Nothing
cat(crayon::yellow("\ntest DHGLM:"))
data("crack") # crack data, LeeNP06 chapter 11 etc
hlfit <- HLfit(y~crack0+(1|specimen),family=Gamma(log),data=crack, HLmethod="REML",
rand.family=inverse.Gamma(log),
resid.model=list(formula=~cycle+(1|specimen),fixed=list(phi=NA)) )
# where phi=NA is a way to force estimatation of a scalar phi OF the residual model.
# This replicates what Lee et al. did, but is not spaMM's default.
# testthat::expect_equal(hlfit$APHLs$p_v,789.60762,tolerance=1e-4)
# testthat::expect_equal(hlfit$APHLs$p_bv,785.36745,tolerance=1e-4)
if (how(hlfit,verbose=FALSE)$obsInfo) {
testthat::expect_equal(AIC(hlfit,short.names = TRUE)[2],c(cAIC=-1606.466),tolerance=1e-4)
} else testthat::expect_equal(AIC(hlfit,short.names = TRUE)[2],c(cAIC=-1607.22365),tolerance=1e-4)
set.seed(123)
simulate(hlfit)
if (FALSE) {
hlfit <- HLfit(y~crack0+(1|specimen),family=Gamma(log),data=crack, HLmethod="REML",
rand.family=inverse.Gamma(log), resid.model=list(formula=~cycle+(1|specimen),fixed=list(lambda=0.666)) )
# and with partially-fixed ranCoefs in the residual dispersion model:
hlfit <- HLfit(y~crack0+(1|specimen),family=Gamma(log),data=crack, HLmethod="REML",
rand.family=inverse.Gamma(log), resid.model=list(formula=~cycle+(cycle|specimen),fixed=list(ranCoefs=list("1"=c(NA,-0.5,NA)))) )
}
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