plot.pdlm: Plot of PDL Models

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

Description

Plot the effects estimated with a polynomial distributed lag model

Usage

## S3 method for class 'pdlm'
plot(x, unit = 10, confidence.level = 0.95,
	labels = NULL, new = TRUE, ...)

Arguments

x	a model of class pdlm created by pdlm
unit	a vector indicating the units for relative risk computation. Default is 10. See estimate_risks for more options
confidence.level	confidence level for interval computation
labels	a vector of quoted strings with alternate labels for the pollutants. Default is the time lag index. See Details
new	if TRUE a new graph window is opened
...	further options for stockplot

Details

This function extracts the coefficients and their standard errors from a polynomial distributed lag model in x and plots a proper graph.

If labels is a vector, it must have the same length as the number of lags plus 1; if it is a quoted string it will be used as a prefix for the labels with the time lag index; and if it is NULL automatically created labels “Lag i” will be used.

Value

This function does not return a value.

Author(s)

Washington Junger [e-mail] and Antonio Ponce de Leon [e-mail]

References

Schwartz, J. (2000) The distributed lag between air pollution and daily deaths. Epidemiology 11(3), 320–326.

See Also

pdlm,estimate_risks,plot_risk

Examples

data(admrio)
setup(admrio,"date")
f <- resp5~s(time)+weekdays+s(tmpmax)+s(humid)
m <- fit_core(f)
dlm <- pdlm(m,"pm10",lags=5,degrees=2)
plot(dlm)

wjunger/ares documentation built on Dec. 23, 2021, 5:17 p.m.