Computes the estimator for the scale parameter as described in Beirlant et al. (2016).
Scale(data, gamma =NULL, logk =FALSE, plot =FALSE, add =FALSE, main ="Estimates of scale parameter",...)
Arguments
data: Vector of n observations.
gamma: Vector of n−1 estimates for the EVI. When NULL (the default value), Hill estimates are computed.
logk: Logical indicating if the estimates are plotted as a function of log(k) (logk=TRUE) or as a function of k. Default is FALSE.
plot: Logical indicating if the estimates should be plotted as a function of k, default is FALSE.
add: Logical indicating if the estimates should be added to an existing plot, default is FALSE.
main: Title for the plot, default is "Estimates of scale parameter".
...: Additional arguments for the plot function, see plot for more details.
Details
The scale estimates are computed based on the following model for the CDF: 1−F(x)=Ax−1/γ, where A:=C1/γ is the scale parameter:
A^k,n=(k+1)/(n+1)Xn−k,n1/Hk,n
where Hk,n are the Hill estimates.
See Section 4.2.1 of Albrecher et al. (2017) for more details.
Returns
A list with following components: - k: Vector of the values of the tail parameter k.
A: Vector of the corresponding scale estimates.
C: Vector of the corresponding estimates for C, see Details.
References
Albrecher, H., Beirlant, J. and Teugels, J. (2017). Reinsurance: Actuarial and Statistical Aspects, Wiley, Chichester.
Beirlant, J., Schoutens, W., De Spiegeleer, J., Reynkens, T. and Herrmann, K. (2016). "Hunting for Black Swans in the European Banking Sector Using Extreme Value Analysis." In: Jan Kallsen and Antonis Papapantoleon (eds.), Advanced Modelling in Mathematical Finance, Springer International Publishing, Switzerland, pp. 147--166.
Author(s)
Tom Reynkens
See Also
ScaleEPD, Scale.2o, Hill
Examples
data(secura)# Hill estimatorH <- Hill(secura$size)S <- Scale(secura$size, gamma=H$gamma, plot=FALSE)# Plot logarithm of scale plot(S$k,log(S$A), xlab="k", ylab="log(Scale)", type="l")