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This paper presents a supplementary, valuable property of the minimum bias estimation (MBE) procedure, addressed in Karson et al. (Technometrics 11 (1969) 461), within the context of a single variable design problem appearing in the response surface methodology (RSM) literature.
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These so-called "minimum bias" measurements set the stage on which all other measurements are made.
Minimum bias and minimum variance are shown to be contradictory experimental design objectives.
The bias estimation is similar to that in [23].
Omitting such factors will then bias estimation results.
The satellite biases derived by NICT do not provide the accuracy bias estimation (Ma and Maruyama, 2003).
The minimum bias design criterion is an important part of response surface methodology.
The run yielded data from several hundred million dimuon and minimum bias triggers.
Method comparison and bias estimation are important components of these studies.
Overall, the results in this paper justify the use of the traditional approach for online bias estimation with a persistent bias model and a simplified forecast bias error covariance estimation.
This would bias estimation of selective fertility.
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