Construction of D-optimal saturated designs for mixture experiments: a computer-aided algorithmic search On the construction of trend free constant block sum PBIB designs

Banerjee, Rahul and Jaggi, Seema and Varghese, Eldho and Bhowmik, Arpan and Varghese, Cini and Datta, Anindita and Lall, Shwetank (2025) Construction of D-optimal saturated designs for mixture experiments: a computer-aided algorithmic search On the construction of trend free constant block sum PBIB designs. Bhartiya Krishi Anusandhan Patrika, 38 (4). pp. 319-323.

Text Bhartiya Krishi Anusandhan Patrika_2025_Eldho Varghese.pdf Download (890kB)

Abstract

Background: Mixture experiments belong to the response surface design category, involving the combination of multiple components to create a product. These products are commonly encountered in daily life. In some cases, mixture experiments yield qualitative responses, such as taste in a fruit punch. Qualitative variables often deviate from a normal distribution. Methods: To address non-normal responses, a generalized linear model, specifically the logistic model, is employed. This study utilizes logistic models and develops suitable search algorithms to obtain saturated D-optimal designs for mixture experiments. The validation of D-optimality criteria is based on the General Equivalence Theorem. Result: For generating locally D-optimal designs, the logistic model is utilized considering non-normally distributed errors. While the procedure remains the same for other nonlinear models, the assumptions regarding error distribution impact the Fisher information matrix (FIM).

Actions (login required)

View Item