Dear All,
I wanted to post some more details about the query I sent to s-news last
week.
I have a vector with a constraint. The constraint is that the sum of the
vector must add up to 1 - but not necessarily positive, i.e.
x[n] <- 1 -(x[1] + ...+x[n-1])
I perform the optimisation on the vector x such that
x <- c(x, 1-sum(x))
In other words,
fn <- function(x){
x <- c(x, 1 - sum(x))
# other calculations here
}
then feed this into nlminb()
out <- nlminb(x, fn)
out.x <- out$parameters
out.x <- c(out.x, 1 - sum(out.x))
out.x
I would like to calculate standard errors for each of the components of x.
Is this possible by outputing the Hessian matrix? Furthermore, how would I
calculate this for the last component (if this is indeed possible) which has
the restriction (i.e. 1-sum(out.x))?
Any help would be much appreciated.
Regards,
John
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