Non-linear univariate and multivariate spatial modelling and optimal design
Description
This thesis developed a novel adaptive methodology for the optimal design of additional sampling based on a geostatistical model that can preserve both multivariate non-linearity and spatial non-linearity present in spatial variables. This methodology can be applied in mining or any other field that deals with spatial data. The results from the different environment case studies demonstrated the potential of the proposed design methodology.
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| ID Code: | 95625 |
|---|---|
| Item Type: | QUT Thesis (PhD) |
| Supervisor: | Thompson, Helen, Kozan, Erhan, & Wolff, Rodney |
| Keywords: | Spatial, Copula, Pair-copula, Geostatistics, Non-linear spatial dependency, Non-linear principal component analysis, Multivariate spatial statistics, Spatial design, Monte Carlo simulation, Sequential design |
| Divisions: | Past > QUT Faculties & Divisions > Science & Engineering Faculty Past > Schools > School of Chemistry, Physics & Mechanical Engineering Current > Schools > School of Mathematical Sciences |
| Institution: | Queensland University of Technology |
| Deposited On: | 31 May 2016 01:51 |
| Last Modified: | 10 Sep 2021 14:46 |
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