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.

Read more about Generalized Inverse Gaussian DistributionSpecial Cases, Entropy

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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