//! Bayesian Nonparametric methods for scirs2-stats
//!
//! This module provides implementations of Bayesian nonparametric models,
//! including:
//!
//! - **Dirichlet Process (DP)**: The fundamental object of Bayesian nonparametrics,
//! a distribution over distributions with concentration parameter α.
//! - **Stick-breaking construction (GEM)**: Sethuraman's constructive representation
//! of the DP, producing mixture weights from Beta(1, α) draws.
//! - **Chinese Restaurant Process (CRP)**: Sequential construction of DP partitions
//! via a metaphorical seating arrangement.
//! - **Pitman-Yor Process (PYP)**: A two-parameter generalisation of the DP that
//! exhibits power-law cluster-size distributions.
//! - **DP Gaussian Mixture Model (DP-GMM)**: Infinite mixture of Gaussians with
//! collapsed Gibbs sampling using the Normal-Inverse-Wishart conjugate prior.
pub use ;
pub use ;