repicea.math.optimizer

Class AbstractOptimizer

java.lang.Object

repicea.math.optimizer.AbstractOptimizer

Direct Known Subclasses:

NewtonRaphsonOptimizer

public abstract class AbstractOptimizer
extends java.lang.Object

This class is the main class for all optimizers.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	AbstractOptimizer.LineSearchMethod
static class	AbstractOptimizer.OptimizationException The OptimizationException class encompasses all the exception that can be thrown when the optimizer fails to reach convergence.

Field Summary

Fields

Modifier and Type	Field and Description
protected Matrix	betaVector
protected boolean	convergenceAchieved
protected double	convergenceCriterion
protected Matrix	hessianMatrix
protected double	optimalValue

Constructor Summary

Constructors

Constructor and Description
AbstractOptimizer() Default constructor.

Method Summary

Modifier and Type	Method and Description
protected void	addOptimizerListener(OptimizerListener listener)
protected void	fireOptimizerEvent(java.lang.String actionString)
double	getConvergenceCriterion()
Matrix	getHessianAtMaximum()
double	getOptimalValue() This method returns the optimal value resulting from the optimization.
Matrix	getParametersAtMaximum()
boolean	isConvergenceAchieved()
protected boolean	isVerboseEnabled()
abstract boolean	optimize(AbstractMathematicalFunction function, java.util.List<java.lang.Integer> indicesOfParametersToOptimize) This method optimizes the likelihood of the StatisticalModel instance.
protected void	removeOptimizerListener(OptimizerListener listener)
void	setConvergenceCriterion(double conv)
void	setVerboseEnabled(boolean verboseEnabled) This method sets the verbose to true or false.
java.lang.String	toString()

Methods inherited from class java.lang.Object

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

Field Detail

convergenceCriterion

protected double convergenceCriterion

convergenceAchieved

protected boolean convergenceAchieved

optimalValue

protected double optimalValue

betaVector

protected Matrix betaVector

hessianMatrix

protected Matrix hessianMatrix

Constructor Detail

AbstractOptimizer

public AbstractOptimizer()

Default constructor.

Method Detail

addOptimizerListener

protected void addOptimizerListener(OptimizerListener listener)

removeOptimizerListener

protected void removeOptimizerListener(OptimizerListener listener)

isConvergenceAchieved

public boolean isConvergenceAchieved()

getParametersAtMaximum

public Matrix getParametersAtMaximum()

getHessianAtMaximum

public Matrix getHessianAtMaximum()

setVerboseEnabled

public void setVerboseEnabled(boolean verboseEnabled)

This method sets the verbose to true or false.

Parameters:

verboseEnabled - true to get the information about the subiteration or false (DEFAULT VALUE).

isVerboseEnabled

protected boolean isVerboseEnabled()

toString

public java.lang.String toString()

Overrides:

toString in class java.lang.Object

getOptimalValue

public double getOptimalValue()

This method returns the optimal value resulting from the optimization.

Returns:

a double

getConvergenceCriterion

public double getConvergenceCriterion()

setConvergenceCriterion

public void setConvergenceCriterion(double conv)

optimize

public abstract boolean optimize(AbstractMathematicalFunction function,
                                 java.util.List<java.lang.Integer> indicesOfParametersToOptimize)
                          throws AbstractOptimizer.OptimizationException

This method optimizes the likelihood of the StatisticalModel instance.

Parameters:

function - a AbstractMathematicalFunction object

indicesOfParametersToOptimize - a List instance that contains the indices of the parameters to be optimized

Throws:

AbstractOptimizer.OptimizationException

fireOptimizerEvent

protected void fireOptimizerEvent(java.lang.String actionString)