MultipleRegressionNormalEquationsT(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 the cholesky decomposition of the normal equations.
Namespace: Altaxo.Calc.LinearRegressionAssembly: AltaxoCore (in AltaxoCore.dll) Version: 4.8.3572.0 (4.8.3572.0)
Syntaxpublic static T[] NormalEquations<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
TBest fitting list of model parameters β for each element in the predictor-arrays.
See Also