Bayesian Hierarchical
Bayesian hierarchical modelling of North Atlantic windiness
... the Bayesian hierarchical space-time models, it was not distinguished be- tween the wind-sea and the swell contributions and the mod- els were not able to distinguish the origin of the waves con- tributing ...
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A Bayesian hierarchical model for glacial dynamics based on the shallow ice approximation and its evaluation using analytical solutions
... Abstract. Bayesian hierarchical modeling can assist the study of glacial dynamics and ice flow ...a Bayesian hierarchical model constructed, which uses exact analytical solutions for the ...
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A composite Bayesian hierarchical model of compositional data with zeros
... We present an effective approach for modelling compositional data with large concentrations of zeros and several levels of variation, ap- plied to a database of elemental compositions of forensic glass of vari- ous use ...
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Spatial Bayesian hierarchical modelling of extreme sea states
... A Bayesian hierarchical framework is used to model extreme sea states, incorpo- rating a latent spatial process to more effectively capture the spatial variation of the ...The Bayesian spatial model ...
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Bayesian Hierarchical Scale Mixtures of Log-Normal Models for Inference in Reliability with Stochastic Constraint
... the Bayesian hierarchical SMLNFT model by utilizing the two-stage MaxEnt prior hierarchy involving µ and a scale mixture hierarch of the SMLNFT ...explores Bayesian inference in reliability for the ...
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A Bayesian Hierarchical Model For Longitudinal Data
... a Bayesian hierarchical model for the analysis of longitudinal data from a randomized controlled clinical tuberculosis ...the Bayesian approach, to estimate the model, we use the Gibbs sampler, which ...
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Spatial Modeling and Mapping of Tuberculosis Using Bayesian Hierarchical Approaches
... applied Bayesian hierarchical regression model to evaluate the urban spatial and spatio- temporal distribution of TB in Rilirão Preto, state of São Paulo, Southeast Brazil between 2006-2009 and to evaluate ...
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The application of Bayesian hierarchical models to heterogeneous DNA profiling data
... The hierarchical model used in this thesis is a clear simplification of the true situation, involving as it does discrete subpopulations between which individuals cannot mate, and within which mating is ...
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Bayesian hierarchical models for misaligned data: a simulation study
... a Bayesian kriging approach to address a point-to-area misalignment problem dealing with blending precipitation gauge data and satellite-derived pre- cipitation ...
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Bayesian Hierarchical Spatial-Temporal Models for Wind Prediction
... The hierarchical Bayesian approach is ideal for this application because it provides a mechanism for combining data from different resources with different spatial/temporal resolution, and it also provides ...
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A Bayesian hierarchical model for comparing average F1 scores
... through Bayesian reasoning, and demonstrate that it can provide much more comprehensive performance comparison between text classifiers than the traditional frequentist null hypothesis significance testing ...
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Comparison of Bayesian and frequentist approaches in modelling risk of preterm birth near the Sydney Tar Ponds, Nova Scotia, Canada
... the Bayesian or the frequentist approaches with spatial data assumed to be available at the individual case level or as spatially aggregated counts in enumeration districts (ED) ...the Bayesian and ...
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Time for a Change: a Tutorial for Comparing Multiple Classifiers Through Bayesian Analysis
... how Bayesian analysis can be employed instead of ...three Bayesian tests: Bayesian correlated t-test, Bayesian signed rank test and a Bayesian hierarchical model that can be used ...
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Bayesian Dynamic Linear Regression Analysis of Infant Growth by Weight
... the Bayesian hierarchical and dynamic linear regression ...The Bayesian hierarchical and dynamic linear regression model was used to explore weight gain of infants incorporating individual and ...
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Modeling hierarchical relationships in epidemiological studies: a Bayesian networks approach
... Hierarchical relationships between risk factors are seldom taken into account in epidemiological studies though some authors stressed the importance of doing so, and proposed a conceptual framework in which each ...
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Hierarchical Bayesian level set inversion
... use a Gaussian random walk proposal distribution for this parameter. We then apply the hierarchical MCMC method from subsection 3.3 initialized with the follow- ing six di↵erent choices of ⌧ = 1, 10, 30, 50, 70, ...
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Hierarchical Bayesian Domain Adaptation
... Multi-task learning is the problem of maxi- mizing the performance of a system across a number of related tasks. When applied to mul- tiple domains for the same task, it is similar to domain adaptation, but symmetric, ...
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Estimating breeding bird survey trends and annual indices for Canada: how do the new hierarchical Bayesian estimates differ from previous estimates?
... Figure A4.2. The proportion of species with BBS trend estimates that fall into the same “Status of Birds in Canada” (Environment Canada 2011) population status category (upper plot) or within 1 population status category ...
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A Comparison of Hierarchical Bayesian Models for Small Area Estimation of Counts
... statistics as private and public agencies try to extract the maximum information from sample survey data. Sample surveys are generally designed to provide esti- mates of characteristics of interest for large areas or ...
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Bayesian methods for hierarchical distance sampling models
... the Bayesian approach compared to the two-stage approach were specific to our case study or can be expected in general is beyond the scope of this ...Our Bayesian approach provides improvements over ...
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