Using R for Data Analysis and Graphics英文版

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Using R for Data Analysis and Graphics英文版
目录
1. Starting Up ........................................................................................................................................................3
1.1 Getting started under Windows.................................................................................................................3
1.2 Use of an Editor Script Window................................................................................................................4
1.3 A Short R Session .....................................................................................................................................5
1.3.1 Entry of Data at the Command Line...................................................................................................6
1.3.2 Entry and/or editing of data in an editor window...................................................................................6
1.3.3 Options for read.table() ..........................................................................................................................6
1.3.4 Options for plot() and allied functions ...................................................................................................7
1.4 Further Notational Details.......................................................................................................................7
1.5 On-line Help.............................................................................................................................................7
1.6 The Loading or Attaching of Datasets......................................................................................................7
1.7 Exercises ..................................................................................................................................................8
2. An Overview of R..............................................................................................................................................9
2.1 The Uses of R ................................................................................................................................................9
2.1.1 R may be used as a calculator. ...............................................................................................................9
2.1.2 R will provide numerical or graphical summaries of data .....................................................................9
2.1.3 R has extensive graphical abilities .......................................................................................................10
2.1.4 R will handle a variety of specific analyses .........................................................................................10
2.1.5 R is an Interactive Programming Language.........................................................................................11
2.2 R Objects.....................................................................................................................................................11
*2.3 Looping .....................................................................................................................................................12
2.3.1 More on looping...................................................................................................................................12
2.4 Vectors ........................................................................................................................................................12
2.4.1 Joining (concatenating) vectors............................................................................................................13
2.4.2 Subsets of Vectors................................................................................................................................13
2.4.3 The Use of NA in Vector Subscripts....................................................................................................13
2.4.4 Factors..................................................................................................................................................14
2.5 Data Frames ...............................................................................................................................................15
2.5.1 Data frames as lists ..............................................................................................................................15
2.5.2 Inclusion of character string vectors in data frames.............................................................................15
2.5.3 Built-in data sets ..................................................................................................................................15
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2.6 Common Useful Functions..........................................................................................................................16
2.6.1 Applying a function to all columns of a data frame.............................................................................16
2.7 Making Tables.............................................................................................................................................17
2.7.1 Numbers of NAs in subgroups of the data ...........................................................................................17
2.8 The Search List ...........................................................................................................................................17
2.9 Functions in R.............................................................................................................................................18
2.9.1 An Approximate Miles to Kilometers Conversion...............................................................................18
2.9.2 A Plotting function...............................................................................................................................18
2.10 More Detailed Information .......................................................................................................................19
2.11 Exercises ...................................................................................................................................................19
3. Plotting.............................................................................................................................................................21
3.1 plot () and allied functions ..........................................................................................................................21
3.1.1 Plot methods for other classes of object...............................................................................................21
3.2 Fine control – Parameter settings...............................................................................................................21
3.2.1 Multiple plots on the one page .............................................................................................................22
3.2.2 The shape of the graph sheet................................................................................................................22
3.3 Adding points, lines and text .......................................................................................................................22
3.3.1 Size, colour and choice of plotting symbol ..........................................................................................23
3.3.2 Adding Text in the Margin...................................................................................................................24
3.4 Identification and Location on the Figure Region ......................................................................................24
3.4.1 identify() ..............................................................................................................................................24
3.4.2 locator()................................................................................................................................................25
3.5 Plots that show the distribution of data values ...........................................................................................25
3.5.1 Histograms and density plots ...............................................................................................................25
3.5.3 Boxplots ...............................................................................................................................................26
3.5.4 Normal probability plots ......................................................................................................................26
3.6 Other Useful Plotting Functions .................................................................................................................27
3.6.1 Scatterplot smoothing ..........................................................................................................................27
3.6.2 Adding lines to plots ............................................................................................................................28
3.6.3 Rugplots ...............................................................................................................................................28
