private static void chi_cdf_test()
//****************************************************************************80
//
// Purpose:
//
// CHI_CDF_TEST tests CHI_CDF, CHI_CDF_INV, CHI_PDF;
//
// Licensing:
//
// This code is distributed under the GNU LGPL license.
//
// Modified:
//
// 26 August 2006
//
// Author:
//
// John Burkardt
//
{
int i;
int seed = 123456789;
Console.WriteLine("");
Console.WriteLine("CHI_CDF_TEST");
Console.WriteLine(" CHI_CDF evaluates the Chi CDF;");
Console.WriteLine(" CHI_CDF_INV inverts the Chi CDF.");
Console.WriteLine(" CHI_PDF evaluates the Chi PDF;");
double a = 1.0;
double b = 2.0;
double c = 3.0;
Console.WriteLine("");
Console.WriteLine(" PDF parameter A = " + a + "");
Console.WriteLine(" PDF parameter B = " + b + "");
Console.WriteLine(" PDF parameter C = " + c + "");
if (!Chi.chi_check(a, b, c))
{
Console.WriteLine("");
Console.WriteLine("CHI_CDF_TEST - Fatal error!");
Console.WriteLine(" The parameters are not legal.");
return;
}
Console.WriteLine("");
Console.WriteLine(" X PDF CDF CDF_INV");
Console.WriteLine("");
for (i = 1; i <= 10; i++)
{
double x = Chi.chi_sample(a, b, c, ref seed);
double pdf = Chi.chi_pdf(x, a, b, c);
double cdf = Chi.chi_cdf(x, a, b, c);
double x2 = Chi.chi_cdf_inv(cdf, a, b, c);
Console.WriteLine(" "
+ x.ToString(CultureInfo.InvariantCulture).PadLeft(12) + " "
+ pdf.ToString(CultureInfo.InvariantCulture).PadLeft(12) + " "
+ cdf.ToString(CultureInfo.InvariantCulture).PadLeft(12) + " "
+ x2.ToString(CultureInfo.InvariantCulture).PadLeft(12) + "");
}
}
private static void chi_sample_test()
//****************************************************************************80
//
// Purpose:
//
// CHI_SAMPLE_TEST tests CHI_MEAN, CHI_SAMPLE, CHI_VARIANCE;
//
// Licensing:
//
// This code is distributed under the GNU LGPL license.
//
// Modified:
//
// 24 January 2007
//
// Author:
//
// John Burkardt
//
{
const int SAMPLE_NUM = 1000;
int i;
int seed = 123456789;
double[] x = new double[SAMPLE_NUM];
Console.WriteLine("");
Console.WriteLine("CHI_SAMPLE_TEST");
Console.WriteLine(" CHI_MEAN computes the Chi mean;");
Console.WriteLine(" CHI_SAMPLE samples the Chi distribution;");
Console.WriteLine(" CHI_VARIANCE computes the Chi variance;");
const double a = 1.0;
const double b = 2.0;
const double c = 3.0;
Console.WriteLine("");
Console.WriteLine(" PDF parameter A = " + a + "");
Console.WriteLine(" PDF parameter B = " + b + "");
Console.WriteLine(" PDF parameter C = " + c + "");
if (!Chi.chi_check(a, b, c))
{
Console.WriteLine("");
Console.WriteLine("CHI_SAMPLE_TEST - Fatal error!");
Console.WriteLine(" The parameters are not legal.");
return;
}
double mean = Chi.chi_mean(a, b, c);
double variance = Chi.chi_variance(a, b, c);
Console.WriteLine("");
Console.WriteLine(" PDF mean = " + mean + "");
Console.WriteLine(" PDF variance = " + variance + "");
for (i = 0; i < SAMPLE_NUM; i++)
{
x[i] = Chi.chi_sample(a, b, c, ref seed);
}
mean = typeMethods.r8vec_mean(SAMPLE_NUM, x);
variance = typeMethods.r8vec_variance(SAMPLE_NUM, x);
double xmax = typeMethods.r8vec_max(SAMPLE_NUM, x);
double xmin = typeMethods.r8vec_min(SAMPLE_NUM, x);
Console.WriteLine("");
Console.WriteLine(" Sample size = " + SAMPLE_NUM + "");
Console.WriteLine(" Sample mean = " + mean + "");
Console.WriteLine(" Sample variance = " + variance + "");
Console.WriteLine(" Sample maximum = " + xmax + "");
Console.WriteLine(" Sample minimum = " + xmin + "");
}