Bayesian A-Optimal Design of Experiment with Quantitative and Qualitative Responses

  • Lulu KangEmail author
  • Xiao Huang
Original Article
Part of the following topical collections:
  1. Algorithms, Analysis and Advanced Methodologies in the Design of Experiments


We consider the problem of A-optimal design of experiment under a Bayesian probabilistic model with both categorical and continuous response variables. The utility function of the local design problem is derived by applying Bayesian experimental design framework. We also develop an efficient optimization algorithm to obtain the local optimal design by combining the particle swarm optimization and the blocked coordinate descent methods. In addition, we discuss two different ways of constructing the global optimal design based on the algorithm for local optimal design. Simulation studies are presented to illustrate the efficiency of our approach.


Bayesian A-optimal design Logistic model Multivariate responses PSO 



This research was supported by U.S. National Science Foundation Grants CMMI-1435902.

Compliance with Ethical Standards

Conflict of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Supplementary material


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Copyright information

© Grace Scientific Publishing 2019

Authors and Affiliations

  1. 1.Department of Applied MathematicsIllinois Institute of TechnologyChicagoUSA

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