/// <summary>
/// Computes the cumulative distribution (CDF) of the distribution at x, i.e. P(X ≤ x).
/// </summary>
/// <param name="x">The location at which to compute the cumulative distribution function.</param>
/// <returns>the cumulative distribution at location <paramref name="x"/>.</returns>
public double CumulativeDistribution(double x)
{
// TODO JVG we can probably do a better job for Cauchy special case
if (Double.IsPositiveInfinity(_freedom))
{
return(Normal.CDF(_location, _scale, x));
}
var k = (x - _location) / _scale;
var h = _freedom / (_freedom + (k * k));
var ib = 0.5 * SpecialFunctions.BetaRegularized(_freedom / 2.0, 0.5, h);
return(x <= _location ? ib : 1.0 - ib);
}
/// <summary>
/// Computes the cumulative distribution (CDF) of the distribution at x, i.e. P(X ≤ x).
/// </summary>
/// <param name="x">The location at which to compute the cumulative distribution function.</param>
/// <param name="location">The location (μ) of the distribution.</param>
/// <param name="scale">The scale (σ) of the distribution. Range: σ > 0.</param>
/// <param name="freedom">The degrees of freedom (ν) for the distribution. Range: ν > 0.</param>
/// <returns>the cumulative distribution at location <paramref name="x"/>.</returns>
/// <seealso cref="CumulativeDistribution"/>
public static double CDF(double location, double scale, double freedom, double x)
{
if (scale <= 0.0 || freedom <= 0.0)
{
throw new ArgumentException(Resources.InvalidDistributionParameters);
}
// TODO JVG we can probably do a better job for Cauchy special case
if (double.IsPositiveInfinity(freedom))
{
return(Normal.CDF(location, scale, x));
}
var k = (x - location) / scale;
var h = freedom / (freedom + (k * k));
var ib = 0.5 * SpecialFunctions.BetaRegularized(freedom / 2.0, 0.5, h);
return(x <= location ? ib : 1.0 - ib);
}
/// <summary>
/// Computes the cumulative distribution (CDF) of the distribution at x, i.e. P(X ≤ x).
/// </summary>
/// <param name="x">The location at which to compute the cumulative distribution function.</param>
/// <param name="alpha">The stability (α) of the distribution. Range: 2 ≥ α > 0.</param>
/// <param name="beta">The skewness (β) of the distribution. Range: 1 ≥ β ≥ -1.</param>
/// <param name="scale">The scale (c) of the distribution. Range: c > 0.</param>
/// <param name="location">The location (μ) of the distribution.</param>
/// <returns>the cumulative distribution at location <paramref name="x"/>.</returns>
/// <seealso cref="CumulativeDistribution"/>
public static double CDF(double alpha, double beta, double scale, double location, double x)
{
if (alpha <= 0.0 || alpha > 2.0 || beta < -1.0 || beta > 1.0 || scale <= 0.0)
{
throw new ArgumentException(Resources.InvalidDistributionParameters);
}
if (alpha == 2d)
{
return(Normal.CDF(location, Constants.Sqrt2 * scale, x));
}
if (alpha == 1d && beta == 0d)
{
return(Cauchy.CDF(location, scale, x));
}
if (alpha == 0.5d && beta == 1d)
{
return(SpecialFunctions.Erfc(Math.Sqrt(scale / (2 * (x - location)))));
}
throw new NotSupportedException();
}
internal static double CumulativeDistributionImpl(double mu, double lambda, double x)
{
return(Normal.CDF(0, 1, Math.Sqrt(lambda / x) * (x / mu - 1)) + Math.Exp(2 * lambda / mu) * Normal.CDF(0, 1, -Math.Sqrt(lambda / x) * (x / mu + 1)));
}