Population size estimation from incomplete multisource lists: A Bayesian perspective on latent class modelling
04 Pubblicazione in atti di convegno
DI CECCO Davide, DI ZIO Marco, Liseo Brunero
We propose a capture–recapture model for estimating the size of a population of interest based on a set of administrative sources and/or surveys in the presence of out-of-scope units (false captures). Our Bayesian approach makes use of a certain class of log - linear models with a latent structure. We also address the presence of sources providing partial information implementing a Gibbs Sampler algorithm which generates from the posterior distribution of the population size in presence of missing data. The proposed method is applied to simulated data sets