Examples - pi.science.regression.PIExponentialRegression
1. How to compute exponential regression for X and Y values ?
/* change decimal places count in formulas */
PIConfiguration.REGRESSION_DECIMAL_PLACES = 6;
/* - prepare X data for exponential regression */
PIVariable X = new PIVariable();
X.AddValues( new int[] { 0, 1, 2, 3, 4, 5 } );
/* - prepare Y data for exponential regression */
PIVariable Y = new PIVariable();
Y.AddValues( new int[] { 3, 7, 10, 24, 50, 95 } );
/* - create and compute regression */
PIExponentialRegression ExponentialRegression = new PIExponentialRegression( X, Y );
ExponentialRegression.Calc();
Console.WriteLine( ExponentialRegression.GetTextFormula() );
Console.WriteLine( ExponentialRegression.GetTextFormulaFilled() );
/* - calc prediction for X = 3.5 */
PIDebug.Blank();
Console.WriteLine( "Prediction for X=3.5 : " + ExponentialRegression.CalcPredictedY( 3.5 ) );
PIDebug.Blank();
Console.WriteLine( "Prediction errors:" );
Console.WriteLine( ExponentialRegression.GetErrors().AsString( 5 ) );
Output:
y = A * B^x
y = 3.046450 * 1.988035^x
Prediction for X=3.5 : 33.75032758924823
Prediction errors:
-0.04645;0.94355;-2.04043;0.06320;2.41282;0.39503
