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) <doi:10.1080/01621459.2015.1040881>. 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.
|Depends:||Rcpp (≥ 0.11.5), methods, editrules, graphics, utils|
|Author:||Quanli Wang, Hang J. Kim, Jerome P. Reiter, Lawrence H. Cox and Alan F. Karr|
|Maintainer:||Quanli Wang <quanli at stat.duke.edu>|
|License:||GPL (≥ 3)|
|CRAN checks:||EditImputeCont results|
|Windows binaries:||r-devel: EditImputeCont_1.0.2.zip, r-release: EditImputeCont_1.0.2.zip, r-oldrel: EditImputeCont_1.0.2.zip|
|OS X Mavericks binaries:||r-release: EditImputeCont_1.0.2.tgz, r-oldrel: EditImputeCont_1.0.2.tgz|
|Old sources:||EditImputeCont archive|
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