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In probability theory and statistics, the gamma distribution is a versatile two-parameter family of continuous probability distributions. [1] The exponential distribution, Erlang distribution, and chi-squared distribution are special cases of the gamma distribution. [2] There are two equivalent parameterizations in common use:
The generalized gamma distribution is a continuous probability distribution with two shape parameters (and a scale parameter). It is a generalization of the gamma distribution which has one shape parameter (and a scale parameter).
The first version was introduced with PowerPoint 3.0 in 1992, to enable electronic presentations to be projected using conference-room computers and to be freely distributed; on Windows, it took advantage of the new feature of embedding TrueType fonts within PowerPoint presentation files to make such distribution easier. [175]
In statistics, a matrix gamma distribution is a generalization of the gamma distribution to positive-definite matrices. [1] It is effectively a different parametrization of the Wishart distribution, and is used similarly, e.g. as the conjugate prior of the precision matrix of a multivariate normal distribution and matrix normal distribution.
G. Gamma distribution; Gamma/Gompertz distribution; Gaussian q-distribution; Generalised hyperbolic distribution; Generalized beta distribution; Generalized chi-squared distribution
The GIG distribution is also the basis for a number of wrapped distributions in the wrapped gamma family. [12] As being a special case of the generalized chi-squared distribution, there are many other applications; for example, in renewal theory [1] and in multi-antenna wireless communications. [13] [14] [15] [16]
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