DSpace at EWHA: Bayesian analysis of regression models with spatially correlated errors and missing observations

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DC Field	Value	Language
dc.contributor.author	오만숙	*
dc.contributor.author	신동완	*
dc.date.accessioned	2016-08-28T11:08:00Z	-
dc.date.available	2016-08-28T11:08:00Z	-
dc.date.issued	2002	*
dc.identifier.issn	0167-9473	*
dc.identifier.other	OAK-1091	*
dc.identifier.uri	https://dspace.ewha.ac.kr/handle/2015.oak/219007	-
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. © 2002 Elsevier Science B.V. All rights reserved.	*
dc.language	English	*
dc.title	Bayesian analysis of regression models with spatially correlated errors and missing observations	*
dc.type	Article	*
dc.relation.issue	4	*
dc.relation.volume	39	*
dc.relation.index	SCIE	*
dc.relation.index	SCOPUS	*
dc.relation.startpage	387	*
dc.relation.lastpage	400	*
dc.relation.journaltitle	Computational Statistics and Data Analysis	*
dc.identifier.doi	10.1016/S0167-9473(01)00084-6	*
dc.identifier.wosid	WOS:000176397600002	*
dc.identifier.scopusid	2-s2.0-0037189356	*
dc.author.google	Oh M.-S.	*
dc.author.google	Shin D.W.	*
dc.author.google	Kim H.J.	*
dc.contributor.scopusid	오만숙(7201600334)	*
dc.contributor.scopusid	신동완(7403352539)	*
dc.date.modifydate	20240116115756	*