MultipleRegressionSvdT(T, T, Boolean) 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 a singular value decomposition and is therefore more numerically stable (especially if ill-conditioned) than the normal equations or QR but also slower.

Namespace: Altaxo.Calc.LinearRegression
Assembly: AltaxoCore (in AltaxoCore.dll) Version: 4.8.3572.0 (4.8.3572.0)

Syntax

Copy

public static T[] Svd<T>(
	T[][] x,
	T[] y,
	bool intercept = false
)
where T : struct, new(), IEquatable<T>, IFormattable

Parameters

x T: List of predictor-arrays.
y T: List of responses
intercept Boolean (Optional): True if an intercept should be added as first artificial predictor value. Default = false.

Type Parameters

T: The type of the predictor and response values.

Return Value

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

Reference

MultipleRegression Class

Svd Overload

Altaxo.Calc.LinearRegression Namespace