Trying to use constrOptim to minimize the sum of squared deviations. I put
the objective function in as: sum((x %*% Y - Z)^2) so i'm trying to get
values for x to minimize the sum of the squared deviations between the
product of x and Y and Z.
Anyways i have no problem using this when x is a 3x1 test variable. it
works great with the constraints and everything. when i actually use it on
my data x is 3x900 or so and it wont optimize it just gives me back my
initial guess....this is the output i'm getting:
$value
[1] 22.7438
$counts
function gradient
906 NA
$convergence
[1] 1
$message
NULL
$outer.iterations
[1] 1
$barrier.value
[1] 1.381551e-06
this is definitely not the right answer and it is just spitting back my
initial guess back.
Any ideas? are there limits as to how big the variables can be for this
function?
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