tesi/neal_8hpp_source.html

#pragma once


#include "../utils/Sampler.hpp"


class Neal3 : public Sampler {

private:

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


  mutable std::mt19937 gen;


  // ========== Core Algorithm Methods ==========


  void step_1_observation(int index);


  int sample_from_log_probs(const std::vector<double>& log_probs);


public:

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


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

      : Sampler(d, p, l, pr), gen(rd()) {};


  // ========== MCMC Interface ==========


  void step() override;

};


Sampler.hpp
Abstract base class for MCMC sampling algorithms.

Data
Manages distance matrices and cluster allocations for points.
Definition Data.hpp:26

Likelihood
Computes log-likelihood for clusters based on distance-based cohesion and repulsion.
Definition Likelihood.hpp:19

Neal3::step
void step() override
Perform one complete iteration of Neal's Algorithm 3.
Definition neal.cpp:80

Neal3::Neal3
Neal3(Data &d, Params &p, Likelihood &l, Process &pr)
Constructor for Neal's Algorithm 3 sampler.
Definition neal.hpp:82

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

Sampler::Sampler
Sampler(Data &d, Params &p, Likelihood &l, Process &pr)
Constructor initializing sampler with required components.
Definition Sampler.hpp:98

Sampler::rd
std::random_device rd
Random device for generating random numbers across sampling algorithms.
Definition Sampler.hpp:74

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