Timescale effect estimation in time-series studies of air pollution and health: A Singular Spectrum Analysis approach

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dc.creatorBilancia, Massimo
dc.creatorStea, Girolamo
dc.date2007-09-26
dc.date2008-06-16
dc.date.accessioned2026-07-07T09:44:23Z
dc.date.available2026-07-07T09:44:23Z
dc.descriptionA wealth of epidemiological data suggests an association between mortality/morbidity from pulmonary and cardiovascular adverse events and air pollution, but uncertainty remains as to the extent implied by those associations although the abundance of the data. In this paper we describe an SSA (Singular Spectrum Analysis) based approach in order to decompose the time-series of particulate matter concentration into a set of exposure variables, each one representing a different timescale. We implement our methodology to investigate both acute and long-term effects of $PM_{10}$ exposure on morbidity from respiratory causes within the urban area of Bari, Italy.
dc.descriptionPublished in at http://dx.doi.org/10.1214/07-EJS123 the Electronic Journal of Statistics (http://www.i-journals.org/ejs/) by the Institute of Mathematical Statistics (http://www.imstat.org)
dc.identifierhttps://arxiv.org/abs/0709.4166
dc.identifierhttp://arxiv.org/abs/0709.4166
dc.identifierElectronic Journal of Statistics 2008, Vol. 2, 432-453
dc.identifierdoi:10.1214/07-EJS123
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/162857
dc.subjectApplications
dc.subject62P12 (Primary) 62J99 (Secondary)
dc.titleTimescale effect estimation in time-series studies of air pollution and health: A Singular Spectrum Analysis approach
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