BALD (version 1.0.0-3)

meanExposureGrowth: A generic function to plot and/or return the posterior of the mean exposure growth for models in BALD.

Description

A generic function to plot and/or return the posterior of the mean exposure growth for models in BALD.

Arguments

object

The object from which to plot and/or return the mean exposure growth.

plotDensity

A logical value. If TRUE, the density is plotted. If plotTrace is also TRUE, then two plots are generated. If they are both FALSE, then only the statistics are returned.

plotTrace

A logical value. If TRUE, the trace is plotted. If plotDensity is also TRUE, then two plots are generated. If they are both FALSE, then only the statistics are returned.

Value

Mainly called for the side effect of plotting.

Details

(Optionally) exposure growth is modeled as an ar1 process. This inherently assumes that periods of high exposure growth are (or at least have the possibility of being) followed by continued high periods. See vignette('BALD').

See Also

meanExposureGrowth("AnnualAggLossDevModelOutput")

Examples

# NOT RUN {
rm(list=ls())
options(device.ask.default=FALSE)
library(BALD)
data(IncrementalGeneralLiablityTriangle)
IncrementalGeneralLiablityTriangle <- as.matrix(IncrementalGeneralLiablityTriangle)
print(IncrementalGeneralLiablityTriangle)
data(PCE)
PCE <- as.matrix(PCE)[,1]
PCE.rate <- PCE[-1] / PCE[-length(PCE)] - 1
PCE.rate.length <- length(PCE.rate)
PCE.years <- as.integer(names(PCE.rate))
years.available <- PCE.years <= max(as.integer(
dimnames(IncrementalGeneralLiablityTriangle)[[1]]))
PCE.rate <- PCE.rate[years.available]
PCE.rate.length <- length(PCE.rate)
standard.model.input <- makeStandardAnnualInput(
incremental.payments = IncrementalGeneralLiablityTriangle,
stoch.inflation.weight = 1,
non.stoch.inflation.weight = 0,
stoch.inflation.rate = PCE.rate,
exp.year.type = 'ay',
extra.dev.years=5,
use.skew.t=TRUE)
# }
# NOT RUN {
standard.model.output <- runLossDevModel(standard.model.input,
burnIn=30.0E+3,
sampleSize=30.0E+3,
thin=10)
meanExposureGrowth(standard.model.output)
# }