Split-Merge sampler for Bayesian nonparametric mixture models. More...

#include <splitmerge.hpp>

Inheritance diagram for SplitMerge:

Public Member Functions
	SplitMerge (Data &d, Params &p, Likelihood &l, Process &pr, bool shuffle)
	Constructor for Split-Merge sampler.
void	step () override
	Perform one iteration of the split-merge algorithm.
int	get_accepted_split () const
	Get number of accepted split moves for diagnostics.
int	get_accepted_merge () const
	Get number of accepted merge moves for diagnostics.
int	get_accepted_shuffle () const
	Get number of accepted shuffle moves for diagnostics.
Public Member Functions inherited from Sampler
	Sampler (Data &d, const Params &p, const Likelihood &l, Process &pr)
	Constructor initializing sampler with required components.
virtual	~Sampler ()=default
	Virtual destructor for proper cleanup of derived classes.

Private Member Functions
void	choose_indeces ()
	Randomly select two observations for split-merge proposal.
void	choose_clusters_shuffle ()
	Select clusters for shuffle move.
void	restricted_gibbs (int iterations, bool only_probabilities=false)
	Generate proposal state via restricted Gibbs sampling.
void	split_move ()
	Execute a split move proposal.
double	compute_acceptance_ratio_split (double likelihood_old_cluster)
	Compute acceptance ratio for split move.
void	merge_move ()
	Execute a merge move proposal.
double	compute_acceptance_ratio_merge (double likelihood_old_ci, double likelihood_old_cj)
	Compute acceptance ratio for merge move.
void	shuffle ()
	Execute a shuffle move proposal.
double	compute_acceptance_ratio_shuffle (double likelihood_old_ci, double likelihood_old_cj, int old_ci_size, int old_cj_size)
	Compute acceptance ratio for shuffle move.

Private Attributes
std::mt19937	gen
	Mersenne Twister random number generator for sampling operations.
int	idx_i
	Index of first randomly chosen observation.
int	idx_j
	Index of second randomly chosen observation.
int	ci
	Cluster assignment of first observation.
int	cj
	Cluster assignment of second observation.
bool	shuffle_bool = false
	Flag to enable shuffle moves (Mena and Martinez, 2014).
Eigen::VectorXi	launch_state
	Launch state for restricted Gibbs sampling.
Eigen::VectorXi	S
	Indices of observations in clusters ci and cj.
Eigen::VectorXi	original_allocations
	Original cluster assignments before move proposal.
double	log_split_gibbs_prob = 0
	Log probability of generating current state via restricted Gibbs (split direction).
double	log_merge_gibbs_prob = 0
	Log probability of generating current state via restricted Gibbs (merge direction).
int	accepted_split = 0
int	accepted_merge = 0
int	accepted_shuffle = 0

Additional Inherited Members
Protected Attributes inherited from Sampler
Data &	data
	Reference to the data object containing observations and current allocations.
const Params &	params
	Reference to the parameters object containing model hyperparameters and MCMC settings.
const 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

Split-Merge sampler for Bayesian nonparametric mixture models.

This class implements the split-merge algorithm, an advanced MCMC method that proposes joint updates to cluster assignments through split and merge moves. This approach can achieve better mixing than sequential Gibbs sampling, particularly for models with strong within-cluster correlations.

The algorithm alternates between three types of moves:

Split moves: Divide a cluster into two subclusters
Merge moves: Combine two clusters into one
Shuffle moves: Redistribute observations between two existing clusters

Each move uses restricted Gibbs sampling to generate proposals, followed by Metropolis-Hastings acceptance/rejection based on prior and likelihood ratios. The algorithm maintains detailed balance and ergodicity.

Note: reference Jain, S. and Neal, R. M. (2004). "A Split-Merge Markov Chain Monte Carlo Procedure for the Dirichlet Process Mixture Model" reference Martinez, A. F. and Mena, R. H. (2014). "On a Nonparametric Change Point Detection Model in Markovian Regimes"

See also: Sampler, SplitMerge_SAMS

Constructor & Destructor Documentation

◆ SplitMerge()

SplitMerge::SplitMerge	(	Data &	d,
		Params &	p,
		Likelihood &	l,
		Process &	pr,
		bool	shuffle )

inline

Constructor for Split-Merge 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 defining the prior
shuffle	Flag to enable shuffle moves in addition to split-merge

Initializes the split-merge sampler with the option to include shuffle moves. When shuffle is enabled, the algorithm can propose redistributions between existing clusters in addition to split-merge moves.

