Description Arguments Details Value See Also Examples
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.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 | 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)
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