Results 41 to 50 of about 7,662,414 (297)

Using hierarchical Bayesian methods to examine the tools of decision-making [PDF]

Judgment and Decision Making, 2011
Hierarchical Bayesian methods offer a principled and comprehensive way to relate psychological models to data. Here we use them to model the patterns of information search, stopping and deciding in a simulated binary comparison judgment task.
Michael D. Lee, Benjamin J. Newell
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Hierarchical modeling of risk factors with and without prior information—the process of regression model evaluation for an example of respiratory diseases in piglet production from daily practice data

Frontiers in Veterinary Science
In veterinary epidemiology, regression models are commonly used to describe animal health and related risk factors. However, model selection and evaluation present ongoing challenges—especially when many potential predictors, complex interactions, and ...
Timur Tug, Fiona Mers, Franziska Schäkel, Doris Höltig, Lothar Kreienbrock, Katja Ickstadt   +5 more
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Performance of criteria for selecting evolutionary models in phylogenetics: a comprehensive study based on simulated datasets

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, Qiao Huijie, Zhang Yanzhou, Shi Weifeng, Ho Simon YW, Xu Weijun, Zhang Aibing, Zhu Chaodong   +7 more
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Probabilistic inference: Task dependency and individual differences of probability weighting revealed by hierarchical Bayesian modelling

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, Caroline eSeer, Florian eLange, Bruno eKopp   +3 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, Saksham Chandra, Andrew Kayser, Ming Hsu, Joshua L. Warren   +4 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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Bayesian Hierarchical Model-Based Information Fusion for Degradation Analysis Considering Non-Competing Relationship

IEEE Access, 2019
Degradation analysis methods are increasingly used in reliability assessment of long-life products. The small sample size problem is worthy of attention in the degradation analysis.
Junyu Guo, Hualin Zheng, Binglin Li, Guo-Zhong Fu   +3 more
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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, Ryan, Gill, Sinjini, Sikdar, Susmita, Datta   +3 more
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HIERARCHICAL BAYESIAN MODELLING OF A FAMILY OF FRFS

Proceedings of the 14th International Workshop on Structural Health Monitoring, 2023
Population-based structural health monitoring (PBSHM) aims to share valuable information among members of a population, such as normal- and damage-condition data, to improve inferences regarding the health states of the members. Even when the population is comprised of nominally-identical structures, benign variations among the members will exist as a ...
Dardeno, T.A., Bull, L.A., Mills, R.S., Dervilis, N., Worden, K.   +4 more
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Evaluating the Benefits of Bayesian Hierarchical Methods for Analyzing Heterogeneous Environmental Datasets: A Case Study of Marine Organic Carbon Fluxes

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, Gregory L. Britten, Yara Mohajerani, Louis Primeau, Louis Primeau, Murat Aydin, Catherine Garcia, Wei-Lei Wang, Benoît Pasquier, Benoît Pasquier, B. B. Cael, B. B. Cael, B. B. Cael, François W. Primeau   +13 more
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