Brain Activity Mapping from MEG Data via a Hierarchical Bayesian Algorithm with Automatic Depth Weighting
Sign Up to like & getrecommendations! Published in 2018 at "Brain Topography"
DOI: 10.1007/s10548-018-0670-7
Abstract: A recently proposed iterated alternating sequential (IAS) MEG inverse solver algorithm, based on the coupling of a hierarchical Bayesian model with computationally efficient Krylov subspace linear solver, has been shown to perform well for both… read more here.
Keywords: algorithm; hierarchical bayesian; meg inverse; brain ... See more keywords
A hierarchical Bayesian spatiotemporal random parameters approach for alcohol/drug impaired-driving crash frequency analysis
Sign Up to like & getrecommendations! Published in 2019 at "Analytic Methods in Accident Research"
DOI: 10.1016/j.amar.2019.01.002
Abstract: Abstract Unobserved heterogeneity, which has been recognized as a critical issue in crash frequency modelling, generates from multiple sources, including observable and unobservable factors, space and time instability, crash severities, etc. However, only a very… read more here.
Keywords: random parameters; hierarchical bayesian; crash; crash frequency ... See more keywords
Modeling pedestrian-injury severities in pedestrian-vehicle crashes considering spatiotemporal patterns: Insights from different hierarchical Bayesian random-effects models
Sign Up to like & getrecommendations! Published in 2020 at "Analytic Methods in Accident Research"
DOI: 10.1016/j.amar.2020.100137
Abstract: Abstract To systematically account for the spatiotemporal features and unobserved heterogeneity within pedestrian-vehicle crashes, this paper employs the spatiotemporal analysis and hierarchical Bayesian random-effects models to explore the factors contributing to pedestrian-injury severities of pedestrian-vehicle… read more here.
Keywords: bayesian random; vehicle; random effects; hierarchical bayesian ... See more keywords
Bayesian analysis of meta-analytic models incorporating dependency: new approaches for the hierarchical Bayesian delta-splitting model
Sign Up to like & getrecommendations! Published in 2020 at "Heliyon"
DOI: 10.1016/j.heliyon.2020.e04835
Abstract: Dependence between studies in meta-analysis is an assumption which is imposed on the structure of hierarchical Bayesian meta-analytic models. Dependence in meta-analysis can occur as a result of study reports using the same data or… read more here.
Keywords: meta analytic; analysis; model; hierarchical bayesian ... See more keywords
Survival analysis of fatigue data: Application of generalized linear models and hierarchical Bayesian model
Sign Up to like & getrecommendations! Published in 2018 at "International Journal of Fatigue"
DOI: 10.1016/j.ijfatigue.2018.07.027
Abstract: Abstract The survival analysis is introduced to describe the fatigue failure process in this paper for obtaining a set of flexible and accurate probabilistic stress-life (P-S-N) curves in fatigue reliability analysis. The generalized linear models… read more here.
Keywords: bayesian model; analysis; generalized linear; hierarchical bayesian ... See more keywords
Hierarchical Bayesian narrative-making under variable uncertainty
Sign Up to like & getrecommendations! Published in 2023 at "Behavioral and Brain Sciences"
DOI: 10.1017/s0140525x22002643
Abstract: Abstract While Conviction Narrative Theory correctly criticizes utility-based accounts of decision-making, it unfairly reduces probabilistic models to point estimates and treats affect and narrative as mechanistically opaque yet explanatorily sufficient modules. Hierarchically nested Bayesian accounts… read more here.
Keywords: hierarchical bayesian; making variable; uncertainty; bayesian narrative ... See more keywords
A hierarchical Bayesian mixture model for inferring the expression state of genes in transcriptomes
Sign Up to like & getrecommendations! Published in 2020 at "Proceedings of the National Academy of Sciences of the United States of America"
DOI: 10.1073/pnas.1919748117
Abstract: Significance How do the cells of an organism—each with an identical genome—give rise to tissues of incredible phenotypic diversity? Key to answering this question is the transcriptome: the set of genes expressed in a given… read more here.
Keywords: state genes; expression state; inferring expression; hierarchical bayesian ... See more keywords
The E-Bayesian and hierarchical Bayesian estimations for the proportional reversed hazard rate model based on record values
Sign Up to like & getrecommendations! Published in 2017 at "Journal of Statistical Computation and Simulation"
DOI: 10.1080/00949655.2017.1326118
Abstract: ABSTRACT In this paper, E-Bayesian and hierarchical Bayesian estimations of the shape parameter, when the underlying distribution belongs to the proportional reversed hazard rate model, are considered. Maximum likelihood, Bayesian and E-Bayesian estimates of the… read more here.
Keywords: hierarchical bayesian; bayesian hierarchical; proportional reversed; hazard rate ... See more keywords
E-Bayesian and Hierarchical Bayesian Estimation of Traffic Intensity in the M/M/1 Queueing System
Sign Up to like & getrecommendations! Published in 2024 at "American Journal of Mathematical and Management Sciences"
DOI: 10.1080/01966324.2024.2440759
Abstract: SYNOPTIC ABSTRACT In this paper, the Bayesian and hierarchical Bayesian estimation of traffic intensity in an M/M/1 queueing system under the mean squared error criterion is considered. E-Bayesian estimators of traffic intensity are computed under… read more here.
Keywords: hierarchical bayesian; bayesian estimation; traffic intensity; bayesian hierarchical ... See more keywords
Hierarchical Bayesian models for predicting spatially correlated curves
Sign Up to like & getrecommendations! Published in 2018 at "Statistics"
DOI: 10.1080/02331888.2018.1547905
Abstract: ABSTRACT Functional data analysis has emerged as a new area of statistical research with a wide range of applications. In this paper, we propose novel models based on wavelets for spatially correlated functional data. These… read more here.
Keywords: bayesian models; correlated curves; spatially correlated; predicting spatially ... See more keywords
Statistical Modeling of Within-Laboratory Precision Using a Hierarchical Bayesian Approach.
Sign Up to like & getrecommendations! Published in 2024 at "Journal of AOAC International"
DOI: 10.1093/jaoacint/qsae069
Abstract: BACKGROUND Reproducibility has been well-studied in the field of food analysis; the relative standard deviation is said to follow the Horwitz curve with certain exceptions. However, little systematic research has been done on predicting repeatability… read more here.
Keywords: laboratory precision; using hierarchical; hierarchical bayesian; precision ... See more keywords