Optimal prediction variance properties of some central composite designs in the hypercube

Charity Uchenna Onwuamaeze

Communications in Statistics - Theory and Methods, 2021, vol. 50, issue 8, 1911-1924

Abstract: Measures of the prediction variance performances of three variations of central composite designs when the region is hypercube were examined and compared using the G-efficiency and I-optimality criterion so as to determine the economical design(s) that perform(s) better than the other. The hypercube is the multidimensional cuboidal region with the axial distance, α=1.0. The designs are the standard central composite designs (CCD), the small composite design (SCD) and minimum run resolution V (minResV) design. Two prediction variance based optimality criteria, I-optimality and G-efficiency were determined, a plot of variance dispersion graph and fraction of design space are used to give a comprehensive picture of the behavior of the prediction variance throughout the region of interest. Comparing the three designs mentioned above for 3, 4, and 5 factors on cuboidal region, the result showed that CCD performed better than SCD and MinResVdesign considering 2, 3, and 5 center points.

Date: 2021
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2019.1656746 (text/html)
Access to full text is restricted to subscribers.

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:taf:lstaxx:v:50:y:2021:i:8:p:1911-1924

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20

DOI: 10.1080/03610926.2019.1656746

Access Statistics for this article

Communications in Statistics - Theory and Methods is currently edited by Debbie Iscoe

More articles in Communications in Statistics - Theory and Methods from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().