Example: The cubic spline interpolant to noisy data with supplied weights

using System;
using Imsl.Math;
using Imsl.Stat;

public class CsSmoothC2Ex1
{
	public static void  Main(String[] args)
	{
		//	Set up a grid
		int n = 300;
		double[] x = new double[n];
		double[] y = new double[n];
		for (int k = 0; k < n; k++)
		{
			x[k] = 3.0 * ((double) (k) / (double) (n - 1));
			y[k] = 1.0 / (.1 + System.Math.Pow(3.0 * (x[k] - 1.0), 4));
		}
		
		//	Seed the random number generator
		Imsl.Stat.Random rn = new Imsl.Stat.Random(1234579);
		rn.Multiplier = 16807;
		
		//	Contaminate the data
		for (int i = 0; i < n; i++)
		{
			y[i] = y[i] + 2.0 * (float) rn.NextDouble() - 1.0;
		}
		
		//	Set the weights
		double sdev = 1.0 / System.Math.Sqrt(3.0);
		double[] weights = new double[n];
		for (int i = 0; i < n; i++)
		{
			weights[i] = sdev;
		}
		
		//	Set the smoothing parameter
		double smpar = (double) n;
		
		//	Smooth the data
		CsSmoothC2 cs = new CsSmoothC2(x, y, weights, smpar);
		double csv = cs.Eval(0.3010);
		Console.Out.WriteLine("The computed cubic spline value at " +
			                  "point .3010 is " + csv);
	}
}

Output

The computed cubic spline value at point .3010 is 0.0335028881575695