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A logistic approximation to the cumulative normal distribution

By Shannon R. Bowling, Mohammad T. Khasawneh, Sittichai Kaewkuekool and Byung Rae Cho

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 accuracyPeer Reviewe

Topics: Àrees temàtiques de la UPC::Matemàtiques i estadística::Investigació operativa, Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica, Logistic distribution, Game theory, Minimax criteria, Lògica matemàtica, Distribució (Teoria de la probabilitat), Jocs, Teoria de
Publisher: School of Industrial and Aeronautic Engineering of Terrassa (ETSEIAT). Universitat Politècnica de Catalunya (UPC)
Year: 2009
OAI identifier: oai:upcommons.upc.edu:2099/8223
Journal:

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