The goal of statistical matching is the estimation of the joint distribution of variables not jointly observed in a sample survey but separately available from independent sample surveys. The lack of joint information on the variables of interest leads to uncertainty about the data generating model. In this paper we propose the use of Bayesian networks to deal with the statistical matching problem since they admit a recursive factorization of a joint distribution useful for evaluating the statistical matching uncertainty in the multivariate context.
Statistical matching by Bayesian Networks / Marella, Daniela; Vicard, Paola; Vitale, Vincenzina. - (2018), pp. 948-953. (Intervento presentato al convegno 49th SIS Scientific Meeting of the Italian Statistical Society tenutosi a Palermo).
Statistical matching by Bayesian Networks
daniela marella;paola vicard;vincenzina vitale
2018
Abstract
The goal of statistical matching is the estimation of the joint distribution of variables not jointly observed in a sample survey but separately available from independent sample surveys. The lack of joint information on the variables of interest leads to uncertainty about the data generating model. In this paper we propose the use of Bayesian networks to deal with the statistical matching problem since they admit a recursive factorization of a joint distribution useful for evaluating the statistical matching uncertainty in the multivariate context.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