3.6.4 Scatterplot matrices..............................................................................................................................28
3.6.5 Dotcharts ..............................................................................................................................................28
3.7 Plotting Mathematical Symbols ..................................................................................................................29
3.8 Guidelines for Graphs.................................................................................................................................29
3.9 Exercises .....................................................................................................................................................29
3.10 References.................................................................................................................................................30
4. Lattice graphics...............................................................................................................................................31
4.1 Examples that Present Panels of Scatterplots – Using xyplot() ...........................................................31
4.2 Some further examples of lattice plots ........................................................................................................32
4.2.1 Plotting columns in parallel .................................................................................................................32
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4.2.2 Fixed, sliced and free scales.................................................................................................................33
4.3 An incomplete list of lattice Functions........................................................................................................33
4.4 Exercises .....................................................................................................................................................33
5. Linear (Multiple Regression) Models and Analysis of Variance ................................................................35
5.1 The Model Formula in Straight Line Regression........................................................................................35
5.2 Regression Objects......................................................................................................................................35
5.3 Model Formulae, and the X Matrix.............................................................................................................36
5.3.1 Model Formulae in General .................................................................................................................37
*5.3.2 Manipulating Model Formulae ..........................................................................................................38
5.4 Multiple Linear Regression Models ............................................................................................................38
5.4.1 The data frame Rubber.........................................................................................................................38
5.4.2 Weights of Books.................................................................................................................................40
5.5 Polynomial and Spline Regression..............................................................................................................41
5.5.1 Polynomial Terms in Linear Models....................................................................................................41
5.5.2 What order of polynomial? ..................................................................................................................42
5.5.3 Pointwise confidence bounds for the fitted curve ................................................................................43
5.5.4 Spline Terms in Linear Models............................................................................................................43
5.6 Using Factors in R Models .........................................................................................................................43
5.6.1 The Model Matrix ................................................................................................................................44
*5.6.2 Other Choices of Contrasts ................................................................................................................45
5.7 Multiple Lines – Different Regression Lines for Different Species .............................................................46
5.8 aov models (Analysis of Variance)..............................................................................................................47
5.8.1 Plant Growth Example .........................................................................................................................47
*5.8.2 Shading of Kiwifruit Vines ................................................................................................................48
5.9 Exercises .....................................................................................................................................................49
5.10 References.................................................................................................................................................50
6. Multivariate and Tree-based Methods..........................................................................................................51
6.1 Multivariate EDA, and Principal Components Analysis.............................................................................51
6.2 Cluster Analysis ..........................................................................................................................................52
6.3 Discriminant Analysis.................................................................................................................................52
6.4 Decision Tree models (Tree-based models) ................................................................................................53
6.5 Exercises .....................................................................................................................................................54
6.6 References...................................................................................................................................................54
*7. R Data Structures .........................................................................................................................................55
7.1 Vectors ........................................................................................................................................................55
7.1.1 Subsets of Vectors................................................................................................................................55
7.1.2 Patterned Data......................................................................................................................................55
7.2 Missing Values ............................................................................................................................................55
7.3 Data frames.................................................................................................................................................56
7.3.1 Extraction of Component Parts of Data frames....................................................................................56
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7.3.2 Data Sets that Accompany R Packages................................................................................................56
7.4 Data Entry Issues........................................................................................................................................57
7.4.1 Idiosyncrasies.......................................................................................................................................57
7.4.2 Missing values when using read.table()................................................................................57
7.4.3 Separators when using read.table()............................................................................................57
7.5 Factors and Ordered Factors .....................................................................................................................57
7.6 Ordered Factors..........................................................................................................................................58
7.7 Lists.............................................................................................................................................................59
*7.8 Matrices and Arrays..................................................................................................................................59
7.8.1 Arrays...................................................................................................................................................60
7.8.2 Conversion of Numeric Data frames into Matrices..............................................................................61
