Bayesian analysis of regression models with spatially correlated errors and missing observations SCIE SCOPUS
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Oh, MS | - |
| dc.contributor.author | Shin, DW | - |
| dc.contributor.author | Kim, HJ | - |
| dc.date.accessioned | 2020-04-21T06:55:43Z | - |
| dc.date.available | 2020-04-21T06:55:43Z | - |
| dc.date.created | 2020-01-28 | - |
| dc.date.issued | 2002-06-28 | - |
| dc.identifier.issn | 0167-9473 | - |
| dc.identifier.uri | https://sciwatch.kiost.ac.kr/handle/2020.kiost/5691 | - |
| dc.description.abstract | A Bayesian approach is proposed for estimating regression models on rectangular grids in which errors are spatially correlated and missing observations are present in the response variable. An easy and efficient Markov chain Monte Carlo algorithm is fully described for posterior inference on parameters and prediction of missing observations. Analysis of a real marine remote-sensing data set is presented to illustrate the method. (C) 2002 Elsevier Science B.V. All rights reserved. | - |
| dc.description.uri | 1 | - |
| dc.language | English | - |
| dc.publisher | ELSEVIER SCIENCE BV | - |
| dc.subject | TIME-SERIES MODELS | - |
| dc.subject | FIELD EXPERIMENTS | - |
| dc.subject | TRIALS | - |
| dc.title | Bayesian analysis of regression models with spatially correlated errors and missing observations | - |
| dc.type | Article | - |
| dc.citation.endPage | 400 | - |
| dc.citation.startPage | 387 | - |
| dc.citation.title | COMPUTATIONAL STATISTICS & DATA ANALYSIS | - |
| dc.citation.volume | 39 | - |
| dc.citation.number | 4 | - |
| dc.contributor.alternativeName | 김한준 | - |
| dc.identifier.bibliographicCitation | COMPUTATIONAL STATISTICS & DATA ANALYSIS, v.39, no.4, pp.387 - 400 | - |
| dc.identifier.doi | 10.1016/S0167-9473(01)00084-6 | - |
| dc.identifier.scopusid | 2-s2.0-0037189356 | - |
| dc.identifier.wosid | 000176397600002 | - |
| dc.type.docType | Article | - |
| dc.description.journalClass | 1 | - |
| dc.subject.keywordPlus | TIME-SERIES MODELS | - |
| dc.subject.keywordPlus | FIELD EXPERIMENTS | - |
| dc.subject.keywordPlus | TRIALS | - |
| dc.subject.keywordAuthor | Gibbs sampling algorithm | - |
| dc.subject.keywordAuthor | Markov chain Monte Carlo | - |
| dc.subject.keywordAuthor | missing value | - |
| dc.subject.keywordAuthor | posterior inference | - |
| dc.subject.keywordAuthor | spatial data | - |
| dc.relation.journalWebOfScienceCategory | Computer Science, Interdisciplinary Applications | - |
| dc.relation.journalWebOfScienceCategory | Statistics & Probability | - |
| dc.description.journalRegisteredClass | scie | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.relation.journalResearchArea | Computer Science | - |
| dc.relation.journalResearchArea | Mathematics | - |
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- Ocean Climate Solutions Research Division > Ocean Climate Response & Ecosystem Research Department > 1. Journal Articles
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