http://www.itl.nist.gov/div898/strd/nls/nls_info.shtml presents a number of nonlinear
regression (nonlinear least squares) problems that are more or less difficult to solve
numerically. Doug Bates prepared an R package
NISTnls which adapted these problems
to R and tested them with the
nls() function of which he was a major author.
I built a related package to allow the same problems to be approached as unconstrained function
minimization problems, which I named
NISTopt. However, this package was, when I prepared
it in 2009, incomplete, particularly in respect to the manuals (Rd files). This vignette
is an attempt to better document that effort and in the process force a review of the
Note that the problems here are NOT good illustrations of tasks to which the various function minimization (also called "optimization", though that generally implies that there are also constraints) tools should be applied. However, they do suggest limits of performance of these tools.
?? We need to be able to set things up so that a separate command is not needed for each start or example. Need to think about this. Also the "setup" approach doesn't seem too helpful.
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