clarke {ZIGP}R Documentation

Clarke's test for non-nested model comparison

Description

'clarke' suggests the better of two (not necessarily nested) models.

Usage

clarke(model1, model2, alpha=0.05, correction=T)

Arguments

model1, model2 the output of two model fits obtained by using 'mle.zigp'.
alpha significance level, defaults to 0.05.
correction boolean, if TRUE (default), the Schwarz correction will be used on the differences of log-likelihoods.

References

Clarke, Kevin A. (2007). A Simple Distribution-Free Test for Nonnested Model Selection. Political Analysis 2007 15(3), 347-363.

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

Examples

data(Seatbelts)
DriversKilled <- as.vector(Seatbelts[,1])           # will be response
kms <- as.vector(Seatbelts[,5]/mean(Seatbelts[,5])) # will be exposure
PetrolPrice <- as.vector(Seatbelts[,6])             # will be covariate 1
law <- as.vector(Seatbelts[,8])                     # will be covariate 2

fm.X.poi <- ~ PetrolPrice + law

fm.X.gp <- ~ PetrolPrice + law
fm.W.gp <- ~ 1

fm.X.zigp <- ~ PetrolPrice + law
fm.W.zigp <- ~ 1
fm.Z.zigp <- ~ 1

poi  <- mle.zigp(Yin=DriversKilled, fm.X=fm.X.poi,  fm.W=NULL,
                 fm.Z=NULL,  Offset = kms, init = FALSE)
gp   <- mle.zigp(Yin=DriversKilled, fm.X=fm.X.gp,   fm.W=fm.W.gp,
                 fm.Z=NULL,  Offset = kms, init = FALSE)
zigp <- mle.zigp(Yin=DriversKilled, fm.X=fm.X.zigp, fm.W=fm.W.zigp,
                 fm.Z=fm.Z.zigp, Offset = kms, init = FALSE)
# it is possible to compare to a Negative Binomial fit:
library(MASS)
nb   <- glm.nb(DriversKilled ~ offset(log(kms)) + PetrolPrice + law)

clarke(poi,gp)
clarke(gp,zigp)
clarke(poi,zigp)
clarke(gp,nb)

[Package ZIGP version 3.3 Index]