Calculates a discrete truncated Gaussian distribution function
for a (discrete) random variable, X, as "slices" of an adapted Gaussian,
in (xmin, xmax) —indeed
(xmin−½, xmax+½).
The user can impose the mean, μ, (or not)
of the original (true) Gaussian.
This is to compensate for the lack of available discrete functions
(other than the classical binomial, Poisson, etc.). |
• Search "discrete probability distributions".
• Gelman, Carlin, Stern,
2004, "Bayesian
data analysis", 2.nd ed., Chapman & Hall/CRC,
home page (Columbia Univ.
in the City of New York). (Not useful; just cites the 'beta-binomial'.)
• Gut, Allan,
2005 (2nd. corr. print. 2007), "Probability: a graduate course",
Springer, New York, NY (USA) (ISBN: 978-0-387-22833-4), Ch. 15, "Sums of a random number
of random variables", p 83. G'b.
• Weisstein, Eric W., "Discrete distributions".
From MathWorld—A Wolfram Web Resource.
• 1860-05-03: Volterra, Vito, birthday. |
