Adaptive Sampling Designs Inference for Sparse and Clustered Populations

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Show simple item record Seber, George en Salehi, MM en 2016-12-06T23:49:13Z en 2012-10-22 en
dc.identifier.citation 70 pages. Springer Science & Business Media 22 Oct 2012 en
dc.identifier.isbn 3642336574 en
dc.identifier.isbn 9783642336577 en
dc.identifier.uri en
dc.description.abstract This book aims to provide an overview of some adaptive techniques used in estimating parameters for finite populations where the sampling at any stage depends on the sampling information obtained to date. en
dc.description.uri en
dc.publisher Springer Science & Business Media en
dc.relation.ispartofseries SpringerBriefs in Statistics en
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. en
dc.rights.uri en
dc.subject Mathematics en
dc.title Adaptive Sampling Designs Inference for Sparse and Clustered Populations en
dc.type Book en
dc.identifier.doi 10.1007/978-3-642-33657-7 en en
pubs.publication-status Published en
dc.rights.accessrights en
pubs.subtype Book en
pubs.elements-id 542869 en
pubs.record-created-at-source-date 2016-12-07 en

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