On the issue of convergence of certain divergence measures related to finding most nearly compatible probability distribution under the discrete set-up
DOI10.1016/J.SPL.2023.109915OpenAlexW4385988446MaRDI QIDQ6084749
Author name not available (Why is that?)
Publication date: 6 November 2023
Published in: Statistics \& Probability Letters (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.spl.2023.109915
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Characterization and structure theory for multivariate probability distributions; copulas (62H05) Probability distributions: general theory (60E05) Characterization and structure theory of statistical distributions (62E10) Statistical aspects of information-theoretic topics (62B10)
Cites Work
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- Entropy differential metric, distance and divergence measures in probability spaces: A unified approach
- Interpreting Kullback--Leibler divergence with the Neyman-Pearson Lemma
- Characterizations of discrete distributions by a conditional distribution and a regression function
- Statistical aspects of divergence measures
- Distributions most nearly compatible with given families of conditional distributions
- On uniform marginal representation of contingency tables
- Bivariate discrete measures via a power series conditional distribution and a regression function
- Conditional specification of statistical models.
- On the construction of a joint distribution given two discrete conditionals
- Compatible Conditional Distributions
- Study of incompatibility or near compatibility of bivariate discrete conditional probability distributions through divergence measures
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