On the robustness of central composite designs when missing two observations

Author:

Alanazi Kareem12,Georgiou Stelios D.1ORCID,Stylianou Stella1

Affiliation:

1. School of Sciences RMIT University Melbourne Victoria Australia

2. Department of Mathematics, College of Science Jouf University Skaka Saudi Arabia

Abstract

AbstractQuite often, many situations arise in experimental work where some experimental runs that may not be feasible because of certain circumstances or existing constraints in the system under investigation. A lot of work has been done in studying classical designs, such as the central composite designs (CCDs), with missing observations. In this paper our interest is to research the losses that may occur when one or two observations are missing. The general formulas for missing two observations are presented in a closed form as a function of α, where α is the value used in the axial part in the CCDs. These are calculated explicitly for CCDs up to factors, for the first time in this paper, and are displayed in tables for practitioners to use. The losses for any value of α, in the axial points of the design, can be derived by simply replacing α with the desirable value in the provided formulas. A detailed comparison between our findings and results already known in the literature also been made.

Publisher

Wiley

Subject

Management Science and Operations Research,Safety, Risk, Reliability and Quality

Reference20 articles.

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2. SimpsonTW PeplinskiJ KochPN AllenlJ.On the use of statistics in design and the implications for deterministic computer experiments.International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. Paper no. V003T30A008. pp 14‐17. Houston  TX: ASME1997.

3. Effects of missing observations on predictive capability of augmented Box-Behnken designs

4. Robustness of split‐plot central composite designs in the presence of a single missing observation;Unna Chukwu A;Pacific J Sci Technol,2013

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1. Central composite designs with three missing observations;Applied Numerical Mathematics;2023-12

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