Moment | R Documentation |
Compute the moment estimates for real extreme value indices as a function of the tail parameter k
. Optionally, these estimates are plotted as a function of k
.
Moment(data, logk = FALSE, plot = FALSE, add = FALSE,
main = "Moment estimates of the EVI", ...)
data |
Vector of |
logk |
Logical indicating if the estimates are plotted as a function of |
plot |
Logical indicating if the estimates should be plotted as a function of |
add |
Logical indicating if the estimates should be added to an existing plot, default is |
main |
Title for the plot, default is |
... |
Additional arguments for the |
The moment estimator for the EVI is introduced by Dekkers et al. (1989) and is a generalisation of the Hill estimator.
See Section 4.2.2 of Albrecher et al. (2017) for more details.
A list with following components:
k |
Vector of the values of the tail parameter |
gamma |
Vector of the corresponding moment estimates. |
Tom Reynkens based on S-Plus
code from Yuri Goegebeur.
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.
Dekkers, A.L.M, Einmahl, J.H.J. and de Haan, L. (1989). "A Moment Estimator for the Index of an Extreme-value Distribution." Annals of Statistics, 17, 1833–1855.
Hill
, genHill
data(soa)
# Hill estimator
H <- Hill(soa$size, plot=FALSE)
# Moment estimator
M <- Moment(soa$size)
# Generalised Hill estimator
gH <- genHill(soa$size, gamma=H$gamma)
# Plot estimates
plot(H$k[1:5000], M$gamma[1:5000], xlab="k", ylab=expression(gamma), type="l", ylim=c(0.2,0.5))
lines(H$k[1:5000], gH$gamma[1:5000], lty=2)
legend("topright", c("Moment", "Generalised Hill"), lty=1:2)
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