# ASA066 The Standard Normal Cumulative Density Function

ASA066 is a MATLAB library which computes the cumulative density function of the standard normal distribution, by David Hill.

ASA066 is Applied Statistics Algorithm 66. Source code for many Applied Statistics Algorithms is available through STATLIB.

### Languages:

ASA066 is available in a C version and a C++ version and a FORTRAN90 version and a MATLAB version.

### Related Data and Programs:

ASA111, a MATLAB library which evaluates the percentage points of the normal distribution.

ASA241, a MATLAB library which evaluates the percentage points of the normal distribution.

DCDFLIB, a FORTRAN90 library which evaluates and inverts a number of statistical distributions.

GSL, a C++ library which includes many routines for evaluating probability distributions.

NORMAL, a MATLAB library which samples the normal distribution.

PROB, a MATLAB library which evaluates and inverts a number of probabilistic distributions.

TEST_VALUES, a MATLAB library which contains sample values for a number of distributions.

UNIFORM, a MATLAB library which samples the uniform distribution.

### Author:

Original FORTRAN77 version by David Hill; MATLAB version by John Burkardt.

### Reference:

Algorithm 39: Areas Under the Normal Curve,
Computer Journal,
Volume 12, Number 2, May 1969, pages 197-198.
2. John Hart, Ward Cheney, Charles Lawson, Hans Maehly, Charles Mesztenyi, John Rice, Henry Thacher, Christoph Witzgall,
Computer Approximations,
Wiley, 1968,
LC: QA297.C64.
3. David Hill,
Algorithm AS 66: The Normal Integral,
Applied Statistics,
Volume 22, Number 3, 1973, pages 424-427.

### Source Code:

• alnorm.m, computes the cumulative density of the standard normal distribution.
• normal_01_cdf_values.m, returns some values of the Normal 01 CDF.
• normp.m, computes the cumulative density of the standard normal distribution.
• nprob.m, computes the cumulative density of the standard normal distribution.
• timestamp.m, prints out the current YMDHMS date as a timestamp.

Last revised on 25 November 2018.