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Authors: John C. Nash, Ravi Varadhan
Title: [download]
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Unifying Optimization Algorithms to Aid Software System Users: optimx for R
Reference: Vol. 43, Issue 9, Aug 2011
Submitted 2010-08-12, Accepted 2011-08-05
Type: Article
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.

Paper: [download]
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Unifying Optimization Algorithms to Aid Software System Users: optimx for R
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Supplements: [download]
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optimx_2011-8.1.tar.gz: R source package
(application/x-gzip, 26.7 KB)
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v43i09.R: R example code from the paper
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Resources: BibTeX | OAI
Creative Commons License
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)
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