GR_crit                 Gelman-Rubin criterion for convergence
JointAI                 JointAI: Joint Analysis and Imputation of
                        Incomplete Data
JointAIObject           Fitted object of class 'JointAI'
MC_error                Calculate and plot the Monte Carlo error
NHANES                  National Health and Nutrition Examination
                        Survey (NHANES) Data
PBC                     PBC data
add_samples             Continue sampling from an object of class
                        JointAI
clean_survname          Convert a survival outcome to a model name
default_hyperpars       Get the default values for hyper-parameters
densplot                Plot the posterior density from object of class
                        JointAI
extract_state           Return the current state of a 'JointAI' model
get_MIdat               Extract multiple imputed datasets from an
                        object of class JointAI
get_missinfo            Obtain a summary of the missing values involved
                        in an object of class JointAI
list_models             List model details
longDF                  Longitudinal example dataset
md_pattern              Missing data pattern
model_imp               Joint Analysis and Imputation of incomplete
                        data
parameters              Parameter names of an JointAI object
plot.JointAI            Plot an object object inheriting from class
                        'JointAI'
plot_all                Visualize the distribution of all variables in
                        the dataset
plot_imp_distr          Plot the distribution of observed and imputed
                        values
predict.JointAI         Predict values from an object of class JointAI
print.Dmat              Summarize the results from an object of class
                        JointAI
rd_vcov                 Extract the random effects variance covariance
                        matrix Returns the posterior mean of the
                        variance-covariance matrix/matrices of the
                        random effects in a fitted JointAI object.
residuals.JointAI       Extract residuals from an object of class
                        JointAI
set_refcat              Specify reference categories for all
                        categorical covariates in the model
sharedParams            Parameters used by several functions in JointAI
simLong                 Simulated Longitudinal Data in Long and Wide
                        Format
sum_duration            Calculate the sum of the computational duration
                        of a JointAI object
traceplot               Create traceplots for a MCMC sample
wideDF                  Cross-sectional example dataset
