Results 1 to 10 of about 50,616 (261)

Accommodating site variation in neuroimaging data using normative and hierarchical Bayesian models [PDF]

NeuroImage, 2022
The potential of normative modeling to make individualized predictions from neuroimaging data has enabled inferences that go beyond the case-control approach.
Johanna M.M. Bayer, Richard Dinga, Seyed Mostafa Kia, Akhil R. Kottaram, Thomas Wolfers, Jinglei Lv, Andrew Zalesky, Lianne Schmaal, Andre Marquand   +8 more
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Recalibrating single-study effect sizes using hierarchical Bayesian models [PDF]

Frontiers in Neuroimaging, 2023
IntroductionThere are growing concerns about commonly inflated effect sizes in small neuroimaging studies, yet no study has addressed recalibrating effect size estimates for small samples. To tackle this issue, we propose a hierarchical Bayesian model to
Zhipeng Cao, Zhipeng Cao, Matthew McCabe, Peter Callas, Renata B. Cupertino, Jonatan Ottino-González, Alistair Murphy, Devarshi Pancholi, Nathan Schwab, Orr Catherine, Kent Hutchison, Janna Cousijn, Alain Dagher, John J. Foxe, Anna E. Goudriaan, Robert Hester, Chiang-Shan R. Li, Wesley K. Thompson, Angelica M. Morales, Edythe D. London, Valentina Lorenzetti, Maartje Luijten, Rocio Martin-Santos, Reza Momenan, Martin P. Paulus, Martin P. Paulus, Lianne Schmaal, Lianne Schmaal, Rajita Sinha, Nadia Solowij, Dan J. Stein, Elliot A. Stein, Anne Uhlmann, Ruth J. van Holst, Dick J. Veltman, Reinout W. Wiers, Murat Yücel, Sheng Zhang, Patricia Conrod, Scott Mackey, Hugh Garavan, The ENIGMA Addiction Working Group   +41 more
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Hierarchical Graphical Bayesian Models in Psychology

Revista Colombiana de Estadística, 2014
The improvement of graphical methods in psychological research can promote their use and a better comprehension of their expressive power. The application of hierarchical Bayesian graphical models has recently become more frequent in psychological ...
GUILLERMO CAMPITELLI, GUILLERMO MACBETH
doaj   +6 more sources

A dynamic hierarchical Bayesian approach for forecasting vegetation condition [PDF]

Natural Hazards and Earth System Sciences, 2022
Agricultural drought, which occurs due to a significant reduction in the moisture required for vegetation growth, is the most complex amongst all drought categories.
E. E. Salakpi, P. D. Hurley, P. D. Hurley, J. M. Muthoka, A. Bowell, A. Bowell, S. Oliver, S. Oliver, P. Rowhani   +8 more
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Hierarchical change-point regression models including random effects to estimate empirical critical loads for nitrogen using Bayesian Regression Models (brms) and JAGS

MethodsX, 2022
The concept of critical loads is used in the framework of the Convention on Long-range Transboundary Air Pollution (UNECE) to define thresholds below which no damaging effects on habitats occur based on the latest scientific knowledge.
Tobias Roth, Simon Tresch, Enzai Du, Sabine Braun   +3 more
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Multilevel selection as Bayesian inference, major transitions in individuality as structure learning [PDF]

Royal Society Open Science, 2019
Complexity of life forms on the Earth has increased tremendously, primarily driven by subsequent evolutionary transitions in individuality, a mechanism in which units formerly being capable of independent replication combine to form higher-level ...
Dániel Czégel, István Zachar, Eörs Szathmáry   +2 more
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Accounting for Modeling Errors and Inherent Structural Variability through a Hierarchical Bayesian Model Updating Approach: An Overview

Sensors, 2020
Mechanics-based dynamic models are commonly used in the design and performance assessment of structural systems, and their accuracy can be improved by integrating models with measured data.
Mingming Song, Iman Behmanesh, Babak Moaveni, Costas Papadimitriou   +3 more
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Application of Multiple Imputation for Missing Values in Three-Way Three-Mode Multi-Environment Trial Data. [PDF]

PLoS ONE, 2015
It is a common occurrence in plant breeding programs to observe missing values in three-way three-mode multi-environment trial (MET) data. We proposed modifications of models for estimating missing observations for these data arrays, and developed a ...
Ting Tian, Geoffrey J McLachlan, Mark J Dieters, Kaye E Basford   +3 more
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Hierarchical Bayesian Models for Multiple Count Data

Austrian Journal of Statistics, 2016
The aim of this paper is to develop a model for analyzing multiple response models for count data and that may take into account complex correlation structures. The model is specified hierarchically in several layers and can be used for sparse data as it
Radu Tunaru
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Software for Bayesian Statistics

Journal of Statistical Software, 2021
In this summary we introduce the papers published in the special issue on Bayesian statistics. This special issue comprises 20 papers on Bayesian statistics and Bayesian inference on different topics such as general packages for hierarchical linear model
Michela Cameletti, Virgilio Gómez-Rubio
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