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A logistic approximation to the cumulative normal distribution

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DOI: 
doi:10.3926/jiem.2009.v2n1.p114-127
Abstract (2. Language): 
Abstract: This paper develops a logistic approximation to the cumulative normal distribution. Although the literature contains a vast collection of approximate functions for the normal distribution, they are very complicated, not very accurate, or valid for only a limited range. This paper proposes an enhanced approximate function. When comparing the proposed function to other approximations studied in the literature, it can be observed that the proposed logistic approximation has a simpler functional form and that it gives higher accuracy, with the maximum error of less than 0.00014 for the entire range. This is, to the best of the authors’ knowledge, the lowest level of error reported in the literature. The proposed logistic approximate function may be appealing to researchers, practitioners and educators given its functional simplicity and mathematical accuracy.
114-127

REFERENCES

References: 

Cadwell, J. H. (1951). The Bivariate Normal Integral. Biometrika, 38, 475-479.
Hamaker, H. C. (1978). Approximating the Cumulative Normal Distribution and its
Inverse. Applied Statistics, 27, 76-77.
Hart, R. G. A. (1963). Close Approximation Related to the Error Function.
Mathematics of Computation, 20, 600-602.
Hiller, F. S., & Liberman, G. J. (2001). Introduction to Operations Research. 7th Ed.,
New York: McGraw-Hill.
Hoyt, J. P. A. (1968). Simple Approximation to the Standard Normal Probability
Density Function. American Statistician, 22(3), 25-26.
Johnson, N. L., & Kotz, S. (1969). Distributions in Statistics: Continuous Univariate
Distributions. Houghton Mifflin Company: Boston.
Lin, J. T. (1988). Alternative to Hamaker’s Approximations to the Cumulative
Normal Distribution and its Inverse. Applied Statistics, 37, 413-414.
Lin, J. T. (1989). Approximating the Normal Tail Probability and its Inverse for use
on a Pocket-Calculator. Applied Statistics, 38, 69-70.
Lin, J. T. (1990). A Simpler Logistic Approximation to the Normal Tail Probability
and its Inverse. Applied Statistics, 39, 255-257.
Polya, G. (1945). Remarks on Computing the Probability Integral in One and Two
Dimensions. Proceedings of the 1st Berkeley Symposium on Mathematical
Statistics and Probability, 63-78.
Schucany, W. R.. & Gray, H. L. (1968). A New Approximation Related to the Error
Function. Mathematics of Computation, 22, 201-202.
Zelen, M., & Severo, N. C. (1966). Probability Functions. In Handbook of
Mathematical Functions, Ed. Abramowitz and I. A. Stegun, Washington D.C.:
Department of US Government.

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