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MultipleRegressionDirectMethodT(IEnumerableTupleT, T, Boolean, DirectRegressionMethod) Method

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.

Namespace: Altaxo.Calc.LinearRegression
Assembly: AltaxoCore (in AltaxoCore.dll) Version: 4.8.3179.0 (4.8.3179.0)
Syntax
C#
Copy
public static T[] DirectMethod<T>(
	IEnumerable<Tuple<T[], T>> samples,
	bool intercept = false,
	DirectRegressionMethod method = DirectRegressionMethod.NormalEquations
)
where T : struct, new(), IEquatable<T>, IFormattable

Parameters

samples  IEnumerableTupleT, T
Sequence of predictor-arrays and their response.
intercept  Boolean  (Optional)
True if an intercept should be added as first artificial predictor value. Default = false.
method  DirectRegressionMethod  (Optional)
The direct method to be used to compute the regression.

Type Parameters

T

[Missing <typeparam name="T"/> documentation for "M:Altaxo.Calc.LinearRegression.MultipleRegression.DirectMethod``1(System.Collections.Generic.IEnumerable{System.Tuple{``0[],``0}},System.Boolean,Altaxo.Calc.LinearRegression.DirectRegressionMethod)"]

Return Value

T
Best fitting list of model parameters β for each element in the predictor-arrays.
See Also