ShiftedLogLogisticDistribution Class 
Namespace: Accord.Statistics.Distributions.Univariate
[SerializableAttribute] public class ShiftedLogLogisticDistribution : UnivariateContinuousDistribution
The ShiftedLogLogisticDistribution type exposes the following members.
Name  Description  

ShiftedLogLogisticDistribution 
Constructs a Shifted LogLogistic distribution
with zero location, unit scale, and zero shape.
 
ShiftedLogLogisticDistribution(Double) 
Constructs a Shifted LogLogistic distribution
with the given location, unit scale and zero shape.
 
ShiftedLogLogisticDistribution(Double, Double) 
Constructs a Shifted LogLogistic distribution
with the given location and scale and zero shape.
 
ShiftedLogLogisticDistribution(Double, Double, Double) 
Constructs a Shifted LogLogistic distribution
with the given location and scale and zero shape.

Name  Description  

Entropy 
Not supported.
(Overrides UnivariateContinuousDistributionEntropy.)  
Location 
Gets the distribution's location value μ (mu).
 
Mean 
Gets the mean for this distribution.
(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 distribution's scale value (σ).
 
Shape 
Gets the distribution's shape value (ξ).
 
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.
(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.
(Overrides UnivariateContinuousDistributionDistributionFunction(Double).)  
DistributionFunction(Double, Double) 
Gets the cumulative distribution function (cdf) for this
distribution in the semiclosed 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(Int32, Double) 
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.)  
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 logprobability 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.
(Overrides UnivariateContinuousDistributionProbabilityDensityFunction(Double).)  
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.)  
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.)  
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 Matrix.) 
The shifted loglogistic distribution is a probability distribution also known as the generalized loglogistic or the threeparameter loglogistic distribution. It has also been called the generalized logistic distribution, but this conflicts with other uses of the term: see generalized logistic distribution.
References:
This examples shows how to create a Shifted LogLogistic distribution, compute some of its properties and generate a number of random samples from it.
// Create a LLD3 distribution with μ = 0.0, scale = 0.42, and shape = 0.1 var log = new ShiftedLogLogisticDistribution(location: 0, scale: 0.42, shape: 0.1); double mean = log.Mean; // 0.069891101544818923 double median = log.Median; // 0.0 double mode = log.Mode; // 0.083441677069328604 double var = log.Variance; // 0.62447259946747213 double cdf = log.DistributionFunction(x: 1.4); // 0.94668863559417671 double pdf = log.ProbabilityDensityFunction(x: 1.4); // 0.090123683626808615 double lpdf = log.LogProbabilityDensityFunction(x: 1.4); // 2.4065722895662613 double ccdf = log.ComplementaryDistributionFunction(x: 1.4); // 0.053311364405823292 double icdf = log.InverseDistributionFunction(p: cdf); // 1.4000000037735139 double hf = log.HazardFunction(x: 1.4); // 1.6905154207038875 double chf = log.CumulativeHazardFunction(x: 1.4); // 2.9316057546685061 string str = log.ToString(CultureInfo.InvariantCulture); // LLD3(x; μ = 0, σ = 0.42, ξ = 0.1)