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Full-Text Articles in Physical Sciences and Mathematics
Bayesian Analytical Approaches For Metabolomics : A Novel Method For Molecular Structure-Informed Metabolite Interaction Modeling, A Novel Diagnostic Model For Differentiating Myocardial Infarction Type, And Approaches For Compound Identification Given Mass Spectrometry Data., Patrick J. Trainor
Electronic Theses and Dissertations
Metabolomics, the study of small molecules in biological systems, has enjoyed great success in enabling researchers to examine disease-associated metabolic dysregulation and has been utilized for the discovery biomarkers of disease and phenotypic states. In spite of recent technological advances in the analytical platforms utilized in metabolomics and the proliferation of tools for the analysis of metabolomics data, significant challenges in metabolomics data analyses remain. In this dissertation, we present three of these challenges and Bayesian methodological solutions for each. In the first part we develop a new methodology to serve a basis for making higher order inferences in metabolomics, …
Quasi-Random Action Selection In Markov Decision Processes, Samuel D. Walker
Quasi-Random Action Selection In Markov Decision Processes, Samuel D. Walker
Electronic Theses and Dissertations
In Markov decision processes an operator exploits known data regarding the environment it inhabits. The information exploited is learned from random exploration of the state-action space. This paper proposes to optimize exploration through the implementation of quasi-random sequences in both discrete and continuous state-action spaces. For the discrete case a permutation is applied to the indices of the action space to avoid repetitive behavior. In the continuous case sequences of low discrepancy, such as Halton sequences, are utilized to disperse the actions more uniformly.
A Multi-Indexed Logistic Model For Time Series, Xiang Liu
A Multi-Indexed Logistic Model For Time Series, Xiang Liu
Electronic Theses and Dissertations
In this thesis, we explore a multi-indexed logistic regression (MILR) model, with particular emphasis given to its application to time series. MILR includes simple logistic regression (SLR) as a special case, and the hope is that it will in some instances also produce significantly better results. To motivate the development of MILR, we consider its application to the analysis of both simulated sine wave data and stock data. We looked at well-studied SLR and its application in the analysis of time series data. Using a more sophisticated representation of sequential data, we then detail the implementation of MILR. We compare …
Revising Common Core Georgia Performance Standards Statistics Lesson Plans To Better Align With Statistical Practice, Rachel Bonilla
Revising Common Core Georgia Performance Standards Statistics Lesson Plans To Better Align With Statistical Practice, Rachel Bonilla
Electronic Theses and Dissertations
In this thesis, lesson plans provided by the Georgia Department of Education are revised to give students better exposure and practice working with real-life data. Three learning tasks and a performance task are presented covering a unit lesson on statistical regression. The development of Georgia statistics curriculum standards are reviewed and presented.