A general approach to the study of L1 asymptotic unbiasedness of kernel density estimators in Rd
| dc.contributor.author | Stinner, Mark | |
| dc.contributor.examiningcommittee | Koulis, Theodoro (Statistics) Prymak, Andriy (Mathematics) | en_US |
| dc.contributor.supervisor | Leblanc, Alexandre (Statistics) | en_US |
| dc.date.accessioned | 2013-08-26T17:00:24Z | |
| dc.date.available | 2013-08-26T17:00:24Z | |
| dc.date.issued | 2013-08-26 | |
| dc.degree.discipline | Statistics | en_US |
| dc.degree.level | Master of Science (M.Sc.) | en_US |
| dc.description.abstract | A technique for establishing L1 asymptotic unbiasedness of a kernel density estimator in Rd that does not depend on the form of the kernel function will be demonstrated. We will introduce the concept of a region sequence of a sequence of kernel functions and show how this can be used to give necessary and sufficient conditions for L1 asymptotic unbiasedness. These results are then applied to kernel density estimators whose form is given and a number of known and novel results are obtained. | en_US |
| dc.description.note | October 2013 | en_US |
| dc.identifier.uri | http://hdl.handle.net/1993/22110 | |
| dc.language.iso | eng | en_US |
| dc.rights | open access | en_US |
| dc.subject | asymptotic | en_US |
| dc.subject | unbiasedness | en_US |
| dc.subject | kernel | en_US |
| dc.subject | density | en_US |
| dc.subject | estimator | en_US |
| dc.title | A general approach to the study of L1 asymptotic unbiasedness of kernel density estimators in Rd | en_US |
| dc.type | master thesis | en_US |