LevyDistribution Class |
Namespace: Accord.Statistics.Distributions.Univariate
The LevyDistribution type exposes the following members.
Name | Description | |
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LevyDistribution |
Constructs a new LevyDistribution
with zero location and unit scale.
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LevyDistribution(Double) |
Constructs a new LevyDistribution in
the given location and with unit scale.
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LevyDistribution(Double, Double) |
Constructs a new LevyDistribution in the
given location and scale.
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Name | Description | |
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Entropy |
Gets the entropy for this distribution.
(Overrides UnivariateContinuousDistributionEntropy.) | |
Location |
Gets the location μ (mu) for this distribution.
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Mean |
Gets the mean for this distribution, which for
the Levy distribution is always positive infinity.
(Overrides UnivariateContinuousDistributionMean.) | |
Median |
Gets the median for this distribution.
(Overrides UnivariateContinuousDistributionMedian.) | |
Mode |
Gets the mode for this distribution.
(Overrides UnivariateContinuousDistributionMode.) | |
Quartiles |
Gets the Quartiles for this distribution.
(Inherited from UnivariateContinuousDistribution.) | |
Scale |
Gets the location c for this distribution.
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StandardDeviation |
Gets the Standard Deviation (the square root of
the variance) for the current distribution.
(Inherited from UnivariateContinuousDistribution.) | |
Support |
Gets the support interval for this distribution.
(Overrides UnivariateContinuousDistributionSupport.) | |
Variance |
Gets the variance for this distribution, which for
the Levy distribution is always positive infinity.
(Overrides UnivariateContinuousDistributionVariance.) |
Name | Description | |
---|---|---|
Clone |
Creates a new object that is a copy of the current instance.
(Overrides DistributionBaseClone.) | |
ComplementaryDistributionFunction |
Gets the complementary cumulative distribution function
(ccdf) for this distribution evaluated at point x.
This function is also known as the Survival function.
(Inherited from UnivariateContinuousDistribution.) | |
CumulativeHazardFunction |
Gets the cumulative hazard function for this
distribution evaluated at point x.
(Inherited from UnivariateContinuousDistribution.) | |
DistributionFunction(Double) |
Gets the cumulative distribution function (cdf) for
this distribution evaluated at point x.
(Inherited from UnivariateContinuousDistribution.) | |
DistributionFunction(Double, Double) |
Gets the cumulative distribution function (cdf) for this
distribution in the semi-closed interval (a; b] given as
P(a < X ≤ b).
(Inherited from UnivariateContinuousDistribution.) | |
Equals | Determines whether the specified object is equal to the current object. (Inherited from Object.) | |
Finalize | Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object.) | |
Fit(Double) |
Fits the underlying distribution to a given set of observations.
(Inherited from UnivariateContinuousDistribution.) | |
Fit(Double, IFittingOptions) |
Fits the underlying distribution to a given set of observations.
(Inherited from UnivariateContinuousDistribution.) | |
Fit(Double, Double) |
Fits the underlying distribution to a given set of observations.
(Inherited from UnivariateContinuousDistribution.) | |
Fit(Double, Int32) |
Fits the underlying distribution to a given set of observations.
(Inherited from UnivariateContinuousDistribution.) | |
Fit(Double, Double, IFittingOptions) |
Fits the underlying distribution to a given set of observations.
(Inherited from UnivariateContinuousDistribution.) | |
Fit(Double, Int32, IFittingOptions) |
Fits the underlying distribution to a given set of observations.
(Inherited from UnivariateContinuousDistribution.) | |
Generate |
Generates a random observation from the current distribution.
(Inherited from UnivariateContinuousDistribution.) | |
Generate(Int32) |
Generates a random vector of observations from the current distribution.
(Inherited from UnivariateContinuousDistribution.) | |
Generate(Random) |
Generates a random observation from the current distribution.
(Inherited from UnivariateContinuousDistribution.) | |
Generate(Int32, Double) |
Generates a random vector of observations from the current distribution.
(Inherited from UnivariateContinuousDistribution.) | |
Generate(Int32, Random) |
Generates a random vector of observations from the current distribution.
(Inherited from UnivariateContinuousDistribution.) | |
Generate(Int32, Double, Random) |
Generates a random vector of observations from the current distribution.
(Inherited from UnivariateContinuousDistribution.) | |
GetHashCode | Serves as the default hash function. (Inherited from Object.) | |
GetRange |
Gets the distribution range within a given percentile.
(Inherited from UnivariateContinuousDistribution.) | |
GetType | Gets the Type of the current instance. (Inherited from Object.) | |
HazardFunction |
Gets the hazard function, also known as the failure rate or
the conditional failure density function for this distribution
evaluated at point x.
(Inherited from UnivariateContinuousDistribution.) | |
InnerComplementaryDistributionFunction |
Gets the complementary cumulative distribution function
(ccdf) for this distribution evaluated at point x.
