Results 221 to 230 of about 99,191 (258)

Inference in Bayesian networks

Nature Biotechnology, 2006
Bayesian networks are increasingly important for integrating biological data and for inferring cellular networks and pathways. What are Bayesian networks and how are they used for inference?
Chris J, Needham, James R, Bradford, Andrew J, Bulpitt, David R, Westhead   +3 more
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Bayesian and Non-Bayesian Methods of Inference

Annals of Internal Medicine, 1983
Excerpt Statistics is an indispensable tool in clinical research. Disagreements over the use of various approaches such as those reflected in the letters-to-the-editor section of this issue (1,2) s...
R D, Small, S S, Schor
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Fuzzy Inference as a Generalization of the Bayesian Inference

Journal of Mathematical Sciences, 2016
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Koroteev, M. V., Terelyanskii, P. V., Ivanyuk, V. A.   +2 more
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Interpreting Generalized Bayesian Inference by Generalized Bayesian Inference

2023
The concept of safe Bayesian inference [ 4] with learning rates [5 ] has recently sparked a lot of research, e.g. in the context of generalized linear models [ 2]. It is occasionally also referred to as generalized Bayesian inference, e.g. in [2 , page 1] – a fact that should let IP advocates sit up straight and take notice, as this term is commonly ...
Rodemann, Julian, Augustin, Thomas, de Heide, Rianne   +2 more
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Bayesian Inferences on Umbrella Orderings

Biometrics, 2005
SummaryIn regression applications with categorical predictors, interest often focuses on comparing the null hypothesis of homogeneity to an ordered alternative. This article proposes a Bayesian approach for addressing this problem in the setting of normal linear and probit regression models.
Hans, Chris, Dunson, David B.
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Bayesian Inference

2012
This chapter provides an overview of the Bayesian approach to data analysis, modeling, and statistical decision making. The topics covered go from basic concepts and definitions (random variables, Bayes' rule, prior distributions) to various models of general use in biology (hierarchical models, in particular) and ways to calibrate and use them (MCMC ...
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In search of Bayesian inference

Communications of the ACM, 2014
Long relegated to the statistical backburner, Bayesian Inference is undergoing a renaissance.
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Bayesian model updating of civil structures with likelihood-free inference approach and response reconstruction technique

Mechanical Systems and Signal Processing, 2022
Qiang Han, Pinghe Ni
exaly  

Robust Approximate Bayesian Inference With Synthetic Likelihood

Journal of Computational and Graphical Statistics, 2021
Christopher Drovandi, David Frazier
exaly  

Bayesian Inference

2023
Wei Liang, Hongsheng Dai
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