ReturnCurves-package: Estimation of Return Curves

In ReturnCurves: Estimation of Return Curves

Estimation of Return Curves

Description

\loadmathjax

Implements the estimation of the \mjeqnpp-probability return curve \insertCiteMurphyBarltropetal2023ReturnCurves, as well as a pointwise and smooth estimation of the angular dependence function \insertCiteWadsworthTawn2013ReturnCurves.

Available functions

adf_est: Estimation of the Angular Dependence Function (ADF)

adf_gof: Goodness of fit of the Angular Dependence Function estimates

airdata: Air pollution data

marggpd: Assessing the Marginal Tail Fits

margtransf: Marginal Transformation

rc_est: Return Curve estimation

rc_gof: Goodness of fit of the Return Curve estimates

rc_unc: Uncertainty of the Return Curve estimates

runShiny: Complementary Shiny app for the ReturnCurves package

Author(s)

Maintainer: Lídia André [e-mail]

Authors:

• Callum Murphy-Barltrop [e-mail]

References

\insertAllCited

Examples

library(ReturnCurves)

data(airdata)

n <- dim(airdata)[1]

# Marginal Transformation
margdata <- margtransf(airdata)

head(margdata@dataexp)

# Return Curves estimation

prob <- 1/n

retcurve <- rc_est(margdata = margdata, p = prob, method = "hill")

head(retcurve@rc)

# ADF estimation
lambda <- adf_est(margdata = margdata, method = "hill")

head(lambda@adf)

ReturnCurves documentation built on April 4, 2025, 5:36 a.m.