EVT fit
Create an S3 object using an EVT (Extreme Value Theory) fit.
EVTfit(gamma, endpoint = NULL, sigma = NULL)
gamma |
Vector of estimates for γ. |
endpoint |
Vector of endpoints (with the same length as |
sigma |
Vector of scale estimates for the GPD (with the same length as |
See Reynkens et al. (2017) and Section 4.3 of Albrecher et al. (2017) for details.
An S3 object containing the above input arguments.
Tom Reynkens
Albrecher, H., Beirlant, J. and Teugels, J. (2017). Reinsurance: Actuarial and Statistical Aspects, Wiley, Chichester.
Reynkens, T., Verbelen, R., Beirlant, J. and Antonio, K. (2017). "Modelling Censored Losses Using Splicing: a Global Fit Strategy With Mixed Erlang and Extreme Value Distributions". Insurance: Mathematics and Economics, 77, 65–77.
# Create MEfit object
mefit <- MEfit(p=c(0.65,0.35), shape=c(39,58), theta=16.19, M=2)
# Create EVTfit object
evtfit <- EVTfit(gamma=c(0.76,0.64), endpoint=c(39096, Inf))
# Create SpliceFit object
splicefit <- SpliceFit(const=c(0.5,0.996), trunclower=0, t=c(1020,39096), type=c("ME","TPa","Pa"),
MEfit=mefit, EVTfit=evtfit)
# Show summary
summary(splicefit)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.