Optimal Designs for Generalized Pareto Model

Improving Pareto Optimal Designs Using Genetic Algorithms

1 Abstract Pareto optimal designs are the best designs that can be produced for a given problem formulation for a given set of criteria when the criteria are not combined in any way. If the goal is to improve the performance in those criteria then it is possible to manipulate the problem formulation to achieve an improvement. The approach adopted is to encode the formulation in a genetic algori...

A-optimal designs for generalized linear model with two parameters

An algebraic method for constructing A-optimal designs for two parameter generalized linear models is presented. It gives sufficient conditions to identify the A-optimal design. When the conditions are satisfied, the A-optimal has exactly two points, which is symmetric but not weight symmetric. The methodology is illustrated by means of selected examples. This result proves the conjecture of Ma...

Optimal Designs for Generalized Linear Models

Both HK1 and HK2 deal with experiments in which the planned analysis is based on a linear model. Selecting designs for such experiments remains a critically important problem. However, there are many problems for which a linear model may not be a great choice. For example, if the response is a binary variable or a count variable rather than a continuous measurement, a linear model may be quite ...

Optimal Designs for Generalized Linear Models with Multiple Design Variables

Binary response experiments are very common in scientific studies. However, the study of optimal designs in this area is in a very underdeveloped stage. Sitter and Torsney (1995a) studied optimal designs for binary response experiments with two design variables. In this paper, we consider a general situation with multiple design variables. A novel approach is proposed to identify optimal design...

Maximin Optimal Designs for the Compartmental Model