Improved power of one-sided tests

Mary C. Meyer and Jianqiang C. Wang

Statistics & Probability Letters, 2012, vol. 82, issue 8, 1619-1622

Abstract: For the classical least-squares model it is often the case that shape or order restrictions are appropriate for the regression function, in the form of a set of linear inequality constraints imposed on the parameters. It is generally understood that the hypothesis test using the constrained alternative will provide higher power than the corresponding test using the unconstrained alternative. We present a formal proof that this is the case. Code for constrained estimation and testing is posted at www.stat.colostate.edu/~meyer/constrparam.htm.

Keywords: Chi-bar-square test; E-bar test; Cone projection; Inequality constraints; Doubly-monotone (search for similar items in EconPapers)
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167715212001599
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:82:y:2012:i:8:p:1619-1622

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.2012.04.016

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 ().