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An approximation to the convolution of gamma distributions

Communications in Statistics - Simulation and Computation, 2016
AbstractIn general, the exact distribution of a convolution of independent gamma random variables is quite complicated and does not admit a closed form.
openaire   +2 more sources

Mixtures of Gamma Distributions With Applications

Journal of Computational and Graphical Statistics, 2001
This article proposes a Bayesian density estimation method based upon mixtures of gamma distributions. It considers both the cases of known mixture size, using a Gibbs sampling scheme with a Metropolis step, and unknown mixture size, using a reversible jump technique that allows us to move from one mixture size to another.
Wiper Michael Peter   +2 more
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Characterizations of the Normal and the Gamma distributions

Zeitschrift f�r Wahrscheinlichkeitstheorie und Verwandte Gebiete, 1973
The Normal and the Gamma distribution, properly translated, are characterized by a uniformly minimum variance property of the sample mean. In fact, we answer in particular a question asked by Kagan in 1966. Also an optimality property of the sample variance is proved to characterize the Normal distribution.
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GAMMA distribution

2011
Kimiko O. Bowman, L. R. Shenton
  +5 more sources

The gamma distribution

1980
The general form of the gamma distribution is $$ f(x\left| {\alpha ,\beta } \right.) = \beta ^\alpha x^{\alpha - 1} e^{ - \beta x} /\Gamma (x){\text{ }}\:x \geqslant 0 $$ The parameter α is a shape parameter and s a scale parameter.
openaire   +1 more source

Gamma Distribution

2021
Rajan Chattamvelli, Ramalingam Shanmugam
openaire   +2 more sources

Gamma-Ray Bursts

Annual Review of Astronomy and Astrophysics, 1995
Gerald J Fishman, Charles A Meegan
exaly  

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