mirror of
https://github.com/hanzoai/jube-fork.git
synced 2026-10-30 18:33:33 +00:00
richard-churchman
cc0a2bee21
Included open-source Accord.net library code natively to the solution given the deprecated state of that project. Accord.net will be supported inside Jube for own needs (such as upgrading to .Net 7+). Accord.net libraries modified to compile to .Net 6. Modified Accord.net libraries to better support Newtonsoft Json.net serialisation. Included annotations in the Accord.net libraries to house important dependency statistics. Serialised json can be used independently of Jube to recall a Neural Network. Removal of Binary Serializer totally as a precursor to the projects support of .Net 7+. Extensive bug fixing in crucial functions of Neural Network training and recall. While this part of the system remains in Alpha, it is substantially more fit for purpose.
289 lines
10 KiB
C#
289 lines
10 KiB
C#
// Accord Statistics Library
|
|
// The Accord.NET Framework
|
|
// http://accord-framework.net
|
|
//
|
|
// Copyright © César Souza, 2009-2017
|
|
// cesarsouza at gmail.com
|
|
//
|
|
// This library is free software; you can redistribute it and/or
|
|
// modify it under the terms of the GNU Lesser General Public
|
|
// License as published by the Free Software Foundation; either
|
|
// version 2.1 of the License, or (at your option) any later version.
|
|
//
|
|
// This library is distributed in the hope that it will be useful,
|
|
// but WITHOUT ANY WARRANTY; without even the implied warranty of
|
|
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
|
|
// Lesser General Public License for more details.
|
|
//
|
|
// You should have received a copy of the GNU Lesser General Public
|
|
// License along with this library; if not, write to the Free Software
|
|
// Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA
|
|
//
|
|
|
|
namespace Accord.Statistics.Distributions
|
|
{
|
|
using System;
|
|
using Accord.Statistics.Distributions.Fitting;
|
|
using Accord.Statistics.Distributions.Univariate;
|
|
using AForge;
|
|
|
|
/// <summary>
|
|
/// Common interface for univariate probability distributions.
|
|
/// </summary>
|
|
///
|
|
/// <remarks>
|
|
/// <para>
|
|
/// This interface is implemented by both univariate <see cref="UnivariateDiscreteDistribution">
|
|
/// Discrete Distributions</see> and <see cref="UnivariateContinuousDistribution">Continuous
|
|
/// Distributions</see>.</para>
|
|
///
|
|
/// <para>
|
|
/// For Multivariate distributions, see <see cref="IMultivariateDistribution"/>.</para>
|
|
/// </remarks>
|
|
///
|
|
/// <seealso cref="NormalDistribution"/>
|
|
/// <seealso cref="GammaDistribution"/>
|
|
/// <seealso cref="UniformContinuousDistribution"/>
|
|
/// <seealso cref="UniformDiscreteDistribution"/>
|
|
///
|
|
public interface IUnivariateDistribution : IDistribution
|
|
{
|
|
|
|
/// <summary>
|
|
/// Gets the mean value for the distribution.
|
|
/// </summary>
|
|
///
|
|
/// <value>The distribution's mean.</value>
|
|
///
|
|
double Mean { get; }
|
|
|
|
/// <summary>
|
|
/// Gets the variance value for the distribution.
|
|
/// </summary>
|
|
///
|
|
/// <value>The distribution's variance.</value>
|
|
///
|
|
double Variance { get; }
|
|
|
|
/// <summary>
|
|
/// Gets the median value for the distribution.
|
|
/// </summary>
|
|
///
|
|
/// <value>The distribution's median.</value>
|
|
///
|
|
double Median { get; }
|
|
|
|
/// <summary>
|
|
/// Gets the mode value for the distribution.
|
|
/// </summary>
|
|
///
|
|
/// <value>The distribution's mode.</value>
|
|
///
|
|
double Mode { get; }
|
|
|
|
/// <summary>
|
|
/// Gets entropy of the distribution.
