In this paper, we tackle the study of the relationship between daily non accidental deaths and air pollution in the city of Philadelphia in the years 1974 -1988. For modelling the data, we propose to make use of dynamic generalized linear models. These models allow to deal with the serial dependence and time-varying effects of the covariates. Inference is performed by using extended Kaiman filter and smoother.

Mortality and air pollution in Philadelphia: a dynamic generalized linear modelling approach

CHIOGNA M.;
2004

Abstract

In this paper, we tackle the study of the relationship between daily non accidental deaths and air pollution in the city of Philadelphia in the years 1974 -1988. For modelling the data, we propose to make use of dynamic generalized linear models. These models allow to deal with the serial dependence and time-varying effects of the covariates. Inference is performed by using extended Kaiman filter and smoother.
Advances in Multivariate Data Analysis
233
244
CHIOGNA M.; GAETAN C.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11585/649404
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