Comparison of data-based methods for non-parametric density estimation
| dc.contributor.advisor | Thompson, James R. | en_US |
| dc.contributor.committeeMember | Scott, David W. | en_US |
| dc.contributor.committeeMember | Gorry, G. Anthony | en_US |
| dc.creator | Factor, Lynette Ethel | en_US |
| dc.date.accessioned | 2018-12-18T21:29:30Z | en_US |
| dc.date.available | 2018-12-18T21:29:30Z | en_US |
| dc.date.issued | 1979 | en_US |
| dc.description.abstract | There 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. | en_US |
| dc.format.digitalOrigin | reformatted digital | en_US |
| dc.format.extent | 60 pp | en_US |
| dc.identifier.callno | Thesis Math. Sci. 1979 Factor | en_US |
| dc.identifier.citation | Factor, 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>. | en_US |
| dc.identifier.digital | RICE2363 | en_US |
| dc.identifier.uri | https://hdl.handle.net/1911/104727 | en_US |
| dc.language.iso | eng | en_US |
| dc.rights | Copyright 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. | en_US |
| dc.title | Comparison of data-based methods for non-parametric density estimation | en_US |
| dc.type | Thesis | en_US |
| dc.type.material | Text | en_US |
| thesis.degree.department | Mathematical Sciences | en_US |
| thesis.degree.discipline | Engineering | en_US |
| thesis.degree.grantor | Rice University | en_US |
| thesis.degree.level | Masters | en_US |
| thesis.degree.name | Master of Arts | en_US |
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