genQQ {ReIns} | R Documentation |
Generalised quantile plot
Description
Computes the empirical quantiles of the UH scores of a data vector and the theoretical quantiles of the standard exponential distribution. These quantiles are then plotted in a generalised QQ-plot with the theoretical quantiles on the -axis and the empirical quantiles on the
-axis.
Usage
genQQ(data, gamma, plot = TRUE, main = "Generalised QQ-plot", ...)
generalizedQQ(data, gamma, plot = TRUE, main = "Generalised QQ-plot", ...)
Arguments
data |
Vector of |
gamma |
Vector of |
plot |
Logical indicating if the quantiles should be plotted in a generalised QQ-plot, default is |
main |
Title for the plot, default is |
... |
Additional arguments for the |
Details
The generalizedQQ
function is the same function but with a different name for compatibility with the old S-Plus
code.
The UH scores are defined as with
the Hill estimates, but other positive estimates for the EVI can also be used. The appropriate positive estimates for the EVI need to be specified in
gamma
. The generalised QQ-plot then plots
for .
See Section 4.2.2 of Albrecher et al. (2017) for more details.
Value
A list with following components:
gqq.the |
Vector of the theoretical quantiles from a standard exponential distribution. |
gqq.emp |
Vector of the empirical quantiles from the logarithm of the UH scores. |
Author(s)
Tom Reynkens based on S-Plus
code from Yuri Goegebeur.
References
Albrecher, H., Beirlant, J. and Teugels, J. (2017). Reinsurance: Actuarial and Statistical Aspects, Wiley, Chichester.
Beirlant J., Goegebeur Y., Segers, J. and Teugels, J. (2004). Statistics of Extremes: Theory and Applications, Wiley Series in Probability, Wiley, Chichester.
Beirlant, J., Vynckier, P. and Teugels, J.L. (1996). "Excess Function and Estimation of the Extreme-value Index." Bernoulli, 2, 293–318.
See Also
Examples
data(soa)
# Compute Hill estimator
H <- Hill(soa$size[1:5000], plot=FALSE)$gamma
# Generalised QQ-plot
genQQ(soa$size[1:5000], gamma=H)