Arbeitspapier
Maximal uniform convergence rates in parametric estimation problems
This paper considers parametric estimation problems with independent, identically,non-regularly distributed data. It focuses on rate-effciency, 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. These rates are shown to be attainable in general classes of parametric estimation problems.
- Sprache
-
Englisch
- Erschienen in
-
Series: cemmap working paper ; No. CWP28/07
- Klassifikation
-
Wirtschaft
Estimation: General
- Thema
-
parametric estimators , uniform convergence , Hellinger distance , Locally Asymptotically Quadratic (LAQ) Families
Schätztheorie
Statistischer Test
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Beckert, Walter
McFadden, Daniel L.
- Ereignis
-
Veröffentlichung
- (wer)
-
Centre for Microdata Methods and Practice (cemmap)
- (wo)
-
London
- (wann)
-
2007
- DOI
-
doi:10.1920/wp.cem.2007.2807
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:44 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Beckert, Walter
- McFadden, Daniel L.
- Centre for Microdata Methods and Practice (cemmap)
Entstanden
- 2007
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