public ParkMillerNormal(long seed)
: base(seed)
{
bReady = false; // Initially, no stored variate avaiable!
dStored = -PZMath_machine.PZMath_DBL_MAX; // Set to arbitrary number
_ran0 = new ParkMillerUniform(seed);
_ran1 = new ParkMillerUniform(seed + 100);
}
/// <summary>
/// reset seed and work space
/// </summary>
protected override void Reset()
{
_random = new ParkMillerUniform(_seed);
}
/// <summary>
/// ChiSquare distribution example
/// </summary>
public static void ExampleSample()
{
ParkMillerUniform random = new ParkMillerUniform();
string folderName = System.Environment.GetFolderPath(System.Environment.SpecialFolder.Desktop) + "\\";
double k = 4.0;
string fileName1 = folderName + "ChiSquare distribution.txt";
FileStream fs1 = new FileStream(fileName1, FileMode.Create, FileAccess.Write);
StreamWriter w1 = new StreamWriter(fs1);
for (int i = 0; i < 10000; i++)
w1.WriteLine(ChiSquareDistribution.Sampler(random, k));
w1.Close();
fs1.Close();
// computational cost of the method
DateTime startTime1 = DateTime.Now;
double result1 = 0.0;
for (int i = 0; i < 10000; i++)
result1 = ChiSquareDistribution.Sampler(random, k);
DateTime endTime1 = DateTime.Now;
TimeSpan duration1 = endTime1 - startTime1;
Console.WriteLine("ChiSquare distribution running time (n = 10,000): " + duration1);
}
/// <summary>
/// reset seed and work space
/// </summary>
protected override void Reset()
{
bReady = false; // Initially, no stored variate avaiable!
dStored = -PZMath_machine.PZMath_DBL_MAX; // Set to arbitrary number
_ran0 = new ParkMillerUniform(_seed);
_ran1 = new ParkMillerUniform(_seed + 100);
}
/// <summary>
/// reset seed and work space
/// </summary>
protected override void Reset()
{
_alpha = _k;
_beta = 1 / _theta;
_random = new ParkMillerUniform(_seed);
}
/// <summary>
/// Gamma distribution example
/// </summary>
public static void ExampleSample()
{
ParkMillerUniform random = new ParkMillerUniform();
string folderName = System.Environment.GetFolderPath(System.Environment.SpecialFolder.Desktop) + "\\";
double k = 2.0;
double theta = 2.0;
double alpha = k;
double beta = 1 / theta;
// Knuth method
string fileName1 = folderName + "Gamma distribution Knuth method.txt";
FileStream fs1 = new FileStream(fileName1, FileMode.Create, FileAccess.Write);
StreamWriter w1 = new StreamWriter(fs1);
for (int i = 0; i < 10000; i++)
w1.WriteLine(GammaDistribution.SampleKnuth(random, k, theta));
w1.Close();
fs1.Close();
// computational cost of Kunth method
DateTime startTime1 = DateTime.Now;
double result1 = 0.0;
for (int i = 0; i < 10000; i++)
result1 = GammaDistribution.SampleKnuth(random, k, theta);
DateTime endTime1 = DateTime.Now;
TimeSpan duration1 = endTime1 - startTime1;
Console.WriteLine("ChiSquare distribution Knuth method running time (n = 10,000): " + duration1);
// MT method
string fileName2 = folderName + "Gamma distribution MT method.txt";
FileStream fs2 = new FileStream(fileName2, FileMode.Create, FileAccess.Write);
StreamWriter w2 = new StreamWriter(fs2);
for (int i = 0; i < 10000; i++)
w2.WriteLine(GammaDistribution.SampleMarsagliaAndTsang(random, alpha, beta));
w2.Close();
fs2.Close();
// computational cost of the method
DateTime startTime2 = DateTime.Now;
double result2 = 0.0;
for (int i = 0; i < 10000; i++)
result2 = GammaDistribution.SampleKnuth(random, alpha, beta);
DateTime endTime2 = DateTime.Now;
TimeSpan duration2 = endTime2 - startTime2;
Console.WriteLine("ChiSquare distribution Knuth method running time (n = 10,000): " + duration2);
}
/// <summary>
/// normal distribution example
/// </summary>
public static void ExampleSample()
{
ParkMillerUniform random = new ParkMillerUniform();
string folderName = System.Environment.GetFolderPath(System.Environment.SpecialFolder.Desktop) + "\\";
double mu = 1.0;
double sigma = 2.0;
// example of Polar method
string fileName1 = folderName + "Polar method.txt";
FileStream fs1 = new FileStream(fileName1, FileMode.Create, FileAccess.Write);
