| ProbGPD {ReIns} | R Documentation | 
Estimator of small exceedance probabilities and large return periods using GPD-MLE
Description
Computes estimates of a small exceedance probability P(X>q) or large return period 1/P(X>q) using the GPD fit for the peaks over a threshold.
Usage
ProbGPD(data, gamma, sigma, q, plot = FALSE, add = FALSE, 
        main = "Estimates of small exceedance probability", ...)
ReturnGPD(data, gamma, sigma, q, plot = FALSE, add = FALSE, 
          main = "Estimates of large return period", ...)
Arguments
| data | Vector of  | 
| gamma | Vector of  | 
| sigma | Vector of  | 
| q | The used large quantile (we estimate  | 
| 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  | 
Details
See Section 4.2.2 in Albrecher et al. (2017) for more details.
Value
A list with following components:
| k | Vector of the values of the tail parameter  | 
| P | Vector of the corresponding probability estimates, only returned for  | 
| R | Vector of the corresponding estimates for the return period, only returned for  | 
| q | The used large quantile. | 
Author(s)
Tom Reynkens.
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.
See Also
Examples
data(soa)
# Look at last 500 observations of SOA data
SOAdata <- sort(soa$size)[length(soa$size)-(0:499)]
# GPD-ML estimator
pot <- GPDmle(SOAdata)
# Exceedance probability
q <- 10^7
ProbGPD(SOAdata, gamma=pot$gamma, sigma=pot$sigma, q=q, plot=TRUE)
# Return period
q <- 10^7
ReturnGPD(SOAdata, gamma=pot$gamma, sigma=pot$sigma, q=q, plot=TRUE)