## Not run:
## load e060517spont data set
data(e060517spont)
## make a data frame using a 2 ms bin width
e060517spontDF <- mkGLMdf(e060517spont,0.002,0,60)
## Keep data relevant to neuron 1
e060517spontDFn1 <- e060517spontDF[e060517spontDF$neuron == "1",]
## get the isi at lag 1 and 2
e060517spontDFn1$isi1 <- isi(e060517spontDFn1,lag=1)
e060517spontDFn1$isi2 <- isi(e060517spontDFn1,lag=2)
## keep only defined elements
e060517spontDFn1 <- e060517spontDFn1[!is.na(e060517spontDFn1$isi2),]
## split the data set into an "early" and a "late" part
e060517spontDFn1e <- e060517spontDFn1[e060517spontDFn1$time <= 30,]
e060517spontDFn1l <- e060517spontDFn1[e060517spontDFn1$time > 30,]
## Fit the late part
e060517spontDFn1lGF <- gssanova(event ~ lN.1*isi1+isi2, data=e060517spontDFn1l, family="binomial", seed=20061001)
## Time transform the early part and perform goodness of fit tests
e060517spont.n1e.tt <- e060517spontDFn1lGF %tt% e060517spontDFn1e
e060517spont.n1e.tt
summary(e060517spont.n1e.tt)
plot(summary(e060517spont.n1e.tt))
## End(Not run)