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summary.segmented.lme<-function(object, .vcov=NULL, digits = max(3, getOption("digits") - 3), ...){
#quale misura di varianza residua ? pi? approriata e deve restituire? da lme.fit o lme.fit.noG
#stesso discorso vale per residui, logLik (and friends)
#browser()
x<- object$lme.fit
dd <- x$dims
LL<- as.numeric(logLik(object))
#Quali residui?
#resd <- resid(object$lme.fit, type = "pearson")
resd <- resid(object$lme.fit.noG, type = "pearson")
if (length(resd) > 5) {
resd <- quantile(resd, na.rm = TRUE)
names(resd) <- c("Min", "Q1", "Med", "Q3", "Max")
}
cat("Segmented mixed-effects model fit by ")
cat(if (x$method == "REML") "REML\n" else "maximum likelihood\n")
print(data.frame(AIC = AIC(object), BIC = BIC(object), logLik = LL, row.names = " "), ...)
# if(!is.null(object$history.boot.restart)) {
# n.sol<-length(unique(object$history.boot.restart[,"psi"]))
# cat("\nFit based on", nrow(object$history.boot.restart), "boot samples,", n.sol, "different solutions found\n")
# }
if(!is.null(object$history.boot.restart)) {
n.sol<-length(unique(object$history.boot.restart[,"psi"]))
cat(" Bootstrap restarting on", nrow(object$history.boot.restart), "samples; ", n.sol, "different solution(s)\n")
}
cat("\n")
print(summary(x$modelStruct), sigma = x$sigma, reEstimates = x$coef$random,...) # verbose = verbose, ...)
cat("Fixed effects:\n ")
# fixF <- x$call$fixed
# if (inherits(fixF, "formula") || is.call(fixF)) {
# cat(deparse(x$call$fixed), "\n")
# } else {
# cat(deparse(lapply(fixF, function(el) as.name(deparse(el)))), "\n")
# }
nomeZ <- object$namesGZ$nameZ
nomiZ <- c(paste(nomeZ,":",sep=""), paste(":",nomeZ,sep=""))
nomiZ <- unlist(sapply(nomiZ, function(.x) grep(.x, names(fixef(object$lme.fit)), value=TRUE)))
nomiZ<-c(nomeZ, nomiZ)
nomiDiffSlope <- c("U", object$namesGZ$nomiUx)
nomiPsi <-c("G0", object$namesGZ$nomiG)
nomiTutti <- names(fixef(object$lme.fit))
nomiLin <- setdiff(nomiTutti, c(nomiZ, nomiDiffSlope, nomiPsi))
nominoG<-setdiff(nomiTutti, nomiPsi)
a<-summary(x)$tTable
# a[nomiPsi,2:5]<-NA
# coefAll<- a[,"Value"]
# coefAll[nominoG]
a[nominoG,"Value"] <- fixef(object$lme.fit.noG)[nominoG]
a[,"t-value"]<-a[,"Value"]/a[,"Std.Error"]
a[,"p-value"]<-2*pt(-abs(a[,"t-value"]), df=a[,"DF"])
a[,4]<- round(a[,4], digits=3)
id.leftS <- nomiZ %in% rownames(a)
nomiOrd<- if(any(id.leftS)) c(nomiLin, nomiZ, nomiDiffSlope, nomiPsi ) else c(nomiLin, nomiDiffSlope, nomiPsi )
a<- a[nomiOrd,]
a["U", 5]<- NA #pValue per U
a["G0",4:5]<-NA
if(!is.null(.vcov)){
a[, "Std.Error"]<- sqrt(diag(.vcov))[nomiOrd]
a[,"t-value"]<-a[,"Value"]/a[,"Std.Error"]
a[,"p-value"]<-2*pt(-abs(a[,"t-value"]), df=a[,"DF"])
}
#a1<-rbind(a[nomiLin,],0,a[nomiZ,],0, a[nomiDiffSlope,],0, a[nomiPsi,])
a1<-rbind(a[nomiLin,], NA, if(any(id.leftS)) a[nomiZ,] else NA, NA, a[nomiDiffSlope,], NA, a[nomiPsi,])
#rownames(a1)<-c(nomiLin, "----", nomiZ, "----", nomiDiffSlope, "----", nomiPsi )
rownames(a1)<-c(nomiLin, "-- leftS:", nomiZ, "-- diffS:", nomiDiffSlope, "-- break:", nomiPsi )
if(!any(id.leftS)) a1[nomiZ, 1]<-0
a1[,5]<- round(a1[,5],4)
#print(a1, na.print="", digits=4)
print(a1, na.print="", digits=4, zero.print = "0")
cat(" psi.link =", object$call$psi.link, "\n")
#print(a1, zero.print="")
cat("\nStandardized Within-Group Residuals:\n")
print(resd, ...)
cat("\nNumber of Observations:", x$dims[["N"]])
cat("\nNumber of Groups: ")
Ngrps <- dd$ngrps[1:dd$Q]
if((lNgrps <- length(Ngrps)) == 1) {
cat(Ngrps, "\n")
} else {
sNgrps <- 1:lNgrps
aux <- rep(names(Ngrps), sNgrps)
aux <- split(aux, array(rep(sNgrps, lNgrps), c(lNgrps,
lNgrps))[!lower.tri(diag(lNgrps))])
names(Ngrps) <- unlist(lapply(aux, paste, collapse = " %in% "))
cat("\n")
print(rev(Ngrps), ...)
}
# if(!is.null(object$history.boot.restart)) {
# n.sol<-length(unique(object$history.boot.restart[,"psi"]))
# cat("\nFit based on", nrow(object$history.boot.restart), "boot samples,", n.sol, "different solutions found\n")
# }
invisible(object)
}
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