Designs for approximately linear regression: two optimality properties of uniform designs

Douglas P. Wiens

Statistics & Probability Letters, 1991, vol. 12, issue 3, 217-221

Abstract: We study regression designs, with an eye to maximizing the minimum power of the standard test for Lack of Fit. The minimum is taken over a broad class of departures from the assumed multiple linear regression model. We show that the uniform design is maximin. This design attains its optimality by maximizing the minimum bias in the regression estimate of [sigma]2. It is thus surprising that this same design has an optimality property relative to the estimation of [sigma]2 -- it minimizes the maximum bias, in a closely related class of departures from linearity.

Keywords: Robustness; regression; designs; uniform; design; minimax; bias; maximin; power; testing; Lack; of; Fit (search for similar items in EconPapers)
Date: 1991
References: Add references at CitEc
Citations: View citations in EconPapers (13)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/0167-7152(91)90081-2
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:12:y:1991:i:3:p:217-221

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 ().