Find argmin of function with unique vector
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Hi,
I want to solve the next problem:
For example, for
and 
I tried to do some things like:
x=[theta,1-theta];
x0 =[0.0001,0.0001];
fun = @(x)sum((x-y)./x);
x = fminsearch(fun,x0);
Any idea how to minimize vector with respect to this scalar?
I know I can just write it like that:
x0 =[0.0001,0.0001];
fun = @(x) (x-y(1))/x + ((1-x)-y(2))/x
x = fminsearch(fun,x0);
But there are more dimensions (then 2) in the original problem so it is impractical to do so.
Thanks!
3 commentaires
Kaustav Bhattacharya
le 25 Juin 2019
If you know n can you not use
x0 = ones(1,n)*0.0001
and then
x = fminsearch(fun,x0) ?
Réponse acceptée
Matt J
le 25 Juin 2019
You need to write code that generates
in vectorized form. Then the rest is easy. The correct way to code your original example is,
in vectorized form. Then the rest is easy. The correct way to code your original example is,f= @(theta) [theta,1-theta];
objective = @(theta)sum((f(theta)-y)./f(theta));
x = fminsearch(objective,0.0001);
Plus de réponses (1)
infinity
le 25 Juin 2019
Modifié(e) : infinity
le 25 Juin 2019
Hello,
Here is an example that you can refer
I find mininum of function
, the initial guess is given by
. The code could be like that
clear
N = 5;
fun = @(t) norm(t,2);
x0 = 1+zeros(1,N);
x = fminsearch(fun,x0)
where I choose N = 5, but it can be changed.
2 commentaires
infinity
le 25 Juin 2019
Yes, it is an idea how to solve problem with mutil-dimensiona. You may adapt the code for your case.
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