Beckert, Walter and McFadden, D. (2004) Maximal uniform convergence rates in parametric estimation problems. Working Paper. Birkbeck, University of London, London, UK.
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Abstract
This paper considers parametric estimation problems with i.i.d. data. It focuses on rate-efficiency, in the sense of maximal possible convergence rates of stochastically bounded estimators, as an optimality criterion, largely unexplored in parametric estimation. Under mild conditions, the Hellinger metric, defined on the space of parametric probability measures, is shown to be an essentially universally applicable tool to determine maximal possible convergence rates.
Metadata
| Item Type: | Monograph (Working Paper) |
|---|---|
| Additional Information: | BWPEF 0405 |
| Keyword(s) / Subject(s): | parametric estimators, uniform convergence, Hellinger distance, Locally Asymptotically Quadratic (LAQ) Families |
| School: | Birkbeck Faculties and Schools > Faculty of Business and Law > Birkbeck Business School |
| Depositing User: | Administrator |
| Date Deposited: | 09 Apr 2019 12:00 |
| Last Modified: | 02 Aug 2023 17:50 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/27107 |
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