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 12 of 12 for “"Bayesian hierarchical modeling"”.
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Bayesian Hierarchical Modeling for Longitudinal Frequency Data
… to compare treatment effectiveness. We propose a Bayesian hierarchical model to describe not only frequency measurements, but also the parameters that govern an individual profile.
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Advances in Bayesian Hierarchical Modeling with Tree-based Methods
… outputs is a major goal of modern statistical modeling. A family of models that are especially suitable for this task is the P\'olya tree type models. Following a divide-and-conquer strategy, these tree-based methods transform the original task into a series of tasks that are smaller in size …
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Using Box-Scores to Determine a Position's Contribution to Winning Basketball Games
… the team's overall ability. Through the use of Bayesian hierarchical modeling and NBA box-score performance categories, this project will determine how each position needs to perform in order for their team to be successful.
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Computability, inference and modeling in probabilistic programming
… and noise, both of which are common in Bayesian hierarchical modeling. This theoretical work bears on the development of probabilistic programming languages (which enable the specification of complex probabilistic models) and their implementations (which can be used to perform Bayesian …
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CyberGIS-enabled spatial decision support for supply chain optimization with uncertainty quantification
… quantification and supply chain optimization modeling into a CyberGIS Gateway application that represents a cutting-edge online cyberGIS environment for users to perform interactive spatial decision-making enabled by advanced cyberinfrastructure. Furthermore, an innovative method combining …
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Extending Space-Time Putative Hazard Models to Detect Latent Risk Features
<p>In recent years small area risk assessment modeling and data analysis around putative hazard sources has become a fundamental part of public health and environmental sciences. This dissertation work examines a novel development of three different space-time Bayesian hierarchical modeling …
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Integrating Functional Genomics with Systems Biology to Discover Drivers and Therapeutic Targets of Human Malignancies
… technology (shSeq), particularly a novel Bayesian hierarchical modeling approach to integrate multiple shRNAs targeting the same gene, which outperforms existing methods. In parallel, I developed a systems biology algorithm, NetBID2, to infer disease drivers from high-throughput genomic …
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From Small to Large: Modeling at the Scale of Ecological Processes to Understand Temperate Forest Range Limits, Biomass, and Traits
… In this dissertation, I employ novel statistical modeling on continent-spanning observational datasets, national forest inventories from temperate regions, with the aim to understand how forest communities may respond to future climate. In each chapter, the methodological focus on scale is …
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Bayesian Hierarchical Models for Data Extrapolation and Analysis in Rare and Pediatric Disease Clinical Trials
… draw conclusions for the pediatric population. Bayesian hierarchical modeling facilitates the combining (or ``borrowing") of information across disparate sources, such as adult and pediatric data. In this thesis we begin by developing, illustrating, and providing suggestions for Bayesian …
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Phylogenetic Niche Modeling
… often biased by environmental condition change. Modeling niche in a phylogenetic framework leverages a clade's shared evolutionary history to pull species estimates closer towards phylogenetic conserved values and farther away from species specific biases. We propose a new Bayesian model of …
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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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Load reduction and invasive mussel effects on eutrophication dynamics in Saginaw Bay, Lake Huron
… on phosphorus flux and cycling in Saginaw Bay. Bayesian approaches were used to quantify the impacts of load reduction and mussel invasion, while at the same time addressing model parameter uncertainty and prediction uncertainty associated with long-term observational data. Annual total …