RWAddPredictors<T,S>

Does not inherit

• Local Index
• Synopsis
• Description
• Example
• Public Constructors
• Public Member Functions

Members

baseToLast() newObservationVec() newRegressionMat()

numAdded() RWAddPredictors() setBaseToLast()

setNewObservationVec() setNewRegressionMat() setNumAdded()

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

Class RWAddPredictors<T,S> 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.

#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;
}

RWAddPredictors();

Default constructor. Constructs an empty RWAddPredictors object.

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

Copy constructor. Constructs a copy of a.

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

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.

bool 
baseToLast();

Returns true if the base calculation is to be set to the new regression matrix and new observation vector.

const RWMathVec<S>& 
newObservationVec() const;

Returns the new observation vector.

const RWGenMat<T>& 
newRegressionMat() const;

Returns the new regression matrix.

size_t 
numAdded() const;

Returns the number of predictors added.

void 
setBaseToLast(bool s);

Sets the "base to last" option to s.

void 
setNewObservationVec(const RWMathVec<S>& o);

Sets the new observation to o.

void 
setNewRegressionMat(const RWGenMat<T>& r); 

Sets the new regression matrix to r.

void   
setNumAdded(size_t na); 

Sets the number of predictors added.

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