K-distribution


In probability and statistics, the K-distribution is a three-parameter family of continuous probability distributions.
The distribution arises by compounding two gamma distributions. In each case, a re-parametrization of the usual form of the family of gamma distributions is used, such that the parameters are:
K-distribution is a special case of variance-gamma distribution, which in turn is a special case of generalised hyperbolic distribution.

Density

The model is that random variable has a gamma distribution with mean and shape parameter, with being treated as a random variable having another gamma distribution, this time with mean and shape parameter. The result is that has the following probability density function for :
where and is a modified Bessel function of the second kind. In this derivation, the K-distribution is a compound probability distribution. It is also a product distribution: it is the distribution of the product of two independent random variables, one having a gamma distribution with mean 1 and shape parameter, the second having a gamma distribution with mean and shape parameter.
A simpler two parameter formalization of the K-distribution is
where v is the shape factor, b is the scale factor, and K is the modified Bessel function of second kind.
This distribution derives from a paper by Eric Jakeman and Peter Pusey who used it to model microwave sea echo. Jakeman and Tough derived the distribution from a biased random walk model. Ward derived the distribution from the product for two random variables, z = a y, where a has a chi distribution and y a complex Gaussian distribution. The modulus of z, |z|, then has K distribution.

Moments

The moment generating function is given by
where is the Whittaker function.
The n-th moments of K-distribution is given by
So the mean and variance are given by

Other properties

All the properties of the distribution are symmetric in and

Applications

K-distribution arises as the consequence of a statistical or probabilistic model used in synthetic-aperture radar imagery. The K-distribution is formed by compounding two separate probability distributions, one representing the radar cross-section, and the other representing speckle that is a characteristic of coherent imaging. It is also used in wireless communication to model composite fast fading and shadowing effects.