Destructor
Prerequisite
Etymology
Solves the linear least-squares fit problem using the singular value
decomposition method.
Synopsis
The operation, calls and results are identical to those for the
LinearFit class. The only difference is a collinearity default of 1e-8
rather than 0. The actual calculations do a singular value
decomposition solution. A method exists to get the constraints
used in solving for missing rank.
Motivation
The creation of this class was driven by the need to provide users with
a reliable least-squares fit method. "Numerical Recipes" recommends that
singular value decomposition (SVD) method be always used for linear
least-squares problems, because of its robustness.
Not everybody agrees with this.
Member Description
LinearFitSVD()
Create a fitter: the normal way to generate a fitter object. Necessary
data will be deduced from the Functional provided with
setFunction()
LinearFitSVD(const LinearFitSVD &other)
Copy constructor (deep copy)
LinearFitSVD &operator=(const LinearFitSVD &other)
Assignment (deep copy)
virtual ~LinearFitSVD()