D-optimal designs for multiresponse linear models with a qualitative factor

D-optimal Factorial Designs under Generalized Linear Models

Generalized linear models (GLMs) have been used widely for modelling the mean response both for discrete and continuous random variables with an emphasis on categorical response. Recently Yang, Mandal and Majumdar (2013) considered full factorial and fractional factorial locally D-optimal designs for binary response and two-level experimental factors. In this paper, we extend their results to a...

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...

Heteroscedastic T-Optimum Designs for Multiresponse Dynamic Models

Optimal Designs in Linear Regression Models

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