Full metadata record

DC FieldValueLanguage
dc.contributor.author김대경-
dc.date.accessioned2021-01-28T05:41:05Z-
dc.date.available2021-01-28T05:41:05Z-
dc.date.issued2002-10-
dc.identifier.citationMetrika, v. 56, issue. 3, page. 247-258en_US
dc.identifier.issn1435-926X-
dc.identifier.issn0026-1335-
dc.identifier.urihttps://link.springer.com/article/10.1007/s001840100177-
dc.identifier.urihttps://repository.hanyang.ac.kr/handle/20.500.11754/157654-
dc.description.abstractFor spatial regressions with sinusoidal surfaces, the ordinary least squares estimator (OLSE) is shown to be asymptotically as efficient as the geeralized least squares estimator (GLSE) in that the covariance matrices of the two estimators have the same nontrivial limit under the same normalization.en_US
dc.description.sponsorshipThis research was supported by a grant from Ewha University.en_US
dc.language.isoen_USen_US
dc.publisherSpringer-Verlag GmbH Germanyen_US
dc.subjectEfficiencyen_US
dc.subjectGLSEen_US
dc.subjectOLSEen_US
dc.subjectSinusoidal surfaceen_US
dc.subjectSpatial regressionen_US
dc.titleEfficiency of the OLSE for regressions on two-dimensional grids with sinusoidal regressors and spatially correlated errorsen_US
dc.typeArticleen_US
dc.identifier.doi10.1007/s001840100177-
dc.relation.journalMETRIKA-
dc.contributor.googleauthorShin, Dong Wan-
dc.contributor.googleauthorKim, Dai-Gyoung-
dc.contributor.googleauthorKim, Han Joon-
dc.relation.code2009210463-
dc.sector.campusE-
dc.sector.daehakCOLLEGE OF SCIENCE AND CONVERGENCE TECHNOLOGY[E]-
dc.sector.departmentDEPARTMENT OF APPLIED MATHEMATICS-
dc.identifier.piddgkim-
Appears in Collections:
COLLEGE OF SCIENCE AND CONVERGENCE TECHNOLOGY[E](과학기술융합대학) > APPLIED MATHEMATICS(응용수학과) > Articles
Files in This Item:
There are no files associated with this item.
Export
RIS (EndNote)
XLS (Excel)
XML


qrcode

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE