Diagnostic Plots for a Fitted GLM-type Model for Time Series of Counts
Produces several diagnostic plots to asses the fit of a GLM-type model for time series of counts.
- Model assessment
"plot"(x, ask = TRUE, ...)
an object of class
"tsglm". Usually the result of a call to
logical value. If
TRUE(and the R session is interactive) the user is asked for input, before a new figure is drawn (see
- further arguments are currently ignored. Only for compatibility with generic function.
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.
tsglm for fitting a GLM for time series of counts.
###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)