Results 41 to 50 of about 1,820,384 (367)
Universality of Bayesian Predictions [PDF]
, 2007 Given the sequential update nature of Bayes rule, Bayesian methods find natural application to prediction problems. Advances in computational methods allow to routinely use Bayesian methods in econometrics.
Sancetta, Alessio
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Inferring a Property of a Large System from a Small Number of Samples
Entropy, 2022 Inferring the value of a property of a large stochastic system is a difficult task when the number of samples is insufficient to reliably estimate the probability distribution.
Damián G. Hernández, Inés Samengo
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On the relation between robust and Bayesian decision making [PDF]
, 2003 This paper compares Bayesian decision theory with robust decision theory where the decision maker optimizes with respect to the worst state realization.
Adam, Klaus
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Erkenntnis, 2020 AbstractThe Sleeping Beauty problem has attracted considerable attention in the literature as a paradigmatic example of how self-locating uncertainty creates problems for the Bayesian principles of Conditionalization and Reflection. Furthermore, it is also thought to raise serious issues for diachronic Dutch Book arguments.
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A surrogate Bayesian framework for a SARS-CoV-2 data driven stochastic model
Computational and Mathematical Biophysics, 2022 Dynamic compartmentalized data (DCD) and compartmentalized differential equations (CDEs) are key instruments for modeling transmission of pathogens such as the SARS-CoV-2 virus.
Ganesh M., Hawkins S. C.
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Theoretical Computer Science, 2010 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Noga Alon +3 more
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Bayesian threshold analysis of litter size in sheep
Revista Colombiana de Ciencias Pecuarias, 2022 Background: Litter size at birth (LSB) is one of the most important economic traits in sheep and could be used in genetic improvement schemes for meat production.
Amin Mortazavi +5 more
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Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach
Social Science Research Network, 2007 Using a Bayesian likelihood approach, we estimate a dynamic stochastic general equilibrium model for the US economy using seven macro-economic time series.
F. Smets, R. Wouters
semanticscholar +1 more source
Learning Bayesian networks: The combination of knowledge and statistical data [PDF]
Machine-mediated learning, 1994 We describe a Bayesian approach for learning Bayesian networks from a combination of prior knowledge and statistical data. First and foremost, we develop a methodology for assessing informative priors needed for learning.
D. Heckerman +2 more
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Scientific ReportsThis paper presents a novel approach for digital twin applications in surgical planning, integrating a differentiable simulator for trajectory generation within segmented medical images and a virtual reality (VR) platform for navigating an overlay of ...
Robin Cremese +9 more
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