# Find argmin of function with unique vector

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DM on 23 Jun 2019
Commented: DM on 26 Jun 2019
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!
Kaustav Bhattacharya on 25 Jun 2019
If you know n can you not use
x0 = ones(1,n)*0.0001
and then
x = fminsearch(fun,x0) ?

Matt J on 25 Jun 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,
f= @(theta) [theta,1-theta];
objective = @(theta)sum((f(theta)-y)./f(theta));
x = fminsearch(objective,0.0001);
DM on 26 Jun 2019
That's what I needed, thank you!!

infinity on 25 Jun 2019
Edited: infinity on 25 Jun 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 CommentsShowHide 1 older comment
infinity on 25 Jun 2019
Yes, it is an idea how to solve problem with mutil-dimensiona. You may adapt the code for your case.