1. SFU Institutional Repository
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  3. CIS Publication
Please use this identifier to cite or link to this item: https://repository.cihe.edu.hk/jspui/handle/cihe/2307
DC FieldValueLanguage
dc.contributor.authorSiu, Wan Chien_US
dc.contributor.otherLing, B. W.-K.-
dc.contributor.otherHo, C. Y.-F.-
dc.contributor.otherDai, Q.-
dc.date.accessioned2022-02-17T06:21:53Z-
dc.date.available2022-02-17T06:21:53Z-
dc.date.issued2015-
dc.identifier.urihttps://repository.cihe.edu.hk/jspui/handle/cihe/2307-
dc.description.abstractWhen the exact unbiasedness condition is relaxed to a near unbiasedness condition, this short communication shows that the best linear near unbiased estimation problem is actually a semi-infinite programming problem. Our recently developed dual parameterization method is applied for solving the problem. Computer numerical simulation results show that the semi-infinite programming approach outperforms the least squares approach.en_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofComputational Statistics & Data Analysisen_US
dc.titleBest linear near unbiased estimation for nonlinear signal models via semi-infinite programming approachen_US
dc.typejournal articleen_US
dc.identifier.doihttps://doi.org/10.1016/j.csda.2015.01.020-
dc.contributor.affiliationSchool of Computing and Information Sciencesen_US
dc.relation.issn0167-9473en_US
dc.description.volume88en_US
dc.description.startpage111en_US
dc.description.endpage118en_US
dc.cihe.affiliatedNo-
item.languageiso639-1en-
item.fulltextNo Fulltext-
item.openairetypejournal article-
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.cerifentitytypePublications-
crisitem.author.deptYam Pak Charitable Foundation School of Computing and Information Sciences-
crisitem.author.orcid0000-0001-8280-0367-
Appears in Collections:CIS Publication
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