Book Image

Simulation for Data Science with R

By : Matthias Templ
Book Image

Simulation for Data Science with R

By: Matthias Templ

Overview of this book

Data Science with R aims to teach you how to begin performing data science tasks by taking advantage of Rs powerful ecosystem of packages. R being the most widely used programming language when used with data science can be a powerful combination to solve complexities involved with varied data sets in the real world. The book will provide a computational and methodological framework for statistical simulation to the users. Through this book, you will get in grips with the software environment R. After getting to know the background of popular methods in the area of computational statistics, you will see some applications in R to better understand the methods as well as gaining experience of working with real-world data and real-world problems. This book helps uncover the large-scale patterns in complex systems where interdependencies and variation are critical. An effective simulation is driven by data generating processes that accurately reflect real physical populations. You will learn how to plan and structure a simulation project to aid in the decision-making process as well as the presentation of results. By the end of this book, you reader will get in touch with the software environment R. After getting background on popular methods in the area, you will see applications in R to better understand the methods as well as to gain experience when working on real-world data and real-world problems.
Table of Contents (18 chapters)
Simulation for Data Science with R
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface
Index

The R statistical environment


R was founded by Ross Ihaka and Robert Gentlemen in 1994/1995. It is based on S, a programming language developed by John Chambers (Bell Laboratories), and Scheme. Since 1997, it has been internationally developed and distributed from Vienna over the Comprehensive R Archive Network (CRAN). R is nowadays the most popular and most used software in the statistical world. In addition, R is free and open source (under the GPL2). R is not only a statistical software, it is an environment for interactive computing with data supporting facilities to produce high-quality graphics. The exchange of code with others is easy since everybody can download R. This might also be one reason why modern methods are often exclusively developed in R. R is an object-oriented programming language and has interfaces to many other software products such as C, C++, Java, and interfaces to databases.

Useful information can be found on the following links.

  • Homepage: http://www.r-project...