Truncation odds
Estimates of truncation odds of the truncated probability mass under the untruncated distribution using truncated Hill.
trDT(data, r = 1, gamma, plot = FALSE, add = FALSE, main = "Estimates of DT", ...)
data
: Vector of observations.r
: Trimming parameter, default is 1
(no trimming).gamma
: Vector of estimates for the EVI obtained from trHill
.plot
: Logical indicating if the estimates of should be plotted as a function of , default is FALSE
.add
: Logical indicating if the estimates of should be added to an existing plot, default is FALSE
.main
: Title for the plot, default is "Estimates of DT"
....
: Additional arguments for the plot
function, see plot
for more details.The truncation odds is defined as
with the upper truncation point and the CDF of the untruncated distribution (e.g. Pareto distribution).
We estimate this truncation odds as
with .
See Beirlant et al. (2016) or Section 4.2.3 of Albrecher et al. (2017) for more details.
A list with following components: - k: Vector of the values of the tail parameter .
Albrecher, H., Beirlant, J. and Teugels, J. (2017). Reinsurance: Actuarial and Statistical Aspects, Wiley, Chichester.
Beirlant, J., Fraga Alves, M.I. and Gomes, M.I. (2016). "Tail fitting for Truncated and Non-truncated Pareto-type Distributions." Extremes, 19, 429--462.
Tom Reynkens based on R
code of Dries Cornilly.
trHill
, trEndpoint
, trQuant
, trDTMLE
# Sample from truncated Pareto distribution. # truncated at 99% quantile shape <- 2 X <- rtpareto(n=1000, shape=shape, endpoint=qpareto(0.99, shape=shape)) # Truncated Hill estimator trh <- trHill(X, plot=TRUE, ylim=c(0,2)) dt <- trDT(X, gamma=trh$gamma, plot=TRUE, ylim=c(0,0.05))