Bolthausen, E (1977). Convergence in distribution of minimum-distance estimators. Metrika, 24(4):215-227.
It is shown that (under some regularity conditions) minimum distance estimators for a (possibly multidimensional) real parameter of a family of univariate continuous distribution functions have an asymptotic distribution. If the distance is derived from the mean-square norm it is proved that the asymptotic distribution is normal. Weak convergence of empirical distribution to the Brownian bridge is the essential tool for the proof.
It is shown that (under some regularity conditions) minimum distance estimators for a (possibly multidimensional) real parameter of a family of univariate continuous distribution functions have an asymptotic distribution. If the distance is derived from the mean-square norm it is proved that the asymptotic distribution is normal. Weak convergence of empirical distribution to the Brownian bridge is the essential tool for the proof.
| Item Type: | Journal Article, refereed, original work |
|---|---|
| Communities & Collections: | 07 Faculty of Science > Institute of Mathematics |
| Dewey Decimal Classification: | 510 Mathematics |
| Uncontrolled Keywords: | Minimum-Distance Estimators, Convergence in Distribution, Skorohod Metric |
| Language: | English |
| Date: | 1977 |
| Deposited On: | 19 Oct 2009 14:21 |
| Last Modified: | 22 Feb 2018 09:56 |
| Publisher: | Springer |
| ISSN: | 0026-1335 |
| OA Status: | Closed |
| Free access at: | Related URL. An embargo period may apply. |
| Publisher DOI: | https://doi.org/10.1007/BF01893411 |
| Related URLs: | http://www.digizeitschriften.de/dms/img/?PPN=PPN358794056_0024&DMDID=dmdlog57 http://www.zentralblatt-math.org/zbmath/search/?q=an%3A0396.62022 |
Full text not available from this repository.
View at publisher
Get full-text in a library
Bolthausen, E