A Bayesian statistical model for end member analysis of sediment geochemistry, incorporating spatial dependences
Mark J. Palmer and
Grant B. Douglas
Journal of the Royal Statistical Society Series C, 2008, vol. 57, issue 3, 313-327
Abstract:
Summary. 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.
Date: 2008
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
https://doi.org/10.1111/j.1467-9876.2007.00615.x
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:bla:jorssc:v:57:y:2008:i:3:p:313-327
Ordering information: This journal article can be ordered from
http://ordering.onli ... 1111/(ISSN)1467-9876
Access Statistics for this article
Journal of the Royal Statistical Society Series C is currently edited by R. Chandler and P. W. F. Smith
More articles in Journal of the Royal Statistical Society Series C from Royal Statistical Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().