MRG32k3a generator
E760432
MRG (multiple recursive generator)
combined multiple recursive generator
pseudorandom number generator
The MRG32k3a generator is a high-quality combined multiple recursive pseudorandom number generator widely used in scientific computing and simulations for its long period and good statistical properties.
Statements (48)
| Predicate | Object |
|---|---|
| instanceOf |
MRG (multiple recursive generator)
ⓘ
combined multiple recursive generator ⓘ pseudorandom number generator ⓘ |
| hasApplication |
Monte Carlo simulation
ⓘ
financial risk simulation ⓘ queueing simulations ⓘ scientific computing ⓘ stochastic modeling ⓘ |
| hasAuthor | Pierre L’Ecuyer NERFINISHED ⓘ |
| hasCategory |
multiple recursive generator with combination
ⓘ
uniform random number generator ⓘ |
| hasCombinationRule | z_n = (x_n - y_n) mod 4294967087 ⓘ |
| hasComponentCount | 2 ⓘ |
| hasComponentType | 3rd-order multiple recursive generator ⓘ |
| hasDesignGoal |
high-quality random variates for simulation
ⓘ
support for parallel and distributed simulations ⓘ |
| hasDimension | 6 ⓘ |
| hasFeature |
ability to jump ahead in the sequence
ⓘ
well-defined stream and substream structure ⓘ |
| hasModulus |
4294944443
ⓘ
4294967087 ⓘ |
| hasOutputRange | (0,1) ⓘ |
| hasOutputType | double-precision uniform variates ⓘ |
| hasPeriodLength | approximately 2^191 ⓘ |
| hasProperty |
good equidistribution properties
ⓘ
good statistical quality ⓘ long period ⓘ supports efficient substream generation ⓘ supports multiple independent streams ⓘ |
| hasRecurrence |
x_n = (1403580 x_{n-2} - 810728 x_{n-3}) mod 4294967087
ⓘ
y_n = (527612 y_{n-1} - 1370589 y_{n-3}) mod 4294944443 ⓘ |
| hasSeedConstraint | state must not be all zeros in each component ⓘ |
| hasStateSize | 6 integers ⓘ |
| hasStreamCountPerSeed | 2^64 streams (conceptual design) ⓘ |
| hasSubstreamCountPerStream | 2^64 substreams (conceptual design) ⓘ |
| hasYearIntroduced | late 1990s ⓘ |
| isAlternativeTo |
Mersenne Twister
NERFINISHED
ⓘ
linear congruential generators ⓘ |
| isDescribedIn | Pierre L’Ecuyer’s papers on combined multiple recursive generators ⓘ |
| isImplementedIn |
Intel Math Kernel Library
NERFINISHED
ⓘ
MATLAB random number generation toolbox NERFINISHED ⓘ NAG Library NERFINISHED ⓘ Python (via various simulation libraries) ⓘ R (via external packages and interfaces) ⓘ RngStreams library NERFINISHED ⓘ SSJ (Stochastic Simulation in Java) library NERFINISHED ⓘ |
| isPreferredFor | high-precision simulation studies ⓘ |
| passesTestSuite | TestU01 Crush battery (under recommended usage) NERFINISHED ⓘ |
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.