Rの本(第3版)<br>The R Book(3)

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Rの本(第3版)
The R Book(3)

  • 言語:ENG
  • ISBN:9781119634324
  • eISBN:9781119634430

ファイル: /

Description

A start-to-finish guide to one of the most useful programming languages for researchers in a variety of fields

In the newly revised Third Edition of The R Book, a team of distinguished teachers and researchers delivers a user-friendly and comprehensive discussion of foundational and advanced topics in the R software language, which is used widely in science, engineering, medicine, economics, and other fields. The book is designed to be used as both a complete text—readable from cover to cover—and as a reference manual for practitioners seeking authoritative guidance on particular topics.

This latest edition offers instruction on the use of the RStudio GUI, an easy-to-use environment for those new to R. It provides readers with a complete walkthrough of the R language, beginning at a point that assumes no prior knowledge of R and very little previous knowledge of statistics. Readers will also find:

  • A thorough introduction to fundamental concepts in statistics and step-by-step roadmaps to their implementation in R;
  • Comprehensive explorations of worked examples in R;
  • A complementary companion website with downloadable datasets that are used in the book;
  • In-depth examination of essential R packages.

Perfect for undergraduate and postgraduate students of science, engineering, medicine economics, and geography, The R Book will also earn a place in the libraries of social sciences professionals.

Table of Contents

Preface

1 Getting started 1

2 Technical background 17

3 Essentials of the R language 55

4 Data input and dataframes 195

5 Graphics 235

6 Graphics in more detail 289

7 Tables 357

8 Probability distributions in R 369

9 Testing 401

10 Regression    433

11 Generalised Linear Models 495

12 Generalised Additive Models 575

13 Mixed-effect models 599

14 Non-linear regression 627

15 Survival analysis 651

16 Designed experiments 669

17 Meta-analysis 701

18 Time Series 717

19 Multivariate Statistics 743

20 Classification and regression trees 765

21 Spatial Statistics 785

22 Bayesian Statistics 807

23 Simulation models 833

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