Hello, and apologies for the upcoming naive questions. I am a biologist who is
trying to teach himself the appropriate areas of math and stats. I welcome
pointers to suggested background reading just as much as I do direct answers to
my question.
Let's say I have a function F() that takes
If 'F' is twice differentiable, this could be done fairly easily
by writing 'F' as a function to be maximized with a1 = a + da, etc., and
using the 'activePars' argument in maxNR{maxLik} to specify the
constraints you want.
More specifically, consider the following:
Fmax -
Here is an example w/optim where you have an objective function
F(x) where you have (possibly a few) constraints of form x_i=x_j, and you
can specify the constraints flexibly, which is what I _think_ you want.
An example from you would have been nice.
## objective function that depends on all
the example I just mailed had an error; it should have been:
## objective function that depends on all parameters, here a, b, c
obfun - function(a,b,c,dd)
sum((dd - (exp(a * 1:100) + exp(b * 1:50) + exp(c * 1:25) ))^2)
fr - function(x, eqspec, dd, obfun) {
## assign variables for parameter
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