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MultipleRegressionNormalEquationsT Method (IEnumerableTupleT, T, Boolean)
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: MathNet.Numerics.LinearRegression
Assembly: MathNet.Numerics (in MathNet.Numerics.dll) Version: 3.7
Syntax
C#
Copy
public static T[] NormalEquations<T>(
	IEnumerable<Tuple<T[], T>> samples,
	bool intercept = false
)
where T : struct, new(), IEquatable<T>, IFormattable

Parameters

samples
Type: System.Collections.GenericIEnumerableTupleT, T
Sequence of predictor-arrays and their response.
intercept (Optional)
Type: SystemBoolean
True if an intercept should be added as first artificial predictor value. Default = false.

Type Parameters

T

Return Value

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