[R] regression constraints (again)

[Brett Robinson]

Im trying to do regressions with constraints that the weights 
are all >=0 and sum(weights) = 1. I've read the archive and have 
set the problem up with solve.QP and just the non-negativity constraints

along the lines of:

y as the data vector 
X as the design matrix 

D <- t(X) %*% X 
d <- t(t(y) %*% X) 
A <- diag(ncol(X)) 
b <- rep(0,ncol(X)) 
fit <- solve.QP(D=D,d=d,A=t(A),b=b,meq=0) 

(as per Gardar Johannesson '01) 

When I try to add the extra constraint that sum(weights)=1 I get errors 
owing to incompatibility of matrices. I add the constraint by putting an

extra column of all ones to A and setting meq=1.

I can work round it I think, by using an intercept and using the extra 
column on the matrix for the sum(weights) constraint but I think that it

should be possible without doing this.

Grateful for any pointers as to where I am going wrong.

Brett Robinson