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.
an object of class
logical value. If
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.
Tobias Liboschik and Philipp Probst
tsglm for fitting a GLM for time series of counts.
1 2 3 4 5 6 7
###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)
Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker.