Learn from Training Data then Quickly Fill in Missing Data

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' < http://gking.harvard.edu/amelia/> but is much faster when filling in values for a single line of data.


Reference manual

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2.0 by Stephen R. Haptonstahl, 2 years ago

Browse source code at https://github.com/cran/FastImputation

Authors: Stephen R. Haptonstahl

Documentation:   PDF Manual  

Task views:

GPL (>= 2) license

Imports methods, Matrix

Suggests testthat, caret, e1071

See at CRAN