In recent years, the growing availability of huge amounts of information, generated in every
sector at high speed and in a wide variety of forms and formats, is unprecedented. The …

This chapter is about an important tool in the data science workbench, Bayesian networks
(BNs). Data science is about generating information from a given data set using applications …

This work is about integrated analysis of data collected as official statistics with
administrative data from operational systems in order to increase the quality of information …

Dealing with incomplete data is a pervasive problem in statistical surveys. Bayesian
networks have been recently used in missing data imputation. In this research, we propose a …

In this article, Object-Oriented Bayesian Networks (OOBN) are proposed as a tool to model
measurement errors in a categorical variable due to respondent. A mixed measurement …

Numbers are not data and data analysis does not necessarily produce information and
knowledge. Statistics, data mining, and artificial intelligence are disciplines focused on …

In this paper we explore the possibility to use a particular class of models, known as
probabilistic expert systems, to define two classes of estimators of a contingency table in …

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 …

In this article, the quality of data produced by national statistical institutes and by
governmental institutions is considered. In particular, the problem of measurement error is …

Analyzing incomplete data for inferring the structure of gene regulatory networks (GRNs) is a
challenging task in bioinformatic. Bayesian network can be successfully used in this field. k …