IDEAS home Printed from https://ideas.repec.org/c/wpa/wuwppr/0212001.html
 

Computer code for: A Short Note on the Numerical Approximation of the Standard Normal Cumulative Distribution and Its Inverse

Author

Listed:
  • Chokri Dridi

    (Department of Agriculture & Consumer Economics, & Regional Economics Applications Laboratory, University of Illinois at Urbana-Champaign)

Abstract

Content: (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

Suggested Citation

  • Chokri Dridi, 2002. "Computer code for: A Short Note on the Numerical Approximation of the Standard Normal Cumulative Distribution and Its Inverse," Computer Programs 0212001, University Library of Munich, Germany.
  • Handle: RePEc:wpa:wuwppr:0212001
    Note: Type of Document - AINSI-C/Python. Content: (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
    as

    Download full text from publisher

    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/prog/papers/0212/0212001.zip
    Download Restriction: no

    More about this item

    Keywords

    ANSI-C Python;

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software
    • C89 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wpa:wuwppr:0212001. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (EconWPA). General contact details of provider: https://econwpa.ub.uni-muenchen.de .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.