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Mar 19 at 21:30 history edited YCor CC BY-SA 4.0
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Jul 13, 2019 at 11:05 answer added Daisuke K timeline score: 5
Jul 25, 2017 at 9:28 answer added F. Jatpil timeline score: 2
Mar 10, 2017 at 4:00 answer added Zurab Silagadze timeline score: 5
Mar 10, 2017 at 3:47 comment added Geoffrey Irving It's worth noting that the complex step derivative is just a thinly disguised version of automatic differentiation. It works because real analytic functions have their derivatives baked into their complex implementations.
Nov 15, 2016 at 0:36 answer added Chris Rackauckas timeline score: 10
May 12, 2011 at 4:33 vote accept Yrogirg
May 8, 2011 at 18:03 comment added J. M. isn't a mathematician BTW... I trust that you only want first derivatives? The higher the derivative order, the less likely any of the proposed methods become successful...
May 8, 2011 at 17:07 comment added J. M. isn't a mathematician @Gilead: The only reason why I linked to it in the comments instead of my answer is that even though I know it's good, I haven't extensively experimented with it.
May 8, 2011 at 16:24 comment added Gilead Ok, I see that J.M. has linked to this method (due to Squire and Trapp) in one of the references.
May 8, 2011 at 16:23 comment added Gilead J.M. has already supplied some excellent ways of performing numerical differentiation, including methods like Cauchy's formula. There is a simple method that I use that gets me first derivatives at near machine precision levels. It is the complex step derivative: $f'(x) = \mathrm{Im}(\frac{x + ih}{h})$, where $h$ can be chosen to be the machine epsilon (see citeseerx.ist.psu.edu/viewdoc/… for guidance). It is trivial to implement in any language with a complex number datatype (e.g. Fortran).
May 8, 2011 at 15:33 answer added J. M. isn't a mathematician timeline score: 18
May 8, 2011 at 14:28 history asked Yrogirg CC BY-SA 3.0