If I understand correctly, you are asking how solve.QP interprets the arguments. I clarified this by constructing a problem I could work manually but that was sophisticated enough to seemingly answer your question: minimize (x1^2+x2^2) subject to (x1+x2)=1. I computed manually that the answer should be x1=x2=0.5. (I used Lagrange multipliers, because that's the first thing that entered my head. However, I also could have substituted (1-x1) for x2 or used the "solver" in MS Excel.) After reading the documentation and trying something that gave an error message, I got the following: > (QP1 <- solve.QP(Dmat=diag(2), dvec=rep(0,2), + Amat=matrix(rep(1,2), c(2,1)), bvec=1, meq=1)) $solution [1] 0.5 0.5 $value [1] 0.25 $unconstrainted.solution [1] 0 0 $iterations [1] 2 0 $iact [1] 1 If this does not answer your question, have you studied the example with "?solve.QP"? If this is still not adequate, PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html and submit another post; I believe that people who follow that guide generally get more useful replies quicker. hope this helps. spencer graves
Serguei Kaniovski wrote:
I'm having difficulty figuring out how to implement the following set of constraints in Quadprog: 1). x1+x2+x3+x4=a1 2). x1+x2+x5+x6=a2 3). x1+x3+x5+x7=a3 4). x1+x2=b1 5). x1+x3=b2 6). x1+x5=b3 for the problem: MIN (x1-c1)2+(x2-c2)2+...+(x8-c8)2. As far a I understand, "solve.QP(Dmat, dvec, Amat, bvec, meq=0, factorized=FALSE)" reads contraints using an element-by-element multiplication, i.e. Amat'*x, not using the matrix-product, i.e. Amat'%*%x, required for the sums on the left-hand-side of 1-6). I would very much appreciate a suggestion on this problem. Thank you, Serguei Kaniovski
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