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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 | 2021-08-26T06:05:23Z | - |
dc.date.available | 2021-08-26T06:05:23Z | - |
dc.date.issued | 2018 | |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84983460644&doi=10.1007%2fs00362-016-0819-y&partnerID=40&md5=3a17c04c9731d257a6a02e8e29f05b2a | |
dc.identifier.uri | https://ir.iimcal.ac.in:8443/jspui/handle/123456789/1289 | - |
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, Joka Diamond Harbour Road, Kolkata, 700 104, India | |
dc.description | ISSN/ISBN - 09325026 | |
dc.description | pp.1255-1268 | |
dc.description | DOI - 10.1007/s00362-016-0819-y | |
dc.description.abstract | We consider the optimal design problem when the design space consists of binary vectors with a string property, i.e., a single stretch of ones. This is done in the framework of second-order least squares estimation which is known to outperform ordinary least squares estimation when the error distribution is asymmetric. Analytical as well as computational results on optimal design measures, under the D- and A-criteria, are obtained. The issue of robustness to the unknown skewness parameter of the error distribution is also explored. Finally, we present several procedures which entail N-run designs that are highly efficient, if not optimal. � 2016, Springer-Verlag Berlin Heidelberg. | |
dc.publisher | SCOPUS | |
dc.publisher | Statistical Papers | |
dc.publisher | Springer New York LLC | |
dc.relation.ispartofseries | 59(3) | |
dc.subject | Design measure | |
dc.subject | Multiplicative algorithm | |
dc.subject | N-run design | |
dc.subject | Robustness | |
dc.subject | Uniform measure | |
dc.title | Optimal designs with string property under asymmetric errors and SLS estimation | |
dc.type | Article | |
Appears in Collections: | Operations Management |
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