Simultaneous Edit-Imputation for Continuous Microdata

An integrated editing and imputation method for continuous microdata under linear constraints is implemented. It relies on a Bayesian nonparametric hierarchical modeling approach as described in Kim et al. (2015) . In this approach, the joint distribution of the data is estimated by a flexible joint probability model. The generated edit-imputed data are guaranteed to satisfy all imposed edit rules, whose types include ratio edits, balance edits and range restrictions.


Reference manual

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1.1.6 by Hang J. Kim, a year ago

Browse source code at

Authors: Quanli Wang , Hang J. Kim , Jerome P. Reiter , Lawrence H. Cox and Alan F. Karr

Documentation:   PDF Manual  

Task views: Missing Data

GPL (>= 3) license

Depends on Rcpp, methods, editrules, graphics, utils, igraph

Linking to Rcpp

See at CRAN