Learn from Training Data then Quickly Fill in Missing Data R package FastImputation version 2.2.1 CRAN Task View: MissingData (https://CRAN.R-project.org/view=MissingData) 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. Software Depends: R (>= 4.0) Imports: methods, Matrix Suggests: testthat, caret, e1071 Stephen R. Haptonstahl <srh@haptonstahl.org> Comprehensive R Archive Network (CRAN) Stephen R. Haptonstahl GPL (>= 2) 2023-09-25 application/tgz https://CRAN.R-project.org/package=FastImputation doi:10.32614/CRAN.package.FastImputation