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An Introduction to R Notes on R A Programming Environment for Data Analysis and Graphics Version 2 2 0 2005 10 06 W N Venables D M Smith and the R Development Core Team Copyright c 1990 W N Venables Copyright c 1992 W N Venables D M Smith Copyright c 1997 R Gentleman R Ihaka Copyright c 1997 1998 M Maechler Copyright c 1999 2005 R Development Core Team Permission is granted to make and distribute verbatim copies of this manual provided the copy right notice and this permission notice are preserved on all copies Permission is granted to copy and distribute modi ed versions of this manual under the condi tions for verbatim copying provided that the entire resulting derived work is distributed under the terms of a permission notice identical to this one Permission is granted to copy and distribute translations of this manual into another language under the above conditions for modi ed versions except that this permission notice may be stated in a translation approved by the R Development Core Team ISBN 3 900051 12 7 i Table of Contents Preface 1 1 Introduction and preliminaries 2 1 1 The R environment 2 1 2 Related software and documentation 2 1 3 R and statistics 2 1 4 R and the window system 3 1 5 Using R interactively 3 1 6 An introductory session 4 1 7 Getting help with functions and features 4 1 8 R commands case sensitivity etc 4 1 9 Recall and correction of previous commands 5 1 10 Executing commands from or diverting output to a le 5 1 11 Data permanency and removing objects 5 2 Simple manipulations numbers and vectors 7 2 1 Vectors and assignment 7 2 2 Vector arithmetic 7 2 3 Generating regular sequences 8 2 4 Logical vectors 9 2 5 Missing values 9 2 6 Character vectors 10 2 7 Index vectors selecting and modifying subsets of a data set 10 2 8 Other types of objects 11 3 Objects their modes and attributes 13 3 1 Intrinsic attributes mode and length 13 3 2 Changing the length of an object 14 3 3 Getting and setting attributes 14 3 4 The class of an object 14 4 Ordered and unordered factors 16 4 1 A speci c example 16 4 2 The function tapply and ragged arrays 16 4 3 Ordered factors 17 5 Arrays and matrices 18 5 1 Arrays 18 5 2 Array indexing Subsections of an array 18 5 3 Index matrices 19 5 4 The array function 20 5 4 1 Mixed vector and array arithmetic The recycling rule 20 5 5 The outer product of two arrays 21 5 6 Generalized transpose of an array 21 5 7 Matrix facilities 22 5 7 1 Matrix multiplication 22 ii 5 7 2 Linear equations and inversion 22 5 7 3 Eigenvalues and eigenvectors 23 5 7 4 Singular value decomposition and determinants 23 5 7 5 Least squares tting and the QR decomposition 23 5 8 Forming partitioned matrices cbind and rbind 24 5 9 The concatenation function c with arrays 24 5 10 Frequency tables from factors 25 6 Lists and data frames 26 6 1 Lists 26 6 2 Constructing and modifying lists 26 6 2 1 Concatenating lists 27 6 3 Data frames 27 6 3 1 Making data frames 27 6 3 2 attach and detach 27 6 3 3 Working with data frames 28 6 3 4 Attaching arbitrary lists 28 6 3 5 Managing the search path 29 7 Reading data from les 30 7 1 The read table function 30 7 2 The scan function 31 7 3 Accessing builtin datasets 31 7 3 1 Loading data from other R packages 31 7 4 Editing data 32 8 Probability distributions 33 8 1 R as a set of statistical tables 33 8 2 Examining the distribution of a set of data 33 8 3 One and two sample tests 36 9 Grouping loops and conditional execution 40 9 1 Grouped expressions 40 9 2 Control statements 40 9 2 1 Conditional execution if statements 40 9 2 2 Repetitive execution for loops repeat and while 40 10 Writing your own functions 42 10 1 Simple examples 42 10 2 De ning new binary operators 43 10 3 Named arguments and defaults 43 10 4 The argument 44 10 5 Assignments within functions 44 10 6 More advanced examples 44 10 6 1 E ciency factors in block designs 44 10 6 2 Dropping all names in a printed array 45 10 6 3 Recursive numerical integration 45 10 7 Scope 46 10 8 Customizing the environment 48 10 9 Classes generic functions and object orientation 48 iii 11 Statistical models in R 50 11 1 De ning statistical models formulae 50 11 1 1 Contrasts 52 11 2 Linear models 53 11 3 Generic functions for extracting model information 53 11 4 Analysis of variance and model comparison 54 11 4 1 ANOVA tables 54 11 5 Updating tted models 54 11 6 Generalized linear models 55 11 6 1 Families 55 11 6 2 The glm function 56 11 7 Nonlinear least squares and maximum likelihood models 58 11 7 1 Least squares 58 11 7 2 Maximum likelihood 59 11 8 Some non standard models 60 12 Graphical procedures 61 12 1 High level plotting commands 61 12 1 1 The plot function 61 12 1 2 Displaying multivariate data 62 12 1 3 Display graphics 62 12 1 4 Arguments to high level plotting functions 63 12 2 Low level plotting commands 64 12 2 1 Mathematical annotation 65 12 2 2 Hershey vector fonts 65 12 3 Interacting with graphics 65 12 4 Using graphics parameters 66 12 4 1 Permanent changes The par function 66 12 4 2 Temporary changes Arguments to graphics functions 67 12 5 Graphics parameters list 67 12 5 1 Graphical elements 68 12 5 2 Axes and tick marks 68 12 5 3 Figure margins 69 12 5 4 Multiple gure environment 70 12 6 Device drivers 71 12 6 1 PostScript diagrams for typeset documents 72 12 6 2 Multiple graphics devices 72 12 7 Dynamic graphics 73 13 Packages 74 13 1 Standard packages 74 13 2 Contributed packages and CRAN 74 13 3 Namespaces 74 Appendix A A sample session 76 Appendix B Invoking R 79 Invoking R from the command line 79 Invoking R under Windows 82 Invoking R under Mac OS X 82 B 1 B 2 B 3 iv Appendix C The command line editor 84 C 1 Preliminaries 84 C 2 Editing actions 84 C 3 Command line editor summary 84 Appendix D Function and variable index 86 Appendix E Concept index 89 Appendix F References 91 Preface Preface 1 This introduction to R is derived from an original set of notes describing the S and S Plus environments written by Bill Venables and David M Smith Insightful Corporation We have made a number of small changes to re ect di erences between the R and S programs and expanded some of the …


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UCLA STATS 13 - An Introduction to R

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