Member Function Documentation

◆ choose_clusters_shuffle()

void SplitMerge::choose_clusters_shuffle ( )

private

Select clusters for shuffle move.

Determines the cluster assignments of the selected observations and prepares for a shuffle move between two existing clusters.

Randomly choose two distinct clusters ci and cj from the current allocations. Update idx_i and idx_j to be random points from these clusters.

◆ choose_indeces()

void SplitMerge::choose_indeces ( )

private

Randomly select two observations for split-merge proposal.

Uniformly samples two distinct observation indices that will be used to determine the type of move (split, merge, or shuffle).

Randomly choose two distinct indices i and j from the data points. Identify their clusters ci and cj. Prepare the launch_state and S vectors for the split-merge operation.

◆ compute_acceptance_ratio_merge()

double SplitMerge::compute_acceptance_ratio_merge	(	double	likelihood_old_ci,
		double	likelihood_old_cj )

private

Compute acceptance ratio for merge move.

Parameters

likelihood_old_ci	Likelihood of first original cluster
likelihood_old_cj	Likelihood of second original cluster

Returns: Log acceptance ratio for the merge proposal

Compute the log acceptance ratio for a merge move.

Parameters

likelihood_old_ci	The log likelihood of cluster ci before the merge.
likelihood_old_cj	The log likelihood of cluster cj before the merge.

Returns: The log acceptance ratio for the merge move.

◆ compute_acceptance_ratio_shuffle()

double SplitMerge::compute_acceptance_ratio_shuffle	(	double	likelihood_old_ci,
		double	likelihood_old_cj,
		int	old_ci_size,
		int	old_cj_size )

private

Compute acceptance ratio for shuffle move.

Parameters

likelihood_old_ci	Likelihood of first cluster before shuffle
likelihood_old_cj	Likelihood of second cluster before shuffle
old_ci_size	Size of first cluster before shuffle
old_cj_size	Size of second cluster before shuffle

Returns: Log acceptance ratio for the shuffle proposal

Compute the log acceptance ratio for a shuffle move.

Returns: The log acceptance ratio for the shuffle move.

◆ compute_acceptance_ratio_split()

double SplitMerge::compute_acceptance_ratio_split ( double likelihood_old_cluster )

private

Compute acceptance ratio for split move.

Parameters

likelihood_old_cluster Likelihood of the original single cluster

Returns: Log acceptance ratio for the split proposal

Computes the Metropolis-Hastings acceptance probability by combining prior ratios, likelihood ratios, and proposal probabilities.

Compute the log acceptance ratio for a split move.

Parameters

likelihood_old_cluster The log likelihood of the original cluster before the split.

Returns: The log acceptance ratio for the split move.

◆ get_accepted_merge()

int SplitMerge::get_accepted_merge ( ) const

inline

Get number of accepted merge moves for diagnostics.

Returns: Count of accepted merge moves

◆ get_accepted_shuffle()

int SplitMerge::get_accepted_shuffle ( ) const

inline

Get number of accepted shuffle moves for diagnostics.

Returns: Count of accepted shuffle moves

◆ get_accepted_split()

int SplitMerge::get_accepted_split ( ) const

inline

Get number of accepted split moves for diagnostics.

Returns: Count of accepted split moves

◆ merge_move()

void SplitMerge::merge_move ( )

private

Execute a merge move proposal.

Attempts to merge two clusters containing the selected observations into a single cluster.

Propose a merge move by combining clusters ci and cj. Compute the acceptance ratio and decide whether to accept or reject the move.

◆ restricted_gibbs()

void SplitMerge::restricted_gibbs	(	int	iterations,
		bool	only_probabilities = false )

private

Generate proposal state via restricted Gibbs sampling.

