QIC

0th

Percentile

Quasi Information Criterion of a Generalised Linear Model for Time Series of Counts

The function computes the Quasi Information Criterion (QIC) of a generalised linear model for time series of counts.

Keywords
Model assessment
Usage
"QIC"(object, ...)
Arguments
object
an object of class "tsglm".
...
additional arguments passed to tscount:::tsglm.loglik. These can be the arguments init.method and init.drop which are explained on the help page of the function tsglm.
Details

The quasi information criterion (QIC) has been proposed by Pan (2001) as alternative to Akaike's information criterion (AIC) which is properly adjusted for regression analysis based on the generalized estimating equations (GEE).

This function computes the QIC of a generalised linear model for time series of counts. In case of models with the Poisson distribution the QIC has approximately the same value as the AIC. However, in case of models with another distribution it can be a more adequate alternative to the AIC.

References

Pan, W. (2001) Akaike's Information Criterion in Generalized Estimating Equations. Biometrics 57, 120--125, http://dx.doi.org/10.1111/j.0006-341X.2001.00120.x.

See Also

tsglm for fitting a GLM for time series of counts.

AIC and BIC for other information criteria.

Aliases
  • QIC
  • QIC.tsglm
Examples
###Campylobacter infections in Canada (see help("campy"))
campyfit <- tsglm(ts=campy, model=list(past_obs=1, past_mean=c(7,13)), distr="nbinom")
QIC(campyfit)
AIC(campyfit)
Documentation reproduced from package tscount, version 1.3.0, License: GPL-2 | GPL-3

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