/// <summary>
/// Creates a new <see cref="GeneralContinuousDistribution"/>
/// using only a cumulative distribution function definition.
/// </summary>
///
/// <param name="support">The distribution's support over the real line.</param>
/// <param name="cdf">A cumulative distribution function.</param>
/// <param name="method">The integration method to use for numerical computations.</param>
///
/// <returns>A <see cref="GeneralContinuousDistribution"/> created from the
/// <paramref name="cdf"/> whose measures and functions are computed using
/// numerical integration and differentiation.</returns>
///
public static GeneralContinuousDistribution FromDistributionFunction(
DoubleRange support, Func <double, double> cdf, IUnivariateIntegration method)
{
GeneralContinuousDistribution dist = new GeneralContinuousDistribution();
dist.support = support;
dist.cdf = cdf;
dist.method = method;
return(dist);
}
/// <summary>
/// Creates a new <see cref="GeneralContinuousDistribution"/> with the given PDF and CDF functions.
/// </summary>
///
/// <param name="distribution">A distribution whose properties will be numerically estimated.</param>
///
public GeneralContinuousDistribution(UnivariateContinuousDistribution distribution)
{
if (distribution == null)
{
throw new ArgumentNullException("distribution");
}
this.method = new InfiniteAdaptiveGaussKronrod(100);
this.pdf = distribution.ProbabilityDensityFunction;
this.cdf = distribution.DistributionFunction;
this.support = distribution.Support;
}
/// <summary>
/// Creates a new <see cref="GeneralContinuousDistribution"/> with the given PDF and CDF functions.
/// </summary>
///
/// <param name="support">The distribution's support over the real line.</param>
/// <param name="density">A probability density function.</param>
/// <param name="distribution">A cumulative distribution function.</param>
///
public GeneralContinuousDistribution(DoubleRange support,
Func <double, double> density, Func <double, double> distribution)
{
if (density == null)
{
throw new ArgumentNullException("density");
}
if (distribution == null)
{
throw new ArgumentNullException("distribution");
}
this.method = new InfiniteAdaptiveGaussKronrod(100);
this.pdf = density;
this.cdf = distribution;
this.support = support;
}
/// <summary>
/// Creates a new <see cref="GeneralContinuousDistribution"/>
/// using only a cumulative distribution function definition.
/// </summary>
///
/// <param name="support">The distribution's support over the real line.</param>
/// <param name="cdf">A cumulative distribution function.</param>
/// <param name="method">The integration method to use for numerical computations.</param>
///
/// <returns>A <see cref="GeneralContinuousDistribution"/> created from the
/// <paramref name="cdf"/> whose measures and functions are computed using
/// numerical integration and differentiation.</returns>
///
public static GeneralContinuousDistribution FromDistributionFunction(
DoubleRange support, Func<double, double> cdf, IUnivariateIntegration method)
{
GeneralContinuousDistribution dist = new GeneralContinuousDistribution();
dist.support = support;
dist.cdf = cdf;
dist.method = method;
return dist;
}
/// <summary>
/// Creates a new <see cref="GeneralContinuousDistribution"/> with the given PDF and CDF functions.
/// </summary>
///
/// <param name="support">The distribution's support over the real line.</param>
/// <param name="density">A probability density function.</param>
/// <param name="distribution">A cumulative distribution function.</param>
///
public GeneralContinuousDistribution(DoubleRange support,
Func<double, double> density, Func<double, double> distribution)
{
if (density == null)
throw new ArgumentNullException("density");
if (distribution == null)
throw new ArgumentNullException("distribution");
this.method = new InfiniteAdaptiveGaussKronrod(100);
this.pdf = density;
this.cdf = distribution;
this.support = support;
}
/// <summary>
/// Creates a new <see cref="GeneralContinuousDistribution"/> with the given PDF and CDF functions.
/// </summary>
///
/// <param name="distribution">A distribution whose properties will be numerically estimated.</param>
///
public GeneralContinuousDistribution(UnivariateContinuousDistribution distribution)
{
if (distribution == null)
throw new ArgumentNullException("distribution");
this.method = new InfiniteAdaptiveGaussKronrod(100);
this.pdf = distribution.ProbabilityDensityFunction;
this.cdf = distribution.DistributionFunction;
this.support = distribution.Support;
}
