Extreme Values in R
Decluster Point Process
Generalized Extreme Value Distribution
Generalized Pareto Distribution
Plot of Empirical Distribution Function
Estimate Extremal Index
Find Threshold
Fit Generalized Extreme Value Distribution
Add Quantile Estimates to plot.gpd
Fit Generalized Pareto Model
Add Expected Shortfall Estimates to a GPD Plot
Implements Bivariate POT Method
Fit Gumbel Distribution
Create Hill Plot
Interpret Results of Bivariate GPD Fit
Sample Mean Excess Plot
Plot Fitted GEV Model
Plot Fitted GPD Model
Plot Fitted Bivariate GPD Model
Plot Fitted POT Model
Peaks Over Thresholds Model
Exploratory QQplot for Extreme Value Analysis
Plot of GPD Tail Estimate of a High Quantile
Calculate Record Development
Calculates Quantiles and Expected Shortfalls
Calculate Return Levels Based on GEV Fit
Plot for GPD Shape Parameter
Plot Tail Estimate From GPD Model
Functions for extreme value theory, which may be divided into the following groups; exploratory data analysis, block maxima, peaks over thresholds (univariate and bivariate), point processes, gev/gpd distributions.