BALD (version 1.0.0-3)

stochasticInflationStationaryMean: A generic function to plot and/or return the posterior of the stochastic inflation stationary mean for models in BALD.

Description

A generic function to plot and/or return the posterior of the stochastic inflation stationary mean for models in BALD.

Arguments

object

The object from which to plot and/or return the stochastic inflation stationary mean.

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

If the model incorporates a stochastic rate of inflation, then that rate is assumed to follow (on the log scale) an autoregressive process of order 1. (The autoregressive process of order 1 is the discrete equivalent to an Ornstein-Uhlenbeck process.) This function plots the posterior for the stationary mean (on the log scale), assuming such a mean was estimated. See vignette('BALD').

See Also

stochasticInflationStationaryMean("AnnualAggLossDevModelOutput") stochasticInflationRhoParameter stochasticInflation

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)
stochasticInflationStationaryMean(standard.model.output)
# }