plot.interv_multiple {tscount} | R Documentation |
Plot for Iterative Intervention Detection Procedure for Count Time Series following Generalised Linear Models
Description
Provides a plot with the intervention effects detected by an iterative procedure (as returned by interv_multiple.tsglm
) and the time series cleaned from these intervention effects.
Usage
## S3 method for class 'interv_multiple'
plot(x, ...)
Arguments
x |
an object of class |
... |
additional arguments to be passed to function |
Details
The vertical red lines indicate where possible interventions were found and the dashed blue line is the time series cleaned from all detected intervention effects.
Author(s)
Tobias Liboschik and Philipp Probst
See Also
interv_multiple
for detecting multiple intervention effects in GLM-type count time series and tsglm
for fitting such a model.
Examples
## Not run:
###Campylobacter infections in Canada (see help("campy"))
campyfit <- tsglm(ts=campy, model=list(past_obs=1, past_mean=c(7,13)))
campyfit_intervmultiple <- interv_multiple(fit=campyfit, taus=80:120,
deltas=c(0,0.8,1), external=FALSE, B=2,
signif_level=0.05) #runs several hours!
plot(campyfit_intervmultiple)
## End(Not run)
[Package tscount version 1.4.3 Index]