mcmcACF: A generic function to plot autocorrelations found in the MCMC...

Description Arguments Details Value See Also Examples

Description

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

Arguments

object

The object from which to plot autocorrelations.

Details

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

Value

Called for the side effect of plotting.

See Also

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

Examples

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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)

## End(Not run)

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

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