This function is also known as the Survival function.
(Inherited from UnivariateContinuousDistribution.) | |
InnerDistributionFunction |
Gets the cumulative distribution function (cdf) for
this distribution evaluated at point x.
(Overrides UnivariateContinuousDistributionInnerDistributionFunction(Double).) | |
InnerInverseDistributionFunction |
Gets the inverse of the cumulative distribution function (icdf) for
this distribution evaluated at probability p. This function
is also known as the Quantile function.
(Overrides UnivariateContinuousDistributionInnerInverseDistributionFunction(Double).) | |
InnerLogProbabilityDensityFunction |
Gets the log-probability density function (pdf) for
this distribution evaluated at point x.
(Inherited from UnivariateContinuousDistribution.) | |
InnerProbabilityDensityFunction |
Gets the probability density function (pdf) for
this distribution evaluated at point x.
(Overrides UnivariateContinuousDistributionInnerProbabilityDensityFunction(Double).) | |
InverseDistributionFunction |
Gets the inverse of the cumulative distribution function (icdf) for
this distribution evaluated at probability p. This function
is also known as the Quantile function.
(Inherited from UnivariateContinuousDistribution.) | |
LogCumulativeHazardFunction |
Gets the log of the cumulative hazard function for this
distribution evaluated at point x.
(Inherited from UnivariateContinuousDistribution.) | |
LogProbabilityDensityFunction |
Gets the log-probability density function (pdf) for
this distribution evaluated at point x.
(Inherited from UnivariateContinuousDistribution.) | |
MemberwiseClone | Creates a shallow copy of the current Object. (Inherited from Object.) | |
ProbabilityDensityFunction |
Gets the probability density function (pdf) for
this distribution evaluated at point x.
(Inherited from UnivariateContinuousDistribution.) | |
QuantileDensityFunction |
Gets the first derivative of the
inverse distribution function (icdf) for this distribution evaluated
at probability p.
(Inherited from UnivariateContinuousDistribution.) | |
ToString |
Returns a String that represents this instance.
(Inherited from DistributionBase.) | |
ToString(IFormatProvider) |
Returns a String that represents this instance.
(Inherited from DistributionBase.) | |
ToString(String) |
Returns a String that represents this instance.
(Inherited from DistributionBase.) | |
ToString(String, IFormatProvider) |
Returns a String that represents this instance.
(Overrides DistributionBaseToString(String, IFormatProvider).) |
Name | Description | |
---|---|---|
HasMethod |
Checks whether an object implements a method with the given name.
(Defined by ExtensionMethods.) | |
IsEqual |
Compares two objects for equality, performing an elementwise
comparison if the elements are vectors or matrices.
(Defined by Matrix.) | |
To(Type) | Overloaded.
Converts an object into another type, irrespective of whether
the conversion can be done at compile time or not. This can be
used to convert generic types to numeric types during runtime.
(Defined by ExtensionMethods.) | |
ToT | Overloaded.
Converts an object into another type, irrespective of whether
the conversion can be done at compile time or not. This can be
used to convert generic types to numeric types during runtime.
(Defined by ExtensionMethods.) |
In probability theory and statistics, the Lévy distribution, named after Paul Lévy, is a continuous probability distribution for a non-negative random variable. In spectroscopy, this distribution, with frequency as the dependent variable, is known as a van der Waals profile. It is a special case of the inverse-gamma distribution.
It is one of the few distributions that are stable and that have probability density functions that can be expressed analytically, the others being the normal distribution and the Cauchy distribution. All three are special cases of the stable distributions, which do not generally have a probability density function which can be expressed analytically.
References:
This examples shows how to create a Lévy distribution and how to compute some of its measures and properties.
// Create a new Lévy distribution on 1 with scale 4.2: var levy = new LevyDistribution(location: 1, scale: 4.2); double mean = levy.Mean; // +inf double median = levy.Median; // 10.232059220934481 double mode = levy.Mode; // NaN double var = levy.Variance; // +inf double cdf = levy.DistributionFunction(x: 1.4); // 0.0011937454448720029 double pdf = levy.ProbabilityDensityFunction(x: 1.4); // 0.016958939623898304 double lpdf = levy.LogProbabilityDensityFunction(x: 1.4); // -4.0769601727487803 double ccdf = levy.ComplementaryDistributionFunction(x: 1.4); // 0.99880625455512795 double icdf = levy.InverseDistributionFunction(p: cdf); // 1.3999999 double hf = levy.HazardFunction(x: 1.4); // 0.016979208476674869 double chf = levy.CumulativeHazardFunction(x: 1.4); // 0.0011944585265140923 string str = levy.ToString(CultureInfo.InvariantCulture); // Lévy(x; μ = 1, c = 4.2)