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Wyświetlanie 1-2 z 2
Tytuł:
Information Geometry of Frechet Distributions
Autorzy:
Arwini, Khadiga Ali
Powiązania:
https://bibliotekanauki.pl/articles/1030590.pdf
Data publikacji:
2020
Wydawca:
Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
Tematy:
Frechet distribution
extreme value distributions
information geometry
statistical manifold
Opis:
Using the Fisher information matrix (FIM) as a Riemannian metric, the family of Frechet distributions determines a two dimensional Riemannian manifold. In this paper we illustrates the information geometry of the Frechet space, and derive the α-geometry as; α-connections, α-curvature tensor, α-Ricci curvature with its eigenvalues and eigenvectors, α-sectional curvature, α-mean curvature, and α-scalar curvature, where we show that Frechet space has a constant α-scalar curvature. The special case where α = 0 corresponds to the geometry induced by the Levi-Civita connection. In addition, we consider three special cases of Frechet distributions as submanifolds with dimension one, and discuss their geometrical structures, then we prove that one of these submanifolds is an isometric isomorph of the exponential manifold, which is important in stochastic process since exponential distributions represent intervals between events for Poisson processes. After that, we introduce log-Frechet distributions, and show that this family of distributions determines a Riemannian 2-manifold which is isometric with the origin manifold. Finally, an explicit expressions for some distances in Frechet space are obtained as, Kullback-Leibler distance, and J-divergence.
Źródło:
World Scientific News; 2020, 144; 296-312
2392-2192
Pojawia się w:
World Scientific News
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The Geometrical Structures of Bivariate Gamma Exponential Distributions
Autorzy:
Arwini, Khadiga Ali
Powiązania:
https://bibliotekanauki.pl/articles/1030111.pdf
Data publikacji:
2020
Wydawca:
Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
Tematy:
Pareto distribution
bivariate distributions
bivariate gamma exponential distribution
gamma distribution
information geometry
statistical manifold
Opis:
This paper is devoted to the information geometry of the family of bivariate gamma exponential distributions, which have gamma and Pareto marginals, and discuss some of its applications. We begin by considering the parameter bivariate gamma exponential manifold as a Riemannian 3-manifold; by following Rao’s idea to use the Fisher information matrix (FIM), and derive the α-geometry as: α-connections, α-curvature tensor, α-Ricci curvature with its eigenvalues and eigenvectors, and α-scalar curvature. Where here the 0-geometry corresponds to the geometry induced by the Levi-Civita connection, and we show that this space has a non-constant negative scalar curvature. In addition, we consider four submanifolds as special cases, and discuss their geometrical structures, and we prove that one of these submanifolds is an isometric isomorph of the univariate gamma manifold. Then we introduce log-bivariate gamma exponential distributions, which have log-gamma and log-Pareto marginals, and we show that this family of distributions determines a Riemannian 3-manifold which is isometric with the origin manifold. We give an analytical solution for the geodesic equations, and obtain the explicit expressions for Kullback-Leibler distance, J-divergence and Bhattacharyya distance. Finally, we prove that the bivariate gamma exponential manifold can be realized in R4, using information theoretic immersions, and we give explicit information geometric tubular neighbourhoods for some special cases.
Źródło:
World Scientific News; 2020, 143; 181-202
2392-2192
Pojawia się w:
World Scientific News
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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