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.
- Model assessment
an object of class
additional arguments passed to
tscount:::tsglm.loglik. These can be the arguments
init.dropwhich are explained on the help page of the function
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.
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.
tsglm for fitting a GLM for time series of counts.
###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)