/// <summary>
/// Generate massive of normal distribution
/// </summary>
/// <param name="n">N</param>
/// <param name="iseed">Iseed number</param>
/// <returns>Massive of normal random numbers</returns>
public List<double> GenCustomNormal(int n, int iseed = 2147483646)
{
// Save primal number to create output list
var curN = n;
if (n % 2 != 0)
{
n++;
}
// Local variables
int i;
// For custom random method
var random = new CustomRandom(iseed);
// Parameter adjustments
var massive = new double[n];
// Body of normal
var nn = n;
var m = n - (n / 2 << 1);
if (m != 0)
{
--nn;
}
var i1 = nn;
for (i = 0; i < i1; i += 2)
{
L1:
var u = random.GenRandNumbCustom();
var v = random.GenRandNumbCustom();
u = u + u - 1;
v = v + v - 1;
var sum = u * u + v * v;
if (sum >= 1)
{
goto L1;
}
var sln = (float)Math.Log(sum);
sln = (float)Math.Sqrt(((-sln - sln) / sum));
massive[i] = u * sln;
massive[i + 1] = v * sln;
}
var massNormaList = new List<double>();
for (var j = 0; j < curN; j++)
{
massNormaList.Add(massive[j]);
}
return massNormaList;
}
/// <summary>
/// Approximate calculation of the integral
/// </summary>
/// <returns></returns>
public double Integral()
{
var random = new CustomRandom(Environment.TickCount);
var underGraph = 0;
const int accuracy = 1000000;
for (var i = 0; i < accuracy; i++)
{
var randNumberX = random.GenRandNumbCustom();
var randNumberY = random.GenRandNumbCustom();
underGraph = Y(randNumberX) > randNumberY ? underGraph + 1 : underGraph;
}
return Convert.ToDouble((double)underGraph/accuracy);
}