|
|
/// </summary>
|
|
///
|
|
/// <value>The distribution's entropy.</value>
|
|
///
|
|
double Entropy { get; }
|
|
|
|
/// <summary>
|
|
/// Gets the support interval for this distribution.
|
|
/// </summary>
|
|
///
|
|
/// <value>A <see cref="DoubleRange"/> containing
|
|
/// the support interval for this distribution.</value>
|
|
///
|
|
DoubleRange Support { get; set; }
|
|
|
|
/// <summary>
|
|
/// Gets the Quartiles for this distribution.
|
|
/// </summary>
|
|
///
|
|
/// <value>A <see cref="DoubleRange"/> object containing the first quartile
|
|
/// (Q1) as its minimum value, and the third quartile (Q2) as the maximum.</value>
|
|
///
|
|
DoubleRange Quartiles { get; }
|
|
|
|
/// <summary>
|
|
/// Gets the distribution range within a given percentile.
|
|
/// </summary>
|
|
///
|
|
/// <remarks>
|
|
/// If <c>0.25</c> is passed as the <paramref name="percentile"/> argument,
|
|
/// this function returns the same as the <see cref="Quartiles"/> function.
|
|
/// </remarks>
|
|
///
|
|
/// <param name="percentile">
|
|
/// The percentile at which the distribution ranges will be returned.</param>
|
|
///
|
|
/// <value>A <see cref="DoubleRange"/> object containing the minimum value
|
|
/// for the distribution value, and the third quartile (Q2) as the maximum.</value>
|
|
///
|
|
DoubleRange GetRange(double percentile);
|
|
|
|
/// <summary>
|
|
/// Gets the cumulative distribution function (cdf) for
|
|
/// this distribution evaluated at point <c>x</c>.
|
|
/// </summary>
|
|
///
|
|
/// <remarks>
|
|
/// The Cumulative Distribution Function (CDF) describes the cumulative
|
|
/// probability that a given value or any value smaller than it will occur.
|
|
/// </remarks>
|
|
///
|
|
double DistributionFunction(double x);
|
|
|
|
/// <summary>
|
|
/// Gets the cumulative distribution function (cdf) for this
|
|
/// distribution in the semi-closed interval (a; b] given as
|
|
/// <c>P(a < X ≤ b)</c>.
|
|
/// </summary>
|
|
///
|
|
/// <param name="a">The start of the semi-closed interval (a; b].</param>
|
|
/// <param name="b">The end of the semi-closed interval (a; b].</param>
|
|
///
|
|
/// <remarks>
|
|
/// The Cumulative Distribution Function (CDF) describes the cumulative
|
|
/// probability that a given value or any value smaller than it will occur.
|
|
/// </remarks>
|
|
///
|
|
double DistributionFunction(double a, double b);
|
|
|
|
/// <summary>
|
|
/// Gets the probability density function (pdf) for
|
|
/// this distribution evaluated at point <c>x</c>.
|
|
/// </summary>
|
|
///
|
|
/// <param name="x">
|
|
/// A single point in the distribution range. For a
|
|
/// univariate distribution, this should be a single
|
|
/// double value. For a multivariate distribution,
|
|
/// this should be a double array.</param>
|
|
///
|
|
/// <remarks>
|
|
/// The Probability Density Function (PDF) describes the
|
|
/// probability that a given value <c>x</c> will occur.
|
|
/// </remarks>
|
|
///
|
|
/// <returns>
|
|
/// The probability of <c>x</c> occurring
|
|
/// in the current distribution.</returns>
|
|
///
|
|
double ProbabilityFunction(double x);
|
|
|
|
/// <summary>
|
|
/// Gets the log-probability density function (pdf)
|
|
/// for this distribution evaluated at point <c>x</c>.
