Having given a lecture on "Numerical Derivatives" just a short time ago, I would like to mention the following:
Many functions, especially in engineering, are not available as formulas built simply from arithmetical operators and elementary functions. They are provided as intricate procedures, as results from simulation runs, or as return values from optimization routines. In all these cases, symbolic differentiation is not a possibility at all. Still, for further processing there will be a need to differentiate these functions. As I understand the literature, Automated Differentiations (AD) is mostly meant for these kinds of applications(*). Another push for AD came from increased interest in the "complex-step derivative approximation" where first an analytic continuation -- often nontrivial -- has to be established, before the derivation can be computed. It may be different in statistical tasks. But a general automated differentiation in R may have to take these kinds of applications into account. Regards Hans Werner (*) See the "Community Portal for AD" <www.autodiff.org> and the definition of automated differentiation there as an example. nashjc wrote: > > [...] > > The clear issue in my mind is that users who need gradients/Jacobians > for R want to be able to send a function X to some process that will > return another function gradX or JacX that computes analytic > derivatives. This has to be "easy", which implies a very simple command > or GUI interface. I am pretty certain the users have almost no interest > in the mechanism, as long as it works. Currently, most use numerical > derivatives, not realizing the very large time penalty and quite large > loss in accuracy that can compromise some optimization and differential > equation codes. I'll try to prepare a few examples to illustrate this > and post them somewhere in the next few weeks. Time, as always, ... > > However, the topic does appear to be on the table. > > JN > -- View this message in context: http://www.nabble.com/Automatic-differentiation-in-R-tp24602805p24634481.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.