# Clarketest: Clarke's test for non-nested model comparison In spatcounts: Spatial count regression

## Description

'Clarketest' suggests the better of two (not necessarily nested) models according to Clarke's statistic for the parameters in each of the iterations.

## Usage

 ```1 2``` ```Clarketest(LogLike1, LogLike2, alpha = 0.05, p = NULL, q = NULL, correction = TRUE) ```

## Arguments

 `LogLike1, LogLike2` the output of two model fits obtained by using 'LogLike'. `alpha` significance level, defaults to 0.05. `p, q` the number of estimated coefficients in models LogLike1 and Loglike2, respectively. `correction` boolean, if TRUE (default), the Schwarz correction will be used on the differences of log-likelihoods.

## References

Clarke, Kevin A. (2003). Nonparametric Model Discrimination in International Relations. Journal of Conflict Resolution 47(1), 72-93.

Schwarz, G. (1978). Estimating the Dimension of a Model. Annals of Statistics 6, 461-464.

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19``` ```data(sim.Yin) data(sim.fm.X) data(sim.region) data(sim.gmat) data(sim.nmat) poi <- est.sc(sim.Yin, ~1+sim.fm.X[,1]+sim.fm.X[,2], sim.region, model="Poi", sim.gmat, sim.nmat, 3) nb <- est.sc(sim.Yin, ~1+sim.fm.X[,1]+sim.fm.X[,2], sim.region, model="NB", sim.gmat, sim.nmat, 3) DIC.poi <- DIC(sim.Yin, ~1+sim.fm.X[,1]+sim.fm.X[,2], sim.region, poi) DIC.nb <- DIC(sim.Yin, ~1+sim.fm.X[,1]+sim.fm.X[,2], sim.region, nb) ll.poi <- LogLike(sim.Yin, ~1+sim.fm.X[,1]+sim.fm.X[,2], sim.region, poi) ll.nb <- LogLike(sim.Yin, ~1+sim.fm.X[,1]+sim.fm.X[,2], sim.region, nb) Clarke.poi.nb <- Clarketest(ll.poi, ll.nb, alpha = 0.05, p = DIC.poi\$p.D, q = DIC.nb\$p.D, correction = TRUE) ```