论文信息 - Data fusion and data grafting

Data fusion and data grafting

Data fusion is concerned with the problem of merging data bases coming from different sources into a single data base when variables are absent or missing in some files. After a survey of the main techniques, we present some new approaches, in particular one based on homogeneity analysis and future directions. We insist on validation problems and caveats.

Gilbert Saporta | G. Saporta

[1] M. Hill,et al. Nonlinear Multivariate Analysis. , 1990 .

[2] Jan de Leeuw,et al. Canonical analysis of categorical data , 1984 .

[3] Roderick J. A. Little,et al. Statistical Analysis with Missing Data , 1988 .

[4] Weila Vila Gu Co. Méthodes statistiques et informatiques pour le traitement des données manquantes. (Statistical and computing methods for the processing of missing data) , 1997 .

[5] Stef van Buuren,et al. Imputation of missing categorical data by maximizing internal consistency , 1992 .

[6] D. Rubin,et al. Multiple Imputation for Nonresponse in Surveys , 1989 .

[7] Gilbert Saporta,et al. Fusion de fichiers : une nouvelle méthode basée sur l'analyse homogène , 1999 .

[8] Ken Baker,et al. Data Fusion: An Appraisal and Experimental Evaluation , 1997 .

[9] Brian Everitt,et al. Homogeneity analysis of incomplete data , 1986 .