Normal Random Numbers: Using Machine Analysis to Choose the Best Algorithm

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Normal Random Numbers: Using Machine Analysis to Choose the Best Algorithm

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ACM Transactions on Mathematical Software (TOMS) archive
Volume 3 , Issue 4 (December 1977) table of contents

Pages: 346 - 358

Year of Publication: 1977

ISSN:0098-3500

Author

W. H. Payne

Computer Science Department, Washington State University, Pullman, WA

Publisher

ACM New York, NY, USA

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Downloads (6 Weeks): 6, Downloads (12 Months): 34, Citation Count: 2

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REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

	1	J. H. Ahrens , U. Dieter, Computer methods for sampling from the exponential and normal distributions, Communications of the ACM, v.15 n.10, p.873-882, Oct. 1972 [doi>10.1145/355604.361593]
	2	AHRENS, J.H., AND DIETER, U. Extension of Forsythe's method for random sampling from the normal distribution. Math. Comput. 27, 124 (1973), 927-937.
	3	James R. Bell, Algorithm 334: Normal random deviates, Communications of the ACM, v.11 n.7, p.498, July 1968 [doi>10.1145/363397.363547]
	4	Richard P. Brent, Algorithm 488: A Gaussian pseudo-random number generator, Communications of the ACM, v.17 n.12, p.704-706, Dec 1974 [doi>10.1145/361604.361629]
	5	DE LuG1s~, B.G A class of algorithms for automatic evaluation of certain elementary functions in a binary computer. Rep. No. 399, Dept. Comptr. Sei., U. of Illinois at Urbana- Champaign, Urbana, Ill., 1970.
	6	DIETER, U., AND A~RENS, J.H. A combinatorial method for the generation of normally distributed random numbers. Computing 11 (1973), 137-146.
	7	Gideon Ehrlich, Loopless Algorithms for Generating Permutations, Combinations, and Other Combinatorial Configurations, Journal of the ACM (JACM), v.20 n.3, p.500-513, July 1973 [doi>10.1145/321765.321781]
	8	FORSYT~IE, G.E. Von Neumann's comparison method for sampling from the normal and other distributions. Math. Comput. 26 (1972), 817-826.
	9	F. M. Ives, Permutation enumeration: four new permutation algorithms, Communications of the ACM, v.19 n.2, p.68-72, Feb. 1976 [doi>10.1145/359997.360002]
	10	KNUTH, D.E. The analysis of algorithms. Acres Congres Int. Math. 8 (1970), 269-274.
	11	KNUTH, D.E. Mathematical analysis of algorithms. Information Processing 71, North- Holland Pub. Co., Amsterdam, 1972, pp. 19-27.
	12	Donald E. Knuth, The art of computer programming, volume 2 (3rd ed.): seminumerical algorithms, Addison-Wesley Longman Publishing Co., Inc., Boston, MA, 1997
	13	G. Marsaglia , M. D. MacLaren , T. A. Bray, A fast procedure for generating normal random variables, Communications of the ACM, v.7 n.1, p.4-10, Jan. 1964 [doi>10.1145/363872.363883]
	14	MARSAGLXA, G. Generating a variable from the tail of the normal distribution. Technometrics 6 (1964), 101-102.
	15	MARSAOLIA, G., AND BRAY, T.A. A convenient method for generating normal variables. SIAM Rev. 6 (1964), 260-264.
	16	M~GGITT, J.E. Pseudo division and pseudo multiplication processes. IBM J. Res. Develop. 6 (1962), 210-226.
	17	MULLER, M.E. An inverse method for the generation of random variables on large-scale computers. Math. Tables Aids Comput. 12 (1958), 167-174 (now Math. Comput.).
	18	Mervin E. Muller, A Comparison of Methods for Generating Normal Deviates on Digital Computers, Journal of the ACM (JACM), v.6 n.3, p.376-383, July 1959 [doi>10.1145/320986.320992]
	19	ORD-SMITH, R.J. Generation of permutation sequences, P. 2. Comptr. J. 14 (May 1971), 136-139.
	20	K. D Tocher, The art of simulation, English Universities Press, 1967
	21	ZELEN, M., AND SEVEaO, N.C. Probability functions. In Handbook of Mathematical Functions, M. Abramowitz and I.A. Stegun, Eds., Nat. Bur. of Standards, Washington, D.C., 1964.

CITED BY 2

	Dong-U Lee , Wayne Luk , John D. Villasenor , Peter Y. K. Cheung, A Gaussian Noise Generator for Hardware-Based Simulations, IEEE Transactions on Computers, v.53 n.12, p.1523-1534, December 2004
	Amirhossein Alimohammad , Saeed Fouladi Fard , Bruce F. Cockburn , Christian Schlegel, A compact and accurate Gaussian variate generator, IEEE Transactions on Very Large Scale Integration (VLSI) Systems, v.16 n.5, p.517-527, May 2008