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

AuthorStephen R. Haptonstahl
Date of publication2016-06-28 08:25:34
MaintainerStephen R. Haptonstahl <srh@haptonstahl.org>
LicenseGPL (>= 2)
Version1.3.1

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Files in this package

FastImputation
FastImputation/inst
FastImputation/inst/CITATION
FastImputation/tests
FastImputation/tests/testthat.R
FastImputation/tests/testthat
FastImputation/tests/testthat/test_BoundNormalizedVariable.R
FastImputation/tests/testthat/test_CovarianceWithMissing.R
FastImputation/tests/testthat/test_NormalizeBoundedVariable.R
FastImputation/NAMESPACE
FastImputation/data
FastImputation/data/FItest.RData
FastImputation/data/FItrue.RData
FastImputation/data/FItrain.RData
FastImputation/R
FastImputation/R/LimitToSet.R FastImputation/R/CovarianceWithMissing.R FastImputation/R/TrainFastImputation.R FastImputation/R/NormalizeBoundedVariable.R FastImputation/R/BoundNormalizedVariable.R FastImputation/R/UnfactorColumns.R FastImputation/R/FastImputation.R
FastImputation/MD5
FastImputation/DESCRIPTION
FastImputation/man
FastImputation/man/UnfactorColumns.Rd FastImputation/man/FItest.Rd FastImputation/man/FItrue.Rd FastImputation/man/TrainFastImputation.Rd FastImputation/man/NormalizeBoundedVariable.Rd FastImputation/man/BoundNormalizedVariable.Rd FastImputation/man/FastImputation.Rd FastImputation/man/LimitToSet.Rd FastImputation/man/CovarianceWithMissing.Rd FastImputation/man/FItrain.Rd

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