7.9 Exercises .....................................................................................................................................................61
8. Functions..........................................................................................................................................................62
8.1 Functions for Confidence Intervals and Tests.............................................................................................62
8.1.1 The t-test and associated confidence interval.......................................................................................62
8.1.2 Chi-Square tests for two-way tables.....................................................................................................62
8.2 Matching and Ordering ..............................................................................................................................62
8.3 String Functions..........................................................................................................................................62
*8.3.1 Operations with Vectors of Text Strings – A Further Example .........................................................62
8.4 Application of a Function to the Columns of an Array or Data Frame ......................................................63
8.4.1 apply() ..................................................................................................................................................63
8.4.2 sapply() ................................................................................................................................................63
*8.5 aggregate() and tapply() ...........................................................................................................................63
*8.6 Merging Data Frames...............................................................................................................................64
8.7 Dates ...........................................................................................................................................................64
8.8. Writing Functions and other Code.............................................................................................................65
8.8.1 Syntax and Semantics ..........................................................................................................................65
8.8.2 A Function that gives Data Frame Details ...........................................................................................66
8.8.3 Compare Working Directory Data Sets with a Reference Set..............................................................66
8.8.4 Issues for the Writing and Use of Functions ........................................................................................66
8.8.5 Functions as aids to Data Management................................................................................................67
8.8.6 Graphs ..................................................................................................................................................67
8.8.7 A Simulation Example .........................................................................................................................67
8.8.8 Poisson Random Numbers ...................................................................................................................68
8.9 Exercises .....................................................................................................................................................68
*9. GLM, and General Non-linear Models .......................................................................................................70
9.1 A Taxonomy of Extensions to the Linear Model .........................................................................................70
9.2 Logistic Regression.....................................................................................................................................71
9.2.1 Anesthetic Depth Example...................................................................................................................72
9.3 glm models (Generalized Linear Regression Modelling)............................................................................74
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9.3.2 Data in the form of counts....................................................................................................................74
9.3.3 The gaussian family .............................................................................................................................74
9.4 Models that Include Smooth Spline Terms..................................................................................................74
9.4.1 Dewpoint Data .....................................................................................................................................74
9.5 Survival Analysis.........................................................................................................................................74
9.6 Non-linear Models ......................................................................................................................................75
9.7 Model Summaries........................................................................................................................................75
9.8 Further Elaborations ..................................................................................................................................75
9.9 Exercises .....................................................................................................................................................75
9.10 References.................................................................................................................................................75
*10. Multi-level Models, Repeated Measures and Time Series .......................................................................76
10.1 Multi-Level Models, Including Repeated Measures Models .....................................................................76
10.1.1 The Kiwifruit Shading Data, Again ...................................................................................................76
10.1.2 The Tinting of Car Windows .............................................................................................................78
10.1.3 The Michelson Speed of Light Data .................................................................................................79
10.2 Time Series Models ...................................................................................................................................80
10.3 Exercises ...................................................................................................................................................80
10.4 References.................................................................................................................................................81
*11. Advanced Programming Topics ................................................................................................................82
11.1. Methods....................................................................................................................................................82
11.2 Extracting Arguments to Functions ..........................................................................................................82
11.3 Parsing and Evaluation of Expressions ....................................................................................................83
11.4 Plotting a mathematical expression ..........................................................................................................84
11.5 Searching R functions for a specified token. .............................................................................................85
12. Appendix 1.....................................................................................................................................................86
12.1 R Packages for Windows...........................................................................................................................86
12.2 Contributed Documents and Published Literature ...................................................................................86
12.3 Data Sets Referred to in these Notes.........................................................................................................86
12.4 Answers to Selected Exercises ..................................................................................................................87
Section 1.6 ....................................................................................................................................................87
Section 2.7 ....................................................................................................................................................87
Section 3.9 ....................................................................................................................................................87
Section 7.9 ....................................................................................................................................................87

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