repicea.stats.model

Interface StatisticalModel<P extends StatisticalDataStructure>

All Known Implementing Classes:

AbstractStatisticalModel, FGMCopulaGLModel, GeneralizedLinearModel, LinearModel

public interface StatisticalModel<P extends StatisticalDataStructure>

This interface defines the services provided by a statistical model.

Method Summary

Modifier and Type	Method and Description
void	doEstimation() This method computes the parameter estimates.
CompositeLogLikelihood	getCompleteLogLikelihood() This method returns the model log-likelihood function.
double	getConvergenceCriterion() This method returns the value of the convergence criterion.
P	getDataStructure() This method returns the data structure.
Estimator	getEstimator() This method returns the optimizer of the log-likelihood function.
java.lang.String	getModelDefinition() This method returns the model definition as entered by the user.
Matrix	getParameters()
Matrix	getPredicted() This method returns a vector of predicted values.
Matrix	getResiduals() This method returns a vector of residuals, that is observed values minus predictions.
void	getSummary() This method returns the results of the fit on screen.
void	setParameters(Matrix beta)

Method Detail

getCompleteLogLikelihood

CompositeLogLikelihood getCompleteLogLikelihood()

This method returns the model log-likelihood function.

Returns:

a LogLikelihood instance

setParameters

void setParameters(Matrix beta)

getParameters

Matrix getParameters()

getSummary

void getSummary()

This method returns the results of the fit on screen.

getPredicted

Matrix getPredicted()

This method returns a vector of predicted values.

Returns:

a Matrix instance

getResiduals

Matrix getResiduals()

This method returns a vector of residuals, that is observed values minus predictions.

Returns:

a Matrix instance

doEstimation

void doEstimation()

This method computes the parameter estimates.

getModelDefinition

java.lang.String getModelDefinition()

This method returns the model definition as entered by the user.

Returns:

a String

getConvergenceCriterion

double getConvergenceCriterion()

This method returns the value of the convergence criterion.

Returns:

a double

getEstimator

Estimator getEstimator()

This method returns the optimizer of the log-likelihood function.

Returns:

an Optimizer instance

getDataStructure

P getDataStructure()

This method returns the data structure.

Returns:

a StatisticalDataStructure derived instance