US EPA

3241858 

Journal Article 

Unifying Optimization Algorithms to Aid Software System Users: optimx for R 

Nash, JC; Varadhan, R 

2011 

Yes 

Journal of Statistical Software
ISSN: 1548-7660 

43 

9 

1-14 

WOS:000294231700001 

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. 

minimization; maximization; wrapper; R; scaling; Newton; gradient