private static void multinomial_sample_test()
//****************************************************************************80
//
// Purpose:
//
// MULTINOMIAL_SAMPLE_TEST tests MULTINOMIAL_SAMPLE.
//
// Licensing:
//
// This code is distributed under the GNU LGPL license.
//
// Modified:
//
// 12 April 2016
//
// Author:
//
// John Burkardt
//
{
const int B = 3;
const int SAMPLE_NUM = 1000;
double[] c =
{
0.125, 0.500, 0.375
}
;
int i;
int j;
int seed = 123456789;
int[] x = new int [B * SAMPLE_NUM];
Console.WriteLine("");
Console.WriteLine("MULTINOMIAL_SAMPLE_TEST");
Console.WriteLine(" MULTINOMIAL_MEAN computes the Multinomial mean;");
Console.WriteLine(" MULTINOMIAL_SAMPLE samples the Multinomial distribution;");
Console.WriteLine(" MULTINOMIAL_VARIANCE computes the Multinomial variance;");
int a = 5;
Console.WriteLine("");
Console.WriteLine(" PDF parameter A = " + a + "");
Console.WriteLine(" PDF parameter B = " + B + "");
typeMethods.r8vec_print(B, c, " PDF parameter C:");
if (!Multinomial.multinomial_check(a, B, c))
{
Console.WriteLine("");
Console.WriteLine("MULTINOMIAL_SAMPLE_TEST - Fatal error!");
Console.WriteLine(" The parameters are not legal.");
return;
}
double[] mean = Multinomial.multinomial_mean(a, B, c);
double[] variance = Multinomial.multinomial_variance(a, B, c);
typeMethods.r8vec_print(B, mean, " PDF mean:");
typeMethods.r8vec_print(B, variance, " PDF variance:");
for (j = 0; j < SAMPLE_NUM; j++)
{
int[] y = Multinomial.multinomial_sample(a, B, c, ref seed);
for (i = 0; i < B; i++)
{
x[i + j * B] = y[i];
}
}
mean = typeMethods.i4row_mean(B, SAMPLE_NUM, x);
variance = typeMethods.i4row_variance(B, SAMPLE_NUM, x);
int[] xmax = typeMethods.i4row_max(B, SAMPLE_NUM, x);
int[] xmin = typeMethods.i4row_min(B, SAMPLE_NUM, x);
Console.WriteLine("");
Console.WriteLine(" Sample size = " + SAMPLE_NUM + "");
Console.WriteLine("");
Console.WriteLine(" Component Mean, Variance, Min, Max:");
Console.WriteLine("");
for (i = 0; i < B; i++)
{
Console.WriteLine(" "
+ (i + 1).ToString(CultureInfo.InvariantCulture).PadLeft(6) + " "
+ mean[i].ToString(CultureInfo.InvariantCulture).PadLeft(12) + " "
+ variance[i].ToString(CultureInfo.InvariantCulture).PadLeft(12) + " "
+ xmin[i].ToString(CultureInfo.InvariantCulture).PadLeft(12) + " "
+ xmax[i].ToString(CultureInfo.InvariantCulture).PadLeft(12) + "");
}
}
