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dc.contributor.authorBailey, R. A.
dc.contributor.authorSajjad, Alia
dc.identifier.citationBailey , R A & Sajjad , A 2021 , ' Optimal incomplete-block designs with low replication : a unified approach using graphs ' , Journal of Statistical Theory and Practice , vol. 15 , no. 4 , 84 .
dc.identifier.otherPURE: 275870165
dc.identifier.otherPURE UUID: c77730af-1a9e-4975-b2c2-626e7976d0ac
dc.identifier.otherORCID: /0000-0002-8990-2099/work/103137826
dc.identifier.otherScopus: 85118689995
dc.identifier.otherWOS: 000715811900001
dc.description.abstractAn incomplete-block design defines both a concurrence graph and a Levi graph. Properties of either graph can be used to compare designs with respect to D-optimality and with respect to A-optimality. In this paper we show that optimality of the design implies strong conditions on connectivity properties of the graph, and use this to classify the optimal designs when the number of observational units is close to minimal.
dc.relation.ispartofJournal of Statistical Theory and Practiceen
dc.rightsCopyright © The Author(s) 2021. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit
dc.subjectBlock designen
dc.subjectConcurrence graphen
dc.subjectLevi graphen
dc.subjectQA Mathematicsen
dc.titleOptimal incomplete-block designs with low replication : a unified approach using graphsen
dc.typeJournal articleen
dc.description.versionPublisher PDFen
dc.contributor.institutionUniversity of St Andrews.Statisticsen
dc.contributor.institutionUniversity of St Andrews.Centre for Interdisciplinary Research in Computational Algebraen
dc.description.statusPeer revieweden

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