Approximating the Inverse Normal

Version 1.2.0.0 (1.68 KB) by Wolfgang Putschögl
Beasley-Springer-Moro algorithm for approximating the inverse normal.
0.0
(0)
688 Downloads
Updated 8 Aug 2011

View License

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

Cite As

Wolfgang Putschögl (2026). Approximating the Inverse Normal (https://www.mathworks.com/matlabcentral/fileexchange/28988-approximating-the-inverse-normal), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2010a
Compatible with any release
Platform Compatibility
Windows macOS Linux
Tags Add Tags
Open in new tab
Version Published Release Notes
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