A v-transformed copula-based simulation model for lithological classification in an Indian copper deposit

Copula functions are widely used for modeling multivariate dependence. Since the multivariate data may not necessarily be linear and Gaussian, the copula model is very often brought into the picture for modeling such multivariate phenomena. The lithological classification in spatial domain is a class of problems dealing with categorical variables. A generalized class of copula model is effective for such classification tasks. In this paper, a non-Gaussian copula (v-transformed copula) model has been used for lithotype classification of an Indian copper deposit. Coupling of Markov chain Monte Carlo (MCMC) simulation and copula discriminant function is performed for this purpose. Specifically, four lithotypes, e.g., granite, quartz, basic, and aplite are simulated in the case study deposit. The efficacy of v-transformed copula discriminant function-based simulation is compared with those of Gaussian copula, t copula, and sequential indicator simulations. Finally, the classification accuracy of all the approaches is examined with ground-truth lithological classes obtained from blast hole information. The results show that the v-transformed copula simulation has a relatively higher classification accuracy (76%) than those of Gaussian copula (70%), t copula (69%), and sequential indicator (70%) simulations.