calendarYearEffectErrorTracePlot: A generic function to generate the trace plots for select...

In BALD: Robust Loss Development Using MCMC

Description

A generic function to generate the trace plots for select calendar year effect errors.

Arguments

object	The object from which to generate the trace plots.
elements	A numeric vector indicating the elements for which to plot the trace. Valid values are 2 through the total number of exposure years(observed and forecast). If NULL, values are selected automatically.

Details

The calendar year effect is comprised of two components: 1) a prior expected value that may be unique to every cell and 2) a diagonal-specific error term. This function generates trace plots for the diagonal specific error terms only. See vignette('BALD').

Value

NULL invisibly. Only called for the side effect of plotting.

See Also

calendarYearEffectErrorTracePlot("AnnualAggLossDevModelOutput") calendarYearEffectErrors

Examples

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)
calendarYearEffectErrorTracePlot(standard.model.output)

## End(Not run)

BALD documentation built on May 2, 2019, 6:51 a.m.