sizeestima {SizeEstimation}

Estimating the sizes of populations who inject drugs from multiple data sources using a Bayesian hierarchical model.

Description

This R package is for reproducing Bao L, Raftery A, Reddy A. (2015) Estimating the Sizes of Populations At Risk of HIV Infection From Multiple Data Sources Using a Bayesian Hierarchical Model, Statistics and Its Interface. This function develops an algorithm for presenting a Bayesian hierarchical model for estimating the sizes of drug injected populations in Bangladesh. The model incorporates multiple commonly used data sources including mapping data, surveys, interventions, capture-recapture data, estimates or guesstimates from organizations, and expert opinion. This function provides the posterior samples of burnin thin at-risk population sizes at the subnational level.

Usage

sizeestima(DATA, size, burnin, thin)

Arguments

DATA

dataset from Bangladesh which used in Bao L, Raftery A, Reddy A. (2015) Estimating the Sizez of Populations At Risk of HIV Infection From Multiple Data Sources Using a Bayesian Hierarchical Model, Statistics and Its Interface.

size

the number of iteration in MCMC algorithm.

burnin

the number of Burn-In in MCMC algorithm.

thin

keep every thin-th scan.

Details

This function runs MCMC algorithm for reproducing Bao L, Raftery A, Reddy A. (2015) Estimating the Sizez of Populations At Risk of HIV Infection From Multiple Data Sources Using a Bayesian Hierarchical Model, Statistics and Its Interface.

Value

A matrix of posterior samples of at-risk population sizes at the sub-national level, where the rows correspond to sub-national areas and the columns correspond to MCMC iterations.

Author(s)

Le Bao, Adrian E. Raftery, Kyongwon Kim

References

Bao L, Raftery A, Reddy A. (2015) Estimating the Sizes of Populations At Risk of HIV Infection From Multiple Data Sources Using a Bayesian Hierarchical Model, Statistics and Its Interface.

See Also

rtnorm rinvgamma dtnorm

Examples

#n.total=sizeestima(DATA,500000,501,100)