ASA266
Estimating the Parameters of a Dirichlet PDF


ASA266 is a MATLAB library which estimates the parameters of a Dirichlet probability density function.

ASA266 is Applied Statistics Algorithm 266. Source code for many Applied Statistics Algorithms is available through STATLIB.

The assumption is that a given process is governed by a Dirichlet distribution with parameters ALPHA(I), I = 1 to N, positive quantities which are required to sum to 1. Each observation of the process yields a vector of N data values. After a number of observations of this sort, it is desired to estimate the the underlying parameters ALPHA of the Dirichlet distribution.

There are a considerable number of routines required to get DIRICH to work. In some cases, there are several versions of the routines, and they all were included, in order to provide a way to check results. Most of the routines are themselves Applied Statistics Algorithms, and their source code is available through STATLIB.

Also included is a routine DIRICHLET_SAMPLE, with which experiments can be carried out. Values for the parameters ALPHA can be chosen, and data generated by DIRICHLET_SAMPLE. Then DIRICH can analyze this data and attempt to determine the values of ALPHA.

Another routine, DIRICHLET_MIX_SAMPLE, allows you to sample a probability distribution that is a weighted mixture of Dirichlet distributions.

Licensing:

The computer code and data files described and made available on this web page are distributed under the GNU LGPL license.

Languages:

ASA266 is available in a C version and a C++ version and a FORTRAN77 version and a FORTRAN90 version and a MATLAB version.

Related Data and Programs:

ASA032, a MATLAB library which evaluates the incomplete Gamma integral.

ASA066, a MATLAB library which evaluates the percentage points of the normal distribution.

ASA091, a MATLAB library which evaluates the percentage points of the Chi-Squared distribution.

ASA103, a MATLAB library which evaluates the digamma or psi function.

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

ASA121, a MATLAB library which evaluates the trigamma function.

ASA147, a MATLAB library which evaluates the incomplete Gamma function.

ASA239, a MATLAB library which evaluates the percentage points of the Chi-Squared distribution and the incomplete Gamma function.

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

ASA245, a MATLAB library which evaluates the logarithm of the Gamma function.

NORMAL, a MATLAB library which samples the normal distribution.

PROB, a MATLAB library which evaluates the PDF, CDF, mean and variance for a number of probability density functions.

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

TOMS291, a MATLAB library which evaluates the logarithm of the Gamma function.

UNIFORM, a MATLAB library which samples the uniform distribution.

Reference:

  1. AG Adams,
    Algorithm 39: Areas Under the Normal Curve,
    Computer Journal,
    Volume 12, Number 2, May 1969, pages 197-198.
  2. Joachim Ahrens, Ulrich Dieter,
    Computer Methods for Sampling from Gamma, Beta, Poisson and Binomial Distributions,
    Computing,
    Volume 12, Number 3, September 1974, pages 223-246.
  3. Joachim Ahrens, Ulrich Dieter,
    Generating Gamma Variates by a Modified Rejection Technique,
    Communications of the ACM,
    Volume 25, Number 1, January 1982, pages 47-54.
  4. Jerry Banks, editor,
    Handbook of Simulation,
    Wiley, 1998,
    ISBN: 0471134031,
    LC: T57.62.H37.
  5. JD Beasley, SG Springer,
    Algorithm AS 111: The Percentage Points of the Normal Distribution,
    Applied Statistics,
    Volume 26, Number 1, 1977, pages 118-121.
  6. Jose Bernardo,
    Algorithm AS 103: Psi ( Digamma ) Function,
    Applied Statistics,
    Volume 25, Number 3, 1976, pages 315-317.
  7. Donald Best, DE Roberts,
    Algorithm AS 91: The Percentage Points of the Chi-Squared Distribution,
    Applied Statistics,
    Volume 24, Number 3, 1975, pages 385-390.
  8. G Bhattacharjee,
    Algorithm AS 32: The Incomplete Gamma Integral,
    Applied Statistics,
    Volume 19, Number 3, 1970, pages 285-287.
  9. William Cody, Kenneth Hillstrom,
    Chebyshev Approximations for the Natural Logarithm of the Gamma Function,
    Mathematics of Computation,
    Volume 21, Number 98, April 1967, pages 198-203.
  10. William Cody, Anthony Strecok, Henry Thacher,
    Chebyshev Approximations for the Psi Function,
    Mathematics of Computation,
    Volume 27, Number 121, January 1973, pages 123-127.
  11. John Hart, Ward Cheney, Charles Lawson, Hans Maehly, Charles Mesztenyi, John Rice, Henry Thacher, Christoph Witzgall,
    Computer Approximations,
    Wiley, 1968,
    LC: QA297.C64.
  12. David Hill, Algorithm AS 66: The Normal Integral,
    Applied Statistics,
    Volume 22, Number 3, 1973, pages 424-427.
  13. Cornelius Lanczos,
    A precision approximation of the gamma function,
    SIAM Journal on Numerical Analysis, B,
    Volume 1, 1964, pages 86-96.
  14. Chi Leung Lau,
    Algorithm AS 147: A Simple Series for the Incomplete Gamma Integral,
    Applied Statistics,
    Volume 29, Number 1, 1980, pages 113-114.
  15. Allan Mcleod,
    Algorithm AS 245: A Robust and Reliable Algorithm for the Logarithm of the Gamma Function,
    Applied Statistics,
    Volume 38, Number 2, 1989, pages 397-402.
  16. A. Naryanan,
    Algorithm AS 266: Maximum Likelihood Estimation of the Parameters of the Dirichlet Distribution,
    Applied Statistics,
    Volume 40, Number 2, 1991, pages 365-374.
  17. Malcolm Pike, David Hill,
    Algorithm 291: Logarithm of Gamma Function,
    Communications of the ACM,
    Volume 9, Number 9, September 1966, page 684.
  18. BE Schneider,
    Algorithm AS 121: Trigamma Function,
    Applied Statistics,
    Volume 27, Number 1, 1978, pages 97-99.
  19. BL Shea,
    Algorithm AS 239: Chi-squared and Incomplete Gamma Integral,
    Applied Statistics,
    Volume 37, Number 3, 1988, pages 466-473.
  20. Michael Wichura,
    Algorithm AS 241: The Percentage Points of the Normal Distribution,
    Applied Statistics,
    Volume 37, Number 3, 1988, pages 477-484.

Source Code:

Examples and Tests:

You can go up one level to the MATLAB source codes.


Last revised on 04 August 2010.