Table of contents for R cookbook / Paul Teetor.
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Preface; The Recipes; A Note on Terminology; Software and Platform Notes; Other Resources; Conventions Used in This Book; Using Code Examples; Safari® Books Online; How to Contact Us; Acknowledgments; Chapter 1: Getting Started and Getting Help; 1.1 Introduction; 1.2 Downloading and Installing R; 1.3 Starting R; 1.4 Entering Commands; 1.5 Exiting from R; 1.6 Interrupting R; 1.7 Viewing the Supplied Documentation; 1.8 Getting Help on a Function; 1.9 Searching the Supplied Documentation; 1.10 Getting Help on a Package; 1.11 Searching the Web for Help; 1.12 Finding Relevant Functions and Packages; 1.13 Searching the Mailing Lists; 1.14 Submitting Questions to the Mailing Lists; Chapter 2: Some Basics; 2.1 Introduction; 2.2 Printing Something; 2.3 Setting Variables; 2.4 Listing Variables; 2.5 Deleting Variables; 2.6 Creating a Vector; 2.7 Computing Basic Statistics; 2.8 Creating Sequences; 2.9 Comparing Vectors; 2.10 Selecting Vector Elements; 2.11 Performing Vector Arithmetic; 2.12 Getting Operator Precedence Right; 2.13 Defining a Function; 2.14 Typing Less and Accomplishing More; 2.15 Avoiding Some Common Mistakes; Chapter 3: Navigating the Software; 3.1 Introduction; 3.2 Getting and Setting the Working Directory; 3.3 Saving Your Workspace; 3.4 Viewing Your Command History; 3.5 Saving the Result of the Previous Command; 3.6 Displaying the Search Path; 3.7 Accessing the Functions in a Package; 3.8 Accessing Built-in Datasets; 3.9 Viewing the List of Installed Packages; 3.10 Installing Packages from CRAN; 3.11 Setting a Default CRAN Mirror; 3.12 Suppressing the Startup Message; 3.13 Running a Script; 3.14 Running a Batch Script; 3.15 Getting and Setting Environment Variables; 3.16 Locating the R Home Directory; 3.17 Customizing R; Chapter 4: Input and Output; 4.1 Introduction; 4.2 Entering Data from the Keyboard; 4.3 Printing Fewer Digits (or More Digits); 4.4 Redirecting Output to a File; 4.5 Listing Files; 4.6 Dealing with Cannot Open File” in Windows; 4.7 Reading Fixed-Width Records; 4.8 Reading Tabular Data Files; 4.9 Reading from CSV Files; 4.10 Writing to CSV Files; 4.11 Reading Tabular or CSV Data from the Web; 4.12 Reading Data from HTML Tables; 4.13 Reading Files with a Complex Structure; 4.14 Reading from MySQL Databases; 4.15 Saving and Transporting Objects; Chapter 5: Data Structures; 5.1 Introduction; 5.2 Appending Data to a Vector; 5.3 Inserting Data into a Vector; 5.4 Understanding the Recycling Rule; 5.5 Creating a Factor (Categorical Variable); 5.6 Combining Multiple Vectors into One Vector and a Factor; 5.7 Creating a List; 5.8 Selecting List Elements by Position; 5.9 Selecting List Elements by Name; 5.10 Building a Name/Value Association List; 5.11 Removing an Element from a List; 5.12 Flatten a List into a Vector; 5.13 Removing NULL Elements from a List; 5.14 Removing List Elements Using a Condition; 5.15 Initializing a Matrix; 5.16 Performing Matrix Operations; 5.17 Giving Descriptive Names to the Rows and Columns of a Matrix; 5.18 Selecting One Row or Column from a Matrix; 5.19 Initializing a Data Frame from Column Data; 5.20 Initializing a Data Frame from Row Data; 5.21 Appending Rows to a Data Frame; 5.22 Preallocating a Data Frame; 5.23 Selecting Data Frame Columns by Position; 5.24 Selecting Data Frame Columns by Name; 5.25 Selecting Rows and Columns More Easily; 5.26 Changing the Names of Data Frame Columns; 5.27 Editing a Data Frame; 5.28 Removing NAs from a Data Frame; 5.29 Excluding Columns by Name; 5.30 Combining Two Data Frames; 5.31 Merging