R: Analysis and Imputation of Categorical-Variable Datasets with Missing Values

# Analysis and Imputation of Categorical-Variable Datasets with Missing Values

## Documentation for package ‘cat’ version 0.0-9

- DESCRIPTION file

## Help Pages

belt | Data on driver injury and seat belt use
belt.frame | Data on driver injury and seat belt use
bipf | Bayesian Iterative Proportional Fitting (BIPF)
crimes | U.S. National Crime Survey
da.cat | Data Augmentation algorithm for incomplete categorical data
dabipf | Data augmentation-Bayesian IPF algorithm for incomplete categorical data
ecm.cat | ECM algorithm for incomplete categorical data
em.cat | EM algorithm for incomplete categorical data
imp.cat | Impute missing categorical data
ipf | Iterative Proportional Fitting
logpost.cat | Log-posterior density for incomplete categorical data
mda.cat | Monotone Data Augmentation algorithm for incomplete categorical data
mi.inference | Multiple imputation inference
older | Older people dataset
older.frame | Older people dataset
prelim.cat | Preliminary manipulations on incomplete categorical data
rngseed | Initialize random number generator seed