Results 31 to 40 of about 758,750 (320)
Cobaya: code for Bayesian analysis of hierarchical physical models [PDF]
Journal of Cosmology and Astroparticle Physics, 2020 We present , a general-purpose Bayesian analysis code aimed at models with complex internal interdependencies. Without the need for specific code by the user, interdependencies between different stages of a model pipeline are exploited for sampling ...
J. Torrado, A. Lewis
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A Noise-Robust Fast Sparse Bayesian Learning Model [PDF]
, 2020 This paper utilizes the hierarchical model structure from the Bayesian Lasso in the Sparse Bayesian Learning process to develop a new type of probabilistic supervised learning approach.
Helgøy, Ingvild M., Li, Yushu
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Comment: Bayesian Checking of the Second Levels of Hierarchical Models
, 2008 Comment: Bayesian Checking of the Second Levels of Hierarchical Models [arXiv:0802.0743]Comment: Published in at http://dx.doi.org/10.1214/07-STS235A the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics ...
Gelman, Andrew
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Bayesian Hierarchical Random Effects Models in Forensic Science
Frontiers in Genetics, 2018 Statistical modeling of the evaluation of evidence with the use of the likelihood ratio has a long history. It dates from the Dreyfus case at the end of the nineteenth century through the work at Bletchley Park in the Second World War to the present day.
Colin G. G. Aitken
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Bayesian hierarchical model for protein identifications [PDF]
Journal of Applied Statistics, 2018 In proteomics, identification of proteins from complex mixtures of proteins extracted from biological samples is an important problem. Among the experimental technologies, mass spectrometry (MS) is the most popular one. Protein identification from MS data typically relies on a ‘two-step’ procedure of identifying the peptide first followed by the ...
Riten, Mitra +3 more
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Frontiers in Environmental Science, 2021 Large compilations of heterogeneous environmental observations are increasingly available as public databases, allowing researchers to test hypotheses across datasets.
Gregory L. Britten +13 more
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Hierarchical Bayesian space-time interpolation versus spatio-temporal BME approach [PDF]
Advances in Geosciences, 2010 The restrictions of the analysis of natural processes which are observed at any point in space or time to a purely spatial or purely temporal domain may cause loss of information and larger prediction errors.
I. Hussain, J. Pilz, G. Spoeck
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Generalized Direct Sampling for Hierarchical Bayesian Models [PDF]
, 2011 We develop a new method to sample from posterior distributions in hierarchical models without using Markov chain Monte Carlo. This method, which is a variant of importance sampling ideas, is generally applicable to high-dimensional models involving large
Braun, Michael, Damien, Paul
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BMC Evolutionary Biology, 2010 Background Explicit evolutionary models are required in maximum-likelihood and Bayesian inference, the two methods that are overwhelmingly used in phylogenetic studies of DNA sequence data.
Luo Arong +7 more
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A Hierarchical Bayesian Implementation of the Experience-Weighted Attraction Model
Computational Psychiatry, 2020 Social and decision-making deficits are often the first symptoms of neuropsychiatric disorders. In recent years, economic games, together with computational models of strategic learning, have been increasingly applied to the characterization of ...
Zhihao Zhang +4 more
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