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 129 for “"Bayesian Analysis"”.
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Bayesian analysis for categorical survey data
In this thesis, we develop Bayesian methodology for univariate and multivariate categorical survey data. The Multinomial model is used and the following problems are addressed. Limited information about the design variables leads us to model the unknown design variables taking into account the …
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Bayesian Analysis of Discrete Longitudinal Data
This thesis explores a Bayesian hierarchical model to compare treatment effectiveness for menopausal symptom relief. Specifically, this model recognizes the discrete nature of the data, as well as its time dependency. Bayesian analysis is used to make inference on each individual profile, as well …
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Bayesian Analysis of Latent Threshold Dynamic Models
… latent threshold modeling and also discusses Bayesian analysis and computation for model fitting. Chapter 3 describes latent threshold multivariate models for a wide range of applications in the real data analysis that follows. Chapter 4 provides US and Japanese macroeconomic data analysis …
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Efficient Bayesian analysis of spatial occupancy models
… about species distribution and occurrence. Bayesian methodology is a popular framework used to model the relationship between species and environmental variables. In this dissertation we develop a Gibbs sampling method using a logit link function in order to model posterior parameters of the …
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A Bayesian analysis of ill-posed problems
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1994.
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Hierarchical Bayesian Analysis of Peruvian Tree Growth Rates
This thesis explores the use of Bayesian statistical methods and hierarchical modeling in order to analyze massive data sets of Peruvian tree growth data. The study is important in finding connections between different parameters (such as the tree's classification or elevation) and rate at which …
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Bayesian Analysis, Endogenous Data,and Convergence of Beliefs
Problems in statistical analysis, economics, and many other disciplines often involve a trade-off between rewards and additional information that could yield higher future rewards. This thesis investigates such a trade-off, using a class of problems known as bandit problems. In these problems, a …
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Noninformative Prior Bayesian Analysis for Statistical Calibration Problems
… value of the response variable. We consider Bayesian methods of analysis for the linear statistical calibration problem, based on noninformative priors. Posterior analyses are assessed and compared with classical inference procedures. It is shown that noninformative prior Bayesian analysis is …
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Bayesian analysis of multivariate stochastic volatility and dynamic models
… may be deterministic or stochastic. We propose Bayesian stochastic search as a feasible variable selection technique for the regression and volatility equations. We develop Markov Chain Monte Carlo (MCMC) algorithms that generate a posteriori restrictions on the elements of both the regression …
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Graphical and Bayesian Analysis of Unbalanced Patient Management Data
… a highly unbalanced dataset and to carry out Bayesian analyses to determine which of five devices best manages patients. An initial Bayesian analysis compared a machine-identical beta-binomial model to a machine-specific beta-binomial model. The response variable was number of in-range visits. …
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An Optimized Bayesian Analysis Framework for the KATRIN Experiment
… of the KATRIN beta spectrum and a comprehensive analysis of the first five measurement campaigns. An improved framework for computing the theoretical beta spectrum and the KATRIN response function is developed to address the complexities arising from the asymmetric field configurations in the …
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Bayesian analysis of finite mixture distributions using the allocation sampler
… intensive tasks required in their analysis. In order to fit a finite mixture distribution taking a Bayesian approach a posterior distribution has to be evaluated. When the number of components in the model is assumed known this posterior distribution can be sampled from using …
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Bayesian Analysis of Temporal and Spatio-temporal Multivariate Environmental Data
… novel additions to the existing literature on Bayesian multiscale models. In addition, we have proposed parallelizable MCMC algorithms to sample from the posterior distributions of the model parameters with enhanced computations.
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Bayesian analysis of electron cyclotron emission measurements at Wendelstein 7-X
… of the uncertainties, a completely new, general Bayesian forward model of a calibration unit with rotating mirror was developed and tested within the Bayesian modeling framework Minerva. The calibrated data then allow to obtain a radiation temperature spectrum. The actual desiderata, i.e. the …
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Inverse uncertainty quantification of trace physical model parameters using Bayesian analysis
… based on Maximum Likelihood Estimation (MLE), Bayesian Maximum A Priori (MAP), and Markov Chain Monte Carlo (MCMC) algorithm for physical models using relevant experimental data. The objective of the present work is to perform the sensitivity analysis of the code input (physical model) …
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Bayesian analysis of spatial and survival models with applications of computation techniques
… discusses the methodologies of applying Bayesian hierarchical models to different data with geographical characteristics or with right-censored failure time. A conditional autoregressive (CAR) prior is used for the model to capture spatial effects. Markov chain Monte Carlo (MCMC) methods …
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