Statistical models in S

By:

Chambers, John M

Material type: Text

TextPublication details: USA: CRC Press, 1953.Description: xv, 608 pages : illustrations ; 24 cmISBN:

9780412830402

DDC classification:

519.502855133 CHA

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.

Summary: This book contains a collection of ten articles by noted statistical researchers on implementing recent ideas in statistical computing using S. The software, S, can be purchased from AT&T Bell Laboratories in North Carolina or Statistical Science Inc in Seattle, WA.

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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode
Books	Prof. Ram Dayal Munda Central Library, IGNTU Amarkantak M.P.	Mathematics	519.502855133 CHA (Browse shelf(Opens below))	Available		66213

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.

This book contains a collection of ten articles by noted statistical researchers on implementing recent ideas in statistical computing using S. The software, S, can be purchased from AT&T Bell Laboratories in North Carolina or Statistical Science Inc in Seattle, WA.

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