|
|
/// </summary>
|
|
///
|
|
/// <param name="x">
|
|
/// A single point in the distribution range. For a
|
|
/// univariate distribution, this should be a single
|
|
/// double value. For a multivariate distribution,
|
|
/// this should be a double array.</param>
|
|
/// <returns>
|
|
/// The logarithm of the probability of <c>x</c>
|
|
/// occurring in the current distribution.</returns>
|
|
///
|
|
double LogProbabilityFunction(double x);
|
|
|
|
/// <summary>
|
|
/// Gets the inverse of the cumulative distribution function (icdf) for
|
|
/// this distribution evaluated at probability <c>p</c>. This function
|
|
/// is also known as the Quantile function.
|
|
/// </summary>
|
|
///
|
|
/// <remarks>
|
|
/// The Inverse Cumulative Distribution Function (ICDF) specifies, for
|
|
/// a given probability, the value which the random variable will be at,
|
|
/// or below, with that probability.
|
|
/// </remarks>
|
|
///
|
|
/// <param name="p">A probability value between 0 and 1.</param>
|
|
///
|
|
/// <returns>A sample which could original the given probability
|
|
/// value when applied in the <see cref="DistributionFunction(double)"/>.</returns>
|
|
///
|
|
double InverseDistributionFunction(double p);
|
|
|
|
/// <summary>
|
|
/// Gets the complementary cumulative distribution function
|
|
/// (ccdf) for this distribution evaluated at point <c>x</c>.
|
|
/// This function is also known as the Survival function.
|
|
/// </summary>
|
|
///
|
|
/// <param name="x">
|
|
/// A single point in the distribution range.</param>
|
|
///
|
|
/// <remarks>
|
|
/// The Complementary Cumulative Distribution Function (CCDF) is
|
|
/// the complement of the Cumulative Distribution Function, or 1
|
|
/// minus the CDF.
|
|
/// </remarks>
|
|
///
|
|
double ComplementaryDistributionFunction(double x);
|
|
|
|
/// <summary>
|
|
/// Gets the hazard function, also known as the failure rate or
|
|
/// the conditional failure density function for this distribution
|
|
/// evaluated at point <c>x</c>.
|
|
/// </summary>
|
|
///
|
|
/// <remarks>
|
|
/// The hazard function is the ratio of the probability
|
|
/// density function f(x) to the survival function, S(x).
|
|
/// </remarks>
|
|
///
|
|
/// <param name="x">
|
|
/// A single point in the distribution range.</param>
|
|
///
|
|
/// <returns>
|
|
/// The conditional failure density function <c>h(x)</c>
|
|
/// evaluated at <c>x</c> in the current distribution.</returns>
|
|
///
|
|
double HazardFunction(double x);
|
|
|
|
/// <summary>
|
|
/// Gets the cumulative hazard function for this
|
|
/// distribution evaluated at point <c>x</c>.
|
|
/// </summary>
|
|
///
|
|
/// <param name="x">
|
|
/// A single point in the distribution range.</param>
|
|
///
|
|
/// <returns>
|
|
/// The cumulative hazard function <c>H(x)</c>
|
|
/// evaluated at <c>x</c> in the current distribution.</returns>
|
|
///
|
|
double CumulativeHazardFunction(double x);
|
|
|
|
/// <summary>
|
|
/// Gets the cumulative hazard function for this
|
|
/// distribution evaluated at point <c>x</c>.
|
|
/// </summary>
|
|
///
|
|
/// <param name="x">
|
|
/// A single point in the distribution range.</param>
|
|
///
|
|
/// <returns>
|
|
/// The cumulative hazard function <c>H(x)</c>
|
|
/// evaluated at <c>x</c> in the current distribution.</returns>
|
|
///
|
|
double LogCumulativeHazardFunction(double x);
|
|
|
|
/// <summary>
|
|
/// Gets the first derivative of the <see cref="InverseDistributionFunction">
|
|
/// inverse distribution function</see> (icdf) for this distribution evaluated
|
|
/// at probability <c>p</c>.
|
|
/// </summary>
|
|
///
|
|
/// <param name="p">A probability value between 0 and 1.</param>
|
|
///
|
|
double QuantileDensityFunction(double p);
|
|
}
|
|
|
|
}
|