Detailed Description

Definition at line 67 of file fit_linear.h.

Storage
mat_t	A
	Local copy of `xpred` (and used as workspace by the SV decomposition)

mat_t	Q
	The first unitary matrix from the SV decomposition.

mat_t	QSI
	Workspace for the SV decomposition and storage for $Q S^{-1}$ .

vec_t	S
	The singular values from the SV decomposition.

vec_t	xt
	SV decomposition workspace and also used to store new predicted values.

vec_t	D
	Balancing factors for A.

vec_t	t
	Only used for the weighted fit (not yet implemented)

size_t	size_par
	Number of parameters.

size_t	size_dat
	Number of data points.

bool	column_scaling
	If true, discard fit components if the associated singular value becomes too small (default true)

double	tol
	Tolerance (default $\sim 2.22\times 10^{-16}$ )

size_t	rank
	The rank of the linear system from the last call to `fit_linear()`

	fit_linear ()

virtual	~fit_linear ()

virtual void	fit_svd (size_t ndat, size_t npar)
	Perform the SV decomposition.

virtual void	fit (size_t npar, size_t ndat, const vec_t &ydat, const mat_t &xpred, vec_t &parms, mat_t &covar, double &chi2)
	Perform a least-squares fit of a linear system. More...

virtual const char *	type ()
	Return string denoting type ("fit_linear")

Member Function Documentation

template<class vec_t = boost::numeric::ublas::vector<double>, class mat_t = boost::numeric::ublas::matrix<double>>

virtual void o2scl::fit_linear< vec_t, mat_t >::fit	(	size_t	npar,
		size_t	ndat,
		const vec_t &	ydat,
		const mat_t &	xpred,
		vec_t &	parms,
		mat_t &	covar,
		double &	chi2
	)

inlinevirtual

This function performs a least-squares fit of the system

$\mathrm{xpred} \cdot \mathrm{parms} = \mathrm{ydat}$

The variance-covariance matrix for the parameters is returned in covar and the value of $\chi^2$ is returned in chi2.

Definition at line 140 of file fit_linear.h.

The documentation for this class was generated from the following file: