stochasticInflationStationaryMean,AnnualAggLossDevModelOutput-method

The object of type <code>AnnualAggLossDevModelOuput</code> from which to plot and/or return the stochastic inflation stationary mean.

object

A logical value. If <code>TRUE</code>, the density is plotted. If <code>plotTrace</code> is also <code>TRUE</code>, then two plots are generated. If they are both <code>FALSE</code>, then only the statistics are returned.

plotDensity

A logical value. If <code>TRUE</code>, the trace is plotted. If <code>plotDensity</code> is also <code>TRUE</code>, then two plots are generated. If they are both <code>FALSE</code>, then only the statistics are returned.

plotTrace

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

Bayesian analysis of loss development on insurance triangles or 'BALD' is a Bayesian model of developing aggregate loss triangles in property casualty insurance. This actuarial model makes use of a heteroskedastic and skewed t-likelihood with endogenous degrees of freedom, employs model averaging by means of Reversible Jump MCMC, and accommodates a structural break in the path of the consumption of benefits. Further, the model is capable of incorporating expert information in the calendar year effect. In an accompanying vignette, this model is applied to two widely studied General Liability and Auto Bodily Injury Liability loss triangles. For a description of the methodology, see Frank A. Schmid (2010) <doi:10.2139/ssrn.1501706>.

Can Wang

BALD

Robust Loss Development Using MCMC

stochasticInflationStationaryMean,AnnualAggLossDevModelOutput-method function

A method to plot and/or return the posterior of the stochastic inflation stationary mean for models in BALD. — stochasticInflationStationaryMean,AnnualAggLossDevModelOutput-method

stochasticInflationStationaryMean,AnnualAggLossDevModelOutput-method: A method to plot and/or return the posterior of the stochastic inflation stationary mean for models in BALD.

Description

Arguments

Value

See Also