mcmcACF,StandardAnnualAggLossDevModelOutput-method

The object from which to plot autocorrelations.

object

A method to plot autocorrelations found in the <acronym>MCMC</acronym> samples for select parameters.

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

mcmcACF,StandardAnnualAggLossDevModelOutput-method function

Add option to plot other values. Currently only plots &#8220;First Rate Of Decay,&#8221; &#8220;First Calendar Year Effect Error,&#8221; and &#8220;First Exposure Year Growth.&#8221;

mcmcACF,StandardAnnualAggLossDevModelOutput-method: A method to plot autocorrelations found in the MCMC samples for select parameters.

Description

Arguments

Value

TODO

Details

See Also