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http://dx.doi.org/10.5351/KJAS.2015.28.6.1227

Minimum Bias Design for Polynomial Regression  

Jang, Dae-Heung (Department of Statistics, Pukyong National University)
Kim, Youngil (School of Business and Economics, ChungAng University)
Publication Information
The Korean Journal of Applied Statistics / v.28, no.6, 2015 , pp. 1227-1234 More about this Journal
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.
Keywords
bias; minimum bias design; Q-optimal design; integrated mean squared error(IMSE);
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