Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 262 for “"Bayesian Approach"”.
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A Bayesian Approach to Impression Formation
Made available in DSpace on 2014-12-10T21:07:44Z (GMT). No. of bitstreams: 1 7411987.pdf: 8261896 bytes, checksum: c76b66755e07cb914b722bfdf004aefc (MD5) Previous issue date: 1973
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A Bayesian approach to feed reconstruction
In this thesis, we developed a Bayesian approach to estimate the detailed composition of an unknown feedstock in a chemical plant by combining information from a few bulk measurements of the feedstock in the plant along with some detailed composition information of a similar feedstock that was …
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A bayesian approach to wireless location problems
Several approaches for indoor location estimation in wireless networks are proposed. We explore non-hierarchical and hierarchical Bayesian graphical models that use prior knowledge about physics of signal propagation, as well as different modifications of Bayesian bivariate spline models. The …
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Learnability, representation, and language : a Bayesian approach
… in language acquisition. By formalizing them in Bayesian terms and evaluating them given realistic, real-world datasets, we achieve insight about what must be assumed about a child's representational capacity, learning mechanism, and cognitive biases. Exploring learnability in the context of an …
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Bayesian Approach Dealing with Mixture Model Problems
… Global Maximum Regions, and the second topic is Bayesian Model Selection for Nonlinear Mixed Effects Model. In the first topic, we consider a finite mixture model, which is used to fit the data from heterogeneous populations for many applications. An Expectation Maximization (EM) algorithm and …
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Design of Advanced Positioning Solutions: A Bayesian Approach
L'abstract è presente nell'allegato / the abstract is in the attachment
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An Applied Bayesian Approach to Network Meta-Analysis
… journals revealed a lack of presentations of Bayesian models within a network meta-analysis framework and thus motivated further research into this combined area of study. The development of four hierarchical Bayesian models applicable to the field of network meta-analysis are presented. Two …
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Multiple testing in spatial epidemiology: a Bayesian approach
In this work we aim to propose a new approach for preliminary epidemiological studies on Standardized Mortality Ratios (SMR) collected in many spatial regions. A preliminary study on SMRs aims to formulate hypotheses to be investigated via individual epidemiological studies that avoid bias carried …
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A pragmatic Bayesian approach to wind field retrieval
… space. This thesis applies a pragmatic Bayesian solution to the problem. The likelihood is a combination of conditional probability distributions for the local wind vectors given the scatterometer data. The prior distribution is a vector Gaussian process that provides the geophysical …
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Nowcasting GDP using dynamic factor model: A Bayesian approach
… known. In this dissertation, we first develop a Bayesian approach to provide a way to deal with unbalanced feature of the data set and to estimate latent common factors when the number of factors is assumed to be fixed and known. Then we extend our method such that it can identify the unknown …
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An Adaptive Bayesian Approach to Bernoulli-Response Clinical Trials
… outcome of Bernoulli-response clinical trials. A Bayesian adaptive design is used to fit the logistic equation to the dose-response curve of Phase II and Phase III clinical trials. Because of inherent restrictions in the logistic model, symmetric candidate densities cannot be used, thereby …
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Probabilistic search: a Bayesian approach in a continuous workspace
… sensor. To model this problem, the widely used Bayesian filtering approach is employed to obtain the general filtering equations for the posterior distribution representing the object's location over the workspace. Given a likelihood and prior belief belonging to the exponential family class, …
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Applications of the Bayesian approach for experimentation and estimation
A Bayesian framework for systematic data collection and parameter estimation is proposed to aid experimentalists in effectively generating and interpreting data. The four stages of the Bayesian framework are: system description, system analysis, experimentation, and estimation. System description …
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A Bayesian approach to computing Brauer groups of cubic surfaces
… and relies on Chebotarev’s density theorem and Bayesian inference to produce, with confidence level > r, a subgroup of the Weyl group of E_6. This subgroup represents the action of Galois on the geometric Picard group of X, from which we compute the Brauer group of X. We give a description of …
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FireFly: A Bayesian Approach to Source Finding in Astronomical Data
… including any prior knowledge we may have. Bayesian statistics is the obvious approach as it allows precise statistical interrogations of the data and the inclusion of all available information. In this thesis, we implement nested sampling and Monte Carlo Markov Chain (MCMC) techniques to …
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A fully Bayesian approach to uncertainty quantification of groundwater models
… regression-based (LSR) calibration. We present a Bayesian framework that explicitly recognizes errors in input forcings and model structure and is tailored for groundwater models. The framework implements a marginalizing step to account for input data variability when evaluating the likelihood, …
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A Bayesian Approach to Beamforming for Uncertain Direction -of -Arrival
In this thesis, we present a Bayesian approach to the problem of beamforming without accurate knowledge about the direction-of-arrival. Under the Bayesian formulation, the proposed beamformer is constructed as a mixture of directional beamformers combined according to the data-driven posterior …
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SENSITIVITY ANALYSIS OF STRUCTURAL PARAMETERS TO MEASUREMENT NONINVARIANCE: A BAYESIAN APPROACH
… framework. Particularly, this study takes a Bayesian approach to investigate the sensitivity of the posterior distribution of structural parameter difference to varying types and magnitudes of noninvariance across two populations. A Monte Carlo simulation was performed to empirically …
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