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Mastering Scientific Computing with R

You're reading from   Mastering Scientific Computing with R Employ professional quantitative methods to answer scientific questions with a powerful open source data analysis environment

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Product type Paperback
Published in Jan 2015
Publisher
ISBN-13 9781783555253
Length 432 pages
Edition 1st Edition
Languages
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Toc

Table of Contents (12) Chapters Close

Preface 1. Programming with R 2. Statistical Methods with R FREE CHAPTER 3. Linear Models 4. Nonlinear Methods 5. Linear Algebra 6. Principal Component Analysis and the Common Factor Model 7. Structural Equation Modeling and Confirmatory Factor Analysis 8. Simulations 9. Optimization 10. Advanced Data Management Index

Other optimization packages


There are a lot more packages available to solve optimization problems in R. Here is a short table summary of the packages or functions that will help you pick the best package and/or function for your optimization problem:

 

Linear Objective

Quadratic Objective

Non-linear Objective

Heuristic Approachs

No contraints, Box constraints

  

optim optimize nlminb

DEoptim rgenoud NMOF

Linear constraints

 

quadprog LowRankQP

constrOptim

 

Linear, integer constraints

Boot lpSolve lpSolveAPI linprog limSolve

   

Quadratic constraints

 

Rcplex Rmosek

  

Semi-definite

Rcsdp

   

Non-linear constraints

  

Rsolnp

 

Note

You can also go to http://cran.rproject.org/web/views/Optimization.html to visit the Optimization and Mathematical Programming web page for a more complete and up-to-date list of the packages available to solve optimization problems.

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