

Fitting Markov Chain Models to Peaks Over a Threshold

Threshold Selection: The Dispersion Index Plot

Extremal Index Plot

Transforms GPD Observations to Unit Frechet Ones and Vice Versa

Extremal Index Estimation

Fitting the point process characterisation to exceedances above a threshold

Graphical Diagnostics: Markov Chains for All Exceedances.

Graphical Diagnostics: the Bivariate Extreme Value Distribution Model.

Compute the Density of the Extremal Index

The Pickands' Dependence Function

Extract Log-Likelihood

Threshold Selection: The Empirical Mean Residual Life Plot

Threshold Selection: The L-moments Plot

Graphical Diagnostic: the Univariate GPD Model

Internal functions and methods

Internal functions and methods for the POT package.

Parametric Bivariate GPD

Profiled Confidence Intervals

Profiled Confidence interval for the GP Distribution

Printing mcpot objects

Printing uvpot objects

Return Periods Tools

Converts Return Periods to Probability and Vice Versa

Printing bvpot objects

Probability Probability Plot

Quantile Quantile Plot

Spectral Density Plot

Mobile Window on a Time Series

Compactly display the structure

Diagnostic for Dependence within Time Series Extremes

Simulate an Markov Chain with a Fixed Extreme Value Dependence from a Fitted mcpot Object

Testing for Tail Independence in Extreme Value Models

Threshold Selection: The Threshold Choice Plot

Return Level Plot

Compute Sample L-moments

Generalized Pareto

The Generalized Pareto Distribution

Overview of the POT package

Generic Function to Compute (Profile) Confidence Intervals

Anova Tables: Univariate Case

High Flood Flows of the Ardieres River at Beaujeu

Return Level Plot: Bivariate Case

Convergence Assessment for Fitted Objects

Anova Tables: Bivariate Case

Dependence Measures For Extreme Values Analysis

Identify Extreme Clusters within a Time Series

Extract model coefficients of a 'pot' model