degreesOfFreedom: A generic function to plot and/or return the posterior of the...

In BALD: Robust Loss Development Using MCMC

Description

A generic function to plot and/or return the posterior of the degrees of freedom for the Student-t in models in BALD.

Arguments

object	The object from which to plot and/or return the degrees of freedom.
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.

Details

When there is zero skew, the degrees of freedom are the degrees of freedom for the non-skewed t. See vignette('BALD').

Value

Mainly called for the side effect of plotting.

References

Kim, Y., and J. McCulloch (2007) “The Skew-Student Distribution with Application to U.S. Stock Market Returns and the Equity Premium,” Department of Economics, Ohio State University, October 2007.

See Also

degreesOfFreedom("AnnualAggLossDevModelOutput")

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)
degreesOfFreedom(standard.model.output)

## End(Not run)

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