Linear transformation methods for multivariate geostatistical simulation

Date of Award


Degree Type


Degree Name

Doctor of Philosophy


School of Natural Sciences


Faculty of Computing, Health and Science


Multivariate geostatistical techniques take into account the statistical and spatial relationships between attributes but can be inferentially and computationally expensive. One way to circumvent these issues is to transform the spatially correlated attributes into a set of decorrelated factors for which the off diagonal elements of the spatial covariance matrix are zero. This requires the derivation of a transformation matrix that exactly or approximately diagonalises the spatial covariance matrix for all separation distances. The resultant factors can then analysed using the more straightforward univariate techniques. This thesis is concerned with the investigation of linear decorrclation methods whereby the resulting factors are linear combinations of the original attributes.

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Access to this thesis is restricted. Please see the Access Note below for access details.