Modeling non-stationary processes through dimension expansion

Luke Bornn, Gavin Shaddick, James V Zidek

Research output: Contribution to journalArticlepeer-review

42 Citations (Scopus)
164 Downloads (Pure)

Abstract

In this paper, 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 multi-dimensional 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 data set 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.
Original languageEnglish
Pages (from-to)281-289
Number of pages9
JournalJournal of the American Statistical Association
Volume107
Issue number497
DOIs
Publication statusPublished - Mar 2012

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