Modeling nonstationary processes through dimension expansion

Bornn, L, Shaddick, G ORCID: https://orcid.org/0000-0002-4117-4264 and Zidek, J 2012. Modeling nonstationary processes through dimension expansion. Journal of the American Statistical Association 107 (497) , pp. 281-289. 10.1080/01621459.2011.646919

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Abstract

In this article, we propose a novel approach to modeling nonstationary spatial fields. The proposed method works by expanding the geographic plane over which these processes evolve into higher-dimensional spaces, transforming and clarifying complex patterns in the physical plane. By combining aspects of multidimensional scaling, group lasso, and latent variable models, a dimensionally sparse projection is found in which the originally nonstationary field exhibits stationarity. Following a comparison with existing methods in a simulated environment, dimension expansion is studied on a classic test-bed dataset historically used to study nonstationary models. Following this, we explore the use of dimension expansion in modeling air pollution in the United Kingdom, a process known to be strongly influenced by rural/urban effects, amongst others, which gives rise to a nonstationary field.

Item Type:	Article
Date Type:	Published Online
Status:	Published
Schools:	?? VCO ??
Publisher:	Taylor and Francis Group
ISSN:	0162-1459
Last Modified:	07 Aug 2024 15:00
URI:	https://orca.cardiff.ac.uk/id/eprint/170705

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