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.

Since:

3.3

Field Summary

Fields

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

Constructor Summary

Constructors

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

Method Summary

Modifier and Type	Method	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 AbstractEvaluation

getCost, getCovariances, getRMS, getSigma

Methods inherited from class Object

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

Field Details

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 Details

LazyUnweightedEvaluation

private 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 Details

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.