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#### INTERNAL FUNCTION(S)
# LINK FUNCTIONS FOR CONSTRAINT OPTIMIZATION (internal)
#We use transLink for Rplus and unif parameters to provide starting parameter
#values that then constrain the parameter values optim generates to be within a
#more sensible range (i.e. mimicking boundary conditions). Otherwise the scale
#of the parameter is too large and optim generates unsuitable parameter
#estimates to test that can be negative etc. The transformed starting estimates
#are back-transformed within the model rss function anyway so it is the proper
#parameter estimates that are used to generate the rss.
transLink <- function(x,boundType) {
# fonction logit
logit <- function(y) {
log(y/(1-y))
}#end of logit
if (length(x) == 1) {
res <- switch(boundType,
R = x,
Rplus = log(x),
unif = logit(x)
)#end of switch
} else {
res <- vector(length = length(x))
for (i in seq_along(x)) {
res[i] <- switch(boundType[i],
R = x[i],
Rplus = log(x[i]),
unif = logit(x[i])
)#end of switch
}#end of for
res
}#end of if/else
}#end of transLink
##
backLink <- function(x,boundType) {
# fonction reciproque de la fonction logit
invlogit <- function(x) {
1/(1+exp(-x))
}#end of invlogit
if (length(x) ==1) {
res <- switch(boundType,
R = x,
Rplus = exp(x),
unif = invlogit(x)
)#end of switch
} else {
res <- vector(length = length(x))
for (i in seq_along(x)) {
res[i] <- switch(boundType[i],
R = x[i],
Rplus = exp(x[i]),
unif = invlogit(x[i])
)#end of switch
}#end of for
res
}#end of if/else
}#end of backLink
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