Man pages for rMIDAS
Multiple Imputation with Denoising Autoencoders

add_bin_labelsReverse numeric conversion of binary vector
add_missingnessApply MAR missingness to data
coalesce_one_hotCoalesce one-hot encoding back to a single variable
col_minmaxScale numeric vector between 0 and 1
combineEstimate and combine regression models from multiply-imputed...
completeImpute missing values using imputation model
convertPre-process data for Midas imputation
import_midasInstantiate Midas class
midas_setupManually set up Python connection
mid_py_setupConfigure python for MIDAS imputation
na_to_nanReplace NA missing values with NaN
overimputePerform overimputation diagnostic test
python_initInitialise connection to Python
set_python_envManually select python binary
skip_if_no_numpySkip test where 'numpy' not available.
trainTrain an imputation model using Midas
undo_minmaxReverse minmax scaling of numeric vector
rMIDAS documentation built on Jan. 30, 2021, 9:05 a.m.