Estimation of the smallest normal variance with applications to variance components models

Panayiotis Bobotas and Stavros Kourouklis

Statistics & Probability Letters, 2017, vol. 131, issue C, 38-45

Abstract: It is proved that improved point and interval estimators for the smallest normal variance can be directly obtained from the unrestricted normal variance estimation counterparts. Applications to estimating the error variance in general random or mixed effects models are given.

Keywords: Decision theory; Improved estimators of a normal variance; Improved confidence intervals of a normal variance; Stein-type estimators; Brewster and Zidek-type estimators; Strawderman-type estimators (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167715217302651
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:131:y:2017:i:c:p:38-45

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

DOI: 10.1016/j.spl.2017.08.005

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 ().