Minimax Average MSE Designs for Estimating Mean Responses

  • Joong-Yang Park (Professor, Department of Statistics, Gyeongsang National University, Chinju, 660-701, Korea)
  • Published : 1996.12.01

Abstract

The unknown response function is usually approximated by a low order polynomial model. Such an approximation always accompanies bias due to model departure. The minimax Average MSE (AMSE) designs are suggested for estimating mean responses. A class of first order minimax AMSE designs is derived and a specific first order minimax AMSE design is selected from the class by optimizing the secondary criterion related to the power of the lack of fit test.

Keywords

References

  1. Biometrika v.79 A New Look At Experimental Design Robustness DeFeo, P.;Myers, R.H.
  2. Journal of Royal Statistical Society Ser. B. v.21 Optimal Experimental Designs(with discussion) Kiefer, J.
  3. Biometika v.62 The Design of Experimenta for Discriminating Between Two Rival Models Atkinson, A.C.;Fedorov, V.V.
  4. Journal of Statistical Planning and Inference v.31 Minimax Designs for Approximately Linear Regression Weins, D. P.
  5. Biometrika v.62 Optimal Design: Experiments for Discriminating Between Several Models Atkinson, A.C.;Fedorov, V.V.
  6. Journal of the American Statistical Association v.54 A Basis for the Selection of A Response Surface Design Box, G.E.P.;Draper, N.R.
  7. The Korean Communications in Statistics v.2 Minimum Mean Squared Error Invariant Designs for Polynomial Approximation Park, J.Y.
  8. Journal of Statistical Planning and Inference v.1 Comparison of Designs for Quadratic Regression on Cubes Galil, Z.;Kiefer, J.
  9. Biometrika v.65 Design Criteria for Detecting Model Inadequacy Jones, E.R.;Mitchell, T.J.