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ReserarchID
5U37Y
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
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When the scientific need to model geochemical elements in soil, is using geostatistical methodologies, for instance krigings, but we can use a new possibility with Bayesian Inference. The models for the analysis were specified by the authors and estimated using Bayesian inference for Gaussian Markov Random Field (GMRF) through the Integrated Nested Laplace Approximation (INLA) algorithm. The results allow us to quantify and assess possible spatial relationships between the distribution of lithium and other possible explanatory elements. Are these other elements significant to the study? We believe the methods outlined here may help to find elements such as lithium, as well as contributing to the prediction and management of new extractions or prospection in a region in order to find each chemical element.
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