We provide a uniformly efficient and simple random variate generator for the entire parameter range of the generalized inverse gaussian distribution. A general algorithm is provided as well that works for all densities that are proportional to a log-concave function φ, even if the normalization constant is not known. It requires only black box access to φ and its derivative.

We consider a system described by a Fokker-Planck equation with a new type of momentumdependent drift coefficient which asymptotically decreases as −1/p for a large momentum p. It is shown that the steady-state of this system is a κ-generalized Gaussian distribution, which is a non-Gaussian distribution with a power-law tail. PACS. 05.20.Dd Kinetic theory – 05.20.-y Classical statistical mechan...

in this paper, we derive the exact analytical expressions for the shannon entropy of generalized orderstatistics from pareto-type and related distributions.

This paper presents Maximum A Posteriori (MAP) estimation of the spectral components of clean speech from the observed data noised by the additive background noise having Gaussian or non-Gaussian statistical distribution. In the proposed algorithm MAP estimator for the spectral components of clean signal is derived using Generalized Gaussian Distribution (GGD) function as a priori statistical m...

In this paper, we consider a form of the generalized logistic distribution named symmetric extended generalized logistic distribution or extended type III generalized logistic distribution. The distribution is derived by compounding a two-parameter generalized Gumbel distribution with a two-parameter generalized gamma distribution. The cumulative distribution and some properties of this distrib...

The statistics of natural images play an important role in many image processing tasks. In particular, statistical assumptions about differences between neighboring pixel values are used extensively in the form of prior information for many diverse applications. The most common assumption is that these pixel difference values can be described be either a Laplace or Generalized Gaussian distribu...

From a distribution of people’s heights in a group to error signal detection, the Gaussian Distribution provides various applications to predict the probability of a generalized distribution. Especially, the Gaussian Distribution is generally applicable to explain a biological or physiological phenomenon because it shows the most realistic distribution in biology and physiology. In the human mu...