adding overall constraint in optim()
This looks like what I call a sumscale problem i.e., some sort of simple function of the parameters sums to a constant. I've done some work on these, but don't have it with me just now. There are several approaches, but they can be quite tricky. Will send some info in about a week or so if you are still stuck and contact me offline. JN (you'll see my name on 3/5 of optim routines via ?optim)
On 2018-05-03 01:52 PM, Michael Ashton wrote:
Hi ?
This is giving me a headache. I?m trying to do a relatively simple optimization ? actually trying to approximate the output from the Excel Solver function but at roughly 1000x the speed. ?
The optimization parameters look like this. The only trouble is that I want to add a constraint that sum(wgt.vect)=1, and I can?t figure out how to do that in optim.
Mo.vect <- as.vector(tail(head(mo,i),1))
wgt.vect <- as.vector(tail(head(moWeightsMax,i),1))
cov.mat <- cov(tail(head(morets,i+12),12))
opt.fun <- function(wgt.vect) -sum(Mo.vect %*% wgt.vect) / (t(wgt.vect) %*% (cov.mat %*% wgt.vect))
LowerBounds<-c(0.2,0.05,0.1,0,0,0)
UpperBounds<-c(0.6,0.3,0.6,0.15,0.1,0.2)
OptimSolution<-optim(wgt.vect, fn=opt.fun, method="L-BFGS-B",lower=LowerBounds,upper=UpperBounds)
Any thoughts are appreciated!
Mike
Michael Ashton, CFA
Managing Principal
Enduring Investments LLC
W: 973.457.4602
C: 551.655.8006
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