Parameters

iterations	Number of restricted Gibbs iterations to perform
only_probabilities	If true, only compute proposal probabilities without updating state

Performs restricted Gibbs sampling on observations in the selected clusters to generate a proposal state. Also computes the probability of generating this state for use in the acceptance ratio.

Perform restricted Gibbs sampling on the points in S to propose new allocations for iter iterations.

Parameters

iterations	Number of Gibbs sampling iterations to perform.
only_probabilities	If true, only compute the probabilities without changing allocations (used in merge move).

◆ shuffle()

void SplitMerge::shuffle ( )

private

Execute a shuffle move proposal.

Redistributes observations between two existing clusters without changing the total number of clusters.

Perform a shuffle move to refine the allocations of points in S. This move helps to improve mixing by allowing points to switch clusters.

◆ split_move()

void SplitMerge::split_move ( )

private

Execute a split move proposal.

Attempts to split a cluster containing both selected observations into two separate clusters using restricted Gibbs sampling to generate the proposal allocation.

Propose a split move by dividing cluster ci into two clusters. Compute the acceptance ratio and decide whether to accept or reject the move.

◆ step()

void SplitMerge::step ( )

overridevirtual

Perform one iteration of the split-merge algorithm.

Executes one step of the split-merge sampler:

Randomly select two observations
Determine move type based on current cluster assignments
Generate proposal via restricted Gibbs sampling
Compute acceptance ratio and accept/reject via Metropolis-Hastings

The algorithm automatically chooses between split, merge, and shuffle moves based on the cluster assignments of the selected observations.

Perform a single split-merge MCMC step. Randomly choose two indices and decide whether to propose a split or merge move.

Implements Sampler.

Member Data Documentation

◆ accepted_merge

int SplitMerge::accepted_merge = 0

private

◆ accepted_shuffle

int SplitMerge::accepted_shuffle = 0

private

◆ accepted_split

int SplitMerge::accepted_split = 0

private

◆ ci

int SplitMerge::ci

private

Cluster assignment of first observation.

◆ cj

int SplitMerge::cj

private

Cluster assignment of second observation.

◆ gen

std::mt19937 SplitMerge::gen

mutableprivate

Mersenne Twister random number generator for sampling operations.

◆ idx_i

int SplitMerge::idx_i

private

Index of first randomly chosen observation.

◆ idx_j

int SplitMerge::idx_j

private

Index of second randomly chosen observation.

◆ launch_state

Eigen::VectorXi SplitMerge::launch_state

private

Launch state for restricted Gibbs sampling.

◆ log_merge_gibbs_prob

double SplitMerge::log_merge_gibbs_prob = 0

private

Log probability of generating current state via restricted Gibbs (merge direction).

◆ log_split_gibbs_prob

double SplitMerge::log_split_gibbs_prob = 0

private

Log probability of generating current state via restricted Gibbs (split direction).

◆ original_allocations

Eigen::VectorXi SplitMerge::original_allocations

private

Original cluster assignments before move proposal.

◆ S

Eigen::VectorXi SplitMerge::S

private

Indices of observations in clusters ci and cj.

◆ shuffle_bool

bool SplitMerge::shuffle_bool = false

private

Flag to enable shuffle moves (Mena and Martinez, 2014).

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

src/samplers/splitmerge.hpp
src/samplers/splitmerge.cpp

Public Member Functions

Private Member Functions

Private Attributes

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ SplitMerge()

Member Function Documentation

◆ choose_clusters_shuffle()

◆ choose_indeces()

◆ compute_acceptance_ratio_merge()

◆ compute_acceptance_ratio_shuffle()

◆ compute_acceptance_ratio_split()

◆ get_accepted_merge()

◆ get_accepted_shuffle()

◆ get_accepted_split()

◆ merge_move()

◆ restricted_gibbs()

◆ shuffle()

◆ split_move()

◆ step()

Member Data Documentation

◆ accepted_merge

◆ accepted_shuffle

◆ accepted_split

◆ ci

◆ cj

◆ gen

◆ idx_i

◆ idx_j

◆ launch_state

◆ log_merge_gibbs_prob

◆ log_split_gibbs_prob

◆ original_allocations

◆ S

◆ shuffle_bool