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Create an S3 object using ME-Pa or ME-GPD splicing fit obtained from SpliceFitPareto
, SpliceFiticPareto
or
SpliceFitGPD
.
SpliceFit(const, trunclower, t, type, MEfit, EVTfit, loglik = NULL, IC = NULL)
An S3 object containing the above input arguments and values for const
.
A summary method is available.
Vector of splicing constants or a single splicing constant.
Lower truncation point.
Vector of splicing points or a single splicing point.
Vector of types of the distributions: "ME"
and then for each fitted EVT distribution: "Pa"
(Pareto), "TPa"
(truncated Pareto) or "GPD"
(GPD).
MEfit
object with details on the mixed Erlang fit.
EVTfit
object with details on the EVT fit.
Log-likelihood of the fitted model. When NULL
(default), not included in the object.
Information criteria of the fitted model. When NULL
(default), not included in the object.
This vector should have length 1, 2 or 3 when included.
Tom Reynkens
See Reynkens et al. (2017) and Section 4.3 in Albrecher et al. (2017) for details.
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
MEfit
, EVTfit
, SpliceFitPareto
, SpliceFiticPareto
, SpliceFitGPD
# 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)
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