dc.contributor.author | Madani, Nasser | |
dc.contributor.author | Emery, Xavier | |
dc.contributor.editor | Stochastic Environmental Research and Risk Assessment | |
dc.contributor.other | Stochastic Environmental Research and Risk Assessment | |
dc.date.accessioned | 2018-08-09T08:26:15Z | |
dc.date.available | 2018-08-09T08:26:15Z | |
dc.date.issued | 2018-07-06 | |
dc.identifier.citation | Madani, N., Emery, X. (2018). “A comparison of search strategies to design the cokriging neighborhood for predicting coregionalized variables”. Stochastic Environmental Research and Risk Assessment, DOI: 10.1007/s00477-018-1578-1. | en_US |
dc.identifier.other | DOI: 10.1007/s00477-018-1578-1 | |
dc.identifier.uri | http://nur.nu.edu.kz/handle/123456789/3380 | |
dc.description.abstract | Cokriging allows predicting coregionalized variables from sampling information, by considering their spatial joint depen- dence structure. When secondary covariates are available exhaustively, solving the cokriging equations may become pro- hibitive, which motivates the use of a moving search neighborhood to select a subset of data, based on their closeness to the target location and the screen effect approximation. This paper investigates the efficiency of different strategies for designing a sub-optimal neighborhood wherein the simplification of the cokriging equations is challenging. To do so, five alternatives (single search, multiple search, strictly collocated search, multi-collocated search and isotopic search) are tested and com- pared with the reference unique neighborhood, through synthetic examples with different data configurations and spatial joint correlation models. The results indicate that the multi-collocated and multiple searches bear the highest resemblance to the reference case under the analyzed spatial structure models, while the single and the isotopic searches, which do not differentiate the primary and secondary sampling designs, yield the poorest results in terms of cokriging error variance. | en_US |
dc.description.sponsorship | The first author acknowledges the Nazarbayev University for funding this work via ‘‘Faculty development compet- itive research Grants for 2018–2020’’ under Contract No. 090118FD5336. The second author acknowledges the Chilean Com- mission for Scientific and Technological Research (CONICYT), through Grant CONICYT PIA Anillo ACT1407. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Stochastic Environmental Research and Risk Assessment | en_US |
dc.rights | CC0 1.0 Universal | * |
dc.rights.uri | http://creativecommons.org/publicdomain/zero/1.0/ | * |
dc.subject | Screening effect | en_US |
dc.subject | Multi-collocated cokriging | en_US |
dc.subject | Strictly collocated cokriging | en_US |
dc.subject | Markov-type models | en_US |
dc.subject | Intrinsic correlation | en_US |
dc.subject | Cokriging neighborhood | en_US |
dc.subject | Heterotopic sampling | en_US |
dc.title | A comparison of search strategies to design the cokriging neighborhood for predicting coregionalized variables | en_US |
dc.type | Article | en_US |
workflow.import.source | science |
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