/// <summary>
/// Generates a random sample from the distribution based on
/// current distribution parameters.
/// </summary>
/// <param name="sdScalingFactor"></param>
/// <param name="incrementalStandardDeviation"></param>
/// <returns></returns>
public double GenerateSample(double sdScalingFactor = 1.0, Func <double, double> incrementalStandardDeviation = null)
{
double tau = DistributionRandomDraws.GammaRandomDraw(Alpha, Beta);
double variance = Lambda / (Lambda * tau);
double incrementalSDValue = 0;
if (incrementalStandardDeviation != null)
{
incrementalSDValue = incrementalStandardDeviation(System.Math.Sqrt(variance));
}
double stdDev = System.Math.Sqrt(variance) + incrementalSDValue;
return(DistributionRandomDraws.GaussianRandomDraw(Mu, stdDev * sdScalingFactor));
}
public static void Test()
{
List <float> vals = new List <float>();
BayesianNormalEstimator bayes = new BayesianNormalEstimator(0, 1, 1.2, 0.01);
for (int i = 0; i < 200; i++)
{
double r = DistributionRandomDraws.GaussianRandomDraw(-2, 0.3);
bayes.AddSample(r);
}
Console.WriteLine(bayes.ToString());
Console.WriteLine();
for (int j = 0; j < 100; j++)
{
double x = bayes.GenerateSample();
vals.Add((float)x);
}
Console.WriteLine(StatUtils.Average(vals));
Console.WriteLine(StatUtils.StdDev(vals));
}
