Overview
Topic status: We're looking for students to study this topic.
In model-based design of experiments we are often interested in collecting data to fit and estimate statistical models. Experiments can be, but quite often are not, designed "optimally", where "optimal" typically means parameter estimates with high precision, i.e., minimum variance. Optimal designs require less number of observations to estimate parameters with the same, or higher, precision than non-optimal designs. Hence optimal designs can reduce the "costs" of experimentation. Practically this can mean: reduced economic costs; reduced loss of life/health; reduced loss of quality; etc. Various projects are available in this area including, but not limited to: optimum designs for variances components models; numerical algorithms for constructing optimum designs; approximation methods in non-linear optimum design; clinical trial design; etc.- Study level
- PhD, Masters
- Supervisors
- QUT
- Organisational unit
Science and Engineering Faculty
- Research area
- Keywords
- mathematics, statistics
- Contact
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Please contact the supervisor.
Dr Helen Thompson
