/// <summary>
/// Find the model parameters β such that their linear combination with all predictor-arrays in X become as close to their response in Y as possible, with least squares residuals.
/// Uses the cholesky decomposition of the normal equations.
/// </summary>
/// <param name="samples">Sequence of predictor-arrays and their response.</param>
/// <param name="intercept">True if an intercept should be added as first artificial predictor value. Default = false.</param>
/// <param name="method">The direct method to be used to compute the regression.</param>
/// <returns>Best fitting list of model parameters β for each element in the predictor-arrays.</returns>
public static T[] DirectMethod <T>(IEnumerable <Tuple <T[], T> > samples, bool intercept = false, DirectRegressionMethod method = DirectRegressionMethod.NormalEquations) where T : struct, IEquatable <T>, IFormattable
{
switch (method)
{
case DirectRegressionMethod.NormalEquations:
return(NormalEquations(samples, intercept));
case DirectRegressionMethod.QR:
return(QR(samples, intercept));
case DirectRegressionMethod.Svd:
return(Svd(samples, intercept));
default:
throw new NotSupportedException(method.ToString());
}
}
/// <summary>
/// Find the model parameters β such that X*β with predictor X becomes as close to response Y as possible, with least squares residuals.
/// </summary>
/// <param name="x">Predictor matrix X</param>
/// <param name="y">Response matrix Y</param>
/// <param name="method">The direct method to be used to compute the regression.</param>
/// <returns>Best fitting vector for model parameters β</returns>
public static Matrix <T> DirectMethod <T>(Matrix <T> x, Matrix <T> y, DirectRegressionMethod method = DirectRegressionMethod.NormalEquations) where T : struct, IEquatable <T>, IFormattable
{
switch (method)
{
case DirectRegressionMethod.NormalEquations:
return(NormalEquations(x, y));
case DirectRegressionMethod.QR:
return(QR(x, y));
case DirectRegressionMethod.Svd:
return(Svd(x, y));
default:
throw new NotSupportedException(method.ToString());
}
}