Ofong Edet Ntekim

Work place: Department of Mathematics, University of Calabar, Calabar, Nigeria

E-mail: offongntekim@gmail.com


Research Interests:


Offong Edet Ntekim is a Lecturer and a researcher at the Department of Mathematics, University of Calabar, Calabar, Nigeria. He obtained his B.Sc (Maths/Stats) and M.Sc (Maths) from University of Calabar, Calabar, Nigeria. He is currently doing his Doctorate degree in Applied Mathematics from the same University. He research interests is Differential Equation, Partial Differential Equation, Integral Equation and Combinatoric. He served as a coordinator; Mathematics for Social Sciences, Advance Mathematics and presently serving as undergraduate Project Coordinator. He was served as a resource person at FGN – UBE 2012 Teachers Professional Development Program. He has many publications in both foreign and local journals and is a member of Mathematical Association of Nigeria.

Author Articles
On E–Optimality Design for Quadratic Response Surface Model

By Ukeme Paulinus Akra Edet Effiong Bassey Ofong Edet Ntekim

DOI: https://doi.org/10.5815/ijmsc.2024.02.02, Pub. Date: 8 Jun. 2024

In response surface methodology, optimality criteria is a major tools used to measure the goodness of a design. Optimal experimental designs (or optimum designs) are a class of experimental designs that are optimal with respect to some statistical criterion. E – Optimality criterion is one of the traditional alphabetical criterion used to explore the right choice of a design in both linear and quadratic response surface models. In this paper, we investigated E – optimal experimental designs for a quadratic response surface model with two factor predictors. We developed an algorithm and a flowchart in line with a program to obtain E – optimal design and compare the result with an existing method. Two designs were formulated each with six points to illustrate the usefulness of the new method. The result revealed that the new technique outperformed better than the existing method. The significance of the later to the former technique is that, it minimizes error due to approximation and also make the computation of the aforementioned optimality easier. We, therefore recommended this method to be used at all length of points when E – optimality is to be evaluated.

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