BALD (version 1.0.0-3)

standardDeviationVsDevelopmentTime: A generic function to plot and/or return the posterior estimated standard deviation by development year.

Description

A generic function to plot and/or return the posterior estimated standard deviation by development year.

Arguments

object

The object from which to plot and/or return the estimated standard deviation by development year.

plot

A logical value. If TRUE, the plot is generated and the statistics are returned; otherwise only the statistics are returned.

Value

Mainly called for the side effect of plotting.

Details

Aggregate loss development models in BALD allow for changes (by development year) in the measurement error around the log incremental payments. This is a generic function that allows for the retrieval and illustration of this standard deviation. See vignette('BALD').

See Also

standardDeviationVsDevelopmentTime("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)
standardDeviationVsDevelopmentTime(standard.model.output)
# }