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extRemes (version 2.1-3)

Extreme Value Analysis

Description

General functions for performing extreme value analysis. In particular, allows for inclusion of covariates into the parameters of the extreme-value distributions, as well as estimation through MLE, L-moments, generalized (penalized) MLE (GMLE), as well as Bayes. Inference methods include parametric normal approximation, profile-likelihood, Bayes, and bootstrapping. Some bivariate functionality and dependence checking (e.g., auto-tail dependence function plot, extremal index estimation) is also included. For a tutorial, see Gilleland and Katz (2016) and for bootstrapping, please see Gilleland (2020) .

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Version

Install

install.packages('extRemes')

Monthly Downloads

3,108

Version

2.1-3

License

GPL (>= 2)

Maintainer

Last Published

November 18th, 2022

Functions in extRemes (2.1-3)

HEAT

Summer Maximum and Minimum Temperature: Phoenix, Arizona
BayesFactor

Estimate Bayes Factor
PORTw

Annual Maximum and Minimum Temperature
Denversp

Denver July hourly precipitation amount.
Ozone4H

Ground-Level Ozone Order Statistics.
Flood

United States Total Economic Damage Resulting from Floods
Rsum

Hurricane Frequency Dataset.
ci.fevd

Confidence Intervals
Tphap

Daily Maximum and Minimum Temperature in Phoenix, Arizona.
Peak

Salt River Peak Stream Flow
SantaAna

Santa Ana Winds Data
atdf

Auto-Tail Dependence Function
ci.rl.ns.fevd.bayesian

Confidence/Credible Intervals for Effective Return Levels
Potomac

Potomac River Peak Stream Flow Data.
blockmaxxer

Find Block Maxima
bvpotbooter

Bootstrap Functions for Bivariate POT
extremalindex

Extemal Index
damage

Hurricane Damage Data
datagrabber.declustered

Get Original Data from an R Object
decluster

Decluster Data Above a Threshold
extRemes internal

extRemes Internal and Secondary Functions
fbvpot

Estimate the Bivariate Peaks-Over-Threshold (POT) Model
distill.fevd

Distill Parameter Information
extRemes-package

extRemes -- Weather and Climate Applications of Extreme Value Analysis (EVA)
devd

Extreme Value Distributions
erlevd

Effective Return Levels
fpois

Fit Homogeneous Poisson to Data and Test Equality of Mean and Variance
findpars

Get EVD Parameters
ftcanmax

Annual Maximum Precipitation: Fort Collins, Colorado
levd

Extreme Value Likelihood
hwmid

Heat Wave Magnitude Index
lr.test

Likelihood-Ratio Test
hwmi

Heat Wave Magnitude Index
logistic

Logistic Dependence Model Likelihood
pextRemes

Probabilities and Random Draws from Fitted EVDs
profliker

Profile Likelihood Function
is.fixedfevd

Stationary Fitted Model Check
mrlplot

Mean Residual Life Plot
parcov.fevd

EVD Parameter Covariance
make.qcov

Covariate Matrix for Non-Stationary EVD Projections
postmode

Posterior Mode from an MCMC Sample
fevd

Fit An Extreme Value Distribution (EVD) to Data
mixbeta

Mixed Beta Dependence Model Likelihood
findAllMCMCpars

Manipulate MCMC Output from fevd Objects
qqnorm

Normal qq-plot with 95 Percent Simultaneous Confidence Bands
rlevd

Return Levels for Extreme Value Distributions
shiftplot

Shift Plot Between Two Sets of Data
strip

Strip Fitted EVD Object of Everything but the Parameter Estimates
xtibber

Test-Inversion Bootstrap for Extreme-Value Analysis
xbooter

Additional Bootstrap Functions for Univariate EVA
trans

Transform Data
qqplot

qq-plot Between Two Vectors of Data with 95 Percent Confidence Bands
taildep

Tail Dependence
return.level

Return Level Estimates
taildep.test

Tail Dependence Test
revtrans.evd

Reverse Transformation
threshrange.plot

Threshold Selection Through Fitting Models to a Range of Thresholds
Fort

Daily precipitation amounts in Fort Collins, Colorado.
CarcasonneHeat

European Climate Assessment and Dataset
Denmint

Denver Minimum Temperature
FCwx

Fort Collins, Colorado Weather Data