Approximating the Inverse Normal

Version 1.2.0.0 (1,68 ko) par Wolfgang Putschögl
Beasley-Springer-Moro algorithm for approximating the inverse normal.
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Mise à jour 8 août 2011

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Applying the inverse transform method to the normal distribution entails evaluation of the inverse normal. This is the Beasley-Springer-Moro algorithm for approximating the inverse normal.

Input: u, a sacalar or matrix with elements between 0 and 1
Output: x, an approximation for the inverse normal at u

Reference:
Pau Glasserman, Monte Carlo methods in financial engineering, vol. 53 of applications of Mathematics (New York),
Springer-Verlag, new York, 2004, p.67-68

Citation pour cette source

Wolfgang Putschögl (2024). Approximating the Inverse Normal (https://www.mathworks.com/matlabcentral/fileexchange/28988-approximating-the-inverse-normal), MATLAB Central File Exchange. Récupéré le .

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Version Publié le Notes de version
1.2.0.0

Thanks to Ben Petschel who provided optimized code that brings it almost on par with the builtin (compiled) norminv/erfcinv!
1.1.0.0

Thanks to Ben Petschel who provided optimized code that brings it almost on par with the builtin (compiled) norminv/erfcinv!
1.0.0.0