Mauro Scanu
Affiliation:
Italian Statistical Institute - ISTAT
Department:
Department for Statistical Production and Technical-Scientific Co-ordination (DCET) - via Cesare Balbo 16, 00184 Roma
Position:
Researcher
Telephone: 06 4673 2887
Fax: 06 4673 2972
E-Mail: scanu@istat.it
Research topics:
Graphical models for complex survey designs
Methods for the integration of two or more sample surveys/archives (record linkage, statistical matching)Methods for missing data imputation
List of publications:
- M. Fortini, B. Liseo, A. Nuccitelli, M. Scanu (2001) On Bayesian Record Linkage Research in Official Statistics
- L. Di Consiglio, M. Scanu (2001) Some results on asymptotics in adaptive cluster sampling Statistics and Probability Letters
- M. Scanu (2003) Metodi Statistici per il Record Linkage Istat - Metodi e Norme n. 16
- M. Di Zio, M. Scanu, L. Coppola, O. Luzi, A. Ponti (2004) Bayesian networks for imputation Journal of the Royal Statistical Society, A
- M. Ballin, M. Scanu, P. Vicard (2005) Propagazione dell’informazione nel campionamento da popolazioni finite: reti bayesiane e poststratificazione Metodi Statistici per l’Integrazione di Dati da Fonti Diverse (eds. Liseo B., Montanari G.E., Torelli N., casa editrice Franco Angeli)
- M. Di Zio, G. Sacco, M. Scanu, P. Vicard (2005) Multivariate techniques for imputation based on Bayesian networks Neural Network World
- M. D'Orazio, M. Di Zio, M. Scanu (2006) Statistical Matching: Theory and Practice Wiley, Chichester
- M. D'Orazio, M. Di Zio, M. Scanu (2006) Statistical Matching for Categorical Data: Displaying Uncertainty and Using Logical Constraints Journal of Official Statistics
- D. Marella, P.L. Conti, M. Scanu (2008) On the matching noise of some nonparametric imputation procedures Statistics and Probability Letters
Working papers
- M. Ballin, M. Scanu, P. Vicard (2005) Model assisted approaches to complex survey sampling from finite populations using Bayesian networks working paper n. 54, Università Roma Tre
- M. Ballin, M. Scanu, P. Vicard (2006) Paradata and Bayesian networks: a tool for monitoring and troubleshooting the data production process Working paper n. 66, Università Roma Tre