org.apache.commons.math3.fitting.leastsquares

Class LeastSquaresFactory.LocalLeastSquaresProblem.LazyUnweightedEvaluation

java.lang.Object

org.apache.commons.math3.fitting.leastsquares.AbstractEvaluation

org.apache.commons.math3.fitting.leastsquares.LeastSquaresFactory.LocalLeastSquaresProblem.LazyUnweightedEvaluation

All Implemented Interfaces:

LeastSquaresProblem.Evaluation

Enclosing class:

LeastSquaresFactory.LocalLeastSquaresProblem

private static class LeastSquaresFactory.LocalLeastSquaresProblem.LazyUnweightedEvaluation
extends AbstractEvaluation

Container with the model lazy evaluation at a particular point.

Field Summary

Fields

Modifier and Type	Field and Description
private ValueAndJacobianFunction	model Model and Jacobian functions.
private RealVector	point Point of evaluation.
private RealVector	target Target values for the model function at optimum.

Constructor Summary

Constructors

Modifier	Constructor and Description
private	LeastSquaresFactory.LocalLeastSquaresProblem.LazyUnweightedEvaluation(ValueAndJacobianFunction model, RealVector target, RealVector point) Create an LeastSquaresProblem.Evaluation with no weights.

Method Summary

Methods

Modifier and Type	Method and Description
RealMatrix	getJacobian() Get the weighted Jacobian matrix.
RealVector	getPoint() Get the abscissa (independent variables) of this evaluation.
RealVector	getResiduals() Get the weighted residuals.

Methods inherited from class org.apache.commons.math3.fitting.leastsquares.AbstractEvaluation

getCost, getCovariances, getRMS, getSigma

Methods inherited from class java.lang.Object

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

Field Detail

point

private final RealVector point

Point of evaluation.

model

private final ValueAndJacobianFunction model

Model and Jacobian functions.

target

private final RealVector target

Target values for the model function at optimum.

Constructor Detail

LeastSquaresFactory.LocalLeastSquaresProblem.LazyUnweightedEvaluation

private LeastSquaresFactory.LocalLeastSquaresProblem.LazyUnweightedEvaluation(ValueAndJacobianFunction model,
                                                                     RealVector target,
                                                                     RealVector point)

Create an LeastSquaresProblem.Evaluation with no weights.

Parameters:

model - the model function

target - the observed values

point - the abscissa

Method Detail

getJacobian

public RealMatrix getJacobian()

Get the weighted Jacobian matrix.

Returns:

the weighted Jacobian: W^1/2 J.

getPoint

public RealVector getPoint()

Get the abscissa (independent variables) of this evaluation.

Returns:

the point provided to LeastSquaresProblem.evaluate(RealVector).

getResiduals

public RealVector getResiduals()

Get the weighted residuals. The residual is the difference between the observed (target) values and the model (objective function) value. There is one residual for each element of the vector-valued function. The raw residuals are then multiplied by the square root of the weight matrix.

Returns:

the weighted residuals: W^1/2 K.