| trTestMLE {ReIns} | R Documentation |
Test for truncated GPD tails
Description
Test between non-truncated GPD tails (light truncation) and truncated GPD tails (rough truncation).
Usage
trTestMLE(data, gamma, tau, alpha = 0.05, plot = TRUE, main = "Test for truncation", ...)
Arguments
data |
Vector of |
gamma |
Vector of |
tau |
Vector of |
alpha |
The used significance level, default is |
plot |
Logical indicating if the P-values should be plotted as a function of |
main |
Title for the plot, default is |
... |
Additional arguments for the |
Details
We want to test
H_0: X has non-truncated GPD tails vs.
H_1: X has truncated GPD tails.
Let \hat{\gamma}_k and \hat{\tau}_k be the truncated MLE estimates for \gamma and \tau.
The test statistic is then
T_{k,n}=k (1+\hat{\tau} (X_{n,n}-X_{-k,n}) )^{-1/\hat{\xi}_k}
which is asymptotically standard exponentially distributed.
We reject H_0 on level \alpha if
T_{k,n}>\ln (1/{\alpha)}. The corresponding P-value is given by
\exp(-T_{k,n}).
See Beirlant et al. (2017) for more details.
Value
A list with following components:
k |
Vector of the values of the tail parameter |
testVal |
Corresponding test values. |
critVal |
Critical value used for the test, i.e. |
Pval |
Corresponding P-values. |
Reject |
Logical vector indicating if the null hypothesis is rejected for a certain value of |
Author(s)
Tom Reynkens.
References
Beirlant, J., Fraga Alves, M. I. and Reynkens, T. (2017). "Fitting Tails Affected by Truncation". Electronic Journal of Statistics, 11(1), 2026–2065.
See Also
trMLE, trDTMLE, trProbMLE, trEndpointMLE, trTestMLE, trTest
Examples
# Sample from GPD truncated at 99% quantile
gamma <- 0.5
sigma <- 1.5
X <- rtgpd(n=250, gamma=gamma, sigma=sigma, endpoint=qgpd(0.99, gamma=gamma, sigma=sigma))
# Truncated ML estimator
trmle <- trMLE(X, plot=TRUE, ylim=c(0,2))
# Test for truncation
trTestMLE(X, gamma=trmle$gamma, tau=trmle$tau)