Entropy (May 2023)

Information-Geometric Approach for a One-Sided Truncated Exponential Family

  • Masaki Yoshioka,
  • Fuyuhiko Tanaka

DOI
https://doi.org/10.3390/e25050769
Journal volume & issue
Vol. 25, no. 5
p. 769

Abstract

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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.

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