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DC Field | Value | Language |
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dc.contributor.author | Huda, Shahariar | |
dc.contributor.author | Mukerjee, Rahul | |
dc.date.accessioned | 2021-08-26T06:05:24Z | - |
dc.date.available | 2021-08-26T06:05:24Z | - |
dc.date.issued | 2017 | |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85027009499&doi=10.1080%2f00949655.2017.1362404&partnerID=40&md5=b4d7af4bd5ed6bce5ae35163b26fc112 | |
dc.identifier.uri | https://ir.iimcal.ac.in:8443/jspui/handle/123456789/1305 | - |
dc.description | Huda, Shahariar, Department of Statistics and OR, Faculty of Science, Kuwait University, P.O. Box-5969, Safat, 13060, Kuwait; Mukerjee, Rahul, Indian Institute of Management Calcutta, Kolkata, India | |
dc.description | ISSN/ISBN - 00949655 | |
dc.description | pp.3195-3207 | |
dc.description | DOI - 10.1080/00949655.2017.1362404 | |
dc.description.abstract | Optimal block designs in small blocks are explored under the A-, E- and D-criteria when the treatments have a natural ordering and interest lies in comparing consecutive pairs of treatments. We first formulate the problem via approximate theory which leads to a convenient multiplicative algorithm for obtaining A-optimal design measures. This, in turn, yields highly efficient exact designs, under the A-criterion, even when the number of blocks is rather small. Moreover, our approach is seen to allow nesting of such efficient exact designs which is an advantage when the resources for the experiment are available in possibly several stages. Illustrative examples are given and tables of A-optimal design measures are provided. Approximate theory is also seen to yield analytical results on E- and D-optimal design measures. � 2017 Informa UK Limited, trading as Taylor & Francis Group. | |
dc.publisher | SCOPUS | |
dc.publisher | Journal of Statistical Computation and Simulation | |
dc.publisher | Taylor and Francis Ltd. | |
dc.relation.ispartofseries | 87(16) | |
dc.subject | A-criterion | |
dc.subject | Approximate theory | |
dc.subject | D-criterion | |
dc.subject | E-criterion | |
dc.subject | Exact design | |
dc.subject | Multiplicative algorithm | |
dc.subject | Nesting | |
dc.subject | Nonbinary block | |
dc.title | Algorithmic and analytical construction of efficient designs in small blocks for comparing consecutive pairs of treatments | |
dc.type | Article | |
Appears in Collections: | Operations Management |
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