An R and S-Plus Companion to Applied Regression
SAGE Publications Inc (Verlag)
978-0-7619-2280-3 (ISBN)
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`This book fits right into a needed niche: rigorous enough to give full explanation of the power of the S language, yet accessible enough to assign to social science graduate students without fear of intimidation. It is a tremendous balance of applied statistical "firepower" and thoughtful explanation. it meets all of the important mechanical needs: each example is given in detail, code and data are freely available, and the nuances of models are given rather than just the bare essentials. It also meets some important theoretical needs: linear models, categorical data analysis, an introduction to applying GLMs, a discussion of model diagnostics and useful instructions on writing customized functions′ - Jeff Gill, University of Florida, Gainesville
John Fox received a BA from the City College of New York and a PhD from the University of Michigan, both in Sociology. He is Professor Emeritus of Sociology at McMaster University in Hamilton, Ontario, Canada, where he was previously the Senator William McMaster Professor of Social Statistics. Prior to coming to McMaster, he was Professor of Sociology, Professor of Mathematics and Statistics, and Coordinator of the Statistical Consulting Service at York University in Toronto. Professor Fox is the author of many articles and books on applied statistics, including /emph{Applied Regression Analysis and Generalized Linear Models, Third Edition} (Sage, 2016). He is an elected member of the R Foundation, an associate editor of the Journal of Statistical Software, a prior editor of R News and its successor the R Journal, and a prior editor of the Sage Quantitative Applications in the Social Sciences monograph series.
Preface
1. Introducing R and S-PLUS
S Basics
An Extended Illustration
S Functions for Basic Statistics
2. Reading and Manipulating Data
Data Input
Working with Data Frames
Matrices, Arrays, and Lists
Data Attributes, Modes, and Classes
3. Exploring and Transforming Data
Examining Distributions
Examining Relationships
Examining Multivariate Data
Transforming Data
4. Fitting Linear Models
Linear Least-Squares Regression
Dummy-Variable Regression
Analysis of Variance Models
User-Specified Contrasts*
General Linear Hypotheses*
Data and Confidence Ellipses
More on 1m and Model Formulas
5. Fitting Generalized Linear Models
The Structure of GLMs
Models for Categorical Responses
Poisson GLMs for Count Data
Odds and Ends
Fitting GLMs by Iterated Weighted Least-Squares*
6. Diagnosing Problems
Unusual Data
Non-Normal Errors
Non-Constant Error Variance
Nonlinearity
Collinearity and Variable Selection
Diagnostics for Generalized Linear Models
7. Drawing Graphs
A General Approach to S Graphics
Putting it Together
Effect Displays
Graphics Devices
8. Writing Programs
Defining Functions
Working With Matrices*
Program Control: Conditionals, Loops, and Recursion
Apply and its Relatives
Object-Oriented Programming in S*
Writing S Programs
| Erscheint lt. Verlag | 30.7.2002 |
|---|---|
| Verlagsort | Thousand Oaks |
| Sprache | englisch |
| Maße | 177 x 254 mm |
| Gewicht | 680 g |
| Themenwelt | Sozialwissenschaften ► Soziologie ► Empirische Sozialforschung |
| ISBN-10 | 0-7619-2280-6 / 0761922806 |
| ISBN-13 | 978-0-7619-2280-3 / 9780761922803 |
| Zustand | Neuware |
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