org.apache.commons.math3.fitting.leastsquares package
 (cf. MATH-1008).@Deprecated public abstract class AbstractLeastSquaresOptimizer extends JacobianMultivariateVectorOptimizer
evaluations, iterations| Modifier | Constructor and Description | 
|---|---|
| protected  | AbstractLeastSquaresOptimizer(ConvergenceChecker<PointVectorValuePair> checker)Deprecated.  | 
| Modifier and Type | Method and Description | 
|---|---|
| protected double | computeCost(double[] residuals)Deprecated.  Computes the cost. | 
| double[][] | computeCovariances(double[] params,
                  double threshold)Deprecated.  Get the covariance matrix of the optimized parameters. | 
| protected double[] | computeResiduals(double[] objectiveValue)Deprecated.  Computes the residuals. | 
| double[] | computeSigma(double[] params,
            double covarianceSingularityThreshold)Deprecated.  Computes an estimate of the standard deviation of the parameters. | 
| protected RealMatrix | computeWeightedJacobian(double[] params)Deprecated.  Computes the weighted Jacobian matrix. | 
| double | getChiSquare()Deprecated.  Get a Chi-Square-like value assuming the N residuals follow N
 distinct normal distributions centered on 0 and whose variances are
 the reciprocal of the weights. | 
| double | getRMS()Deprecated.  Gets the root-mean-square (RMS) value. | 
| RealMatrix | getWeightSquareRoot()Deprecated.  Gets the square-root of the weight matrix. | 
| PointVectorValuePair | optimize(OptimizationData... optData)Deprecated.  Stores data and performs the optimization. | 
| protected void | parseOptimizationData(OptimizationData... optData)Deprecated.  Scans the list of (required and optional) optimization data that
 characterize the problem. | 
| protected void | setCost(double cost)Deprecated.  Sets the cost. | 
computeJacobiancomputeObjectiveValue, getTarget, getTargetSize, getWeightgetLowerBound, getStartPoint, getUpperBounddoOptimize, getConvergenceChecker, getEvaluations, getIterations, getMaxEvaluations, getMaxIterations, incrementEvaluationCount, incrementIterationCount, optimizeprotected AbstractLeastSquaresOptimizer(ConvergenceChecker<PointVectorValuePair> checker)
checker - Convergence checker.protected RealMatrix computeWeightedJacobian(double[] params)
params - Model parameters at which to compute the Jacobian.DimensionMismatchException - if the Jacobian dimension does not
 match problem dimension.protected double computeCost(double[] residuals)
residuals - Residuals.computeResiduals(double[])public double getRMS()
public double getChiSquare()
public RealMatrix getWeightSquareRoot()
protected void setCost(double cost)
cost - Cost value.public double[][] computeCovariances(double[] params,
                            double threshold)
JTJ matrix, where J is the
 Jacobian matrix.
 The threshold parameter is a way for the caller to specify
 that the result of this computation should be considered meaningless,
 and thus trigger an exception.params - Model parameters.threshold - Singularity threshold.SingularMatrixException - if the covariance matrix cannot be computed (singular problem).public double[] computeSigma(double[] params,
                    double covarianceSingularityThreshold)
sd(a[i]) ~= sqrt(C[i][i]), where a[i]
 is the optimized value of the i-th parameter, and C is
 the covariance matrix.params - Model parameters.covarianceSingularityThreshold - Singularity threshold (see
 computeCovariances).SingularMatrixException - if the covariance matrix cannot be computed.public PointVectorValuePair optimize(OptimizationData... optData) throws TooManyEvaluationsException
The list of parameters is open-ended so that sub-classes can extend it with arguments specific to their concrete implementations.
When the method is called multiple times, instance data is overwritten only when actually present in the list of arguments: when not specified, data set in a previous call is retained (and thus is optional in subsequent calls).
 Important note: Subclasses must override
 BaseOptimizer.parseOptimizationData(OptimizationData[]) if they need to register
 their own options; but then, they must also call
 super.parseOptimizationData(optData) within that method.
optimize in class JacobianMultivariateVectorOptimizeroptData - Optimization data. In addition to those documented in
 JacobianMultivariateVectorOptimizer, this method will register the following data:
 TooManyEvaluationsException - if the maximal number of
 evaluations is exceeded.DimensionMismatchException - if the initial guess, target, and weight
 arguments have inconsistent dimensions.protected double[] computeResiduals(double[] objectiveValue)
objectiveValue - Value of the the objective function. This is
 the value returned from a call to
 computeObjectiveValue
 (whose array argument contains the model parameters).DimensionMismatchException - if params has a wrong
 length.protected void parseOptimizationData(OptimizationData... optData)
weightMatrixSqrt
 field is recomputed.parseOptimizationData in class JacobianMultivariateVectorOptimizeroptData - Optimization data. The following data will be looked for:
 Copyright © 2003–2016 The Apache Software Foundation. All rights reserved.