Model-based Bayesian Framework
A Bayesian framework based on a Gaussian mixture model and radial-basis-function Fisher discriminant analysis (BayGmmKda V1.1) for spatial prediction of floods
... out based on a statistical assumption that flooding in the future will occur under the same conditions that triggered them in the past (Tien Bui et ...achieved based on the probability of pixels belonging ...
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A Mixture Based Bayesian Model Averaging Method
... A classical reference is Hoeting et al. [19] with an extensive framework of BMA methodology and applica- tions for different statistical models. Various real data and simulation studies have investigated the ...
9
Semantically aware hierarchical Bayesian network model for knowledge discovery in data : an ontology based framework
... BN model, and in many real-life scenarios training data is scarce [94], [96], ...BN model [84], ...hierarchical Bayesian Network based on GO. However, before the SAHBN model is ...
194
Bayesian integration of flux tower data into a process based simulator for quantifying uncertainty in simulated output
... (NRH) model (Gilmanov et al., 2003). The estimation of the NRH model parameters was performed in a Bayesian framework that yielded posterior distributions of the NRH parameters and posterior ...
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Super-Resolution Using Hidden Markov Model and Bayesian Detection Estimation Framework
... mixture model (FMM) and a Potts Markov model (PMM) for the ...priori model is then a hierarchical Markov ...a Bayesian detection and estimation framework, and appropriate algorithms are ...
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A Bayesian model for event based trust
... the model of choice for computing ‘trust val- ues’ of distributed interactions in the SECURE project [3,4], we did not use in that context a formal probabilistic model of principal ...structure ...
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Products Reliability Prediction Model Based on Bayesian Approach
... prediction based on Bayesian approach ...a Bayesian method for reliability prediction with Weibull distribution for a product’s life ...Their model contains complex integrals and there is no ...
5
A Goal-Directed Bayesian Framework for Categorization
... the Bayesian brain hypothesis, the basic tools needed to perform inference (namely, the ability to generate, implement, select and use generative models) must be supported by the brain’s anatomy and ...to ...
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A wavelet based Bayesian framework for 3D object segmentation in microscopy
... a Bayesian model for segmenting 3D synaptic objects from a given stack of specimen image slices captured using a fluorescent confocal ...likelihood based on the vertical inter-slice intensity profile ...
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Model averaging and its use in economics
... Another model-averaging procedure that has been proposed in Magnus et ...a Bayesian justification. However, it assumes no prior on the model space and thus can not produce inference on posterior ...
107
Bayesian network-based framework for exposure-response study design and interpretation
... We know that prior scientific knowledge about expos- ure and response mechanisms can lead to better design and interpretation of study results. Furthermore, better understanding of the sources of measurement error, op- ...
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Bayesian and Non Bayesian Estimation of the Inverse Weibull Model Based on Generalized Order Statistics
... paper based on n selected GOS from the inverse Weibull model, we consider the problem of Bayesian and non-Bayesian estimation for parameters and reliability func- tion of the ...in ...
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Mathematical modelling approaches for spreading processes : zoonotic influenza and social contagion
... our model framework including both a fitted distance-dependent transmission kernel and a spark term to seed infections from other sources indepen- dent of ...
227
Estimation of the Piecewise Exponential Model by Bayesian P Splines via Gibbs Sampling: Robustness and Reliability of Posterior Estimates
... On the other hand, the major critics to the PE model are (e.g.: [28]): 1) a piecewise constant hazard function is generally not “realistic”; 2) estimates of the hazards are sensitive to the partition of the ...
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Optimal inverse estimation of ecosystem parameters from observations of carbon and energy fluxes
... to model and estimate photosynthesis, respiration, energy balance, stomatal behavior, radiation transfer and tur- bulent gas exchange across the plant canopy on the basis of data from flux tower experiments (van ...
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Definition and Validation of a Business IT Alignment Method for Enterprise Governance Improvement in the Context of Processes Based Organizations
... responsibility model that has been elaborated following the review and based on a global comprehension of the ...This model has already been largely commented in (Feltus et ...responsibility ...
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Bayesian Subtree Alignment Model based on Dependency Trees
... a Bayesian subtree alignment model that in- corporates dependency relations be- tween subtrees in dependency tree struc- tures on both ...tion model is a kind of tree-based re- or- dering ...
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A Bayesian Model for Generative Transition based Dependency Parsing
... the model that don’t include lexical elements in the condition- ing ...This model performs only 1% UAS lower than the best lexicalised model, although it makes much stronger independence ...
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DSGE Model Evaluation in a Bayesian Framework: an Assessment
... the model is true, how false is it?", instead the calibration tries to reply to the question: "Given that the model is false, how true is it? ...testing model process, an econometrician takes ...
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A general model based slicing framework
... when model M is a slice of model M 0 with respect to the slicing criterion S expressed as a snapshot and where S is an instance of M ...requires model invariants to be strengthened; A-1 that requires ...
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