Maindonald, Using R(1).pdf

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Using R for Data Analysis and Graphics
Introduction, Code and Commentary
J H Maindonald
Centre for Bioinformation Science,
Australian National University.
©J. H. Maindonald 2000, 2004. A licence is granted for personal study and classroom use.
Redistribution in any other form is prohibited.
Languages shape the way we think, and determine what we can think about (
Benjamin Whorf.).
10 October 2004
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C a m ba r v ille
B e llbir d
W h ia n W h ia n
B y r a n ge r y
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65
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C o n o n da le
A lly n R iv e r
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B ulbur in
f e m a le
m a le
t a il
le n gt h
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fo o t
le n gt h
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ear co n ch
le n gt h
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Lindenmayer, D. B., Viggers, K. L., Cunningham, R. B., and Donnelly, C. F. : Morphological
variation among populations of the mountain brushtail possum, trichosurus
caninus
Ogibly
(Phalangeridae:Marsupialia). Australian Journal of Zoology 43: 449-459, 1995.
possum
n.
1
Any of many chiefly herbivorous, long-tailed, tree-dwelling, mainly Australian marsupials,
some of which are gliding animals (e.g.
brush-tailed possum, flying possum).
2
a mildly scornful term
for a person.
3
an affectionate
mode of address.
From the Australian Oxford Paperback Dictionary, 2
nd
ed, 1996.
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TABLE OF CONTENTS
Introduction............................................................................................................................................................ 1
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
1.4 Further Notational Details........................................................................................................................... 7
1.5 On-line Help................................................................................................................................................. 7
1.6 The Loading or Attaching of Datasets..........................................................................................................7
1.7 Exercise.........................................................................................................................................................8
2. An Overview of R............................................................................................................................................... 9
2.1 The Uses of R................................................................................................................................................. 9
2.2 R Objects......................................................................................................................................................11
*2.3 Looping...................................................................................................................................................... 12
2.4 Vectors......................................................................................................................................................... 12
2.5 Data Frames................................................................................................................................................ 15
2.6 Common Useful Functions...........................................................................................................................16
2.7 Making Tables..............................................................................................................................................17
2.8 The Search List............................................................................................................................................ 18
2.9 Functions in R..............................................................................................................................................18
2.10 More Detailed Information........................................................................................................................20
2.11 Exercises.................................................................................................................................................... 20
3. Plotting.............................................................................................................................................................. 21
3.1 plot () and allied functions...........................................................................................................................21
3.2 Fine control – Parameter settings............................................................................................................... 21
3.3 Adding points, lines and text........................................................................................................................22
3.4 Identification and Location on the Figure Region...................................................................................... 25
3.5 Plots that show the distribution of data values............................................................................................25
3.6 Other Useful Plotting Functions..................................................................................................................29
3.7 Plotting Mathematical Symbols .................................................................................................................. 30
3.8 Guidelines for Graphs................................................................................................................................. 31
3.9 Exercises...................................................................................................................................................... 31
3.10 References.................................................................................................................................................. 32
4. Lattice graphics................................................................................................................................................ 33
4.1 Examples that Present Panels of Scatterplots – Using xyplot().................................................................. 33
4.3 Exercises...................................................................................................................................................... 35
5. Linear (Multiple Regression) Models and Analysis of Variance................................................................. 37
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5.1 The Model Formula in Straight Line Regression........................................................................................ 37
5.2 Regression Objects.......................................................................................................................................38
5.3 Model Formulae, and the X Matrix............................................................................................................. 38
5.4 Multiple Linear Regression Models.............................................................................................................40
5.5 Polynomial and Spline Regression.............................................................................................................. 43
5.6 Using Factors in R Models.......................................................................................................................... 46
5.7 Multiple Lines – Different Regression Lines for Different Species.............................................................49
5.8 aov models (Analysis of Variance).............................................................................................................. 50
5.9 Exercises...................................................................................................................................................... 52
5.10 References.................................................................................................................................................. 53
6. Multivariate and Tree-Based Methods.......................................................................................................... 55
6.1 Multivariate EDA, and Principal Components Analysis............................................................................. 55
6.2 Cluster Analysis........................................................................................................................................... 56
6.3 Discriminant Analysis..................................................................................................................................56
6.4 Decision Tree models (Tree-based models).................................................................................................58
