Look at nlminb() or optim(), in particular the option `method = L-BFGS-B' or
the function spg() in BB package.
With these you can optimize over any number of variables.
Ravi.
Ravi Varadhan, Ph.D.
Assistant Professor,
Division of Geriatric Medicine and Gerontology
School of Medicine
Johns Hopkins University
Ph. (410) 502-2619
email: rvarad...@jhmi.edu
- Original Message -
From: Esmail esmail...@gmail.com
Date: Saturday, May 23, 2009 10:01 am
Subject: [R] optimizing function over x,y
To: R mailing list r-help@r-project.org
Hello all,
I would like to maximize or minimize a given math function over a
specific set of values.
I was checking out Wolfram Alpha (
and it can do simple optimization problems in math, such as
maximize 15*x - x**2 over 0 to 15
(
which finds the maximum value and input for x in the range 0 to 15.
Very cool. (This is of course a very simple example).
Reading the R documentation I found out that with R I can do this:
f-function(x) (15*x)-x**2
optimize(f, c(0,15), lower=0,upper=15, maximum=TRUE)
which works very nicely too!
What I would like to do, but what Wolfram Alpha apparently can't do
(according to a post in their community forum) is to maximize (or
minimize) functions that contain two variables, x and y, or more. So
for example a very simple example would be
minimize x**2 + y**2 over x:0 to 15, y:0-12 -- this does not work
-- though I'm
unclear about
-- the correct
syntax too.
Is there a way to do this in R in just a neat and easy way as R
optimizes a 1-D function?
For this particular instance I am interested in the minimum of
x * sin(4*x) + 1.1 * sin(2*y), where x,y in range 0-10
so an example of this in R would be great, though in other problems
the range may not be identical for x and y.
Thanks,
Esmail
ps: Has anyone written any programs in Python that they then have used
to call R functions? I am thinking of writing some of my scripts
in
Python, but then accessing some of R's functions.
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