Generalized Efficient Regression-Based Imputation with Latent Processes
Correlation Analysis for gerbil Objects
General Efficient Regression-Based Imputation with Latent processes
Goodness-of-fit testing for gerbil objects
Extracting imputed datasets from gerbil objects
Plotting for gerbil objects
Prints a cor_gerbil object. Printed output includes the average diff...
Prints a gerbil object. Printed output includes a variable-by-variab...
Prints a gof_gerbil object. Printed output pertains to the goodness-...
Summarises a gerbil object. Printed output includes a variable-by-va...
Summarises a gerbil object. Printed output includes a variable-by-va...
Summarises a gerbil object. Printed output pertains to the goodness-...
Write imputed datasets from gerbil objects to a file or files
Implements a new multiple imputation method that draws imputations from a latent joint multivariate normal model which underpins generally structured data. This model is constructed using a sequence of flexible conditional linear models that enables the resulting procedure to be efficiently implemented on high dimensional datasets in practice. See Robbins (2021) <arXiv:2008.02243>.