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D-Optimal Design for a Five-Parameter Logistic Model

  • Zorayr Manukyan
  • William F. Rosenberger
Conference paper
Part of the Contributions to Statistics book series (CONTRIB.STAT.)

Abstract

We explore the D-optimal design for a five-parameter logistic model, which includes a shape parameter to handle asymmetries, and two threshold parameters to account for situations where the asymptotes are not at 0 and 1. The optimal design is five points, including points at -∞ and ∞ representing the thresholds. We compare the efficiencies of the optimal designs arising from the two- and five- parameter models. We find a significant loss of efficiency when the two-parameter model is used on data generated from the five-parameter model.

Keywords

Optimal Design Information Matrix Directional Derivative Markov Chain Monte Carlo Method Optimal Design Point 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Notes

Acknowledgements

The authors thank two excellent referees for their detailed comments. One of the referees found a major mistake, and the authors are deeply appreciative.

References

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  1. 1.The EMMES CorporationRockvilleUSA
  2. 2.Department of StatisticsGeorge Mason UniversityFairfaxUSA

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