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RazorBack::Linls_ Class Reference

Linls_: Class for carrying out linear least-squares using the SVD. More...

#include <Linls.hh>

List of all members.

Public Methods
	Linls_ (size_t NM=0, size_t NP=0)
	Init to empty.
double	lin_reg (const Rmatdbl_ &Xmeas, const Vecdbl_ &Ymeas, double Eps=1e-10)
	lin_reg(Xmeas, Ymeas, Eps): Carries out a linear least squares fit using SVD. More...
size_t	rank () const
	Returns the rank.
double	condition () const
	Returns the condition number.
size_t	deg_freedom () const
	Returns the degrees of freedom.
const Vecdbl_&	param () const
	Returns the parameter estimate.
const Vecdbl_&	sdev () const
	Returns the standard deviation of the parameters.
const Smatdbl_&	correl () const
	Returns the correlation matrix of the parameters.
double	chi_square () const
	Returns the chi-square statistic for the fit quality.
double	residual_dev () const
	Returns the residual deviation for the fit.
Protected Methods
void	adjust_dimensions (const Rmatdbl_ &Xmeas, const Vecdbl_ &Ymeas)
void	make_utb (const Vecdbl_ &B)
size_t	calc_rank (const Vecdbl_ &B, double Eps) const
void	calc_params (const Rmatdbl_ &Xmeas, const Vecdbl_ &Ymeas)
double	calc_chi2 (const Rmatdbl_ &Xmeas, const Vecdbl_ &Ymeas) const
Private Attributes
size_t	Nm
size_t	Np
size_t	Nf
	no. of measurements, no.of params, degrees of freedom.
Svd_	Svd
	an SVD object.
size_t	Rank
	the rank estimate.
Vecdbl_	Utb
	scalprods of U cols w/ RHS.
Vecdbl_	P
Vecdbl_	Sdev
	parameter values and standard deviations.
Smatdbl_	Correl
	parameter correlation matrix.
double	Chi2
	chi-square.

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Detailed Description

Linls_: Class for carrying out linear least-squares using the SVD.

Note that unlike Linreg_, this class is not derived from Paramest_.

Definition at line 35 of file Linls.hh.

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Constructor & Destructor Documentation

RazorBack::Linls_::Linls_ ( size_t NM = 0, size_t NP = 0 ) [inline, explicit]

Init to empty. Definition at line 52 of file Linls.hh.

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Member Function Documentation

double RazorBack::Linls_::lin_reg ( const Rmatdbl_ & Xmeas, const Vecdbl_ & Ymeas, double Eps = 1e-10 )

lin_reg(Xmeas, Ymeas, Eps): Carries out a linear least squares fit using SVD. Xmeas is the data matrix (Nm rows of observations for Np indep. vars, Nm>Np), Ymeas is the Nm observations of the dependent variable. Eps is a small tolerance value used for finding the best SVD rank. Should be a "small multiple of the machine zero". If in doubt, set it to 0.0 and it will be figured out for you. Return value: the chi-square statistics of the fit, or a negative value on error.

size_t RazorBack::Linls_::rank ( ) const [inline]

Returns the rank. Definition at line 70 of file Linls.hh. Referenced by condition().

double RazorBack::Linls_::condition ( ) const [inline]

Returns the condition number. Definition at line 73 of file Linls.hh.

size_t RazorBack::Linls_::deg_freedom ( ) const [inline]

Returns the degrees of freedom. Definition at line 76 of file Linls.hh.

const Vecdbl_ & RazorBack::Linls_::param ( ) const [inline]

Returns the parameter estimate. Definition at line 79 of file Linls.hh.

const Vecdbl_ & RazorBack::Linls_::sdev ( ) const [inline]

Returns the standard deviation of the parameters. Definition at line 82 of file Linls.hh.

const Smatdbl_ & RazorBack::Linls_::correl ( ) const [inline]

Returns the correlation matrix of the parameters. Definition at line 85 of file Linls.hh.

double RazorBack::Linls_::chi_square ( ) const [inline]

Returns the chi-square statistic for the fit quality. Definition at line 88 of file Linls.hh.

double RazorBack::Linls_::residual_dev ( ) const [inline]

Returns the residual deviation for the fit. Definition at line 91 of file Linls.hh.

void RazorBack::Linls_::adjust_dimensions ( const Rmatdbl_ & Xmeas, const Vecdbl_ & Ymeas ) [protected]

void RazorBack::Linls_::make_utb ( const Vecdbl_ & B ) [protected]

size_t RazorBack::Linls_::calc_rank ( const Vecdbl_ & B, double Eps ) const [protected]

void RazorBack::Linls_::calc_params ( const Rmatdbl_ & Xmeas, const Vecdbl_ & Ymeas ) [protected]

double RazorBack::Linls_::calc_chi2 ( const Rmatdbl_ & Xmeas, const Vecdbl_ & Ymeas ) const [protected]

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Member Data Documentation

size_t RazorBack::Linls_::Nm [private]

Definition at line 40 of file Linls.hh.

size_t RazorBack::Linls_::Np [private]

Definition at line 40 of file Linls.hh.

size_t RazorBack::Linls_::Nf [private]

no. of measurements, no.of params, degrees of freedom. Definition at line 40 of file Linls.hh.

Svd_ RazorBack::Linls_::Svd [private]

an SVD object. Definition at line 41 of file Linls.hh.

size_t RazorBack::Linls_::Rank [private]

the rank estimate. Definition at line 42 of file Linls.hh.

Vecdbl_ RazorBack::Linls_::Utb [private]

scalprods of U cols w/ RHS. Definition at line 43 of file Linls.hh.

Vecdbl_ RazorBack::Linls_::P [private]

Definition at line 44 of file Linls.hh.

Vecdbl_ RazorBack::Linls_::Sdev [private]

parameter values and standard deviations. Definition at line 44 of file Linls.hh.

Smatdbl_ RazorBack::Linls_::Correl [private]

parameter correlation matrix. Definition at line 45 of file Linls.hh.

double RazorBack::Linls_::Chi2 [private]

chi-square. Definition at line 46 of file Linls.hh.

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

• Linls.hh

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