# Indiana University

 dc.contributor.advisor Bradley, Richard C. en dc.contributor.author Shaw, Jason en dc.date.accessioned 2010-05-24T15:11:20Z en dc.date.available 2027-01-24T16:11:20Z en dc.date.available 2010-05-31T19:15:05Z dc.date.issued 2010-05-24T15:11:20Z en dc.date.submitted 2005 en dc.identifier.uri http://hdl.handle.net/2022/7180 en dc.description Thesis (PhD) - Indiana University, Mathematics, 2005 en dc.description.abstract This text first looks at sequences of discrete-indexed random fields. When these random fields satisfy certain linear dependence conditions uniformly, each will have a spectral density function (not necessarily continuous) that is bounded between two positive constants. These spectral density functions will en converge in a weak sense to another function (not necessarily continuous) that is also bounded between two positive constants. Two examples will also be given that show the weak form of convergence seems to be the best one can get. An extra condition on the sequence will also be given which will ensure each spectral density function is continuous and that they uniformly converge to a continuous function. Continuous-indexed random fields will then be investigated, and linear dependence coefficients specifically for such random fields will be defined. When a selection of these linear dependence conditions are satisfied, the random field will have a continuous spectral density function. Showing this involves the construction of a special class of random fields using a standard Poisson process and the original random field. dc.language.iso EN en dc.publisher [Bloomington, Ind.] : Indiana University en dc.subject Probability Theory en dc.subject spectral densities en dc.subject random field en dc.subject weak dependence en dc.subject.classification Mathematics en dc.title Spectral densities of discrete and continuous-indexed random fields en dc.type Doctoral Dissertation en
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