Nothing
permutmpj <- function(m,order,estim=TRUE)
{
if(m$nbevt>0)
{
## permuter les coef de la survie et classmb
z <- m$call
z$longitudinal <- NULL
z$fixed <- formula(paste(m$Names$Yname[1],"~1"))
z$random <- ~-1
z$mixture <- ~1
z$B <- c(m$best[1:sum(m$N[1:3])], rep(0,m$ng),1)
z$maxiter <- 0
z$verbose <- FALSE
z[[1]] <- as.name("Jointlcmm")
mjoint <- eval(z, envir=parent.frame())
mjoint_perm <- permut(mjoint, order=order, estim=FALSE)
bperm <- mjoint_perm$best[1:sum(m$N[1:3])]
}
else
{
## permuter les coef de classmb
z <- call("hlme", subject=m$call$subject, data=m$call$data, ng=m$call$ng,
fixed=formula(paste(m$Names$Yname[1], "~1")), random=~-1, mixture=~1,
B=c(m$best[1:m$N[1]], rep(0,m$ng),1), maxiter=0, verbose=FALSE)
if(length(m$call$classmb)) z$classmb <- m$call$classmb
mclass <- eval(z, envir=parent.frame())
mclass_perm <- permut(mclass, order=order, estim=FALSE)
bperm <- mclass_perm$best[1:m$N[1]]
}
## permuter les modeles longitudinaux
#mlong <- eval(m$call$longitudinal, envir=parent.frame())
avt <- sum(m$N[1:3])
for(k in 1:m$K)
{
z <- m$longicall[[k]] #mlong[[k]]$call
z$B <- c(rep(0,m$ng-1), m$best[avt+1:m$npmK[k]])
z$maxiter <- 0
z$posfix <- NULL
z$verbose <- FALSE
mk <- eval(z, envir=parent.frame())
mk_perm <- permut(mk, order=order, estim=FALSE)
bperm <- c(bperm, mk_perm$best[-c(1:(m$ng-1))])
avt <- avt + m$npmK[k]
}
## modele permute
if(estim==TRUE)
{
z <- m$call
z$B <- bperm
mnew <- eval(z, envir=parent.frame())
}
else
{
mnew <- m
mnew$best <- bperm
}
return(mnew)
}
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