Tutorial: Optimization and related nonlinear modelling computations in R

John C. Nash, Tefler School of Management, University of Ottawa (retired), Canada


We will present an overview of the tools in R for optimization and related tasks. Discussion will be by examples, and participants or others are welcome to send problems in advance for possible inclusion in the discussion.

There are many uses of optimization in statistics, especially in model fitting. However, numerical optimization of nonlinear functions, particularly with constraints, is a rich and intricate subject where statisticians are rarely experts. The tutorial will attempt to give R users a handle on the available packages and functions for solving optimization problems in R.


Largely using the optimx package (from the Optimization and solving packages project) that allows a number of the existing optimization tools to be accessed via a common front-end, we will discuss via examples: Example issues that may be addressed to provide participants with an informed view of the optimization landscape are:

Intended audience

R users doing various forms of modelling and estimation who want to know how to appropriately choose and use the available optimization tools and where to find help and advice.


The presenter is the author of Compact Numerical Methods for Computers, Taylor and Francis, 1990. Three algorithms from this book are part of the now-aging optim function in R. He has been recently working (with Ravi Varadhan, Kate Mullen and others) on improved tools and guidance for optimization in R, implementations of which can be found in the Optimization and solving packages project.

Tutorial Materials

Slides are here.