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Numerical Optimization in R: Beyond optim

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  • Varadhan, Ravi

Abstract

Numerical optimization is often an essential aspect of mathematical analysis in science, technology and other areas. The function optim() provides basic optimization capabilities and is among the most widely used functions in R . Additionally, there are various packages and functions for solving various types of optimization problem (the optimization task view on Comprehensive R Archive Network provides a comprehensive list of available options for solving optimization problems in R). In this special volume, four papers are presented which discuss some of the areas in numerical optimization where significant developments have been made recently to enhance the capabilities in R . This introduction provides a brief overview of the volume.

Suggested Citation

  • Varadhan, Ravi, 2014. "Numerical Optimization in R: Beyond optim," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 60(i01).
    • Handle: RePEc:jss:jstsof:v:060:i01
    DOI: http://hdl.handle.net/10.18637/jss.v060.i01
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    References listed on IDEAS

    as
    1. Nash, John C., 2014. "On Best Practice Optimization Methods in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 60(i02).
    2. Birgin, Ernesto G. & Martínez, Jose Mario & Raydan, Marcos, 2014. "Spectral Projected Gradient Methods: Review and Perspectives," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 60(i03).
    3. Varadhan, Ravi & Gilbert, Paul, 2009. "BB: An R Package for Solving a Large System of Nonlinear Equations and for Optimizing a High-Dimensional Nonlinear Objective Function," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 32(i04).
    4. Nash, John C. & Varadhan, Ravi, 2011. "Unifying Optimization Algorithms to Aid Software System Users: optimx for R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 43(i09).
    5. Braun, Michael, 2014. "trustOptim: An R Package for Trust Region Optimization with Sparse Hessians," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 60(i04).
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