Description Usage Arguments Value Author(s) References See Also Examples

View source: R/TrainFastImputation.R

Like Amelia, FastImputation assumes that the columns of the data are multivariate normal or can be transformed into approximately multivariate normal.

1 | ```
TrainFastImputation(x, constraints = list(), idvars, categorical)
``` |

`x` |
Dataframe containing training data. Can have incomplete rows. |

`constraints` |
A list of constraints. See the examples below for formatting details. |

`idvars` |
A vector of column numbers or column names to be ignored in the imputation process. |

`categorical` |
A vector of column numbers or column names of varaibles with a (small) set of possible values. |

An object of class 'FastImputationPatterns' that contains information needed later to impute on a single row.

Stephen R. Haptonstahl srh@haptonstahl.org

https://gking.harvard.edu/amelia

1 2 3 4 5 6 7 8 9 10 11 | ```
data(FI_train) # provides FI_train dataset
patterns_with_constraints <- TrainFastImputation(
FI_train,
constraints=list(list("bounded_below_2", list(lower=0)),
list("bounded_above_5", list(upper=0)),
list("bounded_above_and_below_6", list(lower=0, upper=1))
),
idvars="user_id_1",
categorical="categorical_9")
``` |

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