EVTfit: EVT fit

Description

Create an S3 object using an EVT (Extreme Value Theory) fit.

Usage

EVTfit(gamma, endpoint = NULL, sigma = NULL)

Value

An S3 object containing the above input arguments.

Arguments

gamma: Vector of estimates for \(\gamma\).
endpoint: Vector of endpoints (with the same length as gamma). When NULL (default), a vector containing Inf for each value of gamma will be used.
sigma: Vector of scale estimates for the GPD (with the same length as gamma). When NULL (default), not included in the object.

Author

Tom Reynkens

Details

See Reynkens et al. (2017) and Section 4.3 of Albrecher et al. (2017) for details.

References

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.

Examples

Run this code

# 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)

Run the code above in your browser using DataCamp Workspace