# Generalized Inverse Gaussian Distribution

In probability theory and statistics, the generalized inverse Gaussian distribution (GIG) is a three-parameter family of continuous probability distributions with probability density function

where Kp is a modified Bessel function of the second kind, a > 0, b > 0 and p a real parameter. It is used extensively in geostatistics, statistical linguistics, finance, etc. This distribution was first proposed by Étienne Halphen. It was rediscovered and popularised by Ole Barndorff-Nielsen, who called it the generalized inverse Gaussian distribution, and Herbert Sichel. It is also known as the Sichel distribution. Its statistical properties are discussed in Bent Jørgensen's lecture notes.

### Other articles related to "generalized inverse gaussian distribution":

Generalized Inverse Gaussian Distribution - Entropy
... The entropy of the generalized inverse Gaussian distribution is given as where is a derivative of the modified Bessel function of the second kind with ...

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