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 8 of 8 for “"g-prior"”.
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Data combining using mixtures of g-priors with application on county-level female breast cancer prevalence
… linear models with the classical mixtures of g-priors is investigated. We calculate and compare the posterior estimates and the frequentist properties of the Bayesian estimator from the model with individual and combined data. To resolve the newly identified conditional Lindley paradox and relax …
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Bayesian variable selection for linear mixed models when p is much larger than n with applications in genome wide association studies
… To deal with model selection, we propose novel priors that are extensions for LMMs of nonlocal priors, Zellner-g prior, unit Information prior, and Zellner-Siow prior. For each method, extensive simulation studies and case studies show that these methods improve the recall of true causal SNPs …
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Continuous-Time Models of Arrival Times and Optimization Methods for Variable Selection
… are developed for the point-mass-Laplace and g-prior. Combined with warm-starts and optimality-based bounds tightening procedures provided by the heuristics of the previous chapter, the MIQP model developed for the point-mass-Laplace prior converges to global optimality in a matter of seconds …
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Variable selection for generalized linear mixed models and non-Gaussian Genome-wide associated study data
… We also compare our methods with different priors for variables, including nonlocal prior, unit information prior, Zellner-g prior, and Zellner-Siow prior. Our methods are applied to substance use disorder (alcohol comsumption and cocaine dependence), human health (breast cancer), and plant …
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Bayesian Analysis of Linear Inverse Problems with Applications in Economics and Finance
… The second approach consists in specifying a prior distribution on the parameter of interest of the g-prior type. Then, I detect a class of models for which the prior distribution is able to correct for the ill-posedness also in infinite dimensional problems. I study asymptotic properties of …
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Molecular modeling of sigma 1 and sigma 2 receptor ligands: pharmacophore development and comparison using discotech and bioactivity prediction comparison of ab initio and density functional comfa studies for spiro and other receptor ligands
… methods H F/6-31 G* and B3LY P/6-31 G* prior to model development. These calculations determine the geometry optimization and electrostatic charges for each molecule. CoM FA studies, utilizing SY BY L-X 2. 1, are performed for 41 sigma 1 receptor l igands using the radiol igand [ H ^3] …
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Statistical models with diverging dimensionality
Nowadays in many statistical applications, we face models whose complexity increases with the sample size. Such models pose a challenge to the traditional statistical analysis, and call for new methodologies and new asymptotic studies, which are exactly the focus of my thesis. In particular, my …
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Empirical statistical modelling for crop yields predictions: bayesian and uncertainty approaches
… Carlo (MCMC), Bayesian estimation (with uniform prior) and maximum likelihood estimation (MLE) method. The results obtained from the three procedures yielded similar mean estimates, but the credible intervals were found to be narrower in Bayesian estimates than confidence intervals in MLE method. …