A Short Note on the Numerical Approximation of the Standard Normal Cumulative Distribution and Its Inverse

We provide computer codes in ANSI-C and Python for a fast and accurate computation of the cumulative distribution function (cdf) of the standard normal distribution and the inverse cdf of the same function. For the cdf we use the 5th order Gauss-Legendre quadrature which gives more accurate results compared to Excel and Matlab. The Inverse cdf is computed using rational fraction approximations and gives a result that is seven-decimal place accurate.

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Year of publication:	2002-12-27
Authors:	Dridi, Chokri
Institutions:	EconWPA
Keywords:	C/C++ Gauss-Legendre Quadarture Normal distribution Numerical Integration Rational fraction approximations Software

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Extent:	application/pdf
Series:	Computational Economics.
Type of publication:	Book / Working Paper
Notes:	Type of Document - ; pages: 13 ; figures: included. cdf.c : Is ANSI-C code to compute the cdf of standard normal dist. using a composite fifth-order Gauss-Legendre quadrature cdf-GL.py : same as cdf.c except the code is written in Python cdf.py : Python code to compute the cdf using rational fraction approximations invcdf.py : Python code to compute the inverse cdf using rational fraction approximations. ftp://wueconb.wustl.edu/econ-wp/prog/papers/0212/0212001.zip 13 pages
Classification:	C63 - Computational Techniques ; C88 - Other Computer Software ; C89 - Data Collection and Data Estimation Methodology; Computer Programs. Other
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005412996