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Information-Geometric Approach for a One-Sided Truncated Exponential Family
by
Tanaka, Fuyuhiko
, Yoshioka, Masaki
in
alpha-parallel prior
/ Analysis
/ Asymptotic properties
/ Codes
/ common scale parameter
/ Differential geometry
/ Functions, Exponential
/ Geometrical models
/ Geometry
/ information geometry
/ Information theory
/ Maximum likelihood estimators
/ non-regular model
/ Parameter estimation
/ Random variables
/ statistical manifold
/ Statistical models
/ truncated exponential family
2023
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Information-Geometric Approach for a One-Sided Truncated Exponential Family
by
Tanaka, Fuyuhiko
, Yoshioka, Masaki
in
alpha-parallel prior
/ Analysis
/ Asymptotic properties
/ Codes
/ common scale parameter
/ Differential geometry
/ Functions, Exponential
/ Geometrical models
/ Geometry
/ information geometry
/ Information theory
/ Maximum likelihood estimators
/ non-regular model
/ Parameter estimation
/ Random variables
/ statistical manifold
/ Statistical models
/ truncated exponential family
2023
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Do you wish to request the book?
Information-Geometric Approach for a One-Sided Truncated Exponential Family
by
Tanaka, Fuyuhiko
, Yoshioka, Masaki
in
alpha-parallel prior
/ Analysis
/ Asymptotic properties
/ Codes
/ common scale parameter
/ Differential geometry
/ Functions, Exponential
/ Geometrical models
/ Geometry
/ information geometry
/ Information theory
/ Maximum likelihood estimators
/ non-regular model
/ Parameter estimation
/ Random variables
/ statistical manifold
/ Statistical models
/ truncated exponential family
2023
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Information-Geometric Approach for a One-Sided Truncated Exponential Family
Journal Article
Information-Geometric Approach for a One-Sided Truncated Exponential Family
2023
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Overview
In information geometry, there has been extensive research on the deep connections between differential geometric structures, such as the Fisher metric and the α-connection, and the statistical theory for statistical models satisfying regularity conditions. However, the study of information geometry for non-regular statistical models is insufficient, and a one-sided truncated exponential family (oTEF) is one example of these models. In this paper, based on the asymptotic properties of maximum likelihood estimators, we provide a Riemannian metric for the oTEF. Furthermore, we demonstrate that the oTEF has an α = 1 parallel prior distribution and that the scalar curvature of a certain submodel, including the Pareto family, is a negative constant.
Publisher
MDPI AG,MDPI
Subject
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