Examples - pi.science.regression.PIPolynomialRegression
1. How to compute polynomial regression, degree 2, for X and Y values ?
/* change decimal places count in formulas */
PIConfiguration.REGRESSION_DECIMAL_PLACES = 6;
/* - prepare X data for regression */
PIVariable X = new PIVariable();
X.AddMoreValues( 50.0, 3 );
X.AddMoreValues( 70.0, 3 );
X.AddMoreValues( 80.0, 3 );
X.AddMoreValues( 90.0, 3 );
X.AddMoreValues( 100.0, 3 );
/* - prepare Y data for regression */
PIVariable Y = new PIVariable();
Y.AddValues( new double[] { 3.3, 2.8, 2.9, 2.3, 2.6, 2.1, 2.5, 2.9, 2.4, 3.0, 3.1, 2.8, 3.3,3.5,3.0 } );
/* - create and compute regression */
PIPolynomialRegression polynomialRegression = new PIPolynomialRegression( X, Y, 2 );
/* show degree */
Console.WriteLine( "degree = " + polynomialRegression.Get_degree() );
/* calculate */
polynomialRegression.Calc();
/* - show results */
Console.WriteLine( polynomialRegression.GetTextFormula() );
Console.WriteLine( polynomialRegression.GetTextFormulaFilled() );
PIDebug.Blank();
Console.WriteLine( polynomialRegression.Get_coefficients().AsString( 3 ) );
/* - calc prediction for X = 80 */
PIDebug.Blank();
Console.WriteLine( "Prediction for X=80 : " + polynomialRegression.CalcPredictedY( 80.0 ) );
PIDebug.Blank();
Console.WriteLine( "Prediction errors:" );
Console.WriteLine( polynomialRegression.GetErrors().AsString( 5 ) );
Output:
degree = 2
y = A + Bx + Cx^2
y = 7.960481 - 0.153711x + 0.001076x^2
7.960;-0.154;0.001
Prediction for X=80 : 2.5474226804128497
Prediction errors:
0.33608;-0.16392;-0.06392;-0.17113;0.12887;-0.37113;-0.04742;0.35258;-0.14742;0.16117;
0.26117;-0.03883;-0.04536;0.15464;-0.34536
