A pair of estimating equations for a mean vector

Takemi Yanagimoto

Statistics & Probability Letters, 2000, vol. 50, issue 1, 97-103

Abstract: Consider a class of estimators of a mean vector, indexed by a parameter. We introduce a pair of estimating equations for the parameter and the variance in the normal distribution. The equations provide us with an interpretation of the empirical Bayes method for smoothing and the James-Stein estimator. They can also be applied to various methods such as the S function lowess, the ridge estimator and the method of moving average. An extension to the non-Gaussian case is also discussed.

Keywords: Empirical; Bayes; method; GCV; Lowess; Ridge; estimator; Smoothing; method; Stein; identity (search for similar items in EconPapers)
Date: 2000
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167-7152(00)00092-4
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:50:y:2000:i:1:p:97-103

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 ().