explore_meteorology: Explore Meteorology
In wjunger/ares: Environmental air pollution epidemiology: a library for time series analysis

Description Usage Arguments Details Value Author(s) References See Also Examples

Explore the exposure-response relationship of meteorology

1	explore_meteorology(model, var, df = 4, type = "deviance", new = TRUE, ...)

`model`	a model fitted by `fit_core`
`var`	a quoted string with the name of the meteorology variable
`df`	degrees of freedom for the smoother. If set to 0 the smooth line is not plotted
`type`	a quoted string with the type of residuals to plot
`new`	if `TRUE` a new graph window is opened
`...`	further options for `plot`

The scatter plot of residuals against the meteorology variable is smoothed by means of a spline function defined by df.

This function does not return a value.

Washington Junger wjunger@ims.uerj.br and Antonio Ponce de Leon ponce@ims.uerj.br

Schwartz, J., Spix, C., Touloumi, G. et al. (1996) Methodological issues in studies of air pollution and daily counts of deaths or hospital admissions. J Epidemiol. Community Health 50 (suppl 1), S12–S18.

Hastie, T., Tibshirani, R. (1990) Generalized additive models. 2 ed. Chapman and Hall.

plot,smooth.spline,setup

data(admrio)
setup(admrio,"date")
f <- resp5~s(time)+weekdays+s(humid)
m <- fit_core(f)
explore_meteorology(m,"tmpmax",df=7)
explore_meteorology(m,"humid",df=7)