rc_est.class {ReturnCurves} | R Documentation |
An S4 class to represent the estimation of the Return Curve
Description
An S4 class to represent the estimation of the Return Curve
Usage
rc_est.class(
data,
qmarg,
constrainedshape,
w,
p,
method,
q,
qalphas,
k,
constrained,
tol,
par_init,
interval,
rc
)
Slots
data
A matrix containing the data on the original margins.
qmarg
A vector containing the marginal quantile used to fit the Generalised Pareto Distribution (GPD) for each variable. Default is
rep(0.95, 2)
.constrainedshape
Logical. If
TRUE
(Default), the estimated shape parameter of the Generalised Pareto Distribution (GPD) is constrained to strictly above-1
.w
Sequence of rays between
0
and1
. Default isseq(0, 1, by = 0.01)
.method
String that indicates which method is used for the estimation of the angular dependence function. Must either be
"hill"
, to use the Hill estimator (Hill 1975), or"cl"
to use the smooth estimator based on Bernstein-Bezier polynomials estimated by composite maximum likelihood.p
Curve survival probability. Must be \(p < 1-q\) and \(p < 1-q_\alpha\).
q
Marginal quantile used for the min-projection variable \(T^1\) at angle \(\omega\) \(\left(t^1_\omega = t_\omega - u_\omega | t_\omega > u_\omega\right)\), and/or Hill estimator (Hill 1975). Default is
0.95
.qalphas
A vector containing the marginal quantile used for the Heffernan and Tawn conditional extremes model (Heffernan and Tawn 2004) for each variable, if
constrained = TRUE
. Default set torep(0.95, 2)
.k
Polynomial degree for the Bernstein-Bezier polynomials used for the estimation of the angular dependence function with the composite likelihood method (Murphy-Barltrop et al. 2024). Default set to
7
.constrained
Logical. If
FALSE
(default) no knowledge of the conditional extremes parameters is incorporated in the angular dependence function estimation.tol
Convergence tolerance for the composite maximum likelihood procedure. Default set to
0.0001
.par_init
Initial values for the parameters \(\beta\) of the Bernstein-Bezier polynomials used for estimation of the angular dependence function with the composite likelihood method (Murphy-Barltrop et al. 2024). Default set to a vector of
0
of lengthk-1
.interval
Maximum likelihood estimates \(\hat{\alpha}^1_{x\mid y}\) and \(\hat{\alpha}^1_{y\mid x}\) from the conditional extremes model if
constrained = TRUE
.rc
A matrix containing the estimates of the Return Curve.