StreamWriter w1 = new StreamWriter(fs1);
for (int i = 0; i < 10000; i ++)
w1.WriteLine(NormalDistribution.SamplerPolar(random, mu, sigma));
w1.Close();
fs1.Close();
// computational cost of Polar method
DateTime startTime1 = DateTime.Now;
double result1 = 0.0;
for (int i = 0; i < 10000; i++)
result1 = NormalDistribution.SamplerPolar(random, mu, sigma);
DateTime endTime1 = DateTime.Now;
TimeSpan duration1 = endTime1 - startTime1;
Console.WriteLine("Polar method running time (n = 10,000): " + duration1);
// example of Ratio method
string fileName2 = folderName + "Ratio method.txt";
FileStream fs2 = new FileStream(fileName2, FileMode.Create, FileAccess.Write);
StreamWriter w2 = new StreamWriter(fs2);
for (int i = 0; i < 10000; i ++)
w2.WriteLine(NormalDistribution.SamplerRatio(random, mu, sigma));
w2.Close();
fs2.Close();
// computational cost of Polar method
DateTime startTime2 = DateTime.Now;
double result2 = 0.0;
for (int i = 0; i < 10000; i++)
result2 = NormalDistribution.SamplerRatio(random, mu, sigma);
DateTime endTime2 = DateTime.Now;
TimeSpan duration2 = endTime2 - startTime1;
Console.WriteLine("Ratio method running time (n = 10,000): " + duration2);
}
/// <summary>
/// evolve Strauss process, C. J. Geyer 1999
/// start from empty point array
/// birth-death algorithm
/// </summary>
private void EvolveStraussProcessStartFromEmpty(List<PZPoint[]> sampleList,
double theta1, double theta2, double r,
double lamda, double width, double height,
int total, int burIn, int space,
List<double> birthAcceptRateList, List<double> deathAcceptRateList,
List<int> numberPointsList, List<int> numberClosePointsList)
{
ParkMillerUniform uniformRandom = new ParkMillerUniform();
PZPoint[] oldPointArray = new PZPoint[0];
PZPoint[] newPointArray;
double birthRate = 0;
double deathRate = 0;
double birthAcceptRate = 0;
double deathAcceptRate = 0;
bool acceptNewPointArray = false;
int spaceCount = 0;
// MCMC evolving process
for (int i = 0; i < _total; i++)
{
// birth or death
if (oldPointArray.Length == 0)
// birth only
{
birthRate = 1.0;
deathRate = 0.0;
}
else
{
birthRate = uniformRandom.Sample();
deathRate = 1 - birthRate;
}
int nx = oldPointArray.Length;
int sx = S(oldPointArray, r);
if (birthRate >= deathRate)
// birth
{
// simulate xi distributed proportional to lamda
PZPoint xi = new PZPoint(width * uniformRandom.Sample(), height * uniformRandom.Sample());
newPointArray = new PZPoint[nx + 1];
// get new point array
Array.Copy(oldPointArray, newPointArray, nx);
newPointArray[nx] = xi;
// birth accept rate
birthAcceptRate = BirthAcceptRate(oldPointArray, newPointArray, lamda, width, height, theta1, theta2, r);
birthAcceptRate = birthAcceptRate < 1.0 ? birthAcceptRate : 1.0;
acceptNewPointArray = uniformRandom.Sample() < birthAcceptRate;
}
else
// death
{
int removeIndex = (int)System.Math.Floor(nx * uniformRandom.Sample());
int nxNew = nx - 1;
newPointArray = new PZPoint[nxNew];
// get new point array
if (nx - 1 > 0)
{
for (int indexNew = 0, indexOld = 0; indexNew < nxNew; indexNew++, indexOld ++)
{
if (indexOld != removeIndex)
{
newPointArray[indexNew] = oldPointArray[indexOld];
}
else
{
indexNew--;
}
}
}
// death accept rate
deathAcceptRate = DeathAcceptRate(oldPointArray, newPointArray, lamda, width, height, theta1, theta2, r);
deathAcceptRate = deathAcceptRate < 1.0 ? deathAcceptRate : 1.0;
acceptNewPointArray = uniformRandom.Sample() < deathAcceptRate;
}
if (acceptNewPointArray)
// accept new point array
{
oldPointArray = newPointArray;
}
else
// reject new point array
{
}
// record MCMC
if (i > burIn)
{
if (spaceCount == space)
{
numberPointsList.Add(nx);
numberClosePointsList.Add(sx);
if (birthRate > deathRate)
birthAcceptRateList.Add(birthAcceptRate);
else
deathAcceptRateList.Add(deathAcceptRate);
spaceCount = 0;
PZPoint[] recordPointArray = new PZPoint[oldPointArray.Length];
Array.Copy(oldPointArray, recordPointArray, oldPointArray.Length);
sampleList.Add(recordPointArray);
}
}
spaceCount++;
}
}
