SelectionRegression.Compute Method (Double[,], Double[], Double[])

SelectionRegressionCompute Method (Double, Double, Double)

Computes the best weighted multiple linear regression models.

Namespace: Imsl.Stat
Assembly: ImslCS (in ImslCS.dll) Version: 6.5.2.0

Syntax

public virtual void Compute(
	double[,] x,
	double[] y,
	double[] weights
)

Public Overridable Sub Compute ( 
	x As Double(,),
	y As Double(),
	weights As Double()
)

public:
virtual void Compute(
	array<double,2>^ x, 
	array<double>^ y, 
	array<double>^ weights
)

abstract Compute : 
        x : float[,] * 
        y : float[] * 
        weights : float[] -> unit 
override Compute : 
        x : float[,] * 
        y : float[] * 
        weights : float[] -> unit

Parameters

x: Type: SystemDouble
A double matrix containing the observations of the candidate (independent) variables.
y: Type: SystemDouble
A double array containing the observations of the dependent variable.
weights: Type: SystemDouble
A double array containing the weight for each of the observations.

Exceptions

Exception	Condition
NoVariablesException	is thrown if no variables can enter any model
NegativeWeightException	is thrown if a weight is less than zero.
TooManyObsDeletedException	is thrown if more observations have been deleted than were originally entered
MoreObsDelThanEnteredException	is thrown if more observations are being deleted from the output covariance matrix than were originally entered
DiffObsDeletedException	is thrown if different observations are being deleted from the return matrix than were originally entered

Remarks

The number of columns in x must be equal to the number of variables set in the constructor.

Reference

SelectionRegression Class

Compute Overload

Imsl.Stat Namespace