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

Computes the best weighted multiple linear regression models using frequencies for each observation.

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

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

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

Exception Type	Condition
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