plot.tsglm {tscount} | R Documentation |
Diagnostic Plots for a Fitted GLM-type Model for Time Series of Counts
Description
Produces several diagnostic plots to asses the fit of a GLM-type model for time series of counts.
Usage
## S3 method for class 'tsglm'
plot(x, ask = TRUE, ...)
Arguments
x |
an object of class |
ask |
logical value. If |
... |
further arguments are currently ignored. Only for compatibility with generic function. |
Details
Produces plots of the acf of the Pearson residuals, the Pearson residuals plotted against time, a cumulative periodogramm of the Pearson residuals, a probability integral transform (PIT) histogram (see function pit
) and a marginal calibration plot (see function marcal
). The cumulative periodogramm is plotted with the function cpgram
from package MASS
and is omitted with a warning if this package is not available.
Author(s)
Tobias Liboschik and Philipp Probst
See Also
tsglm
for fitting a GLM for time series of counts.
Examples
###Campylobacter infections in Canada (see help("campy"))
interventions <- interv_covariate(n=length(campy), tau=c(84, 100),
delta=c(1, 0)) #detected by Fokianos and Fried (2010, 2012)
#Linear link function with Negative Binomial distribution:
campyfit <- tsglm(campy, model=list(past_obs=1, past_mean=13),
xreg=interventions, dist="nbinom")
plot(campyfit)