6.5 Exercises...................................................................................................................................................... 58
6.6 References.................................................................................................................................................... 58
*7. R Data Structures...........................................................................................................................................59
7.1 Vectors......................................................................................................................................................... 59
7.2 Missing Values............................................................................................................................................. 59
7.3 Data frames..................................................................................................................................................60
7.4 Data Entry....................................................................................................................................................61
7.5 Factors and Ordered Factors...................................................................................................................... 62
7.6 Ordered Factors...........................................................................................................................................63
7.7 Lists.............................................................................................................................................................. 64
*7.8 Matrices and Arrays.................................................................................................................................. 65
7.9 Exercises...................................................................................................................................................... 66
8. Useful Functions............................................................................................................................................... 68
8.1 Confidence Intervals and Tests....................................................................................................................68
8.2 Matching and Ordering............................................................................................................................... 68
8.3 String Functions...........................................................................................................................................68
8.4 Application of a Function to the Columns of an Array or Data Frame ..................................................... 69
*8.5 aggregate() and tapply()............................................................................................................................ 69
*8.7 Merging Data Frames................................................................................................................................70
8.8 Dates............................................................................................................................................................ 70
8.9 Exercises...................................................................................................................................................... 71
9. Writing Functions and other Code................................................................................................................. 72
9.1 Syntax and Semantics...................................................................................................................................72
9.2 Issues for the Writing and Use of Functions............................................................................................... 73
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9.3 Functions as aids to Data Management...................................................................................................... 73
9.4 A Simulation Example..................................................................................................................................74
9.5 Exercises...................................................................................................................................................... 75
*10. GLM, and General Non-linear Models...................................................................................................... 78
10.1 A Taxonomy of Extensions to the Linear Model........................................................................................78
10.2 Logistic Regression....................................................................................................................................79
10.3 glm models (Generalized Linear Regression Modelling).......................................................................... 82
10.4 Models that Include Smooth Spline Terms................................................................................................ 83
10.5 Survival Analysis........................................................................................................................................83
10.6 Non-linear Models..................................................................................................................................... 83
10.7 Model Summaries...................................................................................................................................... 83
10.8 Further Elaborations................................................................................................................................. 83
10.9 Exercises.................................................................................................................................................... 84
10.10 References................................................................................................................................................ 84
*11. Multi-level Models, Repeated Measures and Time Series........................................................................ 86
11.1 Multi-Level Models, Including Repeated Measures Models..................................................................... 86
11.2 Time Series Models.................................................................................................................................... 90
11.3 Exercises.................................................................................................................................................... 91
11.4 References.................................................................................................................................................. 91
*12. Advanced Programming Topics..................................................................................................................92
12.1. Methods.....................................................................................................................................................92
12.2 Extracting Arguments to Functions .......................................................................................................... 92
12.3 Parsing and Evaluation of Expressions.....................................................................................................93
12.4 Plotting a mathematical expression...........................................................................................................94
12.4 Searching R functions for a specified token.............................................................................................. 95
13. R Resources ....................................................................................................................................................96
13.1 R Packages for Windows............................................................................................................................96
13.2 Literature written by expert users.............................................................................................................. 96
13.3 The R-help electronic mail discussion list................................................................................................. 97
13.4 Competing Systems – XLISP-STAT........................................................................................................... 97
14. Appendix 1...................................................................................................................................................... 98
14.1 Data Sets Referred to in these Notes......................................................................................................... 98
14.2 Answers to Selected Exercises................................................................................................................... 98
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