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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

1,048

Version

1.1-12

License

GPL (>= 2)

Maintainer

Christophe Dutang

Last Published

September 18th, 2026

Functions in POT (1.1-12)

Clusters

Extremal Index Plot
fitbvgpd

Fitting Bivariate Peaks Over a Threshold Using Bivariate Extreme Value Distributions
diplot

Threshold Selection: The Dispersion Index Plot
Fisher Confidence Interval

Fisher Based Confidence Interval for the GP Distribution
Fit the GP Distribution

Fitting a GPD to Peaks Over a Threshold
plot.mcpot

Graphical Diagnostics: Markov Chains for All Exceedances.
gpd2frech

Transforms GPD Observations to Unit Frechet Ones and Vice Versa
fitexi

Extremal Index Estimation
pickdep

The Pickands' Dependence Function
dexi

Compute the Density of the Extremal Index
logLik.pot

Extract Log-Likelihood
lmomplot

Threshold Selection: The L-moments Plot
plot.uvpot

Graphical Diagnostic: the Univariate GPD Model
Internal functions and methods

Internal functions and methods for the POT package.
mrlplot

Threshold Selection: The Empirical Mean Residual Life Plot
qqpareto

QQ-plot for the Pareto distribution
Return Periods Tools

Converts Return Periods to Probability and Vice Versa
retlev

Return Level Plot
print.uvpot

Printing uvpot objects
print.mcpot

Printing mcpot objects
pp

Probability Probability Plot
Profiled Confidence Intervals

Profiled Confidence interval for the GP Distribution
print.bvpot

Printing bvpot objects
plot.bvpot

Graphical Diagnostics: the Bivariate Extreme Value Distribution Model.
qq

Quantile Quantile Plot
tailind.test

Testing for Tail Independence in Extreme Value Models
tsdep.plot

Diagnostic for Dependence within Time Series Extremes
Generalized Pareto

The Generalized Pareto Distribution
summary.pot

Compactly display the structure
bvgpd

Parametric Bivariate GPD
simmcpot

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

Compute Sample L-moments
ts2tsd

Mobile Window on a Time Series
tcplot

Threshold Selection: The Threshold Choice Plot
specdens

Spectral Density Plot
coef.pot

Extract model coefficients of a 'pot' model
POT-package

Overview of the POT package
simmc

Simulate Markov Chains With Extreme Value Dependence Structures
anova.uvpot

Anova Tables: Univariate Case
convassess

Convergence Assessment for Fitted Objects
anova.bvpot

Anova Tables: Bivariate Case
fitpp

Fitting the point process characterisation to exceedances above a threshold
dens

Density Plot: Univariate Case
Flood Flows

High Flood Flows of the Ardieres River at Beaujeu
confint.uvpot

Generic Function to Compute (Profile) Confidence Intervals
clust

Identify Extreme Clusters within a Time Series
chimeas

Dependence Measures For Extreme Values Analysis
fitmcgpd

Fitting Markov Chain Models to Peaks Over a Threshold
retlev.bvpot

Return Level Plot: Bivariate Case