BNPClust/Sampler_8hpp_source.html

#pragma once


#include "Data.hpp"

#include "Likelihood.hpp"

#include "Params.hpp"

#include "Process.hpp"


#include <random>

#include <Rcpp.h>

#include <Eigen/Dense>


class Sampler {

protected:

    // ========== Core Components ==========


    Data &data;


    const Params &params;


    const Likelihood &likelihood;


    Process &process;


    // ========== Random Number Generation ==========


    std::random_device rd;


public:

    // ========== Constructor ==========


    Sampler(Data &d, const Params &p, const Likelihood &l, Process &pr)

        : data(d), params(p), likelihood(l), process(pr) {};


    // ========== Pure Virtual Interface ==========


    virtual void step() = 0;


    virtual ~Sampler() = default;

};


Data.hpp
Data structure for managing point distances and cluster allocations.

Likelihood.hpp
Abstract base class for likelihood computation in clustering models.

Params.hpp
Parameter management for Bayesian nonparametric MCMC models.

Process.hpp
Abstract interface for Bayesian nonparametric processes.

Data
Manages distance matrices and cluster allocations for points.
Definition Data.hpp:27

Likelihood
Abstract base class for likelihood computation.
Definition Likelihood.hpp:27

Process
Abstract base class for Bayesian nonparametric processes.
Definition Process.hpp:41

Sampler::likelihood
const Likelihood & likelihood
Reference to the likelihood computation object for evaluating cluster assignments.
Definition Sampler.hpp:63

Sampler::~Sampler
virtual ~Sampler()=default
Virtual destructor for proper cleanup of derived classes.

Sampler::Sampler
Sampler(Data &d, const Params &p, const Likelihood &l, Process &pr)
Constructor initializing sampler with required components.
Definition Sampler.hpp:97

Sampler::step
virtual void step()=0
Pure virtual method to perform one MCMC sampling step.

Sampler::data
Data & data
Reference to the data object containing observations and current allocations.
Definition Sampler.hpp:55

Sampler::params
const Params & params
Reference to the parameters object containing model hyperparameters and MCMC settings.
Definition Sampler.hpp:59

Sampler::process
Process & process
Reference to the stochastic process object (DP, NGGP, DPW, NGGPW).
Definition Sampler.hpp:67

Sampler::rd
std::random_device rd
Random device for generating random numbers across sampling algorithms.
Definition Sampler.hpp:73

Params
Structure containing all parameters needed for the NGGP (Normalized Generalized Gamma Process) and DP...
Definition Params.hpp:35