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DGA

Performs capture-recapture estimation by averaging over decomposablegraphical models. This implements the approach introduced in Madigan andYork (1997).

Installation

Stable CRAN release:

install.packages("dga")

Example usage

Five lists example from Madigan and York (1997):

library(dga)# Number of lists and prior hyperparameterp<-5data(graphs5)# Decomposable graphical models on 5 lists.delta<-0.5Nmissing<-1:300# Reasonable range for the number of unobserved individuals.# Counts corresponding to list inclusion patterns.Y<-c(0,27,37,19,4,4,1,1,97,22,37,25,2,1,3,5,83,36,34,18,3,5,0,2,30,5,23,8,0,3,0,2)Y<-array(Y,dim=c(2,2,2,2,2))N<-sum(Y)+ Nmissing# Model-wise posterior probaiblities on the total population size.# weights[i,j] is the posterior probability for j missing individuals under model graphs5[[j]].weights<-bma.cr(Y,  Nmissing, delta, graphs5)# Plot of the posterior distribution.plotPosteriorN(weights, N)

References

• David Madigan and Jeremy C. York. “Bayesian methods for estimationof the size of a closed population.”Biometrika. Vol. 84, No. 1(Mar., 1997), pp. 19-31.
• Mauricio Sadinle (2018) Bayesian propagation of record linkageuncertainty into population size estimation of human rights violations.Annals of Applied Statistics Vol. 12 No. 2 pp. 1013-1038

Written by James Johndrow, Kristian Lum, and Patrick Ball.

copyright (c) 2015 Human Rights Data Analysis Group (HRDAG)https://hrdag.org