Sky Mining - Application to Photomorphic Redshift Estimation

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dc.contributor.advisorBorne, Kirk
dc.contributor.authorNayak, Pragyansmita
dc.creatorNayak, Pragyansmita
dc.date.accessioned2015-07-29T18:35:16Z
dc.date.available2015-07-29T18:35:16Z
dc.date.issued2015
dc.description.abstractThe field of astronomy has evolved from the ancient craft of observing the sky. In it's present form, astronomers explore the cosmos not just by observing through the tiny visible window used by our eyes, but also by exploiting the electromagnetic spectrum from radio waves to gamma rays. The domain is undoubtedly at the forefront of data-driven science. The data growth rate is expected to be around 50%-100% per year. This data explosion is attributed largely to the large-scale wide and deep surveys of the different regions of the sky at multiple wavelengths (both ground and space-based surveys).
dc.format.extent229 pages
dc.identifier.urihttps://hdl.handle.net/1920/9619
dc.language.isoen
dc.rightsCopyright 2015 Pragyansmita Nayak
dc.subjectComputer science
dc.subjectAstronomy
dc.subjectStatistics
dc.subjectAstroInformatics
dc.subjectBayesian Networks
dc.subjectData Mining
dc.subjectGeneralized Linear Model
dc.subjectPhotometric Redshift
dc.subjectSky Survey SDSS
dc.titleSky Mining - Application to Photomorphic Redshift Estimation
dc.typeDissertation
thesis.degree.disciplineComputational Science
thesis.degree.grantorGeorge Mason University
thesis.degree.levelDoctoral

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