R语言编程基础教程

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"A.First.Course.in.Statistical.Programming.with.R" 是一本专注于R语言编程的入门教程，适合统计学学习者。由R语言的核心开发者之一和资深R语言作者合著，书中提供了符合R语言标准的真实代码示例。本书旨在帮助读者掌握R语言编程，不仅介绍基础，还强调编程原理，这些原则适用于大多数计算机语言。它探讨了用于开发更复杂项目的技术，使得学习语言的过程更加系统化。每章内的频繁练习有助于读者逐步自信地提升技能，而章节末尾的更深层次练习则用来检验读者的理解程度。所有解决方案、数据集以及任何错误修正都可以在书的官方网站上找到。作者W. John Braun是加拿大韦仕敦大学统计与精算科学系的副教授，他还与John Maindonald共同撰写了另一本名为"Data Analysis and Graphics Using R"的书籍。在这本"A First Course in Statistical Programming with R"中，读者将学习到： 1. **R语言基础**：如何安装和配置R环境，理解R的基本语法，包括变量、数据类型和控制结构。 2. **数据操作**：学习读取和写入数据，数据清洗，以及使用R中的向量、矩阵、列表和数据框进行数据操作。 3. **函数与包的使用**：了解如何创建自定义函数，以及利用R庞大的开源包生态系统进行数据分析。 4. **统计分析**：涵盖基本统计概念，如描述性统计、概率分布、假设检验和置信区间。 5. **绘图与可视化**：使用R的图形设备和ggplot2包创建有效的统计图表。 6. **编程原则**：深入理解面向对象编程、调试和测试，以及代码优化技巧。 7. **项目管理**：学习版本控制（如Git）和项目组织，提高工作效率。 8. **应用案例**：通过实际案例来应用所学知识，解决统计问题。这本书对于希望将R语言作为统计分析工具的初学者来说是一份宝贵的资源，它不仅教授R语言的基础，还注重培养读者的编程思维和解决问题的能力。通过阅读和实践书中的内容，读者将能够熟练地使用R语言进行统计编程。

4 GETTING STARTED

1.5 Font conventions

This book describes how to do computations in R. As we will see in the

next chapter, this requires that the user types input, and R responds with

text or graphs as output. To indicate the difference, we have typeset the user

input in a slanted typewriter font, and text output in an upright version of

the same font. For example,

> This was typed by the user

This is a response from R

In most cases other than this one and certain exercises, we will show the

actual response from R.

We have used the Sweave package

so that R itself is computing the output.

The computations in the text were done

with a pre-release version of R 2.5.0.

There are also situations where the code is purely illustrative and is not

meant to be executed. (Many of those are not correct R code at all; others

illustrate the syntax of R code in a general way.) In these situations we have

typeset the code examples in an upright typewriter font. For example,

f( some arguments )

1.6 Installation of R

R can be downloaded from http://cran.r-project.org!. Most

users should download and install a binary version. This is a version that

has been translated (by compilers) into machine language for execution

on a particular type of computer with a particular operating system. R is

designed to be very portable: it will run on Microsoft Windows, Linux,

Solaris, Mac OSX, and other operating systems, but different binary ver-

sions are required for each. In this book most of what we do would be the

same on any system, but when we write system-speciﬁc instructions, we

will assume that readers are using Microsoft Windows.

Installation on Microsoft Windows is straightforward. A binary

version is available for Windows 98 or above from the web page

http://cran.r-project.org/bin/windows/base.

Download the “setup program,” a ﬁle with a name like

R-2.5.1-

win32.exe

. Clicking on this ﬁle will start an almost automatic installa-

tion of the R system. Though it is possible to customize the installation, the

default responses will lead to a satisfactory installation in most situations,

particularly for beginning users.

One of the default settings of the installation procedure is to create an

R icon on your computer’s desktop.

Once you have installed R, you will be ready to start statistical

programming. Let’s learn how.

6 INTRODUCTION TO THE R LANGUAGE

The ﬁrst line starts with the ﬁrst return value, so is labeled [1]; the second

line starts with the 13th, so is labeled

[13].

The position of the line break shown

here depends on the optional setting

options(width=40). Other choices

of line widths would break in different

places.

Anything that can be computed on a pocket calculator can be computed

at the R prompt. Here are some additional examples:

> # "*" is the symbol for multiplication.

> # Everything following a # sign is assumed to be a

> # comment and is ignored by R.

>3*5

[1] 15

>3-8

[1] -5

>12/4

[1] 3

To quit your R session, type

> q()

If you then hit the Enter key, you will be asked whether to save an

image of the current workspace, or not, or to cancel. The workspace image

contains a record of the computations you’ve done, and may contain some

saved results. Hitting the Cancel option allows you to continue your current

R session. We rarely save the current workspace image, but occasionally

ﬁnd it convenient to do so.

Note what happens if you omit the parentheses

() when attempting to

quit:

function (save = "default", status = 0, runLast = TRUE)

.Internal(quit(save, status, runLast))

<environment: namespace:base>

This has happened because q is a function that is used to tell R to

quit. Typing

q by itself tells R to show us the (not very pleasant-looking)

contents of the function

q. By typing q(), we are telling R to call the

function

q. The action of this function is to quit R. Everything that R

does is done through calls to functions, though sometimes those calls are

hidden (as when we click on menus), or very basic (as when we call the

multiplication function to multiply 3 times 5).

2.1.1 Recording your work

Rather than saving the workspace, we prefer to keep a record of the com-

mands we entered, so that we can reproduce the workspace at a later date.

In Windows, the easiest way to do this is to enter commands in R’s script

editor, available from the

File menu. Commands are executed by high-

lighting them and hitting

Ctrl-R (which stands for “run”). At the end of

a session, save the ﬁnal script for a permanent record of your work. In

other systems a text editor and some form of cut and paste serve the same

purpose.

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