Computer Generation of Poisson Deviates from Modified Normal Distributions

@article{Ahrens1982ComputerGO,
  title={Computer Generation of Poisson Deviates from Modified Normal Distributions},
  author={J. H. Ahrens and Ulrich Dieter},
  journal={ACM Trans. Math. Softw.},
  year={1982},
  volume={8},
  pages={163-179}
}
of Poisson Deviates Distributions Samples from Poisson distributions of mean # _> 10 are generated by truncating suitable normal deviates and applying a correction with low probabdity. For p < 10, inversion is substituted. The method is accurate and it can cope with changing parameters p. Using efficient subprograms for generating uniform, exponential, alid normal deviates, the new algorithm is much faster than all competing methods. 
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References

SHOWING 1-10 OF 18 REFERENCES
Generating gamma variates by a modified rejection technique
TLDR
A modification of the rejection technique begins by sampling from the normal distribution, being able to accept and transform the initial normal observation quickly at least 85 percent of the time. Expand
Extensions of Forsythe’s method for random sampling from the normal distribution
This article is an expansion of G. E. Forsythe's paper "Von Neumann's com- parison method for random sampling from the normal and other distributions" (5). It is shown that Forsythe's method for theExpand
Computer methods for sampling from the exponential and normal distributions
TLDR
The authors' primary conwiba~ion is the rise of polynomiaI sampling (as ex~ p/tiffed in Section 2) to eliminate any dependency on standard&ruction programs. Expand
The art of computer programming. Vol.2: Seminumerical algorithms
TLDR
This professional art of computer programming volume 2 seminumerical algorithms 3rd edition that has actually been written by is one of the best seller books in the world and is never late to read. Expand
Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables
A handbook of mathematical functions that is designed to provide scientific investigations with a comprehensive and self-contained summary of the mathematical functions that arise in physical andExpand
The Art of Computer Programming
TLDR
The arrangement of this invention provides a strong vibration free hold-down mechanism while avoiding a large pressure drop to the flow of coolant fluid. Expand
ACM Transachons on Mathematical Software
  • ACM Transachons on Mathematical Software
  • 1981
Frtnctples of D~screte Event Simulation
  • Frtnctples of D~screte Event Simulation
  • 1978
Principles of Discrete Event Simulation
Computer methods for samphng from gamma , beta , Poisson and binomial distributions
  • Computing
  • 1974
...
1
2
...