BALD (version 1.0.0-3)

mcmcACF: A generic function to plot autocorrelations found in the MCMC samples for select parameters.

Description

A generic function to plot autocorrelations found in the MCMC samples for select parameters.

Arguments

object

The object from which to plot autocorrelations.

Value

Called for the side effect of plotting.

Details

Chains with high autocorrelation require a longer burnin and more samples to fully explore the parameter space. See vignette('BALD').

See Also

mcmcACF("StandardAnnualAggLossDevModelOutput") mcmcACF("BreakAnnualAggLossDevModelOutput")

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)
mcmcACF(standard.model.output)
# }