Andreas Jensen bentrevisor at gmail.com writes:
Hello.
I'm trying to solve a quadratic programming problem of the form min
||Hx - y||^2 s.t. x = 0 and x = t using solve.QP in the quadprog
package but I'm having problems with Dmat not being positive definite,
which is kinda okay since I expect it to be numerically semi-definite
in most cases. As far as I'm aware the problem arises because the
Goldfarb and Idnani method first solves the unconstrained problem
requiring a positive definite matrix. Are there any (fast) packages
that allows me to do QP with (large) semidefinite matrices?
Example:
t - 100
y - signalConvNoisy[1,]
D - crossprod(H,H)
d - crossprod(H,y)
A - cbind(rep(-1, nrow(H)), diag(ncol(H)))
b0 - c(t, rep(0, ncol(H)))
sol - solve.QP(Dmat=D, dvec = d, Amat = A, bvec = b0)$solution
Error in solve.QP(Dmat = D, dvec = d, Amat = A, bvec = b0) :
matrix D in quadratic function is not positive definite!
Thanks in advance,
Andreas Jensen
See the Optimization task view, there are several packages that promise to
handle quadratic programming problems. You may also try one of the nonlinear
optimization packages, they are not much slower nowadays.
Your code cannot be executed as signalConvNoisy is unknown.
Hans Werner
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