Results 11 to 20 of about 4,943,403 (353)
Imprecise probability models for inference in exponential families [PDF]
, 2005 When considering sampling models described by a distribution from an exponential family, it is possible to create two types of imprecise probability models.
Erik Quaeghebeur, Gert de Cooman
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Sparse Exponential Family Principal Component Analysis. [PDF]
Pattern Recognit, 2016 We propose a Sparse exponential family Principal Component Analysis (SePCA) method suitable for any type of data following exponential family distributions, to achieve simultaneous dimension reduction and variable selection for better interpretation of the results. Because of the generality of exponential family distributions, the method can be applied
Lu M, Huang JZ, Qian X.
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Natural Gradient Flow in the Mixture Geometry of a Discrete Exponential Family
Entropy, 2015 In this paper, we study Amari’s natural gradient flows of real functions defined on the densities belonging to an exponential family on a finite sample space.
Luigi Malagò, Giovanni Pistone
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A new exponential family of distributions with applications to engineering and medical data. [PDF]
Sci RepSapkota LP, Bam N, Kumar V.
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ergm 4: New Features for Analyzing Exponential-Family Random Graph Models [PDF]
Journal of Statistical Software, 2021 The ergm package supports the statistical analysis and simulation of network data. It anchors the statnet suite of packages for network analysis in R introduced in a special issue in Journal of Statistical Software in 2008.
P. Krivitsky +3 more
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On Representations of Divergence Measures and Related Quantities in Exponential Families
Entropy, 2021 Within exponential families, which may consist of multi-parameter and multivariate distributions, a variety of divergence measures, such as the Kullback–Leibler divergence, the Cressie–Read divergence, the Rényi divergence, and the Hellinger metric, can ...
Stefan Bedbur, Udo Kamps
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Entropic Dynamics on Gibbs Statistical Manifolds
Entropy, 2021 Entropic dynamics is a framework in which the laws of dynamics are derived as an application of entropic methods of inference. Its successes include the derivation of quantum mechanics and quantum field theory from probabilistic principles.
Pedro Pessoa +2 more
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The curved exponential family of a staged tree [PDF]
Electronic Journal of Statistics, 2020 : Staged tree models are a discrete generalization of Bayesian networks. We show that these form curved exponential families and derive their natural parameters, sufficient statistic, and cumulant-generating func- tion as functions of their graphical ...
Christiane Gorgen +2 more
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Entropy, 2022 By calculating the Kullback–Leibler divergence between two probability measures belonging to different exponential families dominated by the same measure, we obtain a formula that generalizes the ordinary Fenchel–Young divergence.
Frank Nielsen
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, 2021 We introduce a new class of distributions called the generalized odd generalized exponential family. Some of its mathematical properties including explicit expressions for the ordinary and incomplete moments, quantile and generating functions, R ?́?nyi ...
M. Alizadeh +4 more
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