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