Package: BaBooN
Version: 0.0-4
Date: 2010-12-20
Title: The Bayesian Bootstrap Predictive Mean Matching Package -
        Multiple and single imputation for discrete data
Author: Florian Meinfelder <florian.meinfelder@uni-bamberg.de>
Maintainer: Florian Meinfelder <florian.meinfelder@uni-bamberg.de>
Depends: R (>= 2.10.0), MASS, nnet
Description: The package contains two variants of Bayesian Bootstrap
        Predictive Mean Matching to multiply impute missing data. The
        first variant is a variable-by-variable imputation combining
        sequential regression and Predictive Mean Matching (PMM) that
        has been extended for unordered categorical data. The Bayesian
        Bootstrap allows for generating approximately proper multiple
        imputations. The second variant is also based on PMM, but the
        focus is on imputing several variables at the same time. The
        suggestion is to use this variant, if the missing-data pattern
        resembles a data fusion situation, or any other
        missing-by-design pattern, where several variables have
        identical missing-data patterns. Both variants can be run as
        'single imputation' versions, in case the analysis objective is
        of a purely descriptive nature.
License: GPL (>= 2)
URL: http://www.r-project.org
Packaged: 2011-01-06 17:11:54 UTC; Florian
Repository: CRAN
Date/Publication: 2011-01-06 20:10:17
