In this paper, we compare two imputation procedures based on Bayesian networks. One method imputes missing items of a variable taking advantage only on information of its parents, while the other takes advantage of its Markov blanket. A Monte Carlo evaluation is carried on a real data set.
Di Zio, M., Sacco, G., Scanu, M., Vicard, P. (2004). MULTIVARIATE TECHNIQUES FOR IMPUTATION BASED ON BAYESIAN NETWORKS. In Antoch J (a cura di), COMPSTAT - Proceedings in Computational Statistics (pp. 927-934). Heidelberg : Physica Verlag Heidelberg.
MULTIVARIATE TECHNIQUES FOR IMPUTATION BASED ON BAYESIAN NETWORKS
VICARD, Paola
2004-01-01
Abstract
In this paper, we compare two imputation procedures based on Bayesian networks. One method imputes missing items of a variable taking advantage only on information of its parents, while the other takes advantage of its Markov blanket. A Monte Carlo evaluation is carried on a real data set.File in questo prodotto:
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