Ordinary Cokriging Revisited
dc.contributor.author | Goovaerts, Pierre | en_US |
dc.date.accessioned | 2006-09-08T21:10:35Z | |
dc.date.available | 2006-09-08T21:10:35Z | |
dc.date.issued | 1998-01 | en_US |
dc.identifier.citation | Goovaerts, P.; (1998). "Ordinary Cokriging Revisited." Mathematical Geology 30(1): 21-42. <http://hdl.handle.net/2027.42/43198> | en_US |
dc.identifier.issn | 0882-8121 | en_US |
dc.identifier.issn | 1573-8868 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/43198 | |
dc.description.abstract | This paper sets up the relations between simple cokriging and ordinary cokriging with one or several unbiasedness constraints. Differences between cokriging variants are related to differences between models adopted for the means of primary and secondary variables. Because it is not necessary for the secondary data weights to sum to zero, ordinary cokriging with a single unbiasedness constraint gives a larger weight to the secondary information while reducing the occurrence of negative weights. Also the weights provided by such cokriging systems written in terms of covariances or correlograms are not related linearly, hence the estimates are different. The prediction performances of cokriging estimators are assessed using an environmental dataset that includes concentrations of five heavy metals at 359 locations. Analysis of reestimation scores at 100 test locations shows that kriging and cokriging perform equally when the primary and secondary variables are sampled at the same locations. When the secondary information is available at the estimated location, one gains little by retaining other distant secondary data in the estimation. | en_US |
dc.format.extent | 794989 bytes | |
dc.format.extent | 3115 bytes | |
dc.format.mimetype | application/pdf | |
dc.format.mimetype | text/plain | |
dc.language.iso | en_US | |
dc.publisher | Kluwer Academic Publishers-Plenum Publishers; International Association for Mathematical Geology ; Springer Science+Business Media | en_US |
dc.subject.other | Geosciences | en_US |
dc.subject.other | Hydrogeology | en_US |
dc.subject.other | Math. Applications in Geosciences | en_US |
dc.subject.other | Geotechnical Engineering | en_US |
dc.subject.other | Statistics for Engineering, Physics, Computer Science, Chemistry & Geosciences | en_US |
dc.subject.other | Cokriging | en_US |
dc.subject.other | Unbiasedness Constraints | en_US |
dc.subject.other | Negative Weights | en_US |
dc.subject.other | Standardization | en_US |
dc.title | Ordinary Cokriging Revisited | en_US |
dc.type | Article | en_US |
dc.subject.hlbsecondlevel | Geology and Earth Sciences | en_US |
dc.subject.hlbtoplevel | Science | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Department of Civil and Environmental Engineering, The University of Michigan, EWRE Bldg., Room 117, Ann Arbor, Michigan, 48109-2125, U.S.A | en_US |
dc.contributor.affiliationumcampus | Ann Arbor | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/43198/1/11004_2004_Article_412218.pdf | en_US |
dc.identifier.doi | http://dx.doi.org/10.1023/A:1021757104135 | en_US |
dc.identifier.source | Mathematical Geology | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
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