R: Project Code - Nonparametric Bayes

# Project Code - Nonparametric Bayes

## Documentation for package ‘nonparametric.bayes’ version 0.0.1

- DESCRIPTION file
- Package README

## Help Pages

cluster_datapoints | Gibbs sampling for the Chinese Restaurant Process Implementation details can be found in the associated paper The algorithm stops at every 1000th iteration and prints the current cluster configuration.
generate_dirichlet_clusters | Draws from a Dirichlet distribution and shows the clusters that were generated by this draw. Varying alpha, will put more or less mass in the first clusters compared to higher clusters (rhos).
generate_dirichlet_clusters_with_sampled_points | Draws from a Dirichlet distribution and shows the clusters that were generated by this draw. Additionally, adds points to these clusters and shows which clusters are occupied
generate_split_data | Generates a dataset used to exemplify clustering The cluster centers are set relatively far away to see how well the algorithm performs in simple scenarios
rdirichlet | Generate a sample from a Dirichlet distirbution Using: https://en.wikipedia.org/wiki/Dirichlet_distribution#Random_number_generation
rDPM | Sequentially generate draws from a Dirichlet process mixture model, by showing step by step the iterations taken. The plot is centered at 0, with x and y from -5 to 5. The mixture draws the centres for clusters from a Normal distribution with mean mu and standard deviation sigma_0 Additional to plotting the points, it also returns the points sampled.
rDPM_visual | Sequentially generate draws from a Dirichlet process mixture model, by showing step by step the iterations taken. The plot is centered at 0, with x and y from -5 to 5. The mixture draws the centres for clusters from a Normal distribution with mean mu and standard deviation sigma_0