A Study on the Influence of a Missing Cell in a Class of Central Composite Designs

  • Park, Sung-Hyun (Department of Statistics, Seoul National University, Seoul 151-742) ;
  • Noh, Hyun-Gon (Department of Statistics, Seoul National University, Seoul 151-742)
  • Published : 1998.03.01

Abstract

The central composite design is widely used in the response surface analysis, because it can fit the second order model with small experimental points. In practice, the experimental data are not always obtained on all the points. When there are missing observations, many problems due to the missing cells can occur. In this paper, the influence of a missing cell on the central composite design is discussed. First, the influences of a missing cell on the variances of estimated regression coefficents are compared as $\alpha$ varies. Second, how the average predition variance is affected by a missing sell is discussed. And the influence on rotatability is investigated. Third, the influence of a missing cell on optimality, especially on D-optimality and A-optimality, is examined.

Keywords

References

  1. Biometrika v.50 The Choice of a Second Order Rotatable Design. Box, G.E.P.;Draper, N.R.
  2. Technometrics 16 Optimum Composite Design. Lucas, J.M.
  3. Technometrics 3 Response Surface Methodology: 1966-1988. Myers, R.H.;Khuri A.I.;Carter, W.H.
  4. Response Surface Methodology: Process and Product Optimization Using Designed Experiments Myers, R.H.;Montgomery, D.C.
  5. Technometrics 12 On Practical Use of the Concept of D-Optimality. Nalimov, V.V.;Golikova, T.I.;Mikeshina, N.G.
  6. Technometrics 20 Slope-rotatable central composite designs. Hader, R.J.;Park, S.H.
  7. Annals of Institute of Statistical Mathematics 45 A measure of rotatability for second order response surface designs. Park, S.H.;Lim, J.H.;Baba, Y.
  8. Practical Data Analysis for Designed Experiments Yandell, B.S.