Efficiency of the OLSE for regressions on two-dimensional grids with sinusoidal regressors and spatially correlated errors SCIE SCOPUS
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Shin, DW | - |
dc.contributor.author | Kim, DG | - |
dc.contributor.author | Kim, HJ | - |
dc.date.accessioned | 2020-04-21T07:25:47Z | - |
dc.date.available | 2020-04-21T07:25:47Z | - |
dc.date.created | 2020-01-28 | - |
dc.date.issued | 2002 | - |
dc.identifier.issn | 0026-1335 | - |
dc.identifier.uri | https://sciwatch.kiost.ac.kr/handle/2020.kiost/5796 | - |
dc.description.abstract | For spatial regressions with sinusoidal surfaces, the ordinary least squares estimator (OLSE) is shown to be asymptotically as efficient as the generalized least squares estimator (GLSE) in that the covariance matrices of the two estimators have the same nontrivial limit under the same normalization. | - |
dc.description.uri | 1 | - |
dc.language | English | - |
dc.publisher | PHYSICA-VERLAG GMBH & CO | - |
dc.subject | ORDINARY LEAST-SQUARES | - |
dc.subject | MODEL | - |
dc.title | Efficiency of the OLSE for regressions on two-dimensional grids with sinusoidal regressors and spatially correlated errors | - |
dc.type | Article | - |
dc.citation.endPage | 258 | - |
dc.citation.startPage | 247 | - |
dc.citation.title | METRIKA | - |
dc.citation.volume | 56 | - |
dc.citation.number | 3 | - |
dc.contributor.alternativeName | 김한준 | - |
dc.identifier.bibliographicCitation | METRIKA, v.56, no.3, pp.247 - 258 | - |
dc.identifier.doi | 10.1007/s001840100177 | - |
dc.identifier.scopusid | 2-s2.0-0036459221 | - |
dc.identifier.wosid | 000179879000006 | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.subject.keywordPlus | ORDINARY LEAST-SQUARES | - |
dc.subject.keywordPlus | MODEL | - |
dc.subject.keywordAuthor | efficiency | - |
dc.subject.keywordAuthor | GLSE | - |
dc.subject.keywordAuthor | OLSE | - |
dc.subject.keywordAuthor | sinusoidal surface | - |
dc.subject.keywordAuthor | spatial regression | - |
dc.relation.journalWebOfScienceCategory | Statistics & Probability | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Mathematics | - |