| declust |
Extremal index estimation and automatic declustering |
| declust.default |
Extremal index estimation and automatic declustering |
| declust.extremalIndex |
Extremal index estimation and automatic declustering |
| degp3 |
Density, cumulative density, quantiles and random number generation for the extended generalized Pareto distribution 3 |
| dgev |
Density, cumulative density, quantiles and random number generation for the generalized extreme value distribution |
| dglo |
Generalized logistic distribution |
| dgpd |
Density, cumulative density, quantiles and random number generation for the generalized Pareto distribution |
| dgumbel |
The Gumbel distribution |
| edf |
Compute empirical distribution function |
| egp3 |
Create families of distributions |
| egp3RangeFit |
Estimate the EGP3 distribution power parameter over a range of thresholds |
| endPoint |
Calculate upper end point for a fitted extreme value model |
| endPoint.evmBoot |
Calculate upper end point for a fitted extreme value model |
| endPoint.evmOpt |
Calculate upper end point for a fitted extreme value model |
| endPoint.evmSim |
Calculate upper end point for a fitted extreme value model |
| evm |
Extreme value modelling |
| evm.declustered |
Extremal index estimation and automatic declustering |
| evm.default |
Extreme value modelling |
| evmBoot |
Bootstrap an evmOpt fit |
| evmSim |
MCMC simulation around an evmOpt fit |
| evmSimSetSeed |
Set the seed from a fitted evmSim object. |
| extremalIndex |
Extremal index estimation and automatic declustering |
| extremalIndexRangeFit |
Extremal index estimation and automatic declustering |
| makeReferenceMarginalDistribution |
Provide full marginal reference distribution for for maringal transformation |
| MCS |
Multivariate conditional Spearman's rho |
| mex |
Conditional multivariate extreme values modelling |
| mexAll |
Conditional multivariate extreme values modelling |
| mexDependence |
Estimate the dependence parameters in a conditional multivariate extreme values model |
| mexMonteCarlo |
Simulation from dependence models |
| mexRangeFit |
Estimate dependence parameters in a conditional multivariate extreme values model over a range of thresholds. |
| migpd |
Fit multiple independent generalized Pareto models |
| migpdCoefs |
Change values of parameters in a migpd object |
| mrl |
Mean residual life plot |
| pegp3 |
Density, cumulative density, quantiles and random number generation for the extended generalized Pareto distribution 3 |
| pgev |
Density, cumulative density, quantiles and random number generation for the generalized extreme value distribution |
| pglo |
Generalized logistic distribution |
| pgpd |
Density, cumulative density, quantiles and random number generation for the generalized Pareto distribution |
| pgumbel |
The Gumbel distribution |
| plot.bootMCS |
Multivariate conditional Spearman's rho |
| plot.bootmex |
Bootstrap a conditional multivariate extreme values model |
| plot.chi |
Measures of extremal dependence |
| plot.copula |
Plot copulas |
| plot.cv |
Cross-validation for a model object |
| plot.declustered |
Extremal index estimation and automatic declustering |
| plot.egp3RangeFit |
Estimate the EGP3 distribution power parameter over a range of thresholds |
| plot.evmBoot |
Bootstrap an evmOpt fit |
| plot.evmOpt |
Plots for evmOpt objects |
| plot.evmSim |
Plots for evmSim objects |
| plot.extremalIndexRangeFit |
Extremal index estimation and automatic declustering |
| plot.gpdRangeFit |
Estimate generalized Pareto distribution parameters over a range of values |
| plot.lp.evmOpt |
Predict return levels from extreme value models, or obtain the linear predictors. |
| plot.MCS |
Multivariate conditional Spearman's rho |
| plot.mex |
Conditional multivariate extreme values modelling |
| plot.migpd |
Fit multiple independent generalized Pareto models |
| plot.mrl |
Mean residual life plot |
| plot.predict.mex |
Conditional multivariate extreme values modelling |
| plot.rl.evmBoot |
Return levels |
| plot.rl.evmOpt |
Return levels |
| plot.rl.evmSim |
Return levels |
| portpirie |
Rain, wavesurge, portpirie and nidd datasets. |
| predict.evmBoot |
Predict return levels from extreme value models, or obtain the linear predictors. |
| predict.evmOpt |
Predict return levels from extreme value models, or obtain the linear predictors. |
| predict.evmSim |
Predict return levels from extreme value models, or obtain the linear predictors. |
| predict.mex |
Conditional multivariate extreme values modelling |
| print.bootMCS |
Multivariate conditional Spearman's rho |
| print.bootmex |
Bootstrap a conditional multivariate extreme values model |
| print.chi |
Measures of extremal dependence |
| print.cv |
Cross-validation for a model object |
| print.declustered |
Extremal index estimation and automatic declustering |
| print.egp3RangeFit |
Estimate the EGP3 distribution power parameter over a range of thresholds |
| print.evmBoot |
Bootstrap an evmOpt fit |
| print.evmOpt |
Print evmOpt objects |
| print.extremalIndex |
Extremal index estimation and automatic declustering |
| print.gpdRangeFit |
Estimate generalized Pareto distribution parameters over a range of values |
| print.jointExcCurve |
Joint exceedance curves |
| print.lp.evmOpt |
Predict return levels from extreme value models, or obtain the linear predictors. |
| print.MCS |
Multivariate conditional Spearman's rho |
| print.mex |
Conditional multivariate extreme values modelling |
| print.mexList |
Conditional multivariate extreme values modelling |
| print.mrl |
Mean residual life plot |
| print.rl.evmOpt |
Return levels |
| print.summary.bootMCS |
Multivariate conditional Spearman's rho |
| print.summary.chi |
Measures of extremal dependence |
| print.summary.evmBoot |
Bootstrap an evmOpt fit |
| print.summary.gpdRangeFit |
Estimate generalized Pareto distribution parameters over a range of values |
| print.summary.mex |
Conditional multivariate extreme values modelling |
| print.summary.mrl |
Mean residual life plot |
| print.summary.texmexFamily |
Create families of distributions |
| print.texmexFamily |
Create families of distributions |
| rain |
Rain, wavesurge, portpirie and nidd datasets. |
| rain, wavesurge and portpirie |
Rain, wavesurge, portpirie and nidd datasets. |
| regp3 |
Density, cumulative density, quantiles and random number generation for the extended generalized Pareto distribution 3 |
| rFrechet |
Extreme Value random process generation. |
| rgev |
Density, cumulative density, quantiles and random number generation for the generalized extreme value distribution |
| rglo |
Generalized logistic distribution |
| rgpd |
Density, cumulative density, quantiles and random number generation for the generalized Pareto distribution |
| rgumbel |
The Gumbel distribution |
| rl |
Return levels |
| rl.evmBoot |
Return levels |
| rl.evmOpt |
Return levels |
| rl.evmSim |
Return levels |
| rMaxAR |
Extreme Value random process generation. |