A regression approach for estimating the center of symmetry

Fushing Hsieh

Statistics & Probability Letters, 1995, vol. 22, issue 2, 157-160

Abstract: The center of symmetry of a distribution function is estimated by a convenient generalized least squares (GLS) estimator, which is constructed from a regression setup based on the strong approximation of the empirical quantile process. This GLS estimator is shown to be semiparametric efficient in the sense of achieving the Fisher information bound. As a by-product, a [chi]2 test for the symmetry assumption is also derived.

Keywords: Chi-square; test; Generalized; least; squares; estimator; Empirical; quantile; process (search for similar items in EconPapers)
Date: 1995
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/0167-7152(94)00062-D
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:stapro:v:22:y:1995:i:2:p:157-160

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

Access Statistics for this article

Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul

More articles in Statistics & Probability Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().