Not quite because the x_i on the right-hand side also depend on a_j
On Thursday, September 8, 2016, Tim Wheeler <[email protected]>
wrote:
> Isn't the gradient of x_j with respect to a_j just Sum_{j=1}^n (x_i)^b?
>
> On Thursday, September 8, 2016 at 1:08:51 PM UTC-7, Mathieu
> Taschereau-Dumouchel wrote:
>>
>> Hello everyone!
>>
>> I have the following system of n equations
>>
>> x_j= a_j * Sum_{j=1}^n (x_i)^b
>>
>> where 0<b<1 is known. Given a set of a_j, I can solve for the vector x by
>> iterating on the equation. But I would like to know the gradient of the
>> each x_j with respect to a_j. I am wondering if I could use ForwardDiff.jl
>> or another Julia package in some way to do this. Any help would be
>> appreciated.
>>
>> Many thanks!
>>
>
