plot.tsglm: Diagnostic Plots for a Fitted GLM-type Model for Time Series...

In tscount: Analysis of Count Time Series

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 "tsglm". Usually the result of a call to tsglm.
ask	logical value. If TRUE (and the R session is interactive) the user is asked for input, before a new figure is drawn (see devAskNewPage).
...	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)

tscount documentation built on May 11, 2023, 3:04 p.m.