Applications of bayesian networks in official statistics

Abstract

In this paper recent results about the application of Bayesian networks to official statistics are presented. Bayesian networks are multivariate statistical models able to represent and manage complex dependence structures. Here they are proposed as a useful and unique framework by which it is possible to deal with many problems typical of survey data analysis. In particular here we focus on categorical variables and show how to derive classes of contingency table estimators in case of stratified sampling designs. Having this technology poststratification, integration and missing data imputation become possible. Furthermore we briefly discuss how to use Bayesian networks for decision as a support system to monitor and manage the data production process.