#include <Seg_Model.hpp>
Inheritance diagram for Seg_Model:
Public Member Functions | |
virtual | ~Seg_Model () |
destructor | |
uint | Get_D () |
Get dimension. | |
uint | Get_K () |
Get the number of classes. | |
virtual double | LogLikelihood (Spatial_Data *spatd) |
Likelihood. | |
virtual double | Completed_LogLikelihood (Spatial_Data *spatd, vector< double > tik) |
Completed likelihood. | |
virtual double | BIC (Spatial_Data *spatd) |
BIC -- Bayesian Information Criterion. | |
virtual double | ICL (Spatial_Data *spatd) |
ICL -- Integrated Completed Likelihood. | |
double | LogDensity (vector< double > const &X, uint k) |
Compute the log-density for observation X in class k. | |
double | Density (vector< double > const &X, uint k) |
Compute the density for observation X in class k. | |
void | Estimate_Distributions (Spatial_Data *spatd, vector< double > const &tik) |
Estimate the distributions parameters. | |
virtual uint | Degrees_Of_Freedom () |
Number of free parameters. | |
virtual void | Info () |
Display model information. | |
virtual void | Estimate (Spatial_Data *spatd, vector< double > const &tik) |
Estimate model parameters. | |
Protected Attributes | |
vector< Distribution * > | Distrib |
Distributions. |
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Destructor. Abstract. Model-dependent. |
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Compute the BIC -- Bayesian Information Criterion.
Reimplemented in HMRF, and IID_Mixture. |
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Compute the Completed likelihood.
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Number of free parameters.
Reimplemented in HMRF, and IID_Mixture. |
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Compute density at X in the class k, i.e. , f(X | mu_k, sigma_k) |
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Get the dimension |
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Get the number of classes/colors.
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Compute the ICL -- Integrated Completed Likelihood
Reimplemented in HMRF, and IID_Mixture. |
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Print some info on the model. Abstract. Model-dependent. Reimplemented in HMRF, and IID_Mixture. |
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Compute log density at X in the class k, i.e. , log f(X | mu_k, sigma_k) |
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Comptue the Log-Likelihood
Reimplemented in HMRF, and IID_Mixture. |