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Timescale effect estimation in time-series studies of air pollution and health: a singular spectrum analysis approach. (English) Zbl 1320.62220
Summary: A 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.
MSC:
62P12 Applications of statistics to environmental and related topics
62M10 Time series, auto-correlation, regression, etc. in statistics (GARCH)
62M15 Inference from stochastic processes and spectral analysis
Software:
gamair; R; ElemStatLearn
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References:
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