R in a Nutshell
Autor Joseph Adleren Limba Engleză Paperback – 13 noi 2012
Updated for R 2.14 and 2.15, this second edition includes new and expanded chapters on R performance, the ggplot2 data visualization package, and parallel R computing with Hadoop.
* Get started quickly with an R tutorial and hundreds of examples
* Explore R syntax, objects, and other language details
* Find thousands of user-contributed R packages online, including Bioconductor
* Learn how to use R to prepare data for analysis
* Visualize your data with R’s graphics, lattice, and ggplot2 packages
* Use R to calculate statistical fests, fit models, and compute probability distributions
* Speed up intensive computations by writing parallel R programs for Hadoop
* Get a complete desktop reference to R
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Specificații
ISBN-13: 9781449312084
ISBN-10: 144931208X
Pagini: 721
Ilustrații: Illustrations
Dimensiuni: 153 x 228 x 43 mm
Greutate: 1.06 kg
Ediția:2nd edition
Editura: O'Reilly
ISBN-10: 144931208X
Pagini: 721
Ilustrații: Illustrations
Dimensiuni: 153 x 228 x 43 mm
Greutate: 1.06 kg
Ediția:2nd edition
Editura: O'Reilly
Notă biografică
Joseph Adler has many years of experience in data mining and data analysis at companies including DoubleClick, American Express, and VeriSign. He graduated from MIT with an Sc.B and M.Eng in Computer Science and Electrical Engineering from MIT. He is the inventor of several patents for computer security and cryptography, and the author of Baseball Hacks. Currently, he is a senior data scientist at LinkedIn.
Cuprins
- Preface
- R Basics
- Chapter 1: Getting and Installing R
- Chapter 2: The R User Interface
- Chapter 3: A Short R Tutorial
- Chapter 4: R Packages
- The R Language
- Chapter 5: An Overview of the R Language
- Chapter 6: R Syntax
- Chapter 7: R Objects
- Chapter 8: Symbols and Environments
- Chapter 9: Functions
- Chapter 10: Object-Oriented Programming
- Working with Data
- Chapter 11: Saving, Loading, and Editing Data
- Chapter 12: Preparing Data
- Data Visualization
- Chapter 13: Graphics
- Chapter 14: Lattice Graphics
- Chapter 15: ggplot2
- Statistics with R
- Chapter 16: Analyzing Data
- Chapter 17: Probability Distributions
- Chapter 18: Statistical Tests
- Chapter 19: Power Tests
- Chapter 20: Regression Models
- Chapter 21: Classification Models
- Chapter 22: Machine Learning
- Chapter 23: Time Series Analysis
- Additional Topics
- Chapter 24: Optimizing R Programs
- Chapter 25: Bioconductor
- Chapter 26: R and Hadoop
- R Reference
- Bibliography
- Colophon
Descriere
R is rapidly becoming the standard for developing statistical software, and R in a Nutshell provides a quick and practical way to learn this increasingly popular open source language and environment.