TrainFastImputation() uses training data to describe a multivariate normal distribution that the data approximates or can be transformed into approximating and stores this information as an object of class 'FastImputationPatterns'. FastImputation() function uses this 'FastImputationPatterns' object to impute (make a good guess at) missing data in a single line or a whole data frame of data. This approximates the process used by 'Amelia' but is much faster when filling in values for a single line of data.

Documentation

Manual: FastImputation.pdf
Vignette: None available.

Maintainer: Stephen R. Haptonstahl <srh at haptonstahl.org>

Author(s): Stephen R. Haptonstahl

Install package and any missing dependencies by running this line in your R console:

install.packages("FastImputation")

Depends R (>= 2.10)
Imports methods, Matrix
Suggests testthat, caret, e1071
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Package FastImputation
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Version 2.0
Published 2017-03-12
License GPL (>= 2)
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NeedsCompilation no
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CRAN checks FastImputation check results
Package source FastImputation_2.0.tar.gz