anova.hidden: anova for the class hidden

Description

The generic function `anova' is adapted to the objects inheriting from class hidden (anova.hidden) to compute the likelihood ratio test for nested hidden models estimated by `hidden.emfit'.

Usage

# S3 method for hidden
anova(object,objectlarge,...)

Arguments

object

Object of the class hidden, reduced model, i.e. modelA

objectlarge

Object of the class hidden, large model, i.e. modelB

…

Other models and further arguments passed to or from other methods

Details

Nested models, fitted by `hidden.emfit', are compared (e.g. modelA is nested in modelB), the likelihood ratio statistic with the degrees of freedom and the associated pvalue is returned.

Examples

Run this code

# NOT RUN {
data(drinks)
y<-cbind(drinks$lemon.tea,drinks$orange.juice)

f<-~lat*tea+lat*juice+tea*juice  # lat indicates the latent variable
fm<-c("l-l-l")
fmargobs<-marg.list(fm,mflag="m")
Ptr<-matrix(c(0.941, 0.199,
               0.059, 0.801),2,2,byrow=TRUE)
Ptobs<-matrix(c(0.053, 0.215, 0.206, 0.001, 0.039, 0.021, 0.020, 0.176, 0.270,
                0.000, 0.000, 0.000, 0.048, 0.263, 0.360, 0.065, 0.053, 0.211)
                ,2,9,byrow=TRUE)

# saturated model (fsat<-~lat*tea*juice is implicit)
model.obsf<-hmmm.model(marg=fmargobs,
lev=c(2,3,3),names=c("lat","tea","juice"))
modelsat<-hidden.emfit(y,model.obsf,y.eps=0.01,maxit=10,
maxiter=2500,norm.diff.conv=0.001,old.tran.p=Ptr,bb=Ptobs)

# model with constant association
model.coass<-hmmm.model(marg=fmargobs,
lev=c(2,3,3),names=c("lat","tea","juice"),formula=f)
modelca<-hidden.emfit(y,model.coass,y.eps=0.01,maxit=10,
maxiter=2500,norm.diff.conv=0.001,old.tran.p=Ptr,bb=Ptobs)

a<-anova(modelca,modelsat)
# }

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