Statistical Modelling of Extreme Values
Annotate a threshold selection ggplot
Information Criteria
Air pollution data, separately for summer and winter months
Bootstrap a conditional multivariate extreme values model
Measures of extremal dependence
Calculate the copula of a matrix of variables
Cross-validation for the shape parameter in an extreme values model
Cross-validation for a model object
Density, cumulative density, quantiles and random number generation fo...
Density, cumulative density, quantiles and random number generation fo...
Generalized logistic distribution
Density, cumulative density, quantiles and random number generation fo...
The Gumbel distribution
Accurately compute (exp(x) - 1) / x
Accurately compute log(1-exp(x))
Accurately compute log(1 + x) / x
Compute pmax(x y, -1) in such a way that zeros in x beat infinities in...
Compute empirical distribution function
Estimate the EGP3 distribution power parameter over a range of thresho...
Calculate upper end point for a fitted extreme value model
Extreme value modelling
Bootstrap an evmOpt fit
MCMC simulation around an evmOpt fit
Set the seed from a fitted evmSim object.
Extremal index estimation and automatic declustering
Fancy plotting for copulas
Diagnostic plots for an declustered object
Diagnostic plots for the replicate estimated parameter values in an ev...
Diagnostic plots for an evm object
Diagnostic plots for the Markov chains in an evmSim object
Plotting function for return level estimation
Profile likelihood based confidence intervals for GPD
Estimate generalized Pareto distribution parameters over a range of va...
Joint exceedance curves
Log-likelihood for evmOpt objects
Provide full marginal reference distribution for for maringal transfor...
Multivariate conditional Spearman's rho
Conditional multivariate extreme values modelling
Estimate the dependence parameters in a conditional multivariate extre...
Simulation from dependence models
Estimate dependence parameters in a conditional multivariate extreme v...
Fit multiple independent generalized Pareto models
Change values of parameters in a migpd object
Mean residual life plot
Plot copulas
Plots for evmOpt objects
Plots for evmSim objects
Predict return levels from extreme value models, or obtain the linear ...
Print evmOpt objects
Extreme Value random process generation.
Return levels
Extreme Value random process generation.
Simulate from a fitted evm object
Extreme value modelling
Create families of distributions
Process Metropolis output from extreme value model fitting to discard ...
Statistical extreme value modelling of threshold excesses, maxima and multivariate extremes. Univariate models for threshold excesses and maxima are the Generalised Pareto, and Generalised Extreme Value model respectively. These models may be fitted by using maximum (optionally penalised-)likelihood, or Bayesian estimation, and both classes of models may be fitted with covariates in any/all model parameters. Model diagnostics support the fitting process. Graphical output for visualising fitted models and return level estimates is provided. For serially dependent sequences, the intervals declustering algorithm of Ferro and Segers (2003) <doi:10.1111/1467-9868.00401> is provided, with diagnostic support to aid selection of threshold and declustering horizon. Multivariate modelling is performed via the conditional approach of Heffernan and Tawn (2004) <doi:10.1111/j.1467-9868.2004.02050.x>, with graphical tools for threshold selection and to diagnose estimation convergence.