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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)

Programming Language

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
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    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/prog/papers/0212/0212001.zip
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    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

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