Comparison of data-based methods for non-parametric density estimation

dc.contributor.advisorThompson, James R.
dc.contributor.committeeMemberScott, David W.
dc.contributor.committeeMemberGorry, G. Anthony
dc.creatorFactor, Lynette Ethel
dc.date.accessioned2018-12-18T21:29:30Z
dc.date.available2018-12-18T21:29:30Z
dc.date.issued1979
dc.description.abstractThere have been recent developments in data-based methods for estimating densities non-parametrically. In this work we shall compare some methods developed by Scott, Duin and Wahba according to their sensitivity, statistical accuracy and cost of implementation when applied to one-dimensional data sets. We shall illustrate the limitations and tradeoffs of each method. The estimates obtained by each method will also be compared to the maximum likelihood univariate Gaussian estimate. We shall also illustrate the application of Duin's method to two-dimensional data sets and compare the results to the maximum likelihood bivariate Gaussian estimate.
dc.format.digitalOriginreformatted digital
dc.format.extent60 pp
dc.identifier.callnoThesis Math. Sci. 1979 Factor
dc.identifier.citationFactor, Lynette Ethel. "Comparison of data-based methods for non-parametric density estimation." (1979) Master’s Thesis, Rice University. <a href="https://hdl.handle.net/1911/104727">https://hdl.handle.net/1911/104727</a>.
dc.identifier.digitalRICE2363
dc.identifier.urihttps://hdl.handle.net/1911/104727
dc.language.isoeng
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.
dc.titleComparison of data-based methods for non-parametric density estimation
dc.typeThesis
dc.type.materialText
thesis.degree.departmentMathematical Sciences
thesis.degree.disciplineEngineering
thesis.degree.grantorRice University
thesis.degree.levelMasters
thesis.degree.nameMaster of Arts
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