Description |
1 online resource (xxiii, 373 pages) : illustrations |
Contents |
Brief Contents; Contents in Detail; Acknowledgments; Introduction; Why Use R for Your Statistical Work?; Whom Is This Book For?; My Own Background; 1: Getting Started; 1.1 How to Run R; 1.2 A First R Session; 1.3 Introduction to Functions; 1.4 Preview of Some Important R Data Structures; 1.5 Extended Example: Regression Analysis of Exam Grades; 1.6 Startup and Shutdown; 1.7 Getting Help; 2: Vectors; 2.1 Scalars, Vectors, Arrays, and Matrices; 2.2 Declarations; 2.3 Recycling; 2.4 Common Vector Operations; 2.5 Using all() and any(); 2.6 Vectorized Operations; 2.7 NA and NULL Values |
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2.8 Filtering2.9 A Vectorized if-then-else: The ifelse() Function; 2.10 Testing Vector Equality; 2.11 Vector Element Names; 2.12 More on c(); 3: Matrices and Arrays; 3.1 Creating Matrices; 3.2 General Matrix Operations; 3.3 Applying Functions to Matrix Rows and Columns; 3.4 Adding and Deleting Matrix Rows and Columns; 3.5 More on the Vector/Matrix Distinction; 3.6 Avoiding Unintended Dimension Reduction; 3.7 Naming Matrix Rows and Columns; 3.8 Higher-Dimensional Arrays; 4: Lists; 4.1 Creating Lists; 4.2 General List Operations; 4.3 Accessing List Components and Values |
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4.4 Applying Functions to Lists4.5 Recursive Lists; 5: Data Frames; 5.1 Creating Data Frames; 5.2 Other Matrix-Like Operations; 5.3 Merging Data Frames; 5.4 Applying Functions to Data Frames; 6: Factors and Tables; 6.1 Factors and Levels; 6.2 Common Functions Used with Factors; 6.3 Working with Tables; 6.4 Other Factor- and Table-Related Functions; 7: R Programming Structures; 7.1 Control Statements; 7.2 Arithmetic and Boolean Operators and Values; 7.3 Default Values for Arguments; 7.4 Return Values; 7.5 Functions Are Objects; 7.6 Environment and Scope Issues; 7.7 No Pointers in R |
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7.8 Writing Upstairs7.9 Recursion; 7.10 Replacement Functions; 7.11 Tools for Composing Function Code; 7.12 Writing Your Own Binary Operations; 7.13 Anonymous Functions; 8: Doing Math and Simulations in R; 8.1 Math Functions; 8.2 Functions for Statistical Distributions; 8.3 Sorting; 8.4 Linear Algebra Operations on Vectors and Matrices; 8.5 Set Operations; 8.6 Simulation Programming in R; 9: Object-Oriented Programming; 9.1 S3 Classes; 9.2 S4 Classes; 9.3 S3 Versus S4; 9.4 Managing Your Objects; 10: Input/Output; 10.1 Accessing the Keyboard and Monitor; 10.2 Reading and Writing Files |
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10.3 Accessing the Internet11: String Manipulation; 11.1 An Overview of String-Manipulation Functions; 11.2 Regular Expressions; 11.3 Use of String Utilities in the edtdbg Debugging Tool; 12: Graphics; 12.1 Creating Graphs; 12.2 Customizing Graphs; 12.3 Saving Graphs to Files; 12.4 Creating Three-Dimensional Plots; 13: Debugging; 13.1 Fundamental Principles of Debugging; 13.2 Why Use a Debugging Tool?; 13.3 Using R Debugging Facilities; 13.4 Moving Up in the World: More Convenient DebuggingTools; 13.5 Ensuring Consistency in Debugging Simulation Code; 13.6 Syntax and Runtime Errors |
Summary |
A guide to software development using the R programming language covers such topics as closures, recursion, anonymous functions, and debugging techniques |
Notes |
English |
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Print version record |
Subject |
R (Computer program language)
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Statistics -- Data processing.
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MATHEMATICS -- Probability & Statistics -- General.
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R (Computer program language)
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Statistics -- Data processing
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r
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Statistik
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Pubbz R.
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Statistik -- databehandling.
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Matematisk statistik.
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Statistics -- Data processing.
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R (Computer language)
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Form |
Electronic book
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LC no. |
2011025598 |
ISBN |
9781593274108 |
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1593274106 |
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9781593273842 |
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1593273843 |
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