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A RECURSION FORMULA FOR BAYESIAN PROBABILITIES
Psychological Reports, 2003A recursion formula for Bayes' formula is derived. The formula is useful in applications in which diagnoses are added in a stepwise way to predict a criterion. On each step, changes in various diagnostic measures can be easily evaluated.
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On Fuzzy Probabilities in Bayesian Games
2011 Workshop-School on Theoretical Computer Science, 2011This work proposes an application of fuzzy probabilities, respecting an arithmetic restriction, in order to estimate unknown types of players in a bayesian game, thus configuring a fuzzy bayesian game. To this end, besides defining the operations needed for this application, a hypothetical example of a bayesian game is presented and then this ...
Graçaliz Pereira Dimuro+1 more
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Uncertainty plus prior equals rational bias: an intuitive Bayesian probability weighting function.
Psychology Review, 2012Empirical research has shown that when making choices based on probabilistic options, people behave as if they overestimate small probabilities, underestimate large probabilities, and treat positive and negative outcomes differently.
J. Fennell, R. Baddeley
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Inference of emission rates from multiple sources using Bayesian probability theory.
Journal of Environmental Monitoring, 2010The determination of atmospheric emission rates from multiple sources using inversion (regularized least-squares or best-fit technique) is known to be very susceptible to measurement and model errors in the problem, rendering the solution unusable.
E. Yee, T. Flesch
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Vagueness and Bayesian probability
IEEE Transactions on Fuzzy Systems, 1994This paper is a response to Michael Laviolette and John W. Seaman Jr.'s ( ibid. vol.2, no.1, p.4 (1994)) position paper "The efficacy of fuzzy representations of uncertainty," which criticizes fuzzy representations of uncertainty, and suggests that Bayesian probability can do better.
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Bayesian Updating of Seismic Probability
Nuclear Science and Engineering, 1986For those nuclear power plants for which a seismic probabilistic risk assessment has been conducted, it is possible to infer a prediction for the recurrence rate of the safe shutdown earthquake, and then to compare it with the historic seismicity at the site. Using the Bayesian algorithm, it is then possible to update the prediction in such a way as to
S. Seth, H. W. Lewis
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BAYESIAN INFERENCE OF FUZZY PROBABILITIES
International Journal of General Systems, 1997Abstract In this paper, we propose a new method to generalize Bayesian methods both for fuzzy likelihood and fuzzy prior probabilities. Based on interval Bayesian inference developed by Pan and Klir [1996], the proposed method overcomes the difficulty in developing a normalized fuzzy Bayesian inference recognized in the literature [Friihwirth-Schnatter,
Yin Pan, Bo Yuan
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Probabilities: Bayesian Classifiers
2015The earliest attempts to predict an example’s class based on the known attribute values go back to well before World War II—prehistory, by the standards of computer science. Of course, nobody used the term “machine learning,” in those days, but the goal was essentially the same as the one addressed in this book.
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Bayesian Inferences on Predictors of Conception Probabilities
Biometrics, 2005SummaryReproductive scientists and couples attempting pregnancy are interested in identifying predictors of the day‐specific probabilities of conception in relation to the timing of a single intercourse act. Because most menstrual cycles have multiple days of intercourse, the occurrence of conception represents the aggregation across Bernoulli trials ...
Joseph B. Stanford, David B. Dunson
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INDUCTION, PROBABILITY, AND BAYESIAN EPISTEMOLOGY
2003In the last sixty years Finnish analytical philosophers have been extensively investigating induction and probability, and their role in empirical sciences. In this paper the main lines and outcomes of such studies are examined. In particular, the following issues are considered: von Wright’s theory of inductive elimination and his analysis of ...
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