repicea.stats.model.lm

Class LinearModel

java.lang.Object

repicea.stats.model.AbstractStatisticalModel<StatisticalDataStructure>

repicea.stats.model.lm.LinearModel

All Implemented Interfaces:

StatisticalModel<StatisticalDataStructure>

public class LinearModel
extends AbstractStatisticalModel<StatisticalDataStructure>

The LinearModel is a traditional model fitted with an Ordinary Least Squares estimator.

Field Summary

Fields inherited from class repicea.stats.model.AbstractStatisticalModel

completeLLK

Constructor Summary

Constructors

Constructor and Description
LinearModel(DataSet dataSet, java.lang.String modelDefinition) Constructor.

Method Summary

Modifier and Type	Method and Description
protected GenericStatisticalDataStructure	getDataStructureFromDataSet(DataSet dataSet) This method returns the appropriate StatisticalDataStructure from the dataSet.
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.
double	getResidualVariance() This method returns the residual variance only if the optimizer is an instance of OLSOptimizer.
protected Estimator	instantiateDefaultEstimator() This method defines the default optimizer which is to be specific to the derived classes.
protected void	setCompleteLLK() This method sets the log-likelihood function of the model.
void	setParameters(Matrix beta)

Methods inherited from class repicea.stats.model.AbstractStatisticalModel

doEstimation, getCompleteLogLikelihood, getConvergenceCriterion, getDataStructure, getEstimator, getModelDefinition, getOptimizerParameters, getSummary, setConvergenceCriterion, setModelDefinition, setOptimizer, setOptimizerParameters

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

LinearModel

public LinearModel(DataSet dataSet,
                   java.lang.String modelDefinition)

Constructor.

Parameters:

dataSet - a DataSet instance

modelDefinition - a model definition

Method Detail

setParameters

public void setParameters(Matrix beta)

getParameters

public Matrix getParameters()

getResidualVariance

public double getResidualVariance()

This method returns the residual variance only if the optimizer is an instance of OLSOptimizer.

Returns:

a Matrix with a single element

getPredicted

public Matrix getPredicted()

Description copied from interface: StatisticalModel

This method returns a vector of predicted values.

Returns:

a Matrix instance

getResiduals

public Matrix getResiduals()

Description copied from interface: StatisticalModel

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

Returns:

a Matrix instance

setCompleteLLK

protected void setCompleteLLK()

Description copied from class: AbstractStatisticalModel

This method sets the log-likelihood function of the model. It is to be defined in the derived class, since the log-likelihood function depends on the different features of the model.

Specified by:

setCompleteLLK in class AbstractStatisticalModel<StatisticalDataStructure>

instantiateDefaultEstimator

protected Estimator instantiateDefaultEstimator()

Description copied from class: AbstractStatisticalModel

This method defines the default optimizer which is to be specific to the derived classes.

Specified by:

instantiateDefaultEstimator in class AbstractStatisticalModel<StatisticalDataStructure>

Returns:

an Optimizer instance

getDataStructureFromDataSet

protected GenericStatisticalDataStructure getDataStructureFromDataSet(DataSet dataSet)

Description copied from class: AbstractStatisticalModel

This method returns the appropriate StatisticalDataStructure from the dataSet. It is the first instruction to be called in the constructor.

Specified by:

getDataStructureFromDataSet in class AbstractStatisticalModel<StatisticalDataStructure>

Parameters:

dataSet - a DataSet instance

Returns:

a StatisticalDataStructure derived instance