> On 29 Aug 2015, at 20:53, Berend Hasselman <b...@xs4all.nl> wrote:
>
>
>> On 29 Aug 2015, at 18:29, Ravi Varadhan <ravi.varad...@jhu.edu> wrote:
>>
>> In solve.QP(), you don't need to expand the equality into two inequalities.
>> It can DIRECTLY handle the equality constraints. The first `meq' rows of
>> the constraint matrix are equality constraints. Here is the excerpt from
>> the documentation.
>>
>> meq
>> the first meq constraints are treated as equality constraints, all further
>> as inequality constraints (defaults to 0).
>>
>>
>> Therefore, solve.QP() can provide the full functionality of lsqlin in
>> Matlab. However, one caveat is that the bounds constraints have to be
>> implemented via inequalities in solve.QP(), which is a slight pain, but not
>> a deal breaker.
>>
>
> It would be helpful if you could show us how to use solve.QP() in this case.
> I’ve been trying with no success.
>
> B
I’ll answer my comment.
# Example from Matlab for lsqlin
C <- matrix(c(
0.9501, 0.7620, 0.6153, 0.4057,
0.2311, 0.4564, 0.7919, 0.9354,
0.6068, 0.0185, 0.9218, 0.9169,
0.4859, 0.8214, 0.7382, 0.4102,
0.8912, 0.4447, 0.1762, 0.8936), 5, 4, byrow=TRUE)
d <- c(0.0578, 0.3528, 0.8131, 0.0098, 0.1388)
A <- matrix(c(
0.2027, 0.2721, 0.7467, 0.4659,
0.1987, 0.1988, 0.4450, 0.4186,
0.6037, 0.0152, 0.9318, 0.8462), 3, 4, byrow=TRUE)
b <- c(0.5251, 0.2026, 0.6721)
Dmat <- t(C) %*% C
dvec <- (t(C) %*% d)
Aeq <- c(3, 5, 7, 9)
beq <- 4
lb <- rep(-0.1, 4) # lower and upper bounds
ub <- rep( 2.0, 4)
Amat <- rbind(Aeq,-A,diag(4),-diag(4))
bvec <- c(beq,-b,lb,-ub)
rslt <- solve.QP(Dmat, dvec, t(Amat), bvec, meq=1)
rslt$solution
sum(Aeq * rslt$solution) - beq
sum((C %*% rslt$solution - d)^2)
What a fiddle.
Berend
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