prior.form: Heligman-Pollard parameter prior formation

In HPbayes: Heligman Pollard mortality model parameter estimation using Bayesian Melding with Incremental Mixture Importance Sampling

Description

Draws from a uniform distribution with bounds pri.lo and pri.hi to create the prior distribution of the Heligman-Pollard parameters necessary for the Bayesian Melding procedure

Usage

prior.form(pri.lo = c(0, 0, 0, 0, 0, 15, 0, 0), 
pri.hi = c(0.15, 1, 1, 0.25, 15, 55, 0.1, 1.25), theta.dim = 8)

Arguments

pri.lo	Lower bound of the uniform from which the prior is drawn. Defaults to pri.lo = c(0, 0, 0, 0, 0, 15, 0, 0)
pri.hi	Upper bound of the uniform from which the prior is drawn. Defaults to pri.hi = c(0.15, 1, 1, 0.25, 15, 55, 0.1, 1.25)
theta.dim	The number of parameters to be estimated. Defaults to 8

Value

A (1000*theta.dim) x theta.dim matrix containing the 1000*theta.dim sets of the Heligman-Pollard parameters drawn from a uniform distribution

References

Heligman, Larry and John H. Pollard. 1980 "The Age Pattern of Mortality." Journal of the Institute of Actuaries 107:49–80.

Poole, David and Adrian Raftery. 2000. "Inference for Deterministic Simulation Models: The Bayesian Melding Approach." Journal of the American Statistical Association 95:1244–1255.

Raftery, Adrian and Le Bao. 2009. "Estimating and Projecting Trends in HIV/AIDS Gen- eralized Epidemics Using Incremental Mixture Importance Sampling." Technical Report 560, Department of Statistics, University of Washington.

Examples

q0 <- prior.form()

HPbayes documentation built on May 2, 2019, 5:53 a.m.