Projection properties of two-level supersaturated designs constructed from Hadamard designs using Lin’s method
H. Evangelaras () and
S. D. Georgiou
Additional contact information
H. Evangelaras: University of Piraeus
S. D. Georgiou: RMIT University
Metrika: International Journal for Theoretical and Applied Statistics, 2021, vol. 84, issue 8, No 1, 1095-1108
Abstract:
Abstract In the initial stages of experimentation, many factors are examined for a possible significant influence on the response of interest. After such screening, the design used is projected into the significant factors and further evaluation of their effects is performed using the projection design. It is therefore interesting to evaluate the projection properties of screening designs since such an evaluation is extremely useful in selecting the best design for experimentation. In this paper, we examine two-level supersaturated screening designs that are constructed following Lin’s method. Some theoretical results are given and a detailed evaluation of supersaturated designs with up to 12 runs is performed.
Keywords: Screening; Supersaturated designs; Projection properties; Projectivity; D-efficiency (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://link.springer.com/10.1007/s00184-020-00804-z Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:metrik:v:84:y:2021:i:8:d:10.1007_s00184-020-00804-z
Ordering information: This journal article can be ordered from
http://www.springer.com/statistics/journal/184/PS2
DOI: 10.1007/s00184-020-00804-z
Access Statistics for this article
Metrika: International Journal for Theoretical and Applied Statistics is currently edited by U. Kamps and Norbert Henze
More articles in Metrika: International Journal for Theoretical and Applied Statistics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().