FastImputation: Learn from Training Data then Quickly Fill in Missing Data
Version 2.0

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.

Getting started

Package details

AuthorStephen R. Haptonstahl
Date of publication2017-03-12 09:02:10
MaintainerStephen R. Haptonstahl <[email protected]>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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FastImputation documentation built on May 29, 2017, 2:20 p.m.