using System;
using System.Text;
using System.Runtime.InteropServices;
using NagLibrary;

public class NagG02Functions
{
    public static void Main()
    {
        nag_declarations.Nag_IncludeMean mean = nag_declarations.Nag_IncludeMean.Nag_MeanInclude;
        int n = 12;
        int m = 4;
        int ip = (mean == nag_declarations.Nag_IncludeMean.Nag_MeanInclude ? m + 1 : m);
        int tdx = m;
        int tdq = ip + 1;
        double[] x = new double[] { 1.0, 0.0, 0.0, 0.0,
                                    0.0, 0.0, 0.0, 1.0,
                                    0.0, 1.0, 0.0, 0.0,
                                    0.0, 0.0, 1.0, 0.0,
                                    0.0, 0.0, 0.0, 1.0,
                                    0.0, 1.0, 0.0, 0.0,
                                    0.0, 0.0, 0.0, 1.0,
                                    1.0, 0.0, 0.0, 0.0,
                                    0.0, 0.0, 1.0, 0.0,
                                    1.0, 0.0, 0.0, 0.0,
                                    0.0, 0.0, 1.0, 0.0,
                                    0.0, 1.0, 0.0, 0.0 };
        double[] y = new double[] { 33.63, 39.62, 38.18, 41.46, 38.02,
                                    35.83, 35.99, 36.58, 42.92, 37.80,
                                    40.43, 37.89 };
        int[] sx = new int[m];
        double[] b = new double[ip];
        double[] se = new double[ip];
        double[] cov = new double[ip * (ip + 1) / 2];
        double[] res = new double[n];
        double[] h = new double[n];
        double[] q = new double[n * (ip + 1)];
        double[] p = new double[2 * ip + ip * ip];
        double[] com_ar = new double[5 * (ip - 1) + ip * ip];
        nag_declarations.Nag_Boolean svd = nag_declarations.Nag_Boolean.Nag_FALSE;
        int rank = 0;
        double[] wt = new double[n];
        double rss = 0.0, df = 0.0, tol = 0.00001;
        nag_declarations.NagError fail = new nag_declarations.NagError();
        fail.message = new byte[512];
        Encoding enc = Encoding.ASCII;

        for (int i = 0; i < m; i++)
            sx[i] = 1;
        for (int i = 0; i < n; i++)
            wt[i] = 1.0;

        /* nag_regsn_mult_linear (g02dac).
         * Fits a general (multiple) linear regression model
         */
        nag_declarations.nag_regsn_mult_linear(mean, n, x, tdx, m, sx, ip, y, wt, ref rss, ref df,
                                               b, se, cov, res, h, q, tdq, ref svd, ref rank, p,
                                               tol, com_ar, ref fail);
        if (fail.code != 0)
        {
            Console.WriteLine("Error from nag_regsn_mult_linear (g02dac):");
            Console.WriteLine(enc.GetString(fail.message));
        }
        else
        {
            if (svd == nag_declarations.Nag_Boolean.Nag_TRUE)
                Console.WriteLine("Model not of full rank, rank = {0}", rank);
            Console.WriteLine("Residual sum of squares = {0,12:e4}", rss);
            Console.WriteLine("Degrees of freedom = {0, 3:f1}", df);
            Console.WriteLine();
            Console.WriteLine("Variable    Parameter estimate   Standard error");
            for (int j = 0; j < ip; j++)
                Console.WriteLine("{0, 6:d} {1, 20:e4} {2, 20:e4}", j + 1, b[j], se[j]);
            Console.WriteLine();
            Console.WriteLine("    Obs         Residuals              h");
            for (int i = 0; i < n; i++)
                Console.WriteLine("{0, 6:d} {1, 20:e4} {2, 20:e4}", i + 1, res[i], h[i]);
        }
    }
}