| MultipleRegressionNormalEquationsT Method (T, 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 public static T[] NormalEquations<T>(
T[][] x,
T[] y,
bool intercept = false
)
where T : struct, new(), IEquatable<T>, IFormattable
Parameters
- x
- Type: T
List of predictor-arrays. - y
- Type: T
List of responses - intercept (Optional)
- Type: SystemBoolean
True if an intercept should be added as first artificial predictor value. Default = false.
Type Parameters
- T
Return Value
Type:
TBest fitting list of model parameters β for each element in the predictor-arrays.
See Also