/// <summary>
/// Initializes a new instance of the <see cref="FractionFactor"/> class.
/// </summary>
/// <param name="value">The value.</param>
/// <param name="exponent">The exponent.</param>
/// <param name="sequence">The sequence.</param>
/// <param name="editable">if set to <see langword="true" /> [editable].</param>
public FractionFactor(double value, IExpression?exponent = null, INumeric?sequence = null, bool editable = false)
: this(Operations.RoundToMixedFraction(value, 16), exponent, sequence, editable)
{
}
/// <summary> /// Errorses this instance. /// </summary> /// <returns></returns> /// <acknowledgment> /// https://github.com/SarahFrem/AutoRegressive_model_cs/blob/master/RegressionLineaire.cs /// </acknowledgment> public double[,] Errors() => Operations.Subtract(responseVariable, Predictions());
/// <summary>
/// Compute the regressors coefficients from MCO
/// beta = inv(X'*X)*X'*Y
/// </summary>
/// <returns>
/// beta
/// </returns>
/// <acknowledgment>
/// https://github.com/SarahFrem/AutoRegressive_model_cs/blob/master/RegressionLineaire.cs
/// </acknowledgment>
public double[,] RegressorsMCO()
{
var R = RegressionMatrix();
var beta = Operations.Multiply(Operations.Multiply(Operations.Inverse(Operations.Multiply(Operations.Transpose(R), R)), Operations.Transpose(R)), responseVariable);
return(beta);
}
/// <summary> /// Predictionses this instance. /// </summary> /// <returns></returns> /// <acknowledgment> /// https://github.com/SarahFrem/AutoRegressive_model_cs/blob/master/RegressionLineaire.cs /// </acknowledgment> public double[,] Predictions() => Operations.Multiply(RegressionMatrix(), RegressorsMCO());