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Gamma (VSL_RNG_METHOD_GAMMA_GNORM/ VSL_RNG_METHOD_GAMMA_GNORM_ACCURATE)

Random number generator of the gamma distribution with parameters shape
α
, offset
a
, and scale factor
β
. You can generate any successive random number
γα
of the standard gamma distribution (
a =
0,
β
= 1) as follows:
  1. If
    α
    > 1, a gamma distributed random number can be generated as a cube of properly scaled normal random number [Mars2000]. The algorithm is based on the acceptance/rejection method using squeeze technique.
  2. If
    α
    < 1, a gamma distributed random number is generated using two acceptance/rejection based algorithms:
    • If
      α
      < 0.6, a gamma distributed random number is obtained by transformation of exponential power distributed random number [Dev86],
    • Otherwise, rejection method from Weibull distribution is used [Vad77], [Dev86].
When
α
= 1 gamma distribution is reduced to exponential distribution with parameters
a
,
β
. The random numbers of the exponential distribution are generated using method VSL_RNG_METHOD_EXPONENTIAL_ICDF. The gamma distributed random number
γ
with parameters
α
,
a
, and
β
is transformed from
γα
using scale and shift
γ = a + βγα

Product and Performance Information

1

Intel's compilers may or may not optimize to the same degree for non-Intel microprocessors for optimizations that are not unique to Intel microprocessors. These optimizations include SSE2, SSE3, and SSSE3 instruction sets and other optimizations. Intel does not guarantee the availability, functionality, or effectiveness of any optimization on microprocessors not manufactured by Intel. Microprocessor-dependent optimizations in this product are intended for use with Intel microprocessors. Certain optimizations not specific to Intel microarchitecture are reserved for Intel microprocessors. Please refer to the applicable product User and Reference Guides for more information regarding the specific instruction sets covered by this notice.

Notice revision #20110804