论文信息 - Generation of Gaussian distributed random numbers by using a numerical inversion method

Generation of Gaussian distributed random numbers by using a numerical inversion method

Abstract We describe a vectorizable implementation of a numerical inversion method to generate approximately Gaussian distributed random numbers. This method is, on the CRAY-YMP computer, several times faster than the standard Box-Muller-Wiener algorithm. The validity of the approximation is discussed.

Raúl Toral | R. Toral | A. Chakrabarti | Amitabha Chakrabarti

[1] M. E. Muller,et al. A Note on the Generation of Random Normal Deviates , 1958 .

[2] Irene A. Stegun,et al. Handbook of Mathematical Functions. , 1966 .

[3] References , 1971 .

[4] Gunton,et al. Domain growth and scaling in the two-dimensional Langevin model. , 1989, Physical review. B, Condensed matter.

[5] S. Zacks,et al. Introduction to stochastic differential equations , 1988 .

[6] Joachim H. Ahrens,et al. Computer methods for sampling from the exponential and normal distributions , 1972, CACM.

[7] Scott Kirkpatrick,et al. A very fast shift-register sequence random number generatorjournal of computational physics , 1981 .

[8] William H. Press,et al. Numerical recipes , 1990 .

[9] C. Gardiner. Handbook of Stochastic Methods , 1983 .

[10] C. Parsons. THE AMERICAN CHEMICAL SOCIETY. , 1922, Science.