Spatially weighted functional clustering of river network data

O'Donnell, R.A., Miller, C.A. and Scott, E.M. (2015) Spatially weighted functional clustering of river network data. Journal of the Royal Statistical Society: Series C (Applied Statistics), 64(3), pp. 491-506. (doi: 10.1111/rssc.12082) (PMID:25926710) (PMCID:PMC4407953)

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Incorporating spatial covariance into clustering has previously been considered for functional data to identify groups of functions which are similar across space. However, in the majority of situations that have been considered until now the most appropriate metric has been Euclidean distance. Directed networks present additional challenges in terms of estimating spatial covariance due to their complex structure. Although suitable river network covariance models have been proposed for use with stream distance, where distance is computed along the stream network, these models have not been extended for contexts where the data are functional, as is often the case with environmental data. The paper develops a method of calculating spatial covariance between functions from sites along a river network and applies the measure as a weight within functional hierarchical clustering. Levels of nitrate pollution on the River Tweed in Scotland are considered with the aim of identifying groups of monitoring stations which display similar spatiotemporal characteristics.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Scott, Professor Marian and O'Donnell, Dr Ruth and Miller, Professor Claire
Authors: O'Donnell, R.A., Miller, C.A., and Scott, E.M.
College/School:College of Science and Engineering > School of Mathematics and Statistics > Statistics
Journal Name:Journal of the Royal Statistical Society: Series C (Applied Statistics)
Publisher:Wiley-Blackwell Publishing Ltd.
ISSN (Online):1467-9876
Copyright Holders:Copyright © 2014 The Authors
First Published:First published in Journal of the Royal Statistical Society: Series C (Applied Statistics) 64(3):491-506
Publisher Policy:Reproduced under a Creative Commons License

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