Mixed Erlang fit
Create an S3 object using a Mixed Erlang (ME) fit.
MEfit(p, shape, theta, M, M_initial = NULL)
p |
Vector of mixing weights, denoted by α in Verbelen et al. (2015). |
shape |
Vector of shape parameters r. |
theta |
Scale parameter θ. |
M |
Number of mixture components. |
M_initial |
Initial value provided for |
The rate parameter λ used in Albrecher et al. (2017) is equal to 1/θ.
See Reynkens et al. (2017) and Section 4.3 of Albrecher et al. (2017) for more details
An S3 object which contains the input arguments in a list.
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.
Verbelen, R., Gong, L., Antonio, K., Badescu, A. and Lin, S. (2015). "Fitting Mixtures of Erlangs to Censored and Truncated Data Using the EM Algorithm." Astin Bulletin, 45, 729–758
# 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.