# 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

1 2 |

### 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

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)
``` |

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