using System;

​

using Accord.Statistics.Models.Regression.Linear;

​

using Accord.Statistics.Models.Regression.Fitting;

​

class Program

{

    static void Main()

    {

        // Sample data (replace this with your actual x and y data)

        double[] x = { 65.0, 70.0, 75.0, 80.0, 90.0, 100.0, 110.0, 115.0, 120.0, 130.0, 140.0, 150.0, 160.0, 180.0, 200.0 };

        double[] y = { 255.0, 255.0, 254.0, 254.0, 254.0, 254.0, 251.0, 250.0, 240.0, 239.0, 230.0, 224.0, 221.0, 215.0, 214.0 };

​

​

        // Degree of the polynomial

        int degree = 3;

​

        // Compute the polynomial regression coefficients

        double [] coeffs = ComputePolynomialRegressionCoefficients(x, y, degree);

        for(int i = 0 ; i<degree;i++)

            Console.WriteLine(coeffs[i]);

    }

​

    static double[] ComputePolynomialRegressionCoefficients(double[] x, double[] y, int degree)

    {

        // We can create a learning algorithm

            var ls = new PolynomialLeastSquares()

            {

                Degree = degree

            };

        // Create the polynomial regression

        PolynomialRegression  polynomialRegression = ls.Learn(x, y);

        double[] coeffs= polynomialRegression.Weights;

        Console.WriteLine("R_square = "+polynomialRegression.CoefficientOfDetermination(x,y));

        return coeffs;

    }

}

​