trDT | R Documentation |
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 |
r |
Trimming parameter, default is |
gamma |
Vector of |
plot |
Logical indicating if the estimates of |
add |
Logical indicating if the estimates of |
main |
Title for the plot, default is |
... |
Additional arguments for the |
The truncation odds is defined as
D_T=(1-F(T))/F(T)
with T
the upper truncation point and F
the CDF of the untruncated distribution (e.g. Pareto distribution).
We estimate this truncation odds as
\hat{D}_T=\max\{ (k+1)/(n+1) ( R_{r,k,n}^{1/\gamma_k} - 1/(k+1) ) / (1-R_{r,k,n}^{1/\gamma_k}), 0\}
with R_{r,k,n} = X_{n-k,n} / X_{n-r+1,n}
.
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 |
DT |
Vector of the corresponding estimates for the truncation odds |
Tom Reynkens based on R
code of Dries Cornilly.
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.
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))
# Truncation odds
dt <- trDT(X, gamma=trh$gamma, plot=TRUE, ylim=c(0,0.05))
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