QIC: Quasi Information Criterion of a Generalised Linear Model for...

In tscount: Analysis of Count Time Series

Description

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

Usage

## S3 method for class 'tsglm'
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.

Author(s)

Tobias Liboschik

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.

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)

Example output

[1] 893.3044
[1] 821.4763

tscount documentation built on Sept. 8, 2020, 9:08 a.m.