Results 21 to 30 of about 862,083 (298)
Randomization-based, Bayesian inference of causal effects
Journal of Causal Inference, 2023 Bayesian causal inference in randomized experiments usually imposes model-based structure on potential outcomes. Yet causal inferences from randomized experiments are especially credible because they depend on a known assignment process, not a ...
Leavitt Thomas
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On the Geometry of Bayesian Inference [PDF]
Bayesian Analysis, 2019 We provide a geometric interpretation to Bayesian inference that allows us to introduce a natural measure of the level of agreement between priors, likelihoods, and posteriors. The starting point for the construction of our geometry is the simple observation that the marginal likelihood can be regarded as an inner product between the prior and the ...
de Carvalho, Miguel +2 more
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New Frontiers in Bayesian Modeling Using the INLA Package in R
Journal of Statistical Software, 2021 The INLA package provides a tool for computationally efficient Bayesian modeling and inference for various widely used models, more formally the class of latent Gaussian models.
Janet Van Niekerk +3 more
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Bayesian Inference and Compressed Sensing [PDF]
, 2017 This chapter provides the use of Bayesian inference in compressive sensing (CS), a method in signal processing. Among the recovery methods used in CS literature, the convex relaxation methods are reformulated again using the Bayesian framework and this ...
Tesfamicael, Solomon Abedom
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Frontiers in Neuroinformatics, 2018 Recent debates about the conventional traditional threshold used in the fields of neuroscience and psychology, namely P < 0.05, have spurred researchers to consider alternative ways to analyze fMRI data.
Hyemin Han, Joonsuk Park
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Energies, 2023 This paper introduces a novel techno-economic feasibility analysis of energy management utilizing the Homer software v3.14.5 environment for an independent hybrid microgrid.
Abdellah Benallal +5 more
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Ciência Rural, 2021 : Although the fruit yield has a core importance in Tahiti acid lime breeding programs, other traits stand out among the quality fruit and vegetative traits as ones that still need to be improved in selection of superior genotypes.
Renan Garcia Malikouski +6 more
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Bayesian Inference with Projected Densities
SIAM/ASA Journal on Uncertainty Quantification, 2023 Constraints are a natural choice for prior information in Bayesian inference. In various applications, the parameters of interest lie on the boundary of the constraint set. In this paper, we use a method that implicitly defines a constrained prior such that the posterior assigns positive probability to the boundary of the constraint set.
Jasper M. Everink +2 more
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Bayesian statistical inference
Statistica, 2017 This work was translated into English and published in the volume: Bruno De Finetti, Induction and Probability, Biblioteca di Statistica, eds. P. Monari, D.
Bruno De Finetti
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Expectation propagation for large scale Bayesian inference of non-linear molecular networks from perturbation data. [PDF]
PLoS ONE, 2017 Inferring the structure of molecular networks from time series protein or gene expression data provides valuable information about the complex biological processes of the cell.
Zahra Narimani +4 more
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