Results 21 to 30 of about 147,580 (306)
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
doaj +1 more source
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
openaire +4 more sources
The predictive view of Bayesian inference
, 2022 This thesis considers the direct connection between the prediction of future observations and Bayesian inference. Using prediction as a guide, we generalize the Bayesian framework and introduce new methodologies for parameter inference and model ...
Fong, Edwin
core +1 more source
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
doaj +1 more source
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
core +1 more source
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
doaj +1 more source
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
doaj +1 more source
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
doaj +1 more source
Skill rating by Bayesian inference [PDF]
2009 IEEE Symposium on Computational Intelligence and Data Mining, 2009 Systems Engineering often involves computer modelling the behaviour of proposed systems and their components. Where a component is human, fallibility must be modelled by a stochastic agent. The identification of a model of decision-making over quantifiable options is investigated using the game-domain of Chess.
Giuseppe Di Fatta +2 more
openaire +1 more source
HagesLab/Bayesian-Inference-TRPL: Final Publication Version
, 2022 This is the state of Bayesian-Inference-TRPL as of acceptance of our Joule article and is the version of the code used to calculate all inferences presented in that ...
cfai2304, charleshages
core +1 more source