var.rwts: Variance of the rescaled weights when estimating the...

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

Description

Calculates the variance of the rescaled weights

Usage

var.rwts(w)

Arguments

w	A vector of importance weights corresponding to each row of the mixture of the prior and multivariate gaussian draws

Value

A scalar representing the variance of the rescaled weights

Note

Used in the final.resamp function

References

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.

See Also

final.resamp, hp.bm.imis

Examples

#Generate a vector of weights#
wts <- runif(100, 0, .99)
var.rwts(wts)

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