Spatiotemporal smoothing and sulphur dioxide trends over Europe

Adrian W. Bowman, Marco Giannitrapani and E. Marian Scott

Journal of the Royal Statistical Society Series C, 2009, vol. 58, issue 5, 737-752

Abstract: Summary. Spatiotemporal models for sulphur dioxide pollution over Europe are considered within an additive model framework. A suitable description of the spatiotemporal correlation structure of the data is constructed and incorporated in the analysis of the additive model, to ensure that standard errors and other forms of analysis reflect the form of variation that is exhibited by the data. To deal with the large sample size, an updating formula based on binning is derived to provide a computationally manageable implementation of the back‐fitting algorithm. Interaction terms involving space, time and seasonal effects are also considered. This requires three‐dimensional smoothing which is implemented by repeated application of lower dimensional marginal smoothing operations. The properties of this form of smoothing are examined and the estimators are shown to have first‐order behaviour, inherited from the marginal operations, which is equivalent to the full multivariate versions. These models and methods are applied to the sulphur dioxide data, allowing detailed and informative descriptions of the spatiotemporal patterns to be created.

Date: 2009
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
https://doi.org/10.1111/j.1467-9876.2009.00671.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:58:y:2009:i:5:p:737-752

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 ().