TriangularDistribution Class 
Namespace: Accord.Statistics.Distributions.Univariate
[SerializableAttribute] public class TriangularDistribution : UnivariateContinuousDistribution, ISampleableDistribution<double>, IDistribution<double>, IDistribution, ICloneable, IRandomNumberGenerator<double>, IFittableDistribution<double, TriangularOptions>, IFittable<double, TriangularOptions>, IFittable<double>, IFittableDistribution<double>
The TriangularDistribution type exposes the following members.
Name  Description  

TriangularDistribution 
Constructs a Triangular distribution
with the given parameters a, b and c.

Name  Description  

Entropy 
Gets the entropy for this distribution,
defined as 0.5 + log((maxmin)/2)).
(Overrides UnivariateContinuousDistributionEntropy.)  
Max 
Gets the triangular parameter B (the maximum value).
 
Mean 
Gets the mean for this distribution,
defined as (a + b + c) / 3.
(Overrides UnivariateContinuousDistributionMean.)  
Median 
Gets the median for this distribution.
(Overrides UnivariateContinuousDistributionMedian.)  
Min 
Gets the triangular parameter A (the minimum value).
 
Mode 
Gets the mode for this distribution,
also known as the triangular's c.
(Overrides UnivariateContinuousDistributionMode.)  
Quartiles 
Gets the Quartiles for this distribution.
(Inherited from UnivariateContinuousDistribution.)  
StandardDeviation 
Gets the Standard Deviation (the square root of
the variance) for the current distribution.
(Inherited from UnivariateContinuousDistribution.)  
Support  (Overrides UnivariateContinuousDistributionSupport.)  
Variance 
Gets the variance for this distribution, defined
as (a² + b² + c²  ab  ac  bc) / 18.
(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.)  
FindMax 
Finds the index of the last largest value in a set of observations.
 
FindMin 
Finds the index of the first smallest value in a set of observations.
 
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.
(Overrides UnivariateContinuousDistributionFit(Double, Double, IFittingOptions).)  
Fit(Double, Double, TriangularOptions) 
Fits the underlying distribution to a given set of observations.
 
Fit(Double, Int32, IFittingOptions) 
Fits the underlying distribution to a given set of observations.
(Overrides UnivariateContinuousDistributionFit(Double, Int32, IFittingOptions).)  
Fit(Double, Int32, TriangularOptions) 
Fits the underlying distribution to a given set of observations.
 
Generate 
Generates a random observation from the current distribution.
(Overrides UnivariateContinuousDistributionGenerate.)  
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.
(Overrides UnivariateContinuousDistributionGenerate(Int32, Double).)  
GetHashCode  Serves as the default hash function. (Inherited from Object.)  
GetMax(Double, Double, Int32) 
Gets the maximum value in a set of weighted observations.
 
GetMax(Double, Int32, Int32) 
Finds the index of the last largest value in a set of weighted observations.
 
GetMin(Double, Double, Int32) 
Gets the minimum value in a set of weighted observations.
 
GetMin(Double, Int32, Int32) 
Finds the index of the first smallest value in a set of weighted observations.
 
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.) 
In probability theory and statistics, the triangular distribution is a continuous probability distribution with lower limit a, upper limit b and mode c, where a < b and a ≤ c ≤ b.
References:
This example shows how to create a Triangular distribution with minimum 1, maximum 6, and most common value 3.
// Create a new Triangular distribution (1, 3, 6). var trig = new TriangularDistribution(a: 1, b: 6, c: 3); double mean = trig.Mean; // 3.3333333333333335 double median = trig.Median; // 3.2613872124741694 double mode = trig.Mode; // 3.0 double var = trig.Variance; // 1.0555555555555556 double cdf = trig.DistributionFunction(x: 2); // 0.10000000000000001 double pdf = trig.ProbabilityDensityFunction(x: 2); // 0.20000000000000001 double lpdf = trig.LogProbabilityDensityFunction(x: 2); // 1.6094379124341003 double ccdf = trig.ComplementaryDistributionFunction(x: 2); // 0.90000000000000002 double icdf = trig.InverseDistributionFunction(p: cdf); // 2.0000000655718773 double hf = trig.HazardFunction(x: 2); // 0.22222222222222224 double chf = trig.CumulativeHazardFunction(x: 2); // 0.10536051565782628 string str = trig.ToString(CultureInfo.InvariantCulture); // Triangular(x; a = 1, b = 6, c = 3)