R for Programmers

Advanced Techniques

Dan Zhang

• Publisher: CRC Press
• Year: 2017
• eBook ISBN: 9781315352541
• Edition: 1
• Topic: Mathematics
• Subtopic: Information Technology
• Index: Mathematics

This book discusses advanced topics such as R core programing, object oriented R programing, parallel computing with R, and spatial data types. The author leads readers to merge mature and effective methdologies in traditional programing to R programing. It shows how to interface R with C, Java, and other popular programing laguages and platforms.

I

Applying R in Mathematic Calculations and Algorithms

Chapter 1

The Knowledge System and Mathematical Functions of R

This opening chapter of the book mainly introduces the knowledge system and learning materials of R. The mathematical and statistical calculations and visualization of continuous distribution functions were implemented using R in this chapter, which help readers fully understand the R language and quickly handle calculating problems in basic disciplines.

1.1Overview of the Knowledge System of R

Question

How do we learn the R language efficiently?

Introduction

Recently, I met a lot of programmers who want to move to data analytics and begin to learn the R language. Having mastered programming other languages, they tend to consider learning R a simple thing. They always pursue learning speed but never understand it deeply. Some even say it only takes two weeks to master R. However, what they mastered is just the syntax of R—a beginning actually.

The knowledge system of R is not as simple as its syntax. If one does not understand the whole picture of R, how could one master the language? This section will show you the knowledge system of R and tell readers how to master it efficiently.

1.1.1The Knowledge System of R

R is a statistical language, mainly used in aspects including mathematical modeling, statistical computing, data processing, and data visualization. The R language is inherently different from other programming languages. It encapsulates the calculating functions of various basic disciplines. By calling these functions during programming, we can build complex mathematical models orienting to various domains and business. Mastering the syntax of R is just the beginning of learning R. To master it completely, you need to combine the capabilities of basic disciplines (elementary mathematics, advanced mathematics, linear algebra, discrete mathematics, probability theory, and statistics), the knowledge of specific industrials (finance, biology, and Internet), and IT technique (R syntax, R packages, database, and algorithms). In a long-term perspective way, you are capable of mastering the R language completely only if you enhance your level of comprehensive knowledge. In other words, once you have mastered the R language, you are irreplaceable.

1.1.1.1Overview of the Knowledge System of R

The knowledge system of R is complex. You must integrate the knowledge from multiple disciplines in order to master it completely. The most difficult thing is not in the language itself, but the user’s knowledge basics and the capability of using knowledge comprehensively.

First of all, let us take an overall look at the knowledge system as shown in Figure 1.1. Then, I will demonstrate the details of every part.

Figure 1.1 The knowledge system of R.

In Figure 1.1, I divided R’s knowledge system into three parts: IT technique, business knowledge, and capabilities in basic disciplines. This is ju...

Table of contents

• Cover
• Half Title
• Title Page
• Copyright Page
• Dedication
• Contents
• Preface
• Acknowledgments
• About the Author
• About the Translator
• Translator’s Words
• Section I: Applying R in Mathematic Calculations and Algorithms
• Section II: R Programming in Depth
• Section III: Developing R Package
• Bibliography
• Index