Mathematical Sciences: Optimal Design of Experiments and Mixture Estimation

Studden教授和Coster教授将研究与统计实验的最佳设计、混合分布的估计和密度估计有关的问题。设计问题将考虑在多项式，样条和有理函数回归模型。将寻求涉及多目标优化设计方法的问题的解决方案。关于混合几何分布的估计问题，以及一些使用样条核的密度估计也将被考虑。本研究属于统计实验设计领域，旨在为实验科学家提供优化资源利用的策略，提高科学家正确解释实验观察结果的机会，从而加快科学进步的速度。

Professors Studden and Coster will work on problems related to the optimal design of statistical experiments, the estimation of mixture distributions and density estimation. Design problems will be considered in polynomial, spline, and rational function regression models. Solutions to problems involving multi- objective methods for optimal designs will be sought. Estimation problems concerning mixtures of geometric distributions will also be considered along with some density estimation using spline kernels. This research is in the area of statistical experimental design which aims to provide experimental scientists with strategies that will optimize their utilization of resources, improve scientists' chances of correctly interpreting experimental observations, and thereby speed the rate of scientific progress.