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SelectionRegressionCompute Method (Double, Double, Double, Double)
Computes the best weighted multiple linear regression models using frequencies for each observation.

Namespace: Imsl.Stat
Assembly: ImslCS (in ImslCS.dll) Version: 6.5.2.0
Syntax
public virtual void Compute(
	double[,] x,
	double[] y,
	double[] weights,
	double[] frequencies
)

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.
frequencies
Type: SystemDouble
A double array containing the frequency for each of the observations of x.
Exceptions
ExceptionCondition
NoVariablesException is thrown if no variables can enter any model
NegativeFreqException is thrown if a frequency is less than zero.
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.

See Also