Journal article
An Alternative Regularity Condition for Hajek's Representation Theorem
The Annals of statistics, Vol.15(1), pp.427-431
03/01/1987
DOI: 10.1214/aos/1176350277
Abstract
Hajek's representation theorem states that under certain regularity conditions the limiting distribution of an estimator can be written as the convolution of a certain normal distribution with some other distribution. This result, originally developed for finite dimensional problems, has been extended to a number of infinite dimensional settings where it has been used, for example, to establish the asymptotic efficiency of the Kaplan-Meier estimator. The purpose of this note is to show that the somewhat unintuitive regularity condition on the estimators that is usually used can be replaced by a simple one: It is sufficient for the asymptotic information and the limiting distribution of the estimator to vary continuously with the parameter being estimated.
Details
- Title: Subtitle
- An Alternative Regularity Condition for Hajek's Representation Theorem
- Creators
- Luke Tierney
- Resource Type
- Journal article
- Publication Details
- The Annals of statistics, Vol.15(1), pp.427-431
- DOI
- 10.1214/aos/1176350277
- ISSN
- 0090-5364
- eISSN
- 2168-8966
- Language
- English
- Date published
- 03/01/1987
- Academic Unit
- Statistics and Actuarial Science
- Record Identifier
- 9984257598002771
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