probablityOfPayment {BALD} | R Documentation |
A generic function to plot the probability of a payment.
object |
The object from which to plot the probability of a payment. |
plot |
A logical value. If |
Because the model is Bayesian, each estimated payment comes as a distribution.
The median of this distribution is used as a point estimate when plotting and/or returning values.
Note: Negative payments are treated as missing and are not accounted for.
See vignette('BALD')
.
Mainly called for the side effect of plotting. Also returns a matrix containing the (median) probably of payment. Returned invisibly.
rm(list=ls()) library(BALD) data(CumulativeAutoBodilyInjuryTriangle) CumulativeAutoBodilyInjuryTriangle <- as.matrix(CumulativeAutoBodilyInjuryTriangle) sample.col <- (dim(CumulativeAutoBodilyInjuryTriangle)[2] - 6:0) print(decumulate(CumulativeAutoBodilyInjuryTriangle)[1:7, sample.col]) data(HPCE) HPCE <- as.matrix(HPCE)[,1] HPCE.rate <- HPCE[-1] / HPCE[-length(HPCE)] - 1 print(HPCE.rate[(-10):0 + length(HPCE.rate)]) HPCE.years <- as.integer(names(HPCE.rate)) max.exp.year <- max(as.integer( dimnames(CumulativeAutoBodilyInjuryTriangle)[[1]])) years.to.keep <- HPCE.years <= max.exp.year + 3 HPCE.rate <- HPCE.rate[years.to.keep] break.model.input <- makeBreakAnnualInput( cumulative.payments = CumulativeAutoBodilyInjuryTriangle, stoch.inflation.weight = 1, non.stoch.inflation.weight = 0, stoch.inflation.rate = HPCE.rate, first.year.in.new.regime = c(1986, 1987), prior.for.first.year.in.new.regime=c(2,1), exp.year.type = 'ay', extra.dev.years = 5, use.skew.t = TRUE, bound.for.skewness.parameter=5) ## Not run: break.model.output <- runLossDevModel( break.model.input, burnIn=30.0E+3, sampleSize=30.0E+3, thin=10) break.model.output.w.zeros <- accountForZeroPayments(break.model.output) probablityOfPayment(break.model.output.w.zeros) ## End(Not run)