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Objective Bayesian Variable Selection
Journal of the American Statistical Association, 2006A novel fully automatic Bayesian procedure for variable selection in normal regression models is proposed. The procedure uses the posterior probabilities of the models to drive a stochastic search. The posterior probabilities are computed using intrinsic priors, which can be considered default priors for model selection problems; that is, they are ...
Casella, George, Moreno, Elias
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Bayesianism: Objections and Rebuttals
2021Abstract While the laws of probability are rarely disputed, the question of how we should interpret probability judgments is less straightforward. Broadly, there are two ways to conceive of probability—either as an objective feature of the world, or as a subjective measure of our uncertainty. Both notions have their place in science, but
Norman Fenton, David Lagnado
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2020
In this chapter I analyse an objection to phenomenal conservatism to the effect that phenomenal conservatism is unacceptable because it is incompatible with Bayesianism. I consider a few responses and dismiss them as misled or problematic. Then, I argue that the objection doesn’t go through because it rests on an implausible formalization of the notion
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In this chapter I analyse an objection to phenomenal conservatism to the effect that phenomenal conservatism is unacceptable because it is incompatible with Bayesianism. I consider a few responses and dismiss them as misled or problematic. Then, I argue that the objection doesn’t go through because it rests on an implausible formalization of the notion
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Distributed Bayesian object recognition
Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2002A new paradigm for performing realistic object recognition is presented. It is shown how several intuitive notions in the context of geometric hashing can be translated into a well-founded Bayesian approach to object recognition. This interpretation leads to well-justified formulas and gives a precise weighted-voting method for the evidence-gathering ...
I. Rigoutsos, R. Hummel
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Objective Bayesian Epistemology
2010We now turn to the final semantics for probabilistic logic that we consider in this book: the objective Bayesian semantics. In §7.1 we provide an introduction to objective Bayesian epistemology, which holds that the strengths of an agent’s beliefs should be representable by certain probability functions.
Rolf Haenni +3 more
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‘Objective’ bayesian unit root tests
Journal of Applied Econometrics, 1992AbstractDue to weaknesses in traditional tests, a Bayesian approach is developed to investigate whether unit roots exist in macroeconomic time‐series. Bayesian posterior odds comparing unit root models to stationary and trend‐stationary alternatives are calculated using informative priors.
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BAYESIAN PROPAGATION FOR PERCEIVING MOVING OBJECTS
International Journal of Pattern Recognition and Artificial Intelligence, 2006In this paper we address the issue of how form and motion can be integrated in order to provide suitable information to attentively track multiple moving objects. Such integration is designed in a Bayesian framework, and a Belief Propagation technique is exploited to perform coherent form/motion labeling of regions of the observed scene.
BOCCIGNONE, Giuseppe +4 more
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Networks for Objective Bayesianism
2010In principle then we consider only a single model of the premisses, the probability function that has maximum entropy from all those that satisfy the premisses, and see whether that satisfies the conclusion. This model can be represented by a Bayesian network, and one can use this network to calculate the probability Y to attach to the conclusion ...
Rolf Haenni +3 more
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Objective Bayesian probabilistic logic
Journal of Algorithms, 2008This paper develops connections between objective Bayesian epistemology-which holds that the strengths of an agent's beliefs should be representable by probabilities, should be calibrated with evidence of empirical probability, and should otherwise be equivocal-and probabilistic logic.
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On the principal principle and imprecise subjective Bayesianism
European Journal for Philosophy of Science, 2021M. Fischer
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