Data object used for a Tail Dependence model.
RTDE(obs=NULL, simu=list(), contamin=list(),
nbpoint, alpha, omega, method="MDPDE", fix.arg=list(rho=-1),
boundary.method="log", core=1, keepdata, control=list())
# S3 method for RTDE
print(x, ...)
# S3 method for RTDE
summary(object, ...)
# S3 method for RTDE
plot(x, which=1:3, FUN=mean, main, ...)
prob(object, q, ...)
# S3 method for default
prob(object, q, ...)
# S3 method for RTDE
prob(object, q, ...)
RTDE
returns an object of class "RTDE"
having the following components:
obs.type
see dataRTDE
.
data
see dataRTDE
.
fit
see fitRTDE
.
simu
see dataRTDE
.
contamin
see dataRTDE
.
setting
a list summarizing the computation.
bivariate numeric dataset.
a names list with components:
"nb"
, "marg"
, "cop"
, "replicate"
.
When needed, "cop.par"
must be provided,
see dataRTDE
.
a names list with components:
"eps"
, "method"
, "marg"
, "cop"
.
When needed, "cop.par"
must be provided,
see dataRTDE
.
a numeric for the number of largest points to be selected.
a numeric for the power divergence parameter.
a numeric for omega, see section Details.
a character string equals to "MDPDE"
.
a named list of fixed arguments:
either \(rho\) only e.g. list(rho=-1)
or \(rho, delta\) e.g. list(rho=-1, delta=0)
.
a character string: either "log" or "simple", see section Details.
a numeric for the number of core to be used, only relevant for simulated data.
a logical whether to return or not the dataset.
A list of control paremeters for fitRTDE
.
an R object inheriting from "RTDE"
.
arguments to be passed to subsequent methods.
an integer to specify what to plot: 1 eta, 2 delta, 3 probability estimates.
the function to be applied, default to mean
.
a main title for the plot.
vector of quantiles.
Christophe Dutang
The function RTDE
handles (empirical or simulated) data
(cf. dataRTDE
)
and then fits a bivariate tail model using a method
criterion
(cf. fitRTDE
and MDPD
) based
on an extended Pareto distribution approximation (EPD
).
Typical distributions for simulated data and/or contaminations are
Unit Pareto upareto
, Frechet Frechet
.
Frank Frank
, FGM FGM
.
For a good introduction, please refer to references.
C. Dutang, Y. Goegebeur, A. Guillou (2014), Robust and bias-corrected estimation of the coefficient of tail dependence, Volume 57, Insurance: Mathematics and Economics
This work was supported by a research grant (VKR023480) from VILLUM FONDEN and an international project for scientific cooperation (PICS-6416).
See fitRTDE
for the fitting process and
dataRTDE
for the data-handling process.
#####
# (1) simulation
n <- 100
x <- RTDE(simu=list(nb=n, marg="ufrechet", cop="indep", replicate=1),
nbpoint=10:11, alpha=0, omega=1/2)
x
summary(x)
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