Statistical models in S / edited by John M. Chambers, Trevor J. Hastie.

Contributor(s): Chambers, John M, 1941- | Hastie, Trevor J.
Material type: materialTypeLabelBookSeries: Wadsworth & Brooks/Cole computer science series.Publisher: Pacific Grove, Calif. : Wadsworth & Brooks/Cole Advanced Books and Software, c1992 (ie.1991)Description: xv, 608 p. : ill. ; 24 cm.ISBN: 0534167659 (pbk); 0534167640 (casebound).Subject(s): S | DATA PROCESSING | STATISTICAL MODELS | COMPUTER GRAPHICS | STATISTICAL MODELLING | LINEAR MODELS | PROGRAMMING LANGUAGES | MATHEMATICAL STATISTICSHoldings: GRETA POINT: 519.24:004.62 STA | CHRISTCHURCH: CM 519.24 S STA
Contents:
1. An Appetizer / John M. Chambers and Trevor J. Hastie -- 1.1. A Manufacturing Experiment -- 1.2. Models for the Experimental Results -- 1.3. A Second Experiment -- 1.4. Summary -- 2. Statistical Models / John M. Chambers and Trevor J. Hastie -- 2.1. Thinking about Models -- 2.2. Model Formulas in S -- 2.3. More on Models -- 2.4. Internal Organization of Models -- 3. Data for Models / John M. Chambers -- 3.1. Examples of Data Frames -- 3.2. Computations on Data Frames -- 3.3. Advanced Computations on Data -- 4. Linear Models / John M. Chambers -- 4.1. Linear Models in Statistics -- 4.2. S Functions and Objects -- 4.3. Specializing and Extending the Computations -- 4.4. Numerical and Statistical Methods -- 5. Analysis of Variance; Designed Experiments / John M. Chambers, Anne E. Freeny and Richard M. Heiberger -- 5.1. Models for Experiments: The Analysis of Variance -- 5.2. S Functions and Objects -- 5.3. The S Functions: Advanced Use -- 5.4. Computational Techniques -- 6. Generalized Linear Models / Trevor J. Hastie and Daryl Pregibon -- 6.1. Statistical Methods -- 6.2. S Functions and Objects -- 6.3. Specializing and Extending the Computations -- 6.4. Statistical and Numerical Methods -- 7. Generalized Additive Models / Trevor J. Hastie -- 7.1. Statistical Methods -- 7.2. S Functions and Objects -- 7.3. Specializing and Extending the Computations -- 7.4. Numerical and Computational Details -- 8. Local Regression Models / William S. Cleveland, Eric Grosse and William M. Shyu -- 8.1. Statistical Models and Fitting -- 8.2. S Functions and Objects -- 8.3. Specializing and Extending the Computations -- 8.4. Statistical and Computational Methods -- 9. Tree-Based Models / Linda A. Clark and Daryl Pregibon -- 9.1. Tree-Based Models in Statistics -- 9.2. S Functions and Objects -- 9.3. Specializing the Computations -- 9.4. Numerical and Statistical Methods -- 10. Nonlinear Models / Douglas M. Bates and John M. Chambers -- 10.1. Statistical Methods -- 10.2. S Functions -- 10.3. Some Details -- 10.4. Programming Details -- A. Classes and Methods: Object-oriented Programming in S / John M. Chambers -- A.1. Motivation -- A.2. Background -- A.3. The Mechanism -- A.4. An Example of Designing a Class -- A.5. Inheritance -- A.6. The Frames for Methods -- A.7. Group Methods; Methods for Operators -- A.8. Replacement Methods -- A.9. Assignment Methods -- A.10. Generic Functions -- A.11. Comment -- B. S Functions and Classes.
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Item type Current location Call number Copy number Status Date due Barcode
BOOK BOOK CHRISTCH
BOOKS
CM 519.24 S STA 1 Issued 09/06/2015 10827-3001
BOOK BOOK WELLINGTON
BOOKS
519.24:004.62 STA 1 Available B017512

Includes bibliographical references (p. 589-593) and index.

1. An Appetizer / John M. Chambers and Trevor J. Hastie -- 1.1. A Manufacturing Experiment -- 1.2. Models for the Experimental Results -- 1.3. A Second Experiment -- 1.4. Summary -- 2. Statistical Models / John M. Chambers and Trevor J. Hastie -- 2.1. Thinking about Models -- 2.2. Model Formulas in S -- 2.3. More on Models -- 2.4. Internal Organization of Models -- 3. Data for Models / John M. Chambers -- 3.1. Examples of Data Frames -- 3.2. Computations on Data Frames -- 3.3. Advanced Computations on Data -- 4. Linear Models / John M. Chambers -- 4.1. Linear Models in Statistics -- 4.2. S Functions and Objects -- 4.3. Specializing and Extending the Computations -- 4.4. Numerical and Statistical Methods -- 5. Analysis of Variance; Designed Experiments / John M. Chambers, Anne E. Freeny and Richard M. Heiberger -- 5.1. Models for Experiments: The Analysis of Variance -- 5.2. S Functions and Objects -- 5.3. The S Functions: Advanced Use -- 5.4. Computational Techniques -- 6. Generalized Linear Models / Trevor J. Hastie and Daryl Pregibon -- 6.1. Statistical Methods -- 6.2. S Functions and Objects -- 6.3. Specializing and Extending the Computations -- 6.4. Statistical and Numerical Methods -- 7. Generalized Additive Models / Trevor J. Hastie -- 7.1. Statistical Methods -- 7.2. S Functions and Objects -- 7.3. Specializing and Extending the Computations -- 7.4. Numerical and Computational Details -- 8. Local Regression Models / William S. Cleveland, Eric Grosse and William M. Shyu -- 8.1. Statistical Models and Fitting -- 8.2. S Functions and Objects -- 8.3. Specializing and Extending the Computations -- 8.4. Statistical and Computational Methods -- 9. Tree-Based Models / Linda A. Clark and Daryl Pregibon -- 9.1. Tree-Based Models in Statistics -- 9.2. S Functions and Objects -- 9.3. Specializing the Computations -- 9.4. Numerical and Statistical Methods -- 10. Nonlinear Models / Douglas M. Bates and John M. Chambers -- 10.1. Statistical Methods -- 10.2. S Functions -- 10.3. Some Details -- 10.4. Programming Details -- A. Classes and Methods: Object-oriented Programming in S / John M. Chambers -- A.1. Motivation -- A.2. Background -- A.3. The Mechanism -- A.4. An Example of Designing a Class -- A.5. Inheritance -- A.6. The Frames for Methods -- A.7. Group Methods; Methods for Operators -- A.8. Replacement Methods -- A.9. Assignment Methods -- A.10. Generic Functions -- A.11. Comment -- B. S Functions and Classes.

GRETA POINT: 519.24:004.62 STA

CHRISTCHURCH: CM 519.24 S STA

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