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Minimum Bias Design for Polynomial Regression

Authors
Jang, Dae-HeungKim, Youngil
Issue Date
Dec-2015
Publisher
KOREAN STATISTICAL SOC
Keywords
bias; minimum bias design; Q-optimal design; integrated mean squared error(IMSE)
Citation
KOREAN JOURNAL OF APPLIED STATISTICS, v.28, no.6, pp 1227 - 1234
Pages
8
Journal Title
KOREAN JOURNAL OF APPLIED STATISTICS
Volume
28
Number
6
Start Page
1227
End Page
1234
URI
https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/64420
DOI
10.5351/KJAS.2015.28.6.1227
ISSN
1225-066X
2383-5818
Abstract
Traditional criteria for optimum experimental designs depend on the specifications of the model; however, there will be a dilemma when we do not have perfect knowledge about the model. Box and Draper (1959) suggested one direction to minimize bias that may occur in this situation. We will demonstrate some examples with exact solutions that provide a no-bias design for polynomial regression. The most interesting finding is that a design that requires less bias should allocate design points away from the border of the design space.
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