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A Bayesian statistical model for end member analysis of sediment geochemistry, incorporating spatial dependences


  • Mark J. Palmer
  • Grant B. Douglas


An important problem in the management of water supplies is identifying the sources of sediment. The paper develops a Bayesian approach, utilizing an end member model, to estimate the proportion of various sources of sediments in samples taken from a dam. This approach not only allows for the incorporation of prior knowledge about the geochemical compositions of the sources (or end members) but also allows for correlation between spatially contiguous samples and the prediction of the sediment's composition at unsampled locations. Sediments that were sampled from the North Pine Dam in south-east Queensland, Australia, are analysed to illustrate the approach. Copyright (c) 2008 CSIRO Journal compilation (c) 2008 Royal Statistical Society.

Suggested Citation

  • Mark J. Palmer & Grant B. Douglas, 2008. "A Bayesian statistical model for end member analysis of sediment geochemistry, incorporating spatial dependences," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 57(3), pages 313-327.
  • Handle: RePEc:bla:jorssc:v:57:y:2008:i:3:p:313-327

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