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dc.contributor.advisorNezamoddini-Kachouie, Nezamoddin
dc.contributor.authorOnyejekwe, Osita Eluemuno
dc.date.accessioned2018-02-14T17:15:57Z
dc.date.available2018-02-14T17:15:57Z
dc.date.created2017-12
dc.date.issued2017-12
dc.date.submittedDecember 2017
dc.identifier.urihttp://hdl.handle.net/11141/2329
dc.descriptionThesis (Ph.D.) - Florida Institute of Technology, 2017en_US
dc.description.abstractIn this dissertation we have studied the climate factors that contribute to climate change using univariate and multivariate parametric methods as well as nonparametric models. In this study, we have three major contributions. First, the extent of mountain glaciers around the globe and their responses to climate factors are investigated using multivariate methods and we have proposed a predictive model to estimate the mountain glacier response to climate factors. Second, we have addressed the important problem of bandwidth selection in presence of correlated noise in nonparametric regression analysis. We have proposed a denoising method based on an ensemble bandwidth optimization where an adaptive bandwidth chooses the optimal bandwidth for each data point by maximizing the signal to noise ratio. The proposed denoising method is evaluated by running several hundreds of Monte Carlo simulations for various signals corrupted with different types of noise including white Gaussian noise and correlated noise. Third, since most of the observed climate factors are corrupted with the correlated noise, we applied the proposed denoising method to the observed climate factors, and located the representative features including peaks and change points and investigated the correlation of these factors as well as environmental events.en_US
dc.format.mimetypeapplication/pdf
dc.language.isoen_USen_US
dc.rightsCopyright held by author.en_US
dc.titleParametric and Non-Parametric Regression Models with Applications to Climate Changeen_US
dc.typeDissertationen_US
dc.date.updated2018-01-08T21:18:52Z
thesis.degree.nameDoctorate of Philosophy in Operations Researchen_US
thesis.degree.levelDoctoralen_US
thesis.degree.disciplineOperations Researchen_US
thesis.degree.departmentMathematical Sciencesen_US
thesis.degree.grantorFlorida Institute of Technologyen_US
dc.type.materialtext


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