Data Frames by Common Column; 5.32 Accessing Data Frame Contents More Easily; 5.33 Converting One Atomic Value into Another; 5.34 Converting One Structured Data Type into Another; Chapter 6: Data Transformations; 6.1 Introduction; 6.2 Splitting a Vector into Groups; 6.3 Applying a Function to Each List Element; 6.4 Applying a Function to Every Row; 6.5 Applying a Function to Every Column; 6.6 Applying a Function to Groups of Data; 6.7 Applying a Function to Groups of Rows; 6.8 Applying a Function to Parallel Vectors or Lists; Chapter 7: Strings and Dates; 7.1 Introduction; 7.2 Getting the Length of a String; 7.3 Concatenating Strings; 7.4 Extracting Substrings; 7.5 Splitting a String According to a Delimiter; 7.6 Replacing Substrings; 7.7 Seeing the Special Characters in a String; 7.8 Generating All Pairwise Combinations of Strings; 7.9 Getting the Current Date; 7.10 Converting a String into a Date; 7.11 Converting a Date into a String; 7.12 Converting Year, Month, and Day into a Date; 7.13 Getting the Julian Date; 7.14 Extracting the Parts of a Date; 7.15 Creating a Sequence of Dates; Chapter 8: Probability; 8.1 Introduction; 8.2 Counting the Number of Combinations; 8.3 Generating Commmmmmbinations; 8.4 Generating Random Numbers; 8.5 Generating Reproducible Random Numbers; 8.6 Generating a Random Sample; 8.7 Generating Random Sequences; 8.8 Randomly Permuting a Vector; 8.9 Calculating Probabilities for Discrete Distributions; 8.10 Calculating Probabilities for Continuous Distributions; 8.11 Converting Probabilities to Quantiles; 8.12 Plotting a Density Function; Chapter 9: General Statistics; 9.1 Introduction; 9.2 Summarizing Your Data; 9.3 Calculating Relative Frequencies; 9.4 Tabulating Factors and Creating Contingency Tables; 9.5 Testing Categorical Variables for Independence; 9.6 Calculating Quantiles (and Quartiles) of a Dataset; 9.7 Inverting a Quantile; 9.8 Converting Data to Z-Scores; 9.9 Testing the Mean of a Sample (t Test); 9.10 Forming a Confidence Interval for a Mean; 9.11 Forming a Confidence Interval for a Median; 9.12 Testing a Sample Proportion; 9.13 Forming a Confidence Interval for a Proportion; 9.14 Testing for Normality; 9.15 Testing for Runs; 9.16 Comparing the Means of Two Samples; 9.17 Comparing the Locations of Two Samples Nonparametrically; 9.18 Testing a Correlation for Significance; 9.19 Testing Groups for Equal Proportions; 9.20 Performing Pairwise Comparisons Between Group Means; 9.21 Testing Two Samples for the Same Distribution; Chapter 10: Graphics; 10.1 Introduction; 10.2 Creating a Scatter Plot; 10.3 Adding a Title and Labels; 10.4 Adding a Grid; 10.5 Creating a Scatter Plot of Multiple Groups; 10.6 Adding a Legend; 10.7 Plotting the Regression Line of a Scatter Plot; 10.8 Plotting All Variables Against All Other Variables; 10.9 Creating One Scatter Plot for Each Factor Level; 10.10 Creating a Bar Chart; 10.11 Adding Confidence Intervals to a Bar Chart; 10.12 Coloring a Bar Chart; 10.13 Plotting a Line from x and y Points; 10.14 Changing the Type, Width, or Color of a Line; 10.15 Plotting Multiple Datasets; 10.16 Adding Vertical or Horizontal Lines; 10.17 Creating a Box Plot; 10.18 Creating One Box Plot for Each Factor Level; 10.19 Creating a Histogram; 10.20 Adding a Density Estimate to a Histogram; 10.21 Creating a Discrete Histogram; 10.22 Creating a Normal Quantile-Quantile (Q-Q) Plot; 10.23 Creating Other Quantile-Quantile Plots; 10.24 Plotting a Variable in Multiple Colors; 10.25 Graphing a Function; 10.26 Pausing Between Plots; 10.27 Displaying Several Figures on One Page; 10.28 Opening Additional Graphics Windows; 10.29 Writing Your Plot to a File; 10.30 Changing Graphical Parameters; Chapter 11: Linear Regression and ANOVA; 11.1 Introduction; 11.2 Performing Simple Linear Regression; 11.3 Performing Multiple Linear Regression; 11.4 Getting Regression Statistics; 11.5 Understanding the Regression Summary; 11.6 Performing Linear Regression Without an Intercept; 11.7 Performing Linear Regression with Interaction Terms; 11.8 Selecting the Best Regression Variables; 11.9 Regressing on a Subset of Your Data; 11.10 Using an Expression Inside a Regression Formula; 11.11 Regressing on a Polynomial; 11.12 Regressing on Transformed Data; 11.13 Finding the Best Power Transformation (Box-Cox Procedure); 11.14 Forming Confidence Intervals for Regression Coefficients; 11.15 Plotting Regression Residuals; 11.16 Diagnosing a Linear Regression; 11.17 Identifying Influential Observations; 11.18 Testing Residuals for Autocorrelation (Durbin-Watson Test); 11.19 Predicting New Values; 11.20 Forming Prediction Intervals; 11.21 Performing One-Way ANOVA; 11.22 Creating an Interaction Plot; 11.23 Finding Differences Between Means of Groups; 11.24 Performing Robust ANOVA (Kruskal-Wallis Test); 11.25 Comparing Models by Using ANOVA; Chapter 12: Useful Tricks; 12.1 Introduction; 12.2 Peeking at Your Data; 12.3 Widen Your Output; 12.4 Printing the Result of an Assignment; 12.5 Summing Rows and Columns; 12.6 Printing Data in Columns; 12.7 Binning Your Data; 12.8 Finding the Position of a Particular Value; 12.9 Selecting Every nth Element of a Vector; 12.10 Finding Pairwise Minimums or Maximums; 12.11 Generating All Combinations of Several Factors; 12.12 Flatten a Data Frame; 12.13 Sorting a Data Frame; 12.14 Sorting by Two Columns; 12.15 Stripping Attributes from a Variable; 12.16 Revealing the Structure of an Object; 12.17 Timing Your Code; 12.18 Suppressing Warnings and Error Messages; 12.19 Taking Function Arguments from a List; 12.20 Defining Your Own Binary Operators; Chapter 13: Beyond Basic Numerics and Statistics; 13.1 Introduction; 13.2 Minimizing or Maximizing a Single-Parameter Function; 13.3 Minimizing or Maximizing a Multiparameter Function; 13.4 Calculating Eigenvalues and Eigenvectors; 13.5 Performing Principal Component Analysis; 13.6 Performing Simple Orthogonal Regression; 13.7 Finding Clusters in Your Data; 13.8 Predicting a Binary-Valued Variable (Logistic Regression); 13.9 Bootstrapping a Statistic; 13.10 Factor Analysis; Chapter 14: Time Series Analysis; 14.1 Introduction; 14.2 Representing Time Series Data; 14.3 Plotting Time Series Data; 14.4 Extracting the Oldest or Newest Observations; 14.5 Subsetting a Time Series; 14.6 Merging Several Time Series; 14.7 Filling or Padding a Time Series; 14.8 Lagging a Time Series; 14.9 Computing Successive Differences; 14.10 Performing Calculations on Time Series; 14.11 Computing a Moving Average; 14.12 Applying a Function by Calendar Period; 14.13 Applying a Rolling Function; 14.14 Plotting the Autocorrelation Function; 14.15 Testing a Time Series for Autocorrelation; 14.16 Plotting the Partial Autocorrelation Function; 14.17 Finding Lagged Correlations Between Two Time Series; 14.18 Detrending a Time Series; 14.19 Fitting an ARIMA Model; 14.20 Removing Insignificant ARIMA Coefficients; 14.21 Running Diagnostics on an ARIMA Model; 14.22 Making Forecasts from an ARIMA Model; 14.23 Testing for Mean Reversion; 14.24 Smoothing a Time Series; Colophon;
Library of Congress subject headings for this publication:
R (Computer program language)
Mathematical statistics -- Graphic methods -- Data processing.
Statistics -- Data processing.
Multiple comparisons (Statistics)