Results 31 to 40 of about 43,440 (267)
Trabajos de Prehistoria, 2016 The time spans of the so-called ditched enclosures are key to a better understanding of a type of site characterised by complex palimpsests. Several conclusions can be drawn from the 16 radiocarbon dates obtained from Ditch 4 at Marroquíes Bajos ...
Gonzalo Aranda Jiménez +7 more
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The Bayesian Boom: Good Thing or Bad?
Frontiers in Psychology, 2014 A series of high-profile critiques of Bayesian models of cognition have recently sparked controversy. These critiques question the contribution of rational, normative considerations in the study of cognition. The present article takes central claims from
Ulrike eHahn
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Comparing Bayesian Models of Annotation [PDF]
Transactions of the Association for Computational Linguistics, 2018 The analysis of crowdsourced annotations in natural language processing is concerned with identifying (1) gold standard labels, (2) annotator accuracies and biases, and (3) item difficulties and error patterns. Traditionally, majority voting was used for 1, and coefficients of agreement for 2 and 3.
Silviu Paun +5 more
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Bayesian outcome selection modeling
Stat, 2023 In psychiatric and social epidemiology studies, it is common to measure multiple different outcomes using a comprehensive battery of tests thought to be related to an underlying construct of interest. In the research that motivates our work, researchers wanted to assess the impact of in utero alcohol exposure on child cognition and neuropsychological ...
Khue‐Dung Dang +5 more
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A Bayesian Model of Voting in Juries [PDF]
Games and Economic Behavior, 2001 Individual votes in group decisions are here modeled on a framework of inference on parameters determining the distribution of received signals. It is proven that, as the size of the jury increase, the probability of a mistaken judgment goes to zero unless unanimity is needed and the likelihood ratio is bounded. Conditions in terms of the ratio between
John Duggan, César Martinelli
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Bayesian Mixture Modelling for Mortality Projection
Risks, 2021 Although a large number of mortality projection models have been proposed in the literature, relatively little attention has been paid to a formal assessment of the effect of model uncertainty.
Jackie Li, Atsuyuki Kogure
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Troubleshooting Bayesian cognitive models
Psychological Methods, 2021 Using Bayesian methods to apply computational models of cognitive processes, or Bayesian cognitive modeling, is an important new trend in psychological research. The rise of Bayesian cognitive modeling has been accelerated by the introduction of software that efficiently automates the Markov chain Monte Carlo sampling used for Bayesian model fitting --
Beth Baribault, Anne G. E. Collins
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disaggregation: An R Package for Bayesian Spatial Disaggregation Modeling
Journal of Statistical Software, 2023 Disaggregation modeling, or downscaling, has become an important discipline in epidemiology. Surveillance data, aggregated over large regions, is becoming more common, leading to an increasing demand for modeling frameworks that can deal with this data ...
Anita K. Nandi +4 more
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On Identification of Bayesian DSGE Models [PDF]
Journal of Business & Economic Statistics, 2011 In recent years there has been increasing concern about the identification of parameters in dynamic stochastic general equilibrium (DSGE) models. Given the structure of DSGE models it may be difficult to determine whether a parameter is identified.
Koop, Gary +2 more
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Frontiers in Psychology, 2016 Cognitive determinants of probabilistic inference were examined using hierarchical Bayesian modelling techniques. A classic urn-ball paradigm served as experimental strategy, involving a factorial two (prior probabilities) by two (likelihoods) design ...
Moritz eBoos +3 more
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