Neal3 Class Reference

Implementation of Neal's Algorithm 3 for collapsed Gibbs sampling. More...

#include <neal.hpp>

Inheritance diagram for Neal3:

Public Member Functions
	Neal3 (Data &d, Params &p, Likelihood &l, Process &pr)
	Constructor for Neal's Algorithm 3 sampler.
void	step () override
	Perform one complete iteration of Neal's Algorithm 3.
Public Member Functions inherited from Sampler
	Sampler (Data &d, Params &p, Likelihood &l, Process &pr)
	Constructor initializing sampler with required components.
virtual	~Sampler ()=default
	Virtual destructor for proper cleanup of derived classes.

Additional Inherited Members
Protected Attributes inherited from Sampler
Data &	data
	Reference to the data object containing observations and current allocations.
Params &	params
	Reference to the parameters object containing model hyperparameters and MCMC settings.
Likelihood &	likelihood
	Reference to the likelihood computation object for evaluating cluster assignments.
Process &	process
	Reference to the stochastic process object (DP, NGGP, DPW, NGGPW)
std::random_device	rd
	Random device for generating random numbers across sampling algorithms.

Detailed Description

Implementation of Neal's Algorithm 3 for collapsed Gibbs sampling.

This class implements Neal's Algorithm 3, a standard collapsed Gibbs sampler for Bayesian nonparametric mixture models. The algorithm sequentially updates cluster assignments by sampling from the full conditional distribution of each observation, integrating out the cluster parameters.

Algorithm 3 is characterized by:

• Sequential updates: One observation at a time
• Collapsed sampling: Cluster parameters are integrated out analytically
• Full conditionals: Each assignment is sampled from its exact posterior
• Automatic cluster creation/deletion: Clusters are created when needed and deleted when empty

The algorithm is particularly effective for models where the likelihood can be computed in closed form after integrating out cluster-specific parameters.

@reference Neal, R. M. (2000). "Markov Chain Sampling Methods for Dirichlet Process Mixture Models"

See also

Sampler, Process, Likelihood

Constructor & Destructor Documentation

Neal3()

Neal3::Neal3 ( Data & d, Params & p, Likelihood & l, Process & pr )

inline

Constructor for Neal's Algorithm 3 sampler.

Parameters

d	Reference to Data object containing observations
p	Reference to Params object with hyperparameters
l	Reference to Likelihood object for probability computations
pr	Reference to Process object (DP, NGGP, etc.) defining the prior

Initializes the Gibbs sampler with all required components. The random number generator is seeded from the inherited random device.

Member Function Documentation

step()

void Neal3::step ( )

overridevirtual

Perform one complete iteration of Neal's Algorithm 3.

Executes one full sweep of the collapsed Gibbs sampler by sequentially updating the cluster assignment of each observation. The order of updates is typically randomized to avoid systematic bias.

After each full sweep:

• All observations have been considered for reassignment
• Cluster structure may have changed (clusters created/destroyed)
• The Markov chain has advanced by one step

See also

step_1_observation()

Performs a single step of the DP Neal 2 algorithm for all the dataset.

Implements Sampler.

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The documentation for this class was generated from the following files:

• src/samplers/neal.hpp
• src/samplers/neal.cpp