A B C D E G J L M N P Q R S T W misc
texmex-package | Extreme value modelling |
addExcesses | Annotate a threshold selection ggplot |
AIC.evmOpt | Information Criteria |
AIC.evmSim | Information Criteria |
bootExtremalIndex | Extremal index estimation and automatic declustering |
bootMCS | Multivariate conditional Spearman's rho |
bootmex | Bootstrap a conditional multivariate extreme values model |
calcJointExceedanceCurve | Joint exceedance curves |
cgpd | Create families of distributions |
chi | Measures of extremal dependence |
coef.evmBoot | Bootstrap an evmOpt fit |
copula | Calculate the copula of a matrix of variables |
copula.data.frame | Calculate the copula of a matrix of variables |
copula.default | Calculate the copula of a matrix of variables |
copula.matrix | Calculate the copula of a matrix of variables |
cv | Cross-validation for a model object |
cv.evmOpt | Cross-validation for the shape parameter in an extreme values model |
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 |
evmReal | Extreme value modelling |
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 |
geom_jointExcCurve | Joint exceedance curves |
gev | Create families of distributions |
ggacfplots | Diagnostic plots for the Markov chains in an evmSim object |
ggbootdensplots | Diagnostic plots for the replicate estimated parameter values in an evmBoot object |
ggdensplots | Diagnostic plots for the Markov chains in an evmSim object |
ggplot.bootMCS | Multivariate conditional Spearman's rho |
ggplot.chi | Measures of extremal dependence |
ggplot.copula | Fancy plotting for copulas |
ggplot.cv | Cross-validation for a model object |
ggplot.declustered | Diagnostic plots for an declustered object |
ggplot.egp3RangeFit | Estimate the EGP3 distribution power parameter over a range of thresholds |
ggplot.evmBoot | Diagnostic plots for the replicate estimated parameter values in an evmBoot object |
ggplot.evmOpt | Diagnostic plots for an evm object |
ggplot.evmOpt, | Diagnostic plots for an evm object |
ggplot.evmSim | Diagnostic plots for the Markov chains in an evmSim object |
ggplot.extremalIndex | Diagnostic plots for an declustered object |
ggplot.extremalIndexRangeFit | Extremal index estimation and automatic declustering |
ggplot.gpdRangeFit | Estimate generalized Pareto distribution parameters over a range of values |
ggplot.hist.evmOpt | Diagnostic plots for an evm object |
ggplot.lp.evmBoot | Plotting function for return level estimation |
ggplot.lp.evmOpt | Plotting function for return level estimation |
ggplot.lp.evmSim | Plotting function for return level estimation |
ggplot.MCS | Multivariate conditional Spearman's rho |
ggplot.mex | Conditional multivariate extreme values modelling |
ggplot.migpd | Fit multiple independent generalized Pareto models |
ggplot.mrl | Mean residual life plot |
ggplot.ppevm | Diagnostic plots for an evm object |
ggplot.predict.mex | Conditional multivariate extreme values modelling |
ggplot.qqevm | Diagnostic plots for an evm object |
ggplot.rl.evmBoot | Plotting function for return level estimation |
ggplot.rl.evmOpt | Plotting function for return level estimation |
ggplot.rl.evmSim | Plotting function for return level estimation |
ggplotrl | Diagnostic plots for an evm object |
ggtraceplots | Diagnostic plots for the Markov chains in an evmSim object |
glo | Create families of distributions |
gpd | Create families of distributions |
gpd.prof | Profile likelihood based confidence intervals for GPD |
gpdIntCensored | Create families of distributions |
gpdRangeFit | Estimate generalized Pareto distribution parameters over a range of values |
gumbel | Create families of distributions |
JointExceedanceCurve | Joint exceedance curves |
JointExceedanceCurve.default | Joint exceedance curves |
JointExceedanceCurve.mexMC | Joint exceedance curves |
JointExceedanceCurve.predict.mex | Joint exceedance curves |
linearPredictors | Predict return levels from extreme value models, or obtain the linear predictors. |
linearPredictors.evmBoot | Predict return levels from extreme value models, or obtain the linear predictors. |
linearPredictors.evmOpt | Predict return levels from extreme value models, or obtain the linear predictors. |
linearPredictors.evmSim | Predict return levels from extreme value models, or obtain the linear predictors. |
liver | Liver related laboratory data |
logLik.evmOpt | Log-likelihood for evmOpt objects |
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 |
nidd | Rain, wavesurge, portpirie and nidd datasets. |
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 |
qegp3 | Density, cumulative density, quantiles and random number generation for the extended generalized Pareto distribution 3 |
qgev | Density, cumulative density, quantiles and random number generation for the generalized extreme value distribution |
qglo | Generalized logistic distribution |
qgpd | Density, cumulative density, quantiles and random number generation for the generalized Pareto distribution |
qgumbel | The Gumbel distribution |
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. |
simulate.evmBoot | Simulate from a fitted evm object |
simulate.evmOpt | Simulate from a fitted evm object |
simulate.evmSim | Simulate from a fitted evm object |
summary.bootMCS | Multivariate conditional Spearman's rho |
summary.chi | Measures of extremal dependence |
summary.cv | Cross-validation for a model object |
summary.evmBoot | Bootstrap an evmOpt fit |
summary.gpdRangeFit | Estimate generalized Pareto distribution parameters over a range of values |
summary.mex | Conditional multivariate extreme values modelling |
summary.mrl | Mean residual life plot |
summary.predict.mex | Conditional multivariate extreme values modelling |
summary.texmexFamily | Create families of distributions |
summer | Air pollution data, separately for summer and winter months |
summer and winter data | Air pollution data, separately for summer and winter months |
texmex | Extreme value modelling |
texmexFamily | Create families of distributions |
thinAndBurn | Process Metropolis output from extreme value model fitting to discard unwanted observations. |
thinAndBurn.evmSim | Process Metropolis output from extreme value model fitting to discard unwanted observations. |
wavesurge | Rain, wavesurge, portpirie and nidd datasets. |
weibull | Create families of distributions |
winter | Air pollution data, separately for summer and winter months |
.exprel | Accurately compute (exp(x) - 1) / x |
.log1mexp | Accurately compute log(1-exp(x)) |
.log1prel | Accurately compute log(1 + x) / x |
.specfun.safe.product | Compute pmax(x y, -1) in such a way that zeros in x beat infinities in y. |