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

import com.imsl.math.*;
import com.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. * ((double)(k)/(double)(n-1));
            y[k] = 1./(.1 + Math.pow(3.*(x[k]-1.),4));
        }
        
        //	Seed the random number generator
        Random rn = new Random();
        rn.setSeed(1234579);
        rn.setMultiplier(16807);
        
        //	Contaminate the data
        for (int i = 0; i < n; i++) {
            y[i] = y[i] + 2. * rn.nextFloat() - 1.;
        }
        
        //	Set the weights
        double sdev = 1./Math.sqrt(3.);
        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.value(0.3010);
        System.out.println("The computed cubic spline value at point .3010 is "
        + csv);
    }
}

Output

The computed cubic spline value at point .3010 is 0.06458434076781128