RWAddPredictors< T, S > Class Template Reference

Holds information about the addition of predictor variables to a parameter calculation. More...

#include <rw/analytics/regcalc.h>

Inheritance diagram for RWAddPredictors< T, S >:

Public Member Functions
	RWAddPredictors ()
	RWAddPredictors (const RWAddPredictors< T, S > &a)
	RWAddPredictors (const RWGenMat< T > &r, const RWMathVec< S > o, size_t numAdded, bool setBaseToLast=false)
size_t	numAdded () const
void	setNumAdded (size_t na)
Public Member Functions inherited from RWRegressionDataChange< T, S >
bool	baseToLast () const
const RWMathVec< S > &	newObservationVec () const
const RWGenMat< T > &	newRegressionMat () const
void	setBaseToLast (bool s)
void	setNewObservationVec (const RWMathVec< S > &o)
void	setNewRegressionMat (const RWGenMat< T > &r)

Detailed Description

template<class T, class S>
class RWAddPredictors< T, S >

Class RWAddPredictors holds information about the addition of predictor variables to a parameter calculation object's base calculation. This information must consist of the following:

• The new regression matrix. This is the regression matrix used in the parameter calculation's objects base calculation with the predictors to be added appended.
• The new observation vector. This is assumed to be the same as the observation vector used in the parameter calculation object's base calculation.
• The number of predictors added.

Synopsis

#include <rw/analytics/regcalc.h>
RWAddPredictors<double, double> a;

Example

#include <rw/analytics/lsqqr.h>
#include <rw/rstream.h>
 
int main() {
  // Full model regression matrix.
  RWGenMat<double> regMat(
      "6x3 ["
      " 1  1.3 .54"
      " 1  3.5 .65"
      " 1 -2.3 .88"
      " 1  8.2 .76"
      " 1 -4.2 .32"
      " 1  2.4 .43"
      "]");
  // Reduced model regression matrix. Contains the first two
  // columns of regMat.
  RWGenMat<double> reducedRegMat(regMat(RWAll, RWSlice(0, 2)));
 
  RWMathVec<double> observationVec( "[12.3 15.6 22.3
                                      44.1 32.5 65.2]" );
 
  RWLeastSqQRCalc calcObject;
  // Set the base calculation for the parameter calculation
  // object to the reduced regression matrix.
  calcObject.setBaseCalc( reducedRegMat, observationVec );
  if ( calcObject.fail() )
 
  {
    cout << "Parameter calculation for reduced model failed" << endl;
    return 1;
  }
  cout << "Parameters for reduced model:" <<
         calcObject.parameters() << endl;
 
  // Add in the predictor data contained in the last column of
  // the full model regression matrix using the data change
  // class RWAddPredictors.
  RWAddPredictors<double,double> dataChange( regMat,
                                            observationVec, 1 );
  calcObject.addPredToBaseCalc( dataChange );
 
  if ( calcObject.fail() )
  {
    cout << "Parameter calculation for full model failed" << endl;
    return 1;
  }
  cout << "Parameters for full model:" <<
          calcObject.parameters() << endl;
  return 0;
}

Constructor & Destructor Documentation

RWAddPredictors() [1/3]

template<class T , class S >

RWAddPredictors< T, S >::RWAddPredictors ( )

inline

Default constructor. Constructs an empty RWAddPredictors object.

RWAddPredictors() [2/3]

template<class T , class S >

RWAddPredictors< T, S >::RWAddPredictors ( const RWAddPredictors< T, S > & a )

inline

Copy constructor. Constructs a copy of a.

RWAddPredictors() [3/3]

template<class T , class S >

RWAddPredictors< T, S >::RWAddPredictors ( const RWGenMat< T > & r, const RWMathVec< S > o, size_t numAdded, bool setBaseToLast = false )

inline

Constructs an RWAddPredictors object with the given regression matrix and observation vector. It assumes that the matrix r is obtained from the base calculations regression matrix by appending numAdded columns, and that the observation vector o is identical to the base calculations. If setBaseToLast is true, the base calculations regression matrix is set to r.

Member Function Documentation

numAdded()

template<class T , class S >

size_t RWAddPredictors< T, S >::numAdded ( ) const

inline

Returns the number of predictors added.

setNumAdded()

template<class T , class S >

void RWAddPredictors< T, S >::setNumAdded ( size_t na )

inline

Sets the number of predictors added.