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fitted.segmented.lme<-function(object, level=1, sort=TRUE, ...){
#fit: an object of class "segmented.lme"
#What about "fitted(oo$lme.fit.noG)" or "fitted(obj,level=1)+fit$Off"?
#fitted(fitG,level=1)+fit$Off e' proprio uguale a fitted(fit.noG, level=1)
#comunque per level=0 (population parameter) l'identita' non vale, ed e' necessario fare i calcoli
# "manualmente"
#obj<- object[[1]] #sarebbe fit$lme.fit
levelC<- min(level,1) #valori >1 sono riportati ad 1
levelC<-deparse(levelC)
#browser()
switch(levelC,
"0"={
#leftSlope<- if(object$namesGZ$nameZ %in% names(fixef(object[[2]]))) fixef(object[[2]])[object$namesGZ$nameZ] else 0
#b0<-fixef(object[[2]])["(Intercept)"]
#if(is.na(b0)) b0<-0
r<-vector("list", length=length(names(object$psi.i)))
mu0 <- fitted(object$lme.fit.noG, level=0)
for(id in names(object$psi.i)){
diffSlope<-object$fixed.eta.delta[paste(id)]
Psi<- object$fixed.psi[paste(id)]
x<- object$Z[names(object$Z)==id]
#mu<-b0+leftSlope*x+diffSlope*pmax(x-Psi,0)
psi.i <- object$psi.i[paste(id)]
mu<-mu0[names(mu0)==paste(id)]
mu <- mu - diffSlope*pmax(x-psi.i,0) +diffSlope*pmax(x-Psi,0)
r[[id]]<-mu
}
mu<-unlist(r)
names(mu) <- names(object$Z)
# mu<-fitted(obj,level=0) + fit$Off
# if("G0"%in%names(ranef(obj))){
# ni<-tapply(obj$groups[,1], obj$groups[,1], length)
# ki<-rep(ranef(obj)[["G0"]],ni)
# mu<-mu + ki*obj$data[["G0"]]
# }
},
"1"={ mu <- fitted(object$lme.fit.noG, level=level)
# "1"={ mu<-fitted(obj,level=1)+fit$Off #e' proprio uguale a fitted(fit[[2]], level=1)
}
) #end_switch
if(sort) mu<- mu[order(names(mu))]
return(mu)
}
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