Multivariate Estimation using Log-Ratios: A Worked Alternative
Document Type
Conference Proceeding
Publisher
Springer
Faculty
Faculty of Computing, Health and Science
School
School of Engineering / Natural Resources Modelling and Simulation Research Group
RAS ID
14228
Abstract
Common implementations of geostatistical methods, kriging and simulation, ignore the fact that geochemical data are usually reported in weight percent and are thus compositional data. Compositional geostatistics is an approach developed to ensure that the constant sum constraint is respected in estimation and simulation. The compositional geostatistical framework was implemented to test its applicability to an iron ore mine in Western Australia. Cross-validation was used to compare the results from ordinary cokriging of the additive log ratio variables with those from conventional ordinary cokriging. Two methods were used to back-transform the additive logratio estimates, the additive generalized logistic back transformation and Gauss-Hermite Quadrature approximation. Both the Aitchison distance and the Euclidean distance were used to quantify the error between the estimates and original sample values. The results follow the required constraints and produce better estimates when considering the Aitchison distance. When the Euclidean errors are considered the conventional ordinary cokriging estimates are less biased but the distribution of errors for the additive logratio estimates appear to be superior to the conventional ordinary cokriging estimates.
DOI
10.1007/978-94-007-4153-9_27
Access Rights
subscription content
Comments
WARD, C., & Mueller, U. A. (2012). Multivariate Estimation using Log-Ratios: A Worked Alternative. Proceedings of Geostatistics Oslo 2012. (pp. 333-344). Oslo. Springer. Available here