| Bernoulli |
An Bernouli provides an implementation of the Bernouli
distribution with success probability (p)
P(X=1) = p
P(X=0) = 1-p
|
| Beta |
The standard beta distribution defined over the range from (0,1)
|
| Binomial |
Represents a Binomial distribution.
|
| BivariateLogNormal |
Allows for the generation of bivariate lognormal random variables.
|
| BivariateNormal |
Allows for the generation of bivariate normal
random variables
|
| Constant |
Constructs a degenerate distribution with all probability at the provided
point.
|
| DEmpiricalCDF |
Provides a representation for a discrete distribution with
arbitrary values and assigned probabilities to each value.
|
| Distribution |
An Distribution provides a skeletal implementation for classes that must
implement the DistributionIfc.
|
| DUniform |
Models discrete random variables that are uniformly distributed
over a contiguous range of integers.
|
| Exponential |
Models exponentially distributed random variables
This distribution is commonly use to model the time between events
|
| Gamma |
Models random variables that have gamma distribution
For more information on the gamma distribution and its related functions, see
"Object-Oriented Numerical Methods" by D.
|
| Geometric |
The geometric distribution is the probability distribution of
the number Y = X − 1 of failures before the first success,
supported on the set { 0, 1, 2, 3, ...
|
| IncompleteBetaFunctionFraction |
|
| LogLogistic |
|
| Lognormal |
Models the lognormal distribution
This distribution is commonly use to model the time of a task
|
| MTP |
Represents a Mixed translated Poisson random variable
|
| NegativeBinomial |
The number of failures (=0) before the rth success (=1) in a sequence of independent Bernoulli trials
with probability p of success on each trial.
|
| Normal |
Models normally distributed random variables
|
| PearsonType5 |
Represents a Pearson Type V distribution,
see Law (2007) Simulation Modeling and Analysis, McGraw-Hill, pg 293
Code contributed by Seda Gumrukcu
|
| PearsonType6 |
Represents a Pearson Type VI distribution,
see Law (2007) Simulation Modeling and Analysis, McGraw-Hill, pg 294
|
| Poisson |
Represents a Poisson random variable.
|
| ShiftedDistribution |
Represents a Distribution that has been Shifted (translated to the right)
The shift must be >= 0.0
|
| ShiftedGeometric |
The ShiftedeGeometric distribution is the probability distribution of
the number of Bernoulli trials needed to get one success.
|
| ShiftedLossFunctionDistribution |
|
| StudentT |
The Student T distribution
See http://www.mth.kcl.ac.uk/~shaww/web_page/papers/Tdistribution06.pdf
See http://en.wikipedia.org/wiki/Student's_t-distribution
This implementation limits the degrees of freedom to be greater
than or equal to 1.0
Bailey's acceptance rejection is used for sampling by default but
inverse transform can be selected
|
| Triangular |
Represents the Triangular distribution with
parameters - minimum value, maximum value and most likely value
|
| TruncatedDistribution |
|
| Uniform |
Defines a uniform distribution over the given range.
|
| VConstant |
A degenerate distribution on a single value.
|
| Weibull |
This class defines a Weibull distribution
|