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| Authors: | John C. Nash, Ravi Varadhan | ||||
| Title: | Unifying Optimization Algorithms to Aid Software System Users: optimx for R | ||||
| Abstract: | R users can often solve optimization tasks easily using the tools in the optim function in the stats package provided by default on R installations. However, there are many other optimization and nonlinear modelling tools in R or in easily installed add-on packages. These present users with a bewildering array of choices. optimx is a wrapper to consolidate many of these choices for the optimization of functions that are mostly smooth with parameters at most bounds-constrained. We attempt to provide some diagnostic information about the function, its scaling and parameter bounds, and the solution characteristics. optimx runs a battery of methods on a given problem, thus facilitating comparative studies of optimization algorithms for the problem at hand. optimx can also be a useful pedagogical tool for demonstrating the strengths and pitfalls of different classes of optimization approaches including Newton, gradient, and derivative-free methods. | ||||
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Page views:: 10529. Submitted: 2010-08-12. Published: 2011-08-24. |
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| Paper: |
Unifying Optimization Algorithms to Aid Software System Users: optimx for R
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| DOI: |
10.18637/jss.v043.i09
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This work is licensed under the licenses Paper: Creative Commons Attribution 3.0 Unported License Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license. |