In the last 10 years, many advances have been made in the statistical modelling of time series data on air pollution and health. Standard regression methods used initially have been almost fully replaced by semi-parametric approaches (Speckman, 1988; Hastie and Tibshirani, 1990; Green and Silverman, 1994) such as Generalized linear models (GLM) with regression splines (McCullagh and Nelder, 1989), Generalized additive models (GAM) with non-parametric splines (Hastie and Tibshirani, 1990) and GAM with penalized splines (Marx and Eilers, 1998). During the last few years, GAM with non-parametric splines was preferred to fully parametric formulations because of the increased °exibility in estimating the smooth component of the model,.
