plot.interv_multiple

0th

Percentile

Plot for Iterative Intervention Detection Procedure for Count Time Series following Generalised Linear Models

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.

Keywords
Intervention detection
Usage
"plot"(x, ...)
Arguments
x
an object of class "interv_multiple", usually a result of a call to interv_detect.
...
additional arguments to be passed to function plot.
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.

See Also

interv_multiple for detecting multiple intervention effects in GLM-type count time series and tsglm for fitting such a model.

Aliases
  • plot.interv_multiple
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)
Documentation reproduced from package tscount, version 1.3.0, License: GPL-2 | GPL-3

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