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K-distribution
About: K-distribution is a research topic. Over the lifetime, 1281 publications have been published within this topic receiving 51774 citations.
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TL;DR: In this paper, the authors considered the divisors of multivariate probability distributions that are decreasing at infinity not more slowly than normal distributions and that satisfy various symmetry conditions (in particular, the condition of spherical symmetry).
Abstract: The divisors of multivariate probability distributions are considered that are decreasing at infinity not more slowly than normal distributions and that satisfy various symmetry conditions (in particular, the condition of spherical symmetry).
TL;DR: In this article, the entropy and inaccuracy of similarly and oppositely ordered discrete probability distributions have been discussed in detail and it is shown that these inaccuracies are monotonically increasing function of \ for oppositely-ordered distributions and decreasing function of β for similarly ordered distributions.
Abstract: This note deals with the entropy and inaccuracy of similarly and oppositely ordered discrete probability distributions. The concept of inaccuracy range has also been introduced. In particular, the inacuracy of β-Power distributions with respect to another distribution has been discussed in detail. It is shown that these inaccuracies are monotonically increasing function of \ for oppositely ordered distributions and decreasing function of β for similarly ordered distributions.
TL;DR: Burmann series are used to give probability distributions which generalize the known class of distributions given by power series and positive linear operators associated with Burmann-series distribution are described. Convergence of these operators to continuous real functions is studied as discussed by the authors.
Abstract: Burmann series are used to give probability distributions which generalize the known class of distributions given by power series. Positive linear operators associated with Burmann-series distribution are described. Convergence of these operators to continuous real functions is studied. Examples are discussed.
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TL;DR: In this article, an index of uniformity is developed as an alternative to the maximum-entropy principle for selecting continuous, differentiable probability distributions subject to constraints on the first and second raw moments of a distribution.
Abstract: An index of uniformity is developed as an alternative to the maximum-entropy principle for selecting continuous, differentiable probability distributions $\mathcal{P}$ subject to constraints $C$. The uniformity index developed in this paper is motivated by the observation that among all differentiable probability distributions defined on a finite interval $[a,b] \in \mathbb{R}$, it is the uniform probability distribution that minimizes the path length of the associated cumulative distribution function $F_{\mathcal{P}}$ on $[a,b]$. This intuition is extended to situations where there are constraints on the allowable probability distributions. In particular, constraints on the first and second raw moments of a distribution are discussed in detail, including the analytical form of the solutions and numerical studies of particular examples. The resulting "shortest path" distributions are found to be decidedly more heavy-tailed than the associated maximum-entropy distributions, suggesting that entropy and "CDF path length" measure two different aspects of uncertainty for bounded distributions.
01 Jan 2007
TL;DR: The generalized curvi-triangular (GCT) distribution as discussed by the authors allows the shape of the density to be nontriangular and asymmetric, in general, in the symmetric triangular distribution.
Abstract: A family of distributions has been proposed which includes the symmetric triangular distribution as special case. The new family of distributions, which we refer to as generalized curvi-triangular (GCT) distributions, allows the shape of the density to be non-triangular and asymmetric, in general. The properties of GCT distributions along with the inferential procedures regarding the parameters are discussed.