How to implement fminunc for a function with a variable lenght vector input?
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I need to use fminunc to minimize a function that has some inputs that are constants, one input that's a vector which increases in length in each iteration and another input which is also an optimization variable.
So my original function would be something like this:
[loglike] = hyp(V, x, const1, const2)
Where V is a vector of variables that grows in each iteration V = [v1 v2 v3 ... vN] (for example at the third iteration V = [V1 V2 V3]) and x is the other optimization variable.
Going through the documentation I've found that fminunc needs all the inputs to be in a vector, so it's necessary to create an anonymous function:
f = @(w)hyp([w1 w2 w3 ... wN], wN+1, const1, const2)
And then use the fminunc function:
[x fval] = fminunc(f,w0)
However, I can't find a way to make this work.
采纳的回答
Using vectorized commands, functions can be expressed in dimension-independent ways. For example, this function definition doesn't use any knowledge of length(unknowns):
function fval=hypothetical(unknowns)
x=unknowns(1);
V=unknowns(2:end);
fval=x.^3 +norm(V).^2;
end
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