Package | Description |
---|---|
dev.nm.stat.random.rng.univariate.beta | |
dev.nm.stat.random.rng.univariate.gamma | |
dev.nm.stat.random.rng.univariate.normal.truncated |
Constructor and Description |
---|
VanDerWaerden1969(RandomGammaGenerator X,
RandomGammaGenerator Y)
Deprecated.
Construct a random number generator to sample from the beta distribution.
|
Modifier and Type | Class and Description |
---|---|
class |
InverseTransformSamplingGammaRNG
Deprecated.
There exist much more efficient algorithms.
|
class |
KunduGupta2007
Kundu-Gupta propose a very convenient way to generate gamma random variables using generalized
exponential distribution,
when the shape parameter lies between 0 and 1.
|
class |
MarsagliaTsang2000
Marsaglia-Tsang is a procedure for generating a gamma variate as the cube of a suitably scaled
normal variate.
|
class |
XiTanLiu2010a
Xi, Tan and Liu proposed two simple algorithms to generate gamma random numbers based on
the ratio-of-uniforms method and logarithmic transformations of gamma random variable.
|
class |
XiTanLiu2010b
Xi, Tan and Liu proposed two simple algorithms to generate gamma random numbers based on
the ratio-of-uniforms method and logarithmic transformations of gamma random variable.
|
Modifier and Type | Class and Description |
---|---|
class |
InverseTransformSamplingTruncatedNormalRNG
A random variate x defined as
\[
x = \Phi^{-1}( \Phi(\alpha) + U\cdot(\Phi(\beta)-\Phi(\alpha)))\sigma + \mu
\]
with \(\Phi\) the cumulative distribution function and \(\Phi^{-1}\) its inverse, U a
uniform random number on (0, 1), follows the distribution truncated to the range (a,
b).
|
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