/// <summary>
/// Defines a sample stream for a biniomian distribution
/// </summary>
/// <param name="random">The random source</param>
/// <param name="n">The number of trials</param>
/// <param name="p">The probability of success of a given trial</param>
public static IEnumerable <int> SampleBinomial(this IPolyrand random, int n, double p)
{
var sysrand = SysRand.Derive(random);
while (true)
{
yield return(MlStats.SampleFromBinomial(sysrand, n, p));
}
}
public static IEnumerable <float> SampleLaplace(this IPolyrand random, float mean, float scale)
{
var sysrand = SysRand.Derive(random);
while (true)
{
yield return(MlStats.SampleFromLaplacian(sysrand, mean, scale));
}
}
/// <summary>
/// Defines a sample stream for a poisson distribution which represents the probability of
/// a given number of independent events occurring over a period of time at a constant rate
/// </summary>
/// <param name="random">The random source</param>
/// <param name="lambda">The constant rate of occurrence</param>
public static IEnumerable <int> SamplePoisson(this IPolyrand random, double lambda)
{
var sysrand = SysRand.Derive(random);
while (true)
{
yield return(MlStats.SampleFromPoisson(sysrand, lambda));
}
}
public static IEnumerable <double> SampleBeta2(this IPolyrand random, double alpha, double beta)
{
var sysrand = SysRand.Derive(random);
while (true)
{
yield return(MlStats.SampleFromBeta(sysrand, alpha, beta));
}
}
/// <summary>
/// Defines a sample stream for a biniomian distribution
/// </summary>
/// <param name="random">The random source</param>
/// <param name="n">The number of trials</param>
/// <param name="p">The probability of success of a given trial</param>
public static IEnumerable <T> SampleBinomial <T>(this IPolyrand random, T n, double p)
where T : struct
{
var sysrand = SysRand.Derive(random);
while (true)
{
yield return(convert <T>(MlStats.SampleFromBinomial(sysrand, convert <T, int>(n), p)));
}
}
public static IEnumerable <T> SampleLaplace <T>(this IPolyrand random, T mean, T scale)
where T : struct
{
var sysrand = SysRand.Derive(random);
while (true)
{
yield return(convert <T>((MlStats.SampleFromLaplacian(sysrand, convert <T, float>(mean), convert <T, float>(scale)))));
}
}
/// <summary>
/// Defines a sample stream for a poisson distribution which represents the probability of
/// a given number of independent events occurring over a period of time at a constant rate
/// </summary>
/// <param name="random">The random source</param>
/// <param name="lambda">The constant rate of occurrence</param>
public static IEnumerable <T> SamplePoisson <T>(this IPolyrand random, T lambda)
where T : struct
{
var sysrand = SysRand.Derive(random);
var l = convert <T, double>(lambda);
while (true)
{
yield return(convert <T>(MlStats.SampleFromPoisson(sysrand, l)));
}
}
public static IEnumerable <double[]> SampleDirichlet(IPolyrand random, double[] alphas)
{
var sysrand = SysRand.Derive(random);
while (true)
{
var dst = new double[alphas.Length];
MlStats.SampleFromDirichlet(sysrand, alphas, dst);
yield return(dst);
}
}
public static System.Random ToSysRand(this IPolyrand rng) => SysRand.Derive(rng);
