Results 21 to 30 of about 1,563,284 (329)
A survival mediation model with Bayesian model averaging [PDF]
Statistical Methods in Medical Research, 2021 Determining the extent to which a patient is benefiting from cancer therapy is challenging. Criteria for quantifying the extent of “tumor response” observed within a few cycles of treatment have been established for various types of solids as well as hematologic malignancies. These measures comprise the primary endpoints of phase II trials. Regulatory
Jie Zhou +4 more
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Bayesian Model Averaging Using Power-Expected-Posterior Priors
Econometrics, 2020 This paper focuses on the Bayesian model average (BMA) using the power–expected– posterior prior in objective Bayesian variable selection under normal linear models.
Dimitris Fouskakis, Ioannis Ntzoufras
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Identifying Factors Affecting Iran's Social Welfare under Uncertainty: A Bayesian Average Approach [PDF]
اقتصاد باثبات, 2022 Improving the quality of life and the level of social welfare in society is one of the main goals of economic policy makers. Although macroeconomic environment has an important role in the level of social welfare, but the lack of knowledge of a model ...
mohammad alizadeh +4 more
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Environmental Research Letters, 2021 Spatially and temporally explicit information on the biomass in terrestrial ecosystems is essential to better understand the carbon cycle and achieve vegetation resource conservation.
N. Zeng +5 more
semanticscholar +1 more source
Journal of Advanced Transportation, 2021 Identifying the influential factors in incident duration is important for traffic management agency to mitigate the impact of traffic incidents on freeway operation.
Y. Zou +5 more
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Benchmark priors for Bayesian model averaging [PDF]
Journal of Econometrics, 2001 In contrast to a posterior analysis given a particular sampling model, posterior model probabilities in the context of model uncertainty are typically rather sensitive to the specification of the prior. In particular, 'diffuse' priors on model-specific parameters can lead to quite unexpected consequences.
Carmen Fernández +2 more
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Local Bayesian Dirichlet mixing of imperfect models
Scientific Reports, 2023 To improve the predictability of complex computational models in the experimentally-unknown domains, we propose a Bayesian statistical machine learning framework utilizing the Dirichlet distribution that combines results of several imperfect models. This
Vojtech Kejzlar +2 more
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Analyzing Parking Demand Characteristics Using a Bayesian Model Averaging
Applied Sciences, 2023 Parking duration analysis is an important aspect of evaluating parking demand. Identifying accurate distribution characteristics of parking duration can not only enhance parking efficiency and parking facility planning, but also provide essential support
Bo Liu +5 more
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Uncertainty in Heteroscedastic Bayesian Model Averaging
Insurance: Mathematics and Economics, 2023 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Sébastien Jessup +2 more
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ParMA: Parallelized Bayesian Model Averaging for Generalized Linear Models
Journal of Statistical Software, 2022 This paper describes the gretl function package ParMA, which provides Bayesian model averaging (BMA) in generalized linear models. In order to overcome the lack of analytical specification for many of the models covered, the package features an ...
Riccardo (Jack) Lucchetti, Luca Pedini
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