Package | Description |
---|---|
simkit.random |
A collection of Classes used to generate Random Numbers, Random
Variates, and RandomVectors.
|
Modifier and Type | Class and Description |
---|---|
class |
AR1Variate
A simple first order auto regressive AR(1) process.
|
class |
BernoulliVariate
Generates Bernoulli random variates (either int or double).
Parameter: probability = P{X = 1} or the probability of "success"
in a single trial. |
class |
BetaVariate
Generates Beta(alpha, beta) random variates.
|
class |
CompositionVariate
Generates the composition of a list of RandomVariates.
|
class |
ConstantIntegerVariate
This always generates the same
(int) value . |
class |
ConstantVariate
A "RandomVariate" class that is constant.
|
class |
ConvolutionVariate
Generates the convolution (sum) of a number of RandomVariates.
|
class |
DataVariate |
class |
DiscreteIntegerVariate
Generates random variates having an arbitrary discrete distribution with
integer val.
|
class |
DiscreteUniformVariate
Generates Discrete Uniform (a, b) random variates.
Parameters: minimum = smallest possible value (integer).
maximum = largest possible value (integer). |
class |
DiscreteVariate
Generates random variates having an arbitrary discrete distribution.
|
class |
Exponential_64Variate
Generates Exponential random variate using log transform.
|
class |
ExponentialVariate
Generates Exponential random variate using log transform.
|
class |
Gamma_64Variate
Generates Gamma(alpha, beta) random variates.
|
class |
GammaARVariate
Instances of this class generate correlated Gamma random variates based on an
approach in Gaver and Lewis (1986).
|
class |
GammaVariate
Generates Gamma(alpha, beta) random variates.
|
class |
IntegerTraceVariate |
class |
InverseGaussianVariate
Generates random variates having the Inverse Gaussian distribution.
|
class |
LogNormalVariate
Generates random variates from the Log Normal(μ, σ) distribution
based on the exponential transformation of a Normal.
|
class |
MarkovChainVariate
Instances of this class generate values from a Markov Chain with the given
transition probabilities on the state space [0,..n-1] where n is the size of
the transition matrix.
|
class |
MixedVariate
Generates random number from a mix of RandomVariates.
|
class |
NegativeBinomialVariate
Based on Devroye (1986), pp.
|
class |
NormalVariate
Generates Normal(μ, σ) random variate using the Box-Muller algorithm.
|
class |
NormalVariate_64
Generates Normal(mean, std) random variate using the
Box-Muller algorithm.
|
class |
Poisson2Variate |
class |
PoissonVariate
Generates random variates having a Poisson distribution.
|
class |
ResampleVariate
Generates random variates by resampling from a given data array.
|
class |
RightWedgeVariate
Generates a right wedge random variate.
|
class |
TraceVariate
"Generates" numbers specified by the parameters.
|
class |
TriangleVariate
Generates Triangle random variates.
|
class |
TruncatedNormalVariate
Generates Normal variates truncated at 0.0.
|
class |
TruncatedVariate
Generates the maximum of a RandomVariate and a truncation point.
|
class |
TwoStateMarkovVariate
Generates values from a 2-D Markov Chain taking on values {0,1}.
|
class |
UniformVariate
Generates continuous uniform random variates.
|
class |
Weibull_64Variate
Generate from the Weibull distribution having pdf:
f(x) = αxα-1β-αe-(x/β)α, x > 0 |
class |
WeibullVariate
Generate from the Weibull distribution having pdf:
f(x) = αxα-1β-αe-(x/β)α, x > 0 |