AbstractEvaluation (Apache Commons Math 3.6.1 API)

java.lang.Object
- org.apache.commons.math3.fitting.leastsquares.AbstractEvaluation

All Implemented Interfaces:

LeastSquaresProblem.Evaluation
```
public abstract class AbstractEvaluation
extends Object
implements LeastSquaresProblem.Evaluation
```
An implementation of LeastSquaresProblem.Evaluation that is designed for extension. All of the methods implemented here use the methods that are left unimplemented.
TODO cache results?

Since:

3.3

Method Summary

Methods
Modifier and Type	Method and Description
`double`	`getCost()` Get the cost.
`RealMatrix`	`getCovariances(double threshold)` Get the covariance matrix of the optimized parameters.
`double`	`getRMS()` Get the normalized cost.
`RealVector`	`getSigma(double covarianceSingularityThreshold)` Get an estimate of the standard deviation of the parameters.

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface org.apache.commons.math3.fitting.leastsquares.LeastSquaresProblem.Evaluation
getJacobian, getPoint, getResiduals

- Method Detail
  - getCovariances
```
public RealMatrix getCovariances(double threshold)
```
    Get the covariance matrix of the optimized parameters.
    Note that this operation involves the inversion of the J^TJ 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.
    
    Specified by:
    
    getCovariances in interface LeastSquaresProblem.Evaluation
    
    Parameters:
    threshold - Singularity threshold.
    
    Returns:
    the covariance matrix.
  - getSigma
```
public RealVector getSigma(double covarianceSingularityThreshold)
```
    Get an estimate of the standard deviation of the parameters. The returned values are the square root of the diagonal coefficients of the covariance matrix, 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.
    
    Specified by:
    
    getSigma in interface LeastSquaresProblem.Evaluation
    
    Parameters:
    covarianceSingularityThreshold - Singularity threshold (see computeCovariances).
    
    Returns:
    an estimate of the standard deviation of the optimized parameters
  - getRMS
```
public double getRMS()
```
    Get the normalized cost. It is the square-root of the sum of squared of the residuals, divided by the number of measurements.
    
    Specified by:
    
    getRMS in interface LeastSquaresProblem.Evaluation
    
    Returns:
    the cost.
  - getCost
```
public double getCost()
```
    Get the cost.
    
    Specified by:
    
    getCost in interface LeastSquaresProblem.Evaluation
    
    Returns:
    the cost.
    See Also:
    LeastSquaresProblem.Evaluation.getResiduals()

Class AbstractEvaluation

Method Summary

Methods inherited from class java.lang.Object

Methods inherited from interface org.apache.commons.math3.fitting.leastsquares.LeastSquaresProblem.Evaluation

Method Detail

getCovariances

getSigma

getRMS

getCost