#include <HMRF.hpp>
Inheritance diagram for HMRF:
Public Member Functions | |
HMRF () | |
Constructor. | |
HMRF (Neighborhood_System *nhs) | |
Constructor. | |
HMRF (uint k, uint dim, Neighborhood_System *nhs) | |
Constructor. | |
HMRF (Random_Field *rf, vector< Distribution * > const &distrib) | |
Constructor. | |
HMRF (Random_Field *rf, vector< Diag_Normal * > const &distrib) | |
Constructor. | |
HMRF (Random_Field *rf, vector< Normal * > const &distrib) | |
Constructor. | |
HMRF (Random_Field *rf, vector< Laplace * > const &distrib) | |
Constructor. | |
HMRF (Random_Field *rf, vector< HighDim_Normal * > const &distrib) | |
Constructor. | |
~HMRF () | |
Destructor. | |
uint | Get_N () |
Get the number of sites. | |
double | LogLikelihood (Spatial_Data *spatd) |
Likelihood. | |
double | BIC (Spatial_Data *spatd) |
BIC -- Bayesian Information Criterion. | |
double | ICL (Spatial_Data *spatd) |
ICL -- Integrated Completed Likelihood. | |
double | H (uint i, uint k, vector< uint > const &z) |
Hamiltonian. | |
double | Hmf (uint i, uint k) |
Mean-field hamiltonian, ![]() | |
void | Compute_PGmf (vector< double > &P_G) |
void | Set_Zmf (vector< double > const &z) |
Set the mean-field neighborhood, ![]() | |
void | Set_Zmf (vector< double > const &z, uint i) |
Set the mean-field neighborhood, ![]() | |
void | Get_Zmf (vector< double > &z) |
Get the mean-field neighborhood, ![]() | |
void | Simulate (Data *dat, uint gibbs_sampler_nbiter) |
Simulation procedure. | |
void | Simulate (Data *dat, double grad_tol) |
Simulation procedure. | |
void | Set_Gradient (double step, double tol, uint maxiter) |
Set gradient descent parameters. | |
void | Estimate_MRF (vector< double > const &tik) |
Estimate the MRF parameters. | |
void | Estimate (Spatial_Data *spatd, vector< double > const &tik) |
Step M of the NR-EM algorithm. | |
double | Completed_LogLikelihood (Spatial_Data *spatd, vector< double > const &tik) |
Completed likelihood. | |
double | PLIC (Spatial_Data *spatd, vector< uint > const &Z_ICM) |
PLIC -- Pseudolikelihood Information Criterion. | |
uint | Degrees_Of_Freedom () |
Degrees of freedom. | |
void | Info () |
Information. | |
void | ReadFromFile (string filename) |
Read from file. | |
void | WriteToFile (string filename) |
Write to file. | |
Protected Attributes | |
Random_Field * | RF |
(hidden) MRF |
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Default constructor |
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Default constructor |
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Default constructor |
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Detailed constructor |
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Detailed constructor |
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Destructor. |
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Compute the BIC -- Bayesian Information Criterion.
Reimplemented from Seg_Model. |
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Compute the Completed log likelihood.
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Compute
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Number of free parameters ... useful for model selection. Reimplemented from Seg_Model. |
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Estimate the model parameters
Reimplemented from Seg_Model. |
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Estimate then MRF model given the fuzzy classification.
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Get the number of sites.
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Get the mean-field neighborhood,
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Compute the Hamiltonian of the MRF.
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Compute the MRF Hamiltonian mean-field approximation, given
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Compute the ICL -- Integrated Completed Likelihood
Reimplemented from Seg_Model. |
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Comptue the Log-Likelihood
Reimplemented from Seg_Model. |
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PLIC -- Pseudolikelihood Information Criterion
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read from a file file format details : |
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Set the gradient descent parameters.
At each iteration, the model parameters are updated with a step step. The gradient descent is stopped whenever the gradient is under tol or the maximum number of iterations is reached. |
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Set the mean-field neighborhood,
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Set the mean-field neighborhood,
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Simulation procedure. |
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Simulation procedure. |
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save in a file |