| Preface | p. v |
| Typographical Conventions | p. xi |
| Introduction | p. 1 |
| A Quick Overview of S | p. 3 |
| Using S | p. 5 |
| An Introductory Session | p. 6 |
| What Next? | p. 12 |
| Data Manipulation | p. 13 |
| Objects | p. 13 |
| Connections | p. 20 |
| Data Manipulation | p. 27 |
| Tables and Cross-Classification | p. 37 |
| The S Language | p. 41 |
| Language Layout | p. 41 |
| More on S Objects | p. 44 |
| Arithmetical Expressions | p. 47 |
| Character Vector Operations | p. 51 |
| Formatting and Printing | p. 54 |
| Calling Conventions for Functions | p. 55 |
| Model Formulae | p. 56 |
| Control Structures | p. 58 |
| Array and Matrix Operations | p. 60 |
| Introduction to Classes and Methods | p. 66 |
| Graphics | p. 69 |
| Graphics Devices | p. 71 |
| Basic Plotting Functions | p. 72 |
| Enhancing Plots | p. 77 |
| Fine Control of Graphics | p. 82 |
| Trellis Graphics | p. 89 |
| Univariate Statistics | p. 107 |
| Probability Distributions | p. 107 |
| Generating Random Data | p. 110 |
| Data Summaries | p. 111 |
| Classical Univariate Statistics | p. 115 |
| Robust Summaries | p. 119 |
| Density Estimation | p. 126 |
| Bootstrap and Permutation Methods | p. 133 |
| Linear Statistical Models | p. 139 |
| An Analysis of Covariance Example | p. 139 |
| Model Formulae and Model Matrices | p. 144 |
| Regression Diagnostics | p. 151 |
| Safe Prediction | p. 155 |
| Robust and Resistant Regression | p. 156 |
| Bootstrapping Linear Models | p. 163 |
| Factorial Designs and Designed Experiments | p. 165 |
| An Unbalanced Four-Way Layout | p. 169 |
| Predicting Computer Performance | p. 177 |
| Multiple Comparisons | p. 178 |
| Generalized Linear Models | p. 183 |
| Functions for Generalized Linear Modelling | p. 187 |
| Binomial Data | p. 190 |
| Poisson and Multinomial Models | p. 199 |
| A Negative Binomial Family | p. 206 |
| Over-Dispersion in Binomial and Poisson GLMs | p. 208 |
| Non-Linear and Smooth Regression | p. 211 |
| An Introductory Example | p. 211 |
| Fitting Non-Linear Regression Models | p. 212 |
| Non-Linear Fitted Model Objects and Method Functions | p. 217 |
| Confidence Intervals for Parameters | p. 220 |
| Profiles | p. 226 |
| Constrained Non-Linear Regression | p. 227 |
| One-Dimensional Curve-Fitting | p. 228 |
| Additive Models | p. 232 |
| Projection-Pursuit Regression | p. 238 |
| Neural Networks | p. 243 |
| Conclusions | p. 249 |
| Tree-Based Methods | p. 251 |
| Partitioning Methods | p. 253 |
| Implementation in rpart | p. 258 |
| Implementation in tree | p. 266 |
| Random and Mixed Effects | p. 271 |
| Linear Models | p. 272 |
| Classic Nested Designs | p. 279 |
| Non-Linear Mixed Effects Models | p. 286 |
| Generalized Linear Mixed Models | p. 292 |
| GEE Models | p. 299 |
| Exploratory Multivariate Analysis | p. 301 |
| Visualization Methods | p. 302 |
| Cluster Analysis | p. 315 |
| Factor Analysis | p. 321 |
| Discrete Multivariate Analysis | p. 325 |
| Classification | p. 331 |
| Discriminant Analysis | p. 331 |
| Classification Theory | p. 338 |
| Non-Parametric Rules | p. 341 |
| Neural Networks | p. 342 |
| Support Vector Machines | p. 344 |
| Forensic Glass Example | p. 346 |
| Calibration Plots | p. 349 |
| Survival Analysis | p. 353 |
| Estimators of Survivor Curves | p. 355 |
| Parametric Models | p. 359 |
| Cox Proportional Hazards Model | p. 365 |
| Further Examples | p. 371 |
| Time Series Analysis | p. 387 |
| Second-Order Summaries | p. 389 |
| ARIMA Models | p. 397 |
| Seasonality | p. 403 |
| Nottingham Temperature Data | p. 406 |
| Regression with Autocorrelated Errors | p. 411 |
| Models for Financial Series | p. 414 |
| Spatial Statistics | p. 419 |
| Spatial Interpolation and Smoothing | p. 419 |
| Kriging | p. 425 |
| Point Process Analysis | p. 430 |
| Optimization | p. 435 |
| Univariate Functions | p. 435 |
| Special-Purpose Optimization Functions | p. 436 |
| General Optimization | p. 436 |
| Appendices | |
| Implementation-Specific Details | p. 447 |
| Using S-PLUS under Unix/Linux | p. 447 |
| Using S-PLUS under Windows | p. 450 |
| Using R under Unix/Linux | p. 453 |
| Using R under Windows | p. 454 |
| For Emacs Users | p. 455 |
| The S-PLUS GUI | p. 457 |
| Datasets, Software and Libraries | p. 461 |
| Our Software | p. 461 |
| Using Libraries | p. 462 |
| References | p. 465 |
| Index | p. 481 |
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