"getTheta" <- function(mod) {
modelspec <- mod@modelspec
modellist <- mod@modellist
datasetind <- mod@datasetind
th <- vector()
parorder <- list()
for (i in 1:length(modelspec)) {
ds <- which(datasetind == i)
model <- modellist[[ds[1]]]
fixed <- model@fvecind
prel <- model@pvecind
mrel <- model@mvecind
ppars <- append(model@parnames, "prel")
for (p in ppars) {
if (length(slot(modelspec[[datasetind[i]]], p)) != 0) {
removepar <- sort(unique(c(fixed[[p]], prel[[p]])))
rmpar <- sort(unique(c(fixed[[p]], prel[[p]], mrel[[p]])))
parapp <- unlist(slot(model, p))
if (length(model@clinde[[p]]) > 0) {
for (j in 1:length(model@clinde[[p]])) {
ind <- model@clinde[[p]][j]
parapp[ind] <- model@lowcon[[p]][j] - parapp[ind]
if (!p %in% model@positivepar) {
parapp[ind] <- log(parapp[ind])
}
}
}
if (length(model@chinde[[p]]) > 0) {
for (j in 1:length(model@chinde[[p]])) {
ind <- model@chinde[[p]][j]
parapp[ind] <- parapp[ind] + model@highcon[[p]][j]
if (!p %in% model@positivepar) {
parapp[ind] <- log(parapp[ind])
}
}
}
if (length(rmpar) != 0) {
parapp <- parapp[-rmpar]
}
if (length(parapp) != 0) {
ind <- (length(th) + 1):(length(th) + length(parapp))
} else {
ind <- vector()
}
parorder[[length(parorder) + 1]] <- list(
name = p, ind = ind,
dataset = ds, rm = rmpar
)
if (p %in% model@positivepar && length(parapp) != 0) {
parapp <- log(parapp)
}
th <- append(th, parapp)
}
}
}
mod@parorder <- processOrder(parorder, mod)
df <- getDiffTheta(th, mod)
if (mod@modellist[[1]]@lscalpar) {
thetascal <- abs(df$theta)
df$mod@modellist[[1]]@thetascal <- thetascal
df$theta <- df$theta / thetascal
}
list(theta = df$theta, mod = df$mod)
}
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