Results 41 to 50 of about 1,563,284 (329)
Neutron Drip Line in the Ca Region from Bayesian Model Averaging. [PDF]
Physical Review Letters, 2019 The region of heavy calcium isotopes forms the frontier of experimental and theoretical nuclear structure research where the basic concepts of nuclear physics are put to stringent test.
L. Neufcourt +4 more
semanticscholar +1 more source
Model averaging, optimal inference and habit formation
Frontiers in Human Neuroscience, 2014 Postulating that the brain performs approximate Bayesian inference generates principled and empirically testable models of neuronal function – the subject of much current interest in neuroscience and related disciplines.
Thomas H B FitzGerald +2 more
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Recovering Crossed Random Effects in Mixed-Effects Models Using Model Averaging
Methodology, 2022 Random effects contain crucial information to understand the variability of the processes under study in mixed-effects models with crossed random effects (MEMs-CR).
José Ángel Martínez-Huertas +1 more
doaj +1 more source
Bayesian Model Averaging, Learning, and Model Selection* [PDF]
, 2013 Agents have two forecasting models, one consistent with the unique rational expectations equilibrium, another that assumes a time-varying parameter structure. When agents use Bayesian updating to choose between models in a self-referential system, we find that learning dynamics lead to selection of one of the two models.
Evans, George W. +3 more
openaire +3 more sources
BACE and BMA Variable Selection and Forecasting for UK Money Demand and Inflation with Gretl
Econometrics, 2020 In this paper, we apply Bayesian averaging of classical estimates (BACE) and Bayesian model averaging (BMA) as an automatic modeling procedures for two well-known macroeconometric models: UK demand for narrow money and long-term inflation.
Marcin Błażejowski +2 more
doaj +1 more source
Comparing families of dynamic causal models. [PDF]
PLoS Computational Biology, 2010 Mathematical models of scientific data can be formally compared using Bayesian model evidence. Previous applications in the biological sciences have mainly focussed on model selection in which one first selects the model with the highest evidence and ...
Will D Penny +6 more
doaj +1 more source
A Comparison of Model Averaging Techniques to Predict the Spatial Distribution of Soil Properties
Remote Sensing, 2022 This study tested and evaluated a suite of nine individual base learners and seven model averaging techniques for predicting the spatial distribution of soil properties in central Iran.
Ruhollah Taghizadeh-Mehrjardi +5 more
doaj +1 more source
Predictive Analytics by Using Bayesian Model Averaging for Large-Scale Internet of Things
International Journal of Distributed Sensor Networks, 2013 Massive events can be produced today because of the rapid development of the Internet of Things (IoT). Complex event processing, which can be used to extract high-level patterns from raw data, has become an essential part of the IoT middleware ...
Xinghui Zhu, Fang Kui, Yongheng Wang
doaj +1 more source
Drivers of structural convergence: Accounting for model uncertainty and reverse causality
Entrepreneurial Business and Economics Review, 2021 Objective: The objective of the article is the examination of factors that affect structural convergence and assessing their robustness.
Krzysztof Beck
doaj +1 more source
Clustered Bayesian Model Averaging
Bayesian Analysis, 2013 It is sometimes preferable to conduct statistical analyses based on the combination of several models rather than on the selection of a single model, thus taking into account the uncertainty about the true model. Models are usually combined using constant weights that do not distinguish between different regions of the covariate space.
Yu, Qingzhao +2 more
openaire +2 more sources