First time posting here, so I apologize for any missing info upfront. I am working on a program in VBA that calculates a function (which itself calls another function), then calculates the derivative of that function, then uses that to form a Jacobian matrix to calculate the solution via the Newton-Raphson method. My question relates to taking the derivative of a function, $f$.

First, the function has the general form: $f(i, h, q_0, A, x, v(x, X_{min}))$. $i$ is a counter variable, and $h, q_0, A$ and $X_{min}$ are constant single value inputs. The remaining arguments are all members of the same array $x$ or another function $v(x, X_{min})$. The form of the function changes based on the value of $i$. The inputs from the array may be, depending on the value of $i$:

  1. $x_i$ and $x_{i+1}$
  2. $x_i$, $x_{i-1}$, $x_{i+1}$
  3. $x_{i}$ and $x_{i-1}$

The inputs from $v(x)$ may be, again depending on i:

  1. $v(x_i)$
  2. $v(x_{i-1})$ and $v(x_i)$
  3. $v(x_{i-1})$

Here is an example of the function in question: $$f = \frac{1}{h}\bigg[\frac{q_0}{A} * (x_{i + 1} - x_i) + v(x_{i - 1}, X_{min}) * x_{i - 1} - v(x_i, X_{min}) * x_i)\bigg]$$

I am using this form of the finite difference method: $$f′(x) = \frac{−f(x+ 2∆x) + 8f(x+ ∆x) −8f(x−∆x) + f(x−2∆x)}{12\Delta x}$$

My question is, for each time I use this function, do I need to apply the $∆x$ to each instance of the array element passed to the function? Ie, for the case where $x_i$ and $x_{i+1}$ are called, do I need to add or subtract $∆x$ to both $x_i$ and $x_{i+1}$? This would give $x_i$ $+/-$ $1$ or $2∆x$, as well as $x_{i+1}$ $+/-$ $1$ or $2∆x$. Or, according to this method, is it better to calculate the finite difference around $x_i$ only?

And further, for the case where both $v(x_{i-1})$ and $v(x_i)$ are passed to the function $f$, would adding and subtracting $∆x$ to each instance of the $x$ array passed into the $v$ function be required? While I'm at it (and I hope this is overkill), would I also need to calculate the finite difference centered around the values returned by $v(x)$ as well?

Alternatively, is there simply a better way to determine the derivative of this function than the way I'm going about it? I hope I have provided enough info. I didn't include the code, as I think that is a separate question, to be explored once I have an answer to this question.

Thank you!!

  • $\begingroup$ I edited part of your question to use mathjax formatting for the equations. Let me know if I messed anything up and see if you can extend this to the rest of your question $\endgroup$
    – Tyberius
    Jul 20, 2021 at 18:42
  • $\begingroup$ Thank you, I will return to this later today and try to format the rest in mathjax as you suggested. $\endgroup$ Jul 20, 2021 at 19:01

1 Answer 1


With $f(x, y(x))$ while one could technically split up $\frac{\partial f}{\partial y}$ and $\frac{\partial y}{\partial x}$, it isn't necessary. You can just directly perturb both $x$'s at the same time to get the total derivative on $f$ w.r.t. $x$. But, in your equations, $f$ does not actually take $v$ as an input. It might call $v$ with different inputs (the same way it calls $-$, $v$ isn't special). So, it really is just $f(x)$ here.

When it comes to perturbing vector inputs like $x$, you will need to do it one component at the time, meaning you will have to call $f$ many times here. Each perturb $x_i$ gives you one column of your Jacobian. If you happen to know that a certain $x_j$ isn't going to affect $f_i(x)$ at all, you can of course skip all those computations and just fill in the 0 in your jacobian.

There are many issues with numerical derivatives, accuracy, computational time, etc. I would consider a different method if possible. Analytical derivation, automatic differentiation, or switch to a completely different method, like Nelder-Mead or something.

  • $\begingroup$ Ok thank you for your suggestion! I will look into automatic differentiation and see what I can learn about it and how to apply it here. Thanks! $\endgroup$ Jul 22, 2021 at 16:09

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