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EBTailIndex | R Documentation |
Computes a point estimate of the tail index based on the Expectile Based (EB) estimator.
EBTailIndex(data, tau, est=NULL)
data |
A vector of |
tau |
A real in |
est |
A real specifying the estimate of the expectile at the intermediate level |
For a dataset data
of sample size n
, the tail index \gamma
of its (marginal) distribution is estimated using the EB estimator:
\hat{\gamma}_n^E =\left(1+\frac{\hat{\bar{F}}_n(\tilde{\xi}_{\tau_n})}{1-\tau_n}\right)^{-1}
,
where \hat{\bar{F}}_n
is the empirical survival function of the observations, \tilde{\xi}_{\tau_n}
is an estimate of the \tau_n
-th expectile.
The observations can be either independent or temporal dependent. See Padoan and Stupfler (2020) and Daouia et al. (2018) for details.
The so-called intermediate level tau
or \tau_n
is a sequence of positive reals such that \tau_n \to 1
as n \to \infty
. Practically, \tau_n \in (0,1)
is the ratio between the empirical mean distance of the \tau_n
-th expectile from the smaller observations and the empirical mean distance of of the \tau_n
-th expectile from all the observations. An estimate of \tau_n
-th expectile is computed and used in turn to estimate \gamma
.
The value est
, if provided, is meant to be an esitmate of the \tau_n
-th expectile which is used to estimate \gamma
. On the contrary, if est=NULL
, then the routine EBTailIndex
estimate first the \tau_n
-th expectile expectile and then use it to estimate \gamma
.
An estimate of the tain index \gamma
.
Simone Padoan, simone.padoan@unibocconi.it, https://faculty.unibocconi.it/simonepadoan/; Gilles Stupfler, gilles.stupfler@univ-angers.fr, https://math.univ-angers.fr/~stupfler/
Anthony C. Davison, Simone A. Padoan and Gilles Stupfler (2023). Tail Risk Inference via Expectiles in Heavy-Tailed Time Series, Journal of Business & Economic Statistics, 41(3) 876-889.
Daouia, A., Girard, S. and Stupfler, G. (2018). Estimation of tail risk based on extreme expectiles. Journal of the Royal Statistical Society: Series B, 80, 263-292.
HTailIndex, MomTailIndex, MLTailIndex,
# Tail index estimation based on the Expectile based estimator obtained with data
# simulated from an AR(1) with 1-dimensional Student-t distributed innovations
tsDist <- "studentT"
tsType <- "AR"
# parameter setting
corr <- 0.8
df <- 3
par <- c(corr, df)
# Big- small-blocks setting
bigBlock <- 65
smallblock <- 15
# Intermediate level (or sample tail probability 1-tau)
tau <- 0.97
# sample size
ndata <- 2500
# Simulates a sample from an AR(1) model with Student-t innovations
data <- rtimeseries(ndata, tsDist, tsType, par)
# tail index estimation
gammaHat <- EBTailIndex(data, tau)
gammaHat
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