Here is what you do for your problem:
require(BB)
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)
spgSolution <- spg(wgt.vect, fn=opt.fun, lower=LowerBounds,
upper=UpperBounds, project="projectLinear", projectArgs=list(A=matrix(1, 1,
length(wgt.vect)), b=1, meq=1)))
Ravi
________________________________
From: Ravi Varadhan
Sent: Saturday, May 5, 2018 12:31 PM
To: m.ash...@enduringinvestments.com; r-help@r-project.org
Subject: adding overall constraint in optim()
Hi,
You can use the projectLinear argument in BB::spg to optimize with linear
equality/inequality constraints.
Here is how you implement the constraint that all parameters sum to 1.
require(BB)
spg(par=p0, fn=myFn, project="projectLinear", projectArgs=list(A=matrix(1, 1,
length(p0)), b=1, meq=1))
Hope this is helpful,
Ravi
[[alternative HTML version deleted]]
______________________________________________
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
