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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

Summary

Hopefully, throughout this chapter, you learned a variety of methods and techniques to optimize a variety of functions. We covered how to use a wide range of R packages and functions to set up, solve, and visualize different optimization problems, so you should be ready to give your own minimization and maximization problems a try. Now that you are much more familiar with R and its packages for scientific computing, we are ready to move on to our last chapter, which will teach you to clean up and manage your data for efficient programming and analysis in R.

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