R: Fitting Shared Atoms Nested Models via Variational Bayes

# Fitting Shared Atoms Nested Models via Variational Bayes

## Documentation for package ‘SANvi’ version 0.1.1

- DESCRIPTION file
- Package NEWS
- Package README

## Help Pages

estimate_atoms_weights_vi | Estimate the Posterior Atoms and Weights of the Discrete Mixing Distributions
estimate_clustering_vi | Estimate Posterior Clustering Assignments
extract_best | Extract the best run from multiple trials
plot.multistart | Perform variational inference using multiple starting points.
plot.SANvb | Plotting the variational inference output
plot.vi_atoms_weights | Estimate the Posterior Atoms and Weights of the Discrete Mixing Distributions
plot.vi_clustering | Estimate Posterior Clustering Assignments
print.multistart | Perform variational inference using multiple starting points.
print.SANvb | Print variational inference output
print.vi_atoms_weights | Estimate the Posterior Atoms and Weights of the Discrete Mixing Distributions
print.vi_clustering | Estimate Posterior Clustering Assignments
variational_CAM | Mean Field Variational Bayes estimation of CAM
variational_fiSAN | Mean Field Variational Bayes estimation of fiSAN
variational_fSAN | Mean Field Variational Bayes estimation of fSAN
variational_multistart | Perform variational inference